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In this paper, a co-design scheme for simultaneous optimization of the performance of radar and communication system in spectrum coexistence scenario is developed. Considering the possible information mismatch, the interference covariance matrices are reconstructed firstly. Then we adopt the signal-to-interference-plus noise ratio (SINR) on the radar side and the harvested power on the communication side as the performance indicators of the two systems, and obtain a weighted non-convex optimization formulation under the power constraints and similarity constraint. A sequential iterative optimization framework is presented to transform the non-convex problem into several single-variable subproblems, which exploits an alternating iterative procedure that combines Minorization-Maximization (MM) framework and double quadratic form optimizations with separable design (whose solution can be provided in closed-form). Finally, the merits of the proposed design are verified by simulation results.

ABSTRACTThis study examined the impact of student engagement on satisfaction with an undergraduate marketing research course. Student engagement consisted of three dimensions in this study, namely physical engagement, emotional engagement, and cognitive engagement. Flow theory was used to examine the potential impact of the disruption of student learning flow on student engagement and student learning outcomes (i.e. student class satisfaction) using longitudinal data from before and during the COVID-19 pandemic. The data were collected over 10 semesters at an American public university. The data analysis results indicated that physical engagement was negatively associated with student class satisfaction, while emotional engagement and cognitive engagement exhibited a positive association. In addition, physical engagement had a stronger influence on student class satisfaction during the pandemic than before the pandemic, while there was no significant difference in the impact of emotional and cognitive engagement between the periods. Results imply that instructors need to engage students emotionally and intellectually in activities that do not make them work too hard.

The sparse signal phase retrieval (PR) for phaseless short-time Fourier transform (STFT) measurement is a crucial problem manifesting across various applications. The existing solutions involve amplitude and support estimation. Amplitude estimation, a nonlinear least squares problem, faces issues due to the not full rank of the derivative matrix associated with the objective function. Existing support estimation relies on random initialization, reducing accuracy and noise robustness. To address these, a novel phaseless measurement structure and the corresponding solution framework are proposed. Initially, a measurements preprocessing algorithm is employed, utilizing the properties of the measurement matrix to efficiently reduce the dimensions of the solution. Subsequently, a support estimation algorithm based on local search is developed, where the support preestimation takes advantage of the sparse support characteristics. In addition, an amplitude estimation algorithm, utilizing the trust region method, is proposed. The proposed algorithm’s effectiveness and its superiority in accuracy and noise robustness over existing methods are demonstrated through numerical simulations and hardware experiments.

To accurately perceive pulse sequences containing linear frequency modulation (LFM) and M-ary phase shift keying (MPSK) signals, this article introduces a parameter measurement framework based on the finite rate of innovation (FRI) sampling theory. By following the radar reconnaissance approach of inter-pulse parameter estimation, pulse-type identification, and intra-pulse parameter estimation, we propose several measurement methods under the condition of sub-Nyquist sampling. These methods encompass hybrid pulse number estimation using singular value rectification (SVR), pulse-type identification through time-domain breakpoints and shift-invariant subspace (SIS) projection, and intra-pulse parameter estimation of hybrid sequences using linear modulation and interval matching. Our approach enables efficient sensing of hybrid sequences within a unified sampling framework, and through the utilization of FRI sampling theory, the efficiency of the parameter measurement process is significantly enhanced, thereby reducing the sampling pressure. Simulation and hardware experiments demonstrate substantial improvements in accuracy for both inter-pulse and intra-pulse parameter estimation in hybrid sequences when compared to classical methods.

This article designs a multisensor odor detection system for lung cancer detection, which can be used to collect exhaled gas and noninvasive predict lung cancer diseases. In response to the widespread drift problem in multisensor odor detection systems in the medical context, we have added constraints that can represent interclass differences in the improved differential empirical distance and proposed a new formulation. Inspired by the principles of machine learning, we consider the source-domain data as nondrift data, while the target-domain data as cross-domain data. The derived enhanced category discrepancy domain adaption (ECDDA) framework considers the consistency between statistical and geometric distributions. Thereby improving the compensation performance of sensor drift by combining domain adaptation to reduce category distribution differences and Bayesian probability to extract category information, establish an unsupervised cross-domain category difference maximization model for drift compensation, overcome inter-board differences on different machines, and increase the sample size to a certain extent when used for medical data consolidation. The results show the effectiveness of the proposed design.

We conducted frequency and direction of arrival estimations when more signals than sensors were present using a sub-Nyquist sampling system. We proposed a degrees of freedom (DOF) extension arrayed modulated wideband converter method based on a novel joint space-frequency sparse model, which can increase the DOF of the receiving array by appropriately increasing the sub-Nyquist sampling rate, was proposed. Our method does not require any special sparse array arrangement or an increase in the number of channels, thereby reducing cost and simplifying implementation. Coherent signals and source ambiguity were theoretically analyzed, and rigorous reconstruction conditions were provided for each case. Numerical results were provided to verify the effectiveness of the proposed method.

The finite-rate-of-innovation (FRI) sampling method can reconstruct signals with few samples. However, classical FRI sampling often has serious model mismatch when dealing with asymmetric pulse signals. The variable-pulse-width (VPW) signal model is composed of asymmetric pulses with variable width, which can better match the asymmetric pulse signals in the actual signal measurement, such as electrocardiogram (ECG) and bidirectional reflectance distribution function (BRDF). The VPW-FRI sampling theory provides an effective alternative to sub-Nyquist sampling of such signals. Recent studies have used time encoding machine (TEM), an alternative sampling scheme, to replace the analog-to-digital converter in classical FRI frameworks. Such devices acquire signal samples through time measurement rather than measuring the intensity, with lower power consumption and less electronic interference. However, the existing TEM-FRI sampling methods do not match the VPW signal model. In this article, a sampling method based on TEM-FRI sampling scheme for VPW signals is proposed. We extend the signal model of TEM-FRI sampling framework to VPW signal, and give the mathematical derivation of the perfect reconstruction for VPW signal based on TEM-FRI sampling method. For the VPW signal containing K pulses, our method can guarantee the perfect reconstruction of VPW signals when the number of samples $N~\ge ~4K+1$ in one signal period. And we present a robust reconstruction algorithm by denoising samples in the frequency domain, the simulation results show that our proposed method is more robust than classical FRI sampling method in the presence of noise. In addition, we present a TEM-based FRI sampling hardware system, and explain how to implement the sampling kernel in our hardware system with an analog filter device. According to the experiments, the TEM-FRI hardware system can sample and reconstruct the VPW signal.

Digital reading has been a research trend recently. This study reviewed studies published in the area of mobile technology-supported reading education (MTSRE) in the Scopus database from 2005 to 2020. The analysis was conducted from four aspects, namely the article information, the study design and execution, how mobile technology was used, and the statistical methods and research issues. The results indicated that: 1) MTSRE has aroused the research interest of researchers; 2) most studies on MTSRE explore its effects, elementary school students are the most common participants, the experimental design method was mostly adopted, and studies conducted with in-class activities were the most common; 3) the MTSRE research investigated how to introduce different instructional strategies in MTSRE, and it was found that inquiry-based learning was most frequently used; 4) for statistical methods, descriptive statistics, were the most frequently applied, and the research topics were mainly focused on the cognition domain.

Lithium-ion batteries (LIBs) are considered a rechargeable and commercial energy storage device for electronic equipment such as smartphone and electric vehicles. Despite the prospective future of LIBs, unsatisfied electrochemical properties like reversible capacity, cycle ability and coulombic efficiency still hinder their development. High volume expansion rate, uncontrolled Li dendrite growth and unsatisfied solid electrolyte interphase also occur when LIBs are applied in long-time usage. Numerous modification methods such as exploring high-capacity anode/cathode materials, constructing artificial solid electrolyte interphase and improved conductive binders can be adopted to enhance the performances. Among them, particulate modification for LIBs anode and electrolytes is receiving tremendous attraction in the recent work. The method is composed of changing the morphology and particle size of the active materials, also introduce nano-size additives to the main structure. This review emphasizes on introducing and discussing the modification in following aspects: particulate modification on carbon group IVA element anodes, introduction of additives like transition metal oxide nanoparticles into anode and electrolyte materials, dissipate the influence of Li dendrite growth and ameliorate the performances of solid electrolyte interface. This review hopes to be denoted for the future development of LIBs with the comprehensive understanding on the particulate modification.

Aiming for the robustness improvement in a noisy environment, we propose a new representation method based on Lorentzian pulse fitting for the analytical expression process of the measured lightning channel base current (LCBC) in this article. The Lorentzian pulse train is determined only by a finite number of free parameters, which can be estimated from the high-energy part of the LCBC signal spectrum. To obtain Fourier coefficients from the LCBC measurements, we design a sum-of-sinc digital filter. In addition, we propose a denoising algorithm based on nuclear norm minimization to improve the accuracy of the parameter estimation process. By using only the high-energy spectrum region, our method is more resistant to noise during the fitting process. Furthermore, although the Lorentzian pulse fitting method cannot strictly achieve the value of LCBC as 0 at the time of $t=0_+$, it provides a simple and integrable expression form in the time domain, which has great application value in the analysis of lightning magnetic field characteristics. Simulation results demonstrate that our proposed method achieves higher analytical expression accuracy for LCBC signal in noisy environments than the classical versions, both in terms of the signal itself and its first derivative.

Fungal infections usually occur in immunocompromised patients. Intravenous immunoglobulin (IVIG) has been used as therapeutic interventions for many infectious diseases, but seldom applied in mycosis due to unknown antifungal specificity. This study aims to determine the presence of antifungal antibodies in IVIG. Binding reactivity of IVIG with crude and recombinant antigens of Candida albicans, Aspergillus fumigatus, Cryptococcus neoformansand Talaromyces marneffeiwere observed in a dose-dependent manner, similar with mixed normal human sera. The antifungal specificity was further confirmed by competitive enzyme-linked immunosorbent assays (ELISA) inhibited by rabbit specific antifungal polyclonal antibodies (PAbs) and homogenous crude antigens with inhibitions of 65.5-87.2% and 73.1-94.2%, respectively. Moreover, IVIG also reacted with fungal glycoproteins (Csa2,Cpl1 and Mp1p) in a dose-dependent way, which was inhibited by specific rabbit PAbs and homogenous antigens with different inhibitions and pulled down 72.8-83.8% of specific antibodies if preabsorption IVIG with Dynabeads® coupled with homogenous glycoproteins. These results furthermore verified the antifungal specificity of IVIG. Among four brands of IVIG, there was different antifungal IgG against C. albicans(P< 0.05) and C. neoformans(P< 0.05), while no difference for A. fumigatus(P= 0.086) and T. marneffei(P= 0.057). IVIG contained a significantly higher level of specific IgG for C. albicansthan other three fungi (P<0.001). In conclusion, we proved antifungal IgG against C. albicans, A. fumigatus, C. neoformansand T. marneffeipresent in IVIG, which might be expected to provide a possible immunoregulation choice for mycosis and an evaluation to humoral immunity against fungi.

In this work, we present a novel radar-communication spectrum sharing framework for transmission design. The design degrees of freedom (DoFs) under control are the radar transmit waveforms and the communication system code-book. The formulation of the spectrum sharing problem is stated as the maximization of the radar signal-to-interference-plus-noise ratio (SINR) under the constraints concerning the transmit energy, the radar similarity with a radar reference waveform, the communication system rate achievable. Compared with the traditional alternating convex transformation approach for the resulting non-convex problem, a novel algorithm is proposed based on the derived local design for radar waveform (LDFRW) to reduce the computational complexity. The numerical results show the merits of the proposed design.

The linear frequency modulated pulse stream (LFMPS) is a finite rate of innovation (FRI) signal that depends on a finite number of parameters within a unit of time, and precise measurement of these parameters holds great significance in the engineering field. However, traditional LFMPS sensing methods face challenges such as complex sampling structures, high sampling rates, and poor parameter estimation accuracy. This article proposes a universal pulse stream sampling structure based on FRI sampling theory to address these issues. The structure utilizes the periodicity of LFMPS to locate pulses from the sub-Nyquist samples of the first signal period. Then, window functions are constructed to separate the LFM pulse in the second period and perceive the related parameter through the parameter matching method. We analyze the effect of the LFM waveform on pulse positioning in the first period and demonstrate the feasibility of estimating the chirp-rate (CR) factor using the parameter matching method. Numerical simulation results show that our proposed algorithm achieves accurate LFM signal measurement at lower sampling rates and has stronger noise immunity during parameter measurement compared to classical sensing approaches.

Phase-shift keying (PSK) signals exist widely in radar and communications systems. However, in noncooperative scenarios, measuring PSK signals demands a wide range of detection bandwidth, and the measurement schemes using the Nyquist theorem need a relatively high sampling rate. In this article, we propose a two-part cooperative sub-Nyquist sampling (TCSS) system for robust measurement of the discontinuity locations (DLs) and carrier frequency (CF) of PSK signals based on the finite rate of innovation (FRI) sampling and the structured sparsity. The minimum number of samples needed by the TCSS system depends only on the number of estimated parameters but not on the CF and bandwidth. The TCSS system comprises the delayed autocorrelation sampling (DAS) and orthogonal time-staggered sampling (OTS) structures. First, the DLs are measured by the DAS structure using the subspace method. In addition, for binary-PSK signals, a two-stage structured orthogonal matching pursuit (S-OMP) algorithm is used to improve the parameter measurement’s robustness based on the DLs’ structured sparsity. The within-symbol samples of the OTS structure are obtained based on the estimated DLs, and the CF is calculated using the subspace method and the robust Chinese remainder theorem (R-CRT). Compared with similar measurement schemes, the proposed method has higher robustness for parameter measurements over a wide bandwidth and is easier to implement in engineering. Simulations and hardware results illustrate the efficiency of the TCSS system.

Spectrum measurement and direction of arrival (DOA) estimation methods based on traditional Nyquist theory lead to high sampling rate and a large amount of data, which bring challenges to hardware and signal processing. An array cooperative modulated wideband converter (ACMWC) sub-Nyquist sampling system for spectrum measurement and DOA estimation is proposed in this work. Based on a linear array (LA) cooperative MWC sampling structure with an arbitrary array element position, we construct a unified space–frequency-domain sparse model by combining the modulation information of different sensors and the spatial phase information of the array to estimate carrier and DOA simultaneously. Combining multisensor data to jointly reconstruct spectrum and estimate DOA can improve data utilization and estimation accuracy. In addition, we also give a spatial separation processing scheme based on the sparsity characteristics of signal spatial distribution, which can greatly reduce the computational complexity. Compared with similar approaches, the problem of source ambiguity and coherent signals in array parameter estimation can be solved by the time–space distribution characteristics of spectrum and DOA. Moreover, the proposed method relaxes the restrictions on array manifolds and can be used for LA with arbitrary sensor positions with wider application prospects. The effectiveness of the proposed method is verified by simulation and hardware results.

To mitigate the impact of shot noise on the parameter measurement process of finite rate of innovation (FRI) signals, this article proposes a sub-Nyquist modulation sampling system with two measurement channels. The noisy signal is sampled in the main channel after being filtered by a sinc kernel to obtain the aliasing Fourier coefficients, whereas the FRI signal is shifted out of the baseband with a cosine modulation function in the accessory channel to expose the shot noise information to the low frequency band. The burst time parameters of shot noise can be estimated using the annihilating filter method from the samples in the accessory channel, while the parameters of the FRI signal will be measured from the observations in the main channel after the shot noise information has been removed. If the rate of innovation (RI) of the FRI signal is $\rho _{L}$ and is affected by $K$ impulses of shot noise, the entire measurement process only requires $\rho _{L}\cdot \tau +2K$ points to be sampled per unit time $\tau $ . To enhance the robustness of the measurement process in actual circuit systems, a corrected annihilating filter method is proposed, and the parameter measurement error when employing this method is analyzed. Numerical and hardware experiments demonstrate that, compared to classical antinoise algorithms, the proposed method not only measures the parameters of FRI signals contaminated by shot noise more accurately, but also significantly improves the robustness of the measurement process in nonideal environments.

Accurate measurement of the M-ary phase shift keying (MPSK) signal determined by finite parameters per unit of time is significant in engineering fields, such as digital microwave and satellite communication. In this article, we propose a sub-Nyquist sampling system with two channels for measuring characteristic parameters of MPSK signals based on the finite rate of innovation (FRI) sampling theory. The carrier frequency parameter measurement process is modeled as a convex optimization problem, solvable using the parameter matching method on the estimated grid. The minimum harmonic frequency of the carrier is determined to build the exact grid, and the carrier frequency is estimated through a greedy search based on the given cost function. Even when the truth value of the carrier frequency is unknown, the discontinuity location parameters can be measured with high precision using the spectral estimation method on the Fourier coefficients of the MPSK signal. We propose an upper bound on the estimation error of this separable measurement method for signals with one segment. The amplitude and phase parameters can be measured by solving a least square problem. Our proposed measurement system, with lower hardware complexity, can accurately measure the MPSK signal with $K$ segments by sampling only $2K$ + 5 points in a period, at a much lower sampling rate than the carrier frequency. Numerical simulations and hardware experiments demonstrate the superior performance of our state-of-the-art measurement method.

With the development of radar, wireless communications, remote sensing, and other fields, the signal bandwidth is getting wider. Traditional spectrum sensing and direction of arrival (DOA) estimation based on Nyquist sampling leads to a high sampling rate, which poses challenges to signal acquisition and processing equipment. In this article, a novel sub-Nyquist spectrum sensing and DOA estimation method based on the space-time trilinear model is proposed to improve the performance, and also solve the rank deficiency problem in the presence of coherent signals. First, based on a uniform linear array (ULA) modulated wideband converter (MWC) sub-Nyquist sampling system, a space-time trilinear model constructed directly by sub-Nyquist sampling is proposed which can make full use of the spatial and temporal multidimensional information of the signal simultaneously to achieve better performance. Compared to previous works, it avoids the computation of correlation matrices or signal subspaces, so the estimation is not affected by the nonideal statistical properties of finite snapshots. Then, based on the proposed space-time trilinear model, we provide a simple extension to overcome the rank deficiencies associated with coherent signals by exploiting the spatial phase differences between subarrays, while improving the robustness of the system. The effectiveness of the proposed method is verified by simulation and hardware experiments.

This letter investigates the spectral compatibility for a communication system operating on same frequency with radar by exploiting multiple input multiple output (MIMO) configurations, where the radar system acts as the primary platform, while the communication system is the secondary platform. A multiple constrained formulation including transmitter power and peak-to-average power ratio (PAR), aims at radar signal-to-interference-plus-noise ratio (SINR) and communication power harvesting optimization. The design variables consist of the space-time transmit sequences for the two coexistence systems. We derive an optimal procedure that decomposes the developed non-convex formulation into a sequence of subproblems based on the cost function modified alternating direction method of multipliers (CM-ADMM) techniques. Finally, to reveal the effectiveness and superiority of the proposed algorithm in different scenarios, numerical results are provided.

The finite rate of innovation (FRI) sampling theory offers a pathway for the sub-Nyquist sampling of nonbandlimited parametric signals. However, the successful application of FRI-based techniques requires prior knowledge of the model order of the parameterized signal being sampled. This article presents an efficient method for measuring the model order of FRI signals by leveraging the low-rank features of Toeplitz matrices. In a noisy environment, we conduct an initial analysis and identify that the key factor affecting the estimation of model order is the problem of small singular values in the Toeplitz matrix caused by noise. In response to this, we present a plug-and-play convolutional neural networks (CNNs)-based denoising module as well as an efficient algorithm for singular value rectification (SVR). Compared to classical methods for measuring model order, the proposed approach does not require signal reconstruction or resampling. As a result, our proposed technique has lower complexity and achieves significantly improved accuracy and efficiency under the same signal-to-noise ratio (SNR). We validate our approach through simulation experiments and hardware testing, and the results demonstrate that our method substantially enhances the accuracy and robustness of model order estimation in noisy environments.

As a problem of reconstructing the original signal from phaseless short-time Fourier transform (STFT) measurement, STFT phase retrieval (PR) is widespread in many fields. The existing PR algorithms for STFT measurement can uniquely determine the original signal (up to a global phase); however, they are invalid when outlier interference exists. Aiming at this problem, we propose a weighted convex optimization PR method by introducing a weight matrix that can identify outliers. Meanwhile, a two-channel phaseless measurement structure based on the mask technique and the corresponding calculation algorithm are proposed to obtain the weight matrix. In particular, by accumulating the measurement results of all short-time segments, the support of outliers can be well-identified in the weight matrix calculation. Simulation and hardware experiments demonstrate the performance improvement of the proposed approach compared with the existing methods, which shows its effectiveness in suppressing outlier interference.

Finite rate of innovation (FRI) sampling is widely used in modern high-resolution range-Doppler (RD) detection systems to reduce the sampling rate. However, as the sampling rate decreases, the method becomes more noise-sensitive. This study proposes a deep atomic norm denoising network (DAND-Net) to denoise FRI samples of RD signals and estimate the noise levels (NLs). Based on the sparse common support property of the FRI samples, the denoising problem of the RD signals was modeled as an atomic norm soft thresholding problem, which jointly used multiple measurement vectors and could be unfolded into a model-driven deep network. The trainability and generalization ability of the network were improved by introducing piecewise linear functions and new trainable variables. By introducing an NL estimation operator, the NL could be better estimated during denoising, and the network training and convergence better supported. Additionally, the plug-and-play method could be used to complete denoising prior to many existing FRI methods. The simulation experiments showed that the proposed denoising network can achieve better denoising and NL estimation results with fewer iterations.

The development of advanced high-efficiency adsorbents is the key to promoting the iterative progress of gas separation and capture technology. Herein, a series of N-doped ultrathin carbon nanosheets (Zn-NDPCs) with a micromeso hierarchical connected porous structure are synthesized by directly annealing Zn-poly(4-vinylpyridine) coordination compounds. Among them, Zn-NDPC-500 has a high surface area (1146 m2g–1), rich N-doped active sites, and unimodal ultramicropores (0.5 nm). The thickness of Zn-NDPC-500 is only 3.8 nm, and it has rough surface morphology. Benefiting from the synergy of the above structures on the interaction between gas molecules and materials, Zn-NDPC-500 shows excellent adsorption capacity for C2H2(3.2), C2H6(2.7), C3H8(4.8), and CO2(2.5 mmol g–1) and high ideal adsorbed solution theory (IAST) selectivity for C2H2/CH4, C2H6/CH4, C3H8/CH4, CO2/CH4, and CO2/N2as high as 33.4, 20.3, 404.6, 11.3, and 63.9, respectively, under ambient conditions.

Assisted by computational mechanics methods and deep learning, this paper proposes a data-driven method for predicting random acoustic radiation and localizing underwater source in a shallow sea. A combined method of the pseudo excitation method (PEM), the finite element method (FEM), the virtual mass method (VM), and the image method-based boundary element method (I-BEM) is developed to predict the random acoustic radiation influenced by the random vibration of the fluid-structure interaction and the sound reflection of the sea surface and the seabed. The ConvNeXt network is trained on a huge number of acoustic field data generated by PEM/FEM-VM/I-BEM to extract power spectral density (PSD) features of sound pressure at sample field points. The trained models are ultimately employed to predict random acoustic radiation and localize underwater source. The simulation results demonstrate that the proposed method is effective and universal for random sound radiation prediction and source localization in the shallow sea. [ABSTRACT FROM AUTHOR]

Transitional metal chalcogenides like WS2play a significant role as cocatalysts in activating PMS (peroxymonosulfate) due to their high reductivity. Three WS2samples with different morphologies, specific surface areas, and 1 T phase contents were prepared in this study. Characterizations by SEM, TEM, BET, XRD, Raman, XPS, and catalytic degradation experiments confirmed that the a-WS2sample exhibited the richest morphology, the largest specific surface area, the highest 1 T phase content, and the best cocatalytic performance. The a-WS2/Fe(II)/PMS system efficiently degraded 20 mg/L phenol within 15 minutes and was also effective in degrading pollutants like RhB (Rhodamine B) and OFX (Ofloxacin). Characterization predicted the degradation pathway of phenol and revealed 10 intermediate products. The degradation mechanism indicated that the presence of WS2accelerated the conversion of Fe(III) to Fe(II), thereby further promoting the activation of PMS. ·SO4−, ·OH, and ·O2−were identified as the main active radicals in this system. a-WS2exhibits characteristics such as high catalytic performance, good stability, high recyclability, and a low ion leaching rate, and it generates sulfur vacancies during use. This system shows promising prospects in the treatment of high-concentration organic wastewater.

Gaussian pulse streams can be characterized by a finite number of unit-time parameters, and classical Finite Rate of Innovation (FRI) sampling enables sub-Nyquist sensing of these signals. However, prior knowledge of its shape factor is required, limiting FRI's applicability. This paper proposes a solution to the FRI sampling problem of Gaussian pulse streams with an unknown pulse shape factor. We aim to fit pulse shape information from sub-Nyquist samples and reconstruct parameters using spectral estimation methods. We first demonstrate the feasibility of fitting the shape factor from sub-Nyquist samples and provide the fitting algorithm and related fitting errors in detail. This paper also provides the Cramer-Rao lower bound (CRLB) on parameter estimation accuracy of Gaussian pulse streams under analog white Gaussian noise, offering a statistical perspective of our proposed information fitting method's performance. We qualitatively demonstrate that the information-fitting method can also be applied to a wider range of FRI pulse stream forms. Simulation experiments show that our proposed information fitting method achieves high accuracy in parameter estimation of the signal when the pulse shape factor is unknown. [ABSTRACT FROM AUTHOR]

Musa ornataand Musa velutinaare members of the Musaceae family and are indigenous to the South and Southeast Asia. They are very popular in the horticultural market, but the lack of genomic sequencing data and genetic studies has hampered efforts to improve their ornamental value. In this study, we generated the first chromosome-level genome assemblies for both species by utilizing Oxford Nanopore long reads and Hi-C reads. The genomes of M. ornataand M. velutinawere assembled into 11 pseudochromosomes with genome sizes of 427.85 Mb and 478.10 Mb, respectively. Repetitive sequences comprised 46.70% and 50.91% of the total genomes for M. ornataand M. velutina, respectively. Differentially expressed gene (DEG) and Gene Ontology (GO) enrichment analyses indicated that upregulated genes in the mature pericarps of M. velutinawere mainly associated with the saccharide metabolic processes, particularly at the cell wall and extracellular region. Furthermore, we identified polygalacturonase (PG) genes that exhibited higher expression level in mature pericarps of M. velutinacompared to other tissues, potentially being accountable for pericarp dehiscence. This study also identified genes associated with anthocyanin biosynthesis pathway. Taken together, the chromosomal-level genome assemblies of M. ornataand M. velutinaprovide valuable insights into the mechanism of pericarp dehiscence and anthocyanin biosynthesis in banana, which will significantly contribute to future genetic and molecular breeding efforts.

Given factors such as reduced land availability for onshore wind farms, wind resource enrichment levels, and costs, there is a growing trend of establishing wind farms in deserts, the Gobi, and other arid regions. Therefore, the relationship between sand-dust weather environments and wind turbine operations has garnered significant attention. To investigate the impact of wind turbine wakes on sand-dust transportation, this study employs large eddy simulation to model flow fields, coupled with an actuator line model for simulating rotating blades and a multiphase particle in cell model for simulating sand particles. The research focuses on a horizontal axis wind turbine model and examines the motion and spatiotemporal distribution characteristics of four typical sizes of sand particles in the turbine wake. The findings reveal that sand particles of varying sizes exhibit a spiral settling pattern after traversing the rotating plane of wind turbine blades, influenced by blade shedding vortex and gravity. Sand particles tend to cluster in the peripheries of the vortex cores of low vorticity in the wind turbine wake. The rotation of wind turbines generates a wake vortex structure that causes a significant clustering of sand particles at the tip vortex. As the wake distance increases, the particles that cluster at the turbine’s tip gradually spread outward to approximately twice the rotor diameter and then begin to mix with the incoming flow environment. Wind turbines have a noticeable impact on sand-dust transportation, hindering their movement to a significant extent. The average sand-blocking rate exhibits a trend of initially increasing and then decreasing as the wake distance increases. At its peak, the sand-blocking rate reaches an impressive 67.55%. The presence of wind turbines induces the advanced settling of sand particles, resulting in a “triangular” distribution of the deposition within the ground projection area of the wake.

Low-cost materials with a highly efficient adsorption capability prepared from corn straw and medicago (abbreviated to CB and MB), which can effectively remove benzo(a)pyrene (BaP) from contaminated soil, were prepared at a temperature of 350 °C under limited-oxygen conditions. The appearance traits, contents of C, H, N and functional group types of CB and MB were obtained by SEM, elemental analysis and FT-IR. Through the batch method, it was found that the adsorption of BaP by CB and MB was in accordance with pseudo-secondary kinetics because the correlation coefficients are 0.855 with CB and 0.948 with MB, respectively, and the maximum adsorption capacity in the fitting (CB: 78.2 mg kg−1, MB: 88.8 mg kg−1) was consistent with the actual measurement (CB: 79.8 mg kg−1, MB: 89.3 mg kg−1). Freundlich and Langmuir equations can well describe the isothermal adsorption data of CB and MB due to the correlation coefficients all being greater than 0.87. Soil samples treated with ASE were separated by solid-phase extraction (SPE) with different biochar contents in packed columns. It was found that the contributions of CB and MB to the removal of BaP increased from 58.5% and 60.4% to 80.6% and 82.1%, respectively, which could effectively reduce BaP in polluted soil.

Aqueous zinc-ion batteries (ZIBs) have attracted extensive attention due to their low cost, environmental friendliness, and high volumetric specific capacity. However, the design of cathode materials with high performance for ZIBs is quite limited. In this paper, a kind of manganese-based metal-organic framework/carbon nanotubes (Mn-MOF/CNT) composite is prepared as the cathode material for ZIBs via a one-pot in situ solvothermal method. Particularly, the assembled Mn-MOF/CNT//Zn battery exhibits high specific capacity (260 mAh g−1at 50 mA g−1) and excellent capacity retention (approximately 100 %) after 900 cycles at 1000 mA g−1. This significant electrochemical performance is attributed to the high porosity and the high conductivity of Mn-MOF/CNT, as well as the Mn2+electrolyte additive. This work renders a new sight to design high-performance MOF-based cathode materials for aqueous ZIBs.

The nitrite efficient utilization microorganism Wickerhamomyces anomalusRZWP01 was identified. Using nitrite and ammonium as the sole nitrogen source, the nitrogen removal rate of W. anomalusRZWP01 was 97.4% and 87.1%, respectively. W. anomalusRZWP01 grew well in the nitrite medium with glucose or xylose as the only carbon source. However, the W. anomalusRZWP01 cannot live on the nitrite medium with lactose, citric acid, and methanol as the only carbon source. The maximal cell concentration occurred in the nitrite medium with glucose as the only carbon source at a C/N ratio of 20 for 48 h, reaching 8.92 × 108cell mL−1. W. anomalusRZWP01 was the first reported yeast that can efficiently utilize nitrite. The isolation and identification of W. anomalusRZWP01 enriched the microbial resources of nitrite-degrading microorganisms and provided functional microorganisms for the water treatment of sustainable aquaculture.

Aqueous zinc-ion batteries (AZIBs) have demonstrated significant potential for storing energy in power grids due to their high theoretical specific capacity, eco-friendliness, and safer operation. However, the practical implementation of AZIBs faces obstacles such as the growth of zinc dendrites, hydrogen evolution reaction (HER), and corrosion of zinc metal. In this study, a conjugated organic polymer (COP) named PYBZ is utilized as an interface layer for zinc metal using a scraping method. The PYBZ coating not only mitigates the corrosion of zinc metal and HER but also promotes deposition along the Zn (002) plane and suppresses the growth of zinc dendrites. Consequently, the PYBZ@Zn symmetric battery demonstrates an extended cycling lifespan over 1900 h at 1 mA cm−2and higher average Coulombic efficiency (CE) of 98.3 % over 450 cycles in PYBZ@Zn||Cu asymmetric battery at 0.5 mA cm−2. PYBZ@Zn||MnO2full battery also exhibits higher capacity and superior cycling stability compared to Zn||MnO2full battery. This study provides valuable insights into COP design and construction techniques for highly reversible Zn anodes as well as other areas involving metal ion batteries like the design of solid electrolyte.

Materials with a room-temperature phosphorescence (RTP) property have wide application fields. For practical applications, it is highly desirable that only a small amount of RTP phosphors was attached to the widely used hydrophobic polymers, especially the coating polymers, to avoid impairing the physical properties of polymers while reserving RTP function. In this work, aqueous latexes of copolymers of acrylate and vinylidene chloride (VDC) were prepared through the green emulsion polymerization in the presence of an extremely small amount of RTP phosphor (0.062 wt % relative to the solid), N-hydroxyethyl 4-bromo-1,8-naphthalimide (HBN). Once being excited, the hydrophobic soft films formed from these latexes were dual-emissive, including a broad fluorescence emission in the region of ultraviolet and blue light and a broad RTP emission signal covering from 530 to 690 nm under ambient condition (air, room temperature). X-ray diffraction and Differential scanning calorimetry characterizations demonstrated that the obtained acrylate–VDC copolymers had a very low crystallization degree, and their glass transition temperatures were around, even less than room temperature, much less than the ever-used rigid hydrophobic polymers for supporting RTP phosphors. The HBN-doped acrylate–VDC copolymer films emitted an orange color under UV light, and the emission color could respond reversibly to medium polar to nonpolar solvents.

Based on the elastohydrodynamic theory, the nonlinear dynamic behavior of worn oil-lubricated rolling bearings is explored, and the dynamic response including the effect of trajectory of the axis center, the accelerated speed, and the film thickness is analyzed. The worn model is represented by the worn depth. The discrete iterative method and implicit Euler method are combined to solve the dynamic equations. In numerical examples, the trajectory of the axis center, the accelerated speed and the film thickness under different worn depths are discussed. It is found that the stabilized point shows significant variation with the worn depth, and the wear effect is also quite related with the rolling speed. The trajectory of the axis center of worn bearing subjected to a step load is also examined in detail.

Thermoelectric properties of n-type LnTSbO (Ln = lanthanides and T = Zn, Mn) were firstly investigated by the first-principles method and the semi-classical Boltzmann theory. The results show that a multiple-valley structure appears around the bottom of conduction band. The valley with a high band degeneracy consists of the bands with a weak band dispersion, leading to large magnitudes of the Seebeck coefficient but low electrical conductivity. The valley with a low band degeneracy is made up of the bands with an intense band dispersion, resulting in a high electrical conductivity but small magnitudes of the Seebeck coefficient. The thermoelectric properties are dominated by the energy difference, ΔE, between the valleys. The ΔEvalue of LnZnSbO linearly increases with the ionic radius of Ln. The thermoelectric properties are thus effectively modulated by varying the lanthanides. As a result, LnZnSbO (Ln = Ce-Nd) with the moderate values of ΔEshows a better thermoelectric performance. The multiple-valley effect is an effective way to modulate the thermoelectric properties of n-type LnTSbO.

All-optical interrogation of population neuron activity is a promising approach to deciphering the neural circuit mechanisms supporting brain functions. However, this interrogation is currently limited to local brain areas. Here, we incorporate patterned photo-stimulation into light-sheet microscopy, allowing simultaneous targeted optogenetic manipulation and brain-wide monitoring of the neuronal activities of head-restrained behaving larval zebrafish. Using this system, we photo-stimulate arbitrarily selected neurons (regions as small as ~10-20 neurons in 3D) in zebrafish larvae with pan-neuronal expression of a spectrally separated calcium indicator, GCaMP6f, and an activity actuator, ChrimsonR, and observe downstream neural circuit activation and behavior generation. This approach allows us to dissect the causal role of neural circuits in brain functions and behavior generation.

A tannic acid-Fe coordination compound has been prepared via a simple mechanochemical method. The compound could be used as precursors for the fabrication of porous carbon, which was successfully applied as adsorbent for CO2capture. The obtained porous adsorbent, NFePC-10-A, exhibited relatively high CO2uptake capacities of 5.8 and 3.4 mmol g–1at 0 and 25 °C, respectively. In addition, the initial isosteric heat of adsorption and selectivity for CO2/N2were as high as 63.16 kJ mol–1and 22.7 (0 °C). Meanwhile, the adsorbent underwent an efficient reusability, indicating a good potential for practical use. This feasible strategy might provide a novel precursor for the large-scale production of bio-derived carbonaceous adsorbents with tailored texture and porosity for CO2capture and storage.

Development of high-performance nonprecious metals and their nanocomposites as oxygen reduction electrocatalysts is critical but still challenging for fuel cells and metal–air batteries. Here, we introduce a synthetic strategy to fabricate graphite-wrapped Fe core–shell nanoparticles anchored on graphene as an efficient and stable pH-universal electrocatalyst for oxygen reduction reaction (ORR). The coordination among Fe3+, ellagic acid, and graphene oxide would drive the formation of a sandwichlike assembly, which was subsequently converted into graphene-supported Fe@graphitic carbon core–shell nanoparticles (denoted as GEF). The obtained GEFs exhibited remarkable ORR activity and durability in a wide range of pHs. Most notably, GEF pyrolized at 900 °C showed that the onset and half-wave potential at 1.01 and 0.90 V were more positive than those of a commercial Pt/C (onset and half-wave potential: 0.94 and 0.84 V) in alkaline media. Meanwhile, it also demonstrated comparable or even better activity as compared with the commercial Pt/C catalysts in acidic and neutral electrolytes.

Changes in splicing are known to affect the function and regulation of genes. We analyzed splicing events that take place during the postnatal development of the prefrontal cortex in humans, chimpanzees, and rhesus macaques based on data obtained from 168 individuals. Our study revealed that among the 38,822 quantified alternative exons, 15% are differentially spliced among species, and more than 6% splice differently at different ages. Mutations in splicing acceptor and/or donor sites might explain more than 14% of all splicing differences among species and up to 64% of high-amplitude differences. A reconstructed trans-regulatory network containing 21 RNA-binding proteins explains a further 4% of splicing variations within species. While most age-dependent splicing patterns are conserved among the three species, developmental changes in intron retention are substantially more pronounced in humans.

(E)-β-Caryophyllene is a sesquiterpene compound widely distributed in plants and functions in plant defence. However, little is known about the sequence and function of (E)-β-caryophyllene synthase in lima bean (Phaseolus lunatus). Here, we report a new full-length cDNA (PlCAHS) encoding (E)-β-caryophyllene synthase, a possible key enzyme of plant defence. The cDNA of PlCAHScontains an open reading frame of 1 761 bp, encoding a protein of 586 amino acids with a predicted mass of 67.95 kDa. The deduced amino acid sequence shows 52% identity with sesquiterpene synthase MtCAHS of Medicago truncatula.Based on phylogenetic analysis, PlCAHSis classified as the terpene synthases (TPS)-a subfamily. The recombinant enzyme, expressed in Escherichia coli,catalysed the formation of a major product (E)-β-caryophyllene (82%) and a minor product α-humulene (18%) from farnesyl diphosphate. Real-time quantitative PCR (qRT-PCR) analysis found that the PlCAHStranscript was significantly up-regulated in leaves after treatment with spider mites and alamethicin (ALA), suggesting its ecological function in plant defence.

The existing Finite Rate of Innovation (FRI) sampling theory can realize the efficient measurement of Gaussian pulse streams with fixed modal functions. However, it is hard to sample that signal with variable pulse width factors by a sub-Nyquist rate. To get around this challenge, we propose an extended FRI sampling method based on Taylor series expansion in this paper, where the signal is first filtered by the exponential reproducing kernel, then each pulse can be reconstructed sequentially. For a single pulse, we first prove that the pulse width factor does not interfere with the estimation process of the time delay parameter, and we also present its Cramer-Rao lower Bound (CRB). The signal Fourier coefficient can then be reformulated by the Taylor series expansion of order N − 1 to realize the decoupling of the pulse width factor before the final estimation. We derive the order limit of expansion from the perspective of numerical stability, and we also give the upper bound on the estimation error of the pulse width factor for N = 2. Simulation results show that, compared with the classical methods, the proposed state-of-the-art algorithm can achieve a higher precision reconstruction of the Gaussian pulse stream signal. [ABSTRACT FROM AUTHOR]

In this study, a g-C3N4/Ag3PO4composite Z-heterojunction photocatalyst was prepared with a simple in situ deposition method, and was first applied to the degradation of Ofloxacin (OFX). When the theoretical g-C3N4to Ag3PO4mass ratio was 1:10 (denoted as AC-10), the OFX degradation was optimal, and the degradation efficiency reached 71.9 % within 10 min. Steady state fluorescence emission spectroscopy (PL), electrochemical impedance spectroscopy (EIS), transient photocurrent (I-t) and N2adsorption-desorption (BET) studies showed that AC-10 had the best charge separation efficiency and highest specific surface area. Additionally, the effects of AC-10 dosage, OFX concentration, pH value, anions, humic acid and water source on the degradation process were also studied. A cycling experiment showed that AC-10 exhibited good stability. Three-dimensional excitation-emission matrix spectroscopy (3D EEMs), LC-MS data and ECOSAR models were used to explore the process for degradation of OFX and predict the biotoxicities of byproducts, and these results indicated that the catalyst was environmentally friendly. In addition, electron spin resonance (ESR) experiments and capture of the active species showed that photogenerated holes (h+) played a major role in the reaction. Finally, the optical properties and the energy band structure of the catalyst were analyzed by UVvis diffuse reflectance spectroscopy (DRS) and Mott-Schottky (M-S) methods, and a Z-type heterojunction charge transfer mechanism was proposed.

Passion fruit (Passiflora edulisSims) is a vine of the Passifloragenus in the Passifloraceae family. The extracted components include flavonoids and terpenoids, which have good anti-anxiety and anti-inflammatory effects in humans. In this study, we analyzed the transcriptomes of four tissues of the Zixiang variety using RNA-Seq, which provided a dataset for functional gene mining. The de novoassembly of these reads generated 96,883 unigenes, among which 61,022 unigenes were annotated (62.99% yield). In addition to its edible value, another important application of passion fruit is its medicinal value. The flavonoids and terpenoids are mainly derivatives of luteolin, apigenin, cycloartane triterpenoid saponins and other active substances in leaf extracts. A series of candidate unigenes in the transcriptome data that are potentially involved in the flavonoid and terpenoid synthesis pathways were screened using homology-based BLAST and phylogenetic analysis. The results showed that the biosynthesis of triterpenoids in passion fruit comes from the branches of the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate/1-deoxy-D-xylulose 5-phosphate (MEP/DOXP) pathways, which is different from the MVA pathway that is used in other fruit trees. Most of the candidate genes were found to be highly expressed in the leaves and/or flowers. Quantitative real-time PCR (qRT-PCR) verification was carried out and confirmed the reliability of the RNA-Seq data. Further amplification and functional analysis of these putative unigenes will provide additional insight into the biosynthesis of flavonoids and terpenoids in passion fruit.

An ultrathin composite polymer electrolyte based on a novel poly(cyclocarbonate-ether) matrix, reinforced with 3D functional skeleton, and co-plasticized by IL and LLZTO, possessed good mechanical strength and electrochemical stability.

Micron-sized Si-based materials have gained much attention recently in the pursuit of high-performance and low-cost lithium-ion battery (LIBs). However, huge volume variation and poor conductivity induce a rapid performance decline of Si microparticles. Herein, porous silicon microsphere segregated in graphene and carbon nanotube network (pSi/HCNT/rGO) is constructed by one-step hybrid and reduction self-assembly strategy. Carbon nanotubes provide the “safety belt” for the entire structure to block aggregation between rGO layers. The hierarchical porous structure composed by intrinsic pore structure of pSi and flexible carbon network effectively buffers the volume expansion and ensures the structural and interface stability in the lithium storage process, which also delivers multiple conductive pathways to boost Li+/e−migration efficiency. Proper configuration design leads to high charging capacity of 2319 mAh g−1at 0.1 A g−1, exceptional initial Coulombic efficiency of 87.5 % (vs pSi of 55.8 %) and stable long cycle performance of 583 mAh g−1after 400 cycles at 5 A g−1when pSi/HCNT/rGO applying in half battery. The pSi/HCNT/rGO||LiFePO4(LFP) full battery also shows the capacity maintenance of 96 % after 150 cycles at 1 C.

AbstractThe drag coefficient is important in meteorological studies of the boundary layer because it describes the air–sea momentum flux. Eight drag coefficient schemes were assessed. These parametrizations were compared taking into account data from in situand laboratory observations. The drag coefficients determined using three schemes were consistent with the level-off phenomenon, supported by the results of laboratory studies. The drag coefficient determined using one scheme decreased at wind speeds higher than approximately 30 m s−1, in agreement with indirect measurements under typhoon conditions. In contrast, the drag coefficients determined using the other four schemes increased with wind speed, even under high wind regimes. Sensitivity tests were performed using simulations of two super typhoons in the Weather Research and Forecasting model. While the typhoon tracks were negligibly sensitive to the parametrization used, the typhoon intensities (the maximum 10-m wind speed and the minimum sea level pressure), sizes, and structure, were very sensitive to it.

Aim:Duchenne muscular dystrophy (DMD) is an X-linked genetic muscular disorder with no effective treatment at present. Mesenchymal stem cell (MSC) transplantation has been used to treat DMD, but the efficiency is low. Our previous studies show that activation of Wnt3a signaling promotes myogenic differentiation of MSCs in vitro. Here we report an effective MSC transplantation therapy in mdx mice by activation of Wnt3a signaling.Methods:MSCs were isolated from mouse bone marrow, and pretreated with Wnt3a-conditioned medium (Wnt3a-CM), then transplanted into mdx mice. The recipient mice were euthanized at 4, 8, 12, 16 weeks after the transplantation, and muscle pathological changes were examined. The expression of dystrophin in muscle was detected using immunofluorescence staining, RT-PCR and Western blotting.Results:Sixteen weeks later, transplantation of Wnt3a-pretreated MSCs in mdx mice improved the characteristics of dystrophic muscles evidenced by significant reductions in centrally nucleated myofibers, the variability range of cross-sectional area (CSA) and the connective tissue area of myofibers. Furthermore, transplantation of Wnt3a-pretreated MSCs in mdx mice gradually and markedly increased the expression of dystrophin in muscle, and improved the efficiency of myogenic differentiation.Conclusion:Transplantation of Wnt3a-pretreated MSCs in mdx mice results in long-term amelioration of the dystrophic phenotype and restores dystrophin expression in muscle. The results suggest that Wnt3a may be a promising candidate for the treatment of DMD.

In studies of development and aging, the expression of many genes has been shown to undergo drastic changes at mRNA and protein levels. The connection between mRNA and protein expression level changes, as well as the role of posttranscriptional regulation in controlling expression level changes in postnatal development and aging, remains largely unexplored. Here, we survey mRNA and protein expression changes in the prefrontal cortex of humans and rhesus macaques over developmental and aging intervals of both species’ lifespans. We find substantial decoupling of mRNA and protein expression levels in aging, but not in development. Genes showing increased mRNA/protein disparity in primate brain aging form expression patterns conserved between humans and macaques and are enriched in specific functions involving mammalian target of rapamycin (mTOR) signaling, mitochondrial function and neurodegeneration. Mechanistically, aging-dependent mRNA/protein expression decoupling could be linked to a specific set of RNA binding proteins and, to a lesser extent, to specific microRNAs. Increased decoupling of mRNA and protein expression profiles observed in human and macaque brain aging results in specific co-expression profiles composed of genes with shared functions and shared regulatory signals linked to specific posttranscriptional regulators. Genes targeted and predicted to be targeted by the aging-dependent posttranscriptional regulation are associated with biological processes known to play important roles in aging and lifespan extension. These results indicate the potential importance of posttranscriptional regulation in modulating aging-dependent changes in humans and other species.