Search

In this paper, a noise test on the viaduct of a city in China was conducted to analyze the effect of trapezoidal sleepers, sound barriers, and the combination of trapezoidal sleepers and sound barriers on the spatial distribution characteristics of overall noise. A statistical energy analysis model was established to analyze the influence of these sound barrier configurations. The results show that at the speed of 60 km/h, the trapezoidal sleeper track can reduce the overall noise by 2.0 dB to 6.0 dB. The upright-type sound barrier can reduce the overall noise by 10.3 dB to 13.2 dB, with the most significant frequency band of noise reduction above 800 Hz; the combination of the trapezoidal sleeper and sound barrier has a significant noise reduction effect above 31.5 Hz, and the overall noise reduction can reach 13.8 dB to 23.1 dB. The high-frequency wheel-rail noise decays faster with distance, while the low-frequency bridge structure noise decays slowly with distance. When sound barriers are set up on both sides of the viaduct, the sound pressure level at the near field point is further reduced by 3.3 dB to 5.2 dB compared with sound barriers on only one side. Compared with a section with no sound barriers, the noise inside the sound barriers is about 1.2 dB higher than when the sound barriers are set on one side or both sides of the viaduct.

N-doped T-Nb2O5 microflowers (N-Nb2O5) assembled by [001]-oriented nanoflakes are prepared. The special structure of N-Nb2O5 endows them with improved electronic conductivity and pseudocapacitive behavior, leading to superior Li+ storage properties.

As an important free energy source, the membrane voltage (V m ) regulates many essential physiological processes in bacteria. However, in comparison with eukaryotic cells, knowledge of bacterial electrophysiology is very limited. Here, we developed a set of novel genetically encoded bacterial V m sensors which allow single-cell recording of bacterial V m dynamics in live cells with high temporal resolution. Using these new sensors, we reveal the electrically “excitable” and “resting” states of bacterial cells dependent on their metabolic status. In the electrically excitable state, frequent hyperpolarization spikes in bacterial V m are observed, which are regulated by Na + /K + ratio of the medium and facilitate increased antibiotic tolerance. In the electrically resting state, bacterial V m displays significant cell-to-cell heterogeneity and is linked to the cell fate after antibiotic treatment. Our findings demonstrate the potential of our newly developed voltage sensors to reveal the underpinning connections between bacterial V m and antibiotic tolerance.

Underwater acoustic target recognition is an important aspect of underwater acoustic research. In recent years, machine learning has been developed continuously, which is widely and effectively applied in underwater acoustic target recognition. In order to acquire good recognition results and reduce the problem of overfitting, Adequate data sets are essential. However, underwater acoustic samples are relatively rare, which has a certain impact on recognition accuracy. In this paper, in addition of the traditional audio data augmentation method, a new method of data augmentation using generative adversarial network is proposed, which uses generator and discriminator to learn the characteristics of underwater acoustic samples, so as to generate reliable underwater acoustic signals to expand the training data set. The expanded data set is input into the deep neural network, and the transfer learning method is applied to further reduce the impact caused by small samples by fixing part of the pre-trained parameters. The experimental results show that the recognition result of this method is better than the general underwater acoustic recognition method, and the effectiveness of this method is verified.

As an important free energy source, the membrane voltage (Vm) regulates many essential physiological processes in bacteria. However, in comparison with eukaryotic cells, knowledge of bacterial electrophysiology is very limited. Here, we developed a set of novel genetically encoded bacterial Vm sensors which allow single-cell recording of bacterial Vm dynamics in live cells with high temporal resolution. Using these new sensors, we reveal the electrically “excitable” and “resting” states of bacterial cells dependent on their metabolic status. In the electrically excitable state, frequent hyperpolarization spikes in bacterial Vm are observed, which facilitates increased antibiotic tolerance. In the electrically resting state, bacterial Vm displays significant cell-to-cell heterogeneity and is linked to the cell fate after antibiotic treatment.

In the presence of multiple sources, the performance of direction-of-arrival (DOA) estimation based on beam power maximization is susceptible to the energy leaking from the interference beams to the target beam, especially in the case that the signal of interest (SOI) is quite weak. To address this issue, a robust wideband DOA estimation method is proposed in this paper. Unlike those conventional high-resolution methods which mitigate the influence of energy leakage by reducing beamwidths and sidelobe levels, the proposed method achieves this by directly reconstructing the element-space data to approach the received hydrophone data of the single-source scenario containing only the SOI. Element-space data reconstruction (ESDR) for the SOI is achieved by removing the element-space waveforms of all the interference signals from the received hydrophone data. Moreover, an iterative algorithm is developed to adaptively extract the element-space waveform of each interference signal, without requiring the prior information of the array amplitude response coefficients and hydrophone coordinates of a distorted towed array. Simulation results show that the proposed method outperforms its counterparts in terms of estimation accuracy for a multi-source scenario. Meanwhile, the DOA estimation performance of the proposed method in a multi-source environment is close to that obtained by the beam power maximization method in the single-source scenario, even if the signal-to-interference ratio (SIR) is as low as −25 dB. At-sea experimental results prove that, even though the number of signal sources is as many as seven and the SOI is contaminated by real ocean ambient noise, the proposed method still achieves a better DOA estimation performance compared to existing state-of-the-art methods.

This paper focuses on the automatic target recognition (ATR) method based on ship-radiated noise and proposes an underwater acoustic target recognition (UATR) method based on ResNet. In the proposed method, a multi-window spectral analysis (MWSA) method is used to solve the difficulty that the traditional time–frequency (T–F) analysis method has in extracting multiple signal characteristics simultaneously. MWSA generates spectrograms with different T–F resolutions through multiple window processing to provide input for the classifier. Because of the insufficient number of ship-radiated noise samples, a conditional deep convolutional generative adversarial network (cDCGAN) model was designed for high-quality data augmentation. Experimental results on real ship-radiated noise show that the proposed UATR method has good classification performance.

Description, Bacteria use subcellular proteinaceous liquid droplets to survive stress., Liquid-liquid phase separation is emerging as a crucial phenomenon in several fundamental cell processes. A range of eukaryotic systems exhibit liquid condensates. However, their function in bacteria, which, in general, lack membrane-bound compartments, remains less clear. Here, we used high-resolution optical microscopy to observe single bacterial aggresomes, nanostructured intracellular assemblies of proteins, to undercover their role in cell stress. We find that proteins inside aggresomes are mobile and undergo dynamic turnover, consistent with a liquid state. Our observations are in quantitative agreement with phase-separated liquid droplet formation driven by interacting proteins under thermal equilibrium that nucleate following diffusive collisions in the cytoplasm. We have found aggresomes in multiple species of bacteria and show that these emergent, metastable liquid-structured protein assemblies increase bacterial fitness by enabling cells to tolerate environmental stresses.

Despite notable genetic influences, obesity mainly results from the overconsumption of food, which arises from the interplay of physiological, cognitive and environmental factors. In patients with obesity, eating is determined more by external cues than by internal physiological needs. However, how environmental context drives non-homeostatic feeding is elusive. Here, we identify a population of somatostatin (

After the policy was released in 2018, listed companies increased the frequency and amount of repurchases. Some studies believe that managers will give up long-term investment which is beneficial to the sustainable development of enterprises due to the short-term performance response caused by share repurchases. This paper took the repurchase firms in the high-tech industry from 2008 to 2018 as samples, it is found that the company’s share repurchase promotes R&D expenditure and will not reduce expenditure in R&D for short-term stock price reaction. Furthermore, the heterogeneity study found that in state-owned firms, the company’s share buybacks have a more significant role in promoting R&D expenditure.

The aim of the research is the design of prefabricated steel-spring floating-slab track to be applied in urban express rail transit systems. Using a developed vehicle-track dynamic-coupling equation for steel-spring floating-slab track, the effects of length, thickness, vertical damping, and use of side-mounted isolators on the floating-slab track were investigated experimentally using full-scale model and under different working conditions. The finding of the study revealed the following: (1) The prefabricated steel-spring floating-slab track can be applied to urban express rail transit, because it meets the requirements of high-speed transit while efficiently reducing noise. (2) The floating-slab track’s stability slightly increases with the increase of its length and thickness. As thickness increases, vertical displacement of the rail increases slightly, and lateral stability increases, thereby slightly improving the vehicle’s running stability. (3) When the intercity electric multiple-unit train travels along the prefabricated steel-spring floating-slab-track bed at different speeds, the wheel-axle lateral force, wheel-rail vertical force, the derailment coefficient, the wheel-weight reduction rate, and the lateral acceleration of the vehicle body are all less than the specified limits of Chinese code, thus fully meeting the safety requirements of train operation. (4) Appropriately increasing the vertical-support damping of the floating slab can improve the vehicle’s vertical dynamic performance, reduce the vertical displacement of the rail, and lower the vibration response of the floating slab. (5) Adding side-mounted vibration isolators at the joint of the floating slab could greatly improve the stability of the floating slab itself and appropriately reduce the vehicle’s vertical vibration response. Due to the optimization and establishment of relevant factors influencing the performance of prefabricated steel-string floating-slab track achieved in the study, the results obtained are particularly useful for setting safety, comfort, and stability requirements of the floating slab.

Abnormal activation of the IGF1R signaling pathway accelerates melanoma development and metastases. RNAi systems with complex cloning procedures and unsatisfactory efficiency in suppressing gene expression have become the technical difficulties that hinder their utility when studying gene knockdown. Here we established a simplified adenovirus-mediated gene knockdown system by which a single adenoviral vector carries multiple siRNA fragments that can effectively suppress IGF1R expression in melanoma cells. We first generated the adenovirus that simultaneously expresses three human or mouse siRNAs targeting IGF1R (AdRIGF1R-OK). qRT-PCR and immunofluorescence staining revealed that IGF1R expression was significantly decreased in the melanoma cells that were infected with AdRIGF1R-OK. Bioluminescence imaging showed that the size of the tumor formed by the xenografts infected with AdRIGF1R-OK was significantly smaller than that of the controls. Annexin V-FITC flow cytometry assay, immunofluorescence staining for cleaved caspase-3, and Hoechst staining showed that more cells underwent apoptosis after infection with AdRIGF1R-OK. Luciferase reporter assay, crystal violet cell viability assay, and cell-cycle analysis showed that the proliferation of melanoma cells infected with AdRIGF1R-OK was significantly decreased compared to the controls. This study demonstrates that the OK system is effective in silencing gene expression, with promising potential to treat melanoma and other diseases. Keywords: RNAi technology, gene therapy, melanoma, IGF1R, one-step knockdown system, adenovirus

A substantial body of literature believes that Chinese companies engage in aggressive tax avoidance, while the macro data show that the corporate sector is heavily taxed. This paper is focused on understanding the tax positions of the Chinese corporate sector, and addressing the conflict between macro data and corporate tax avoidance research. We construct a sample of all Chinese listed companies from 2012 to 2017 and adopt a modified cash effective tax rate (ETR) tax avoidance measurement model. We find that on average, Chinese listed companies are under-sheltering. Specifically, most companies in China do not avoid taxes, even pay higher taxes. In further study, we interpret the generation mechanism of tax under-sheltering. We conduct a grouping OLS regression to test managerial decisions for external reporting incentives. We then examine the moderating effects of corporate ownership on managerial reporting incentive. To make our explanation more robust, we discuss the effects of loss firms. Our study enriches the research on enterprises' tax avoidance and earnings management.

To acquire the enhanced underwater ship-radiated noise signal in the presence of array shape distortion in a passive sonar system, the phase difference of the line-spectrum component in ship-radiated noise is often exploited to estimate the time-delay difference for the beamforming-based signal enhancement. However, the time-delay difference estimation performance drastically degrades with decreases of the signal-to-noise ratio (SNR) of the line-spectrum component. Meanwhile, although the time-delay difference estimation performance of the high-frequency line-spectrum components is generally superior to that of the low-frequency one, the phase difference measurements of the high-frequency line-spectrum component often easily encounter the issue of modulus 2π ambiguity. To address the above issues, a novel time-frequency joint time-delay difference estimation method is proposed in this paper. The proposed method establishes a data-driven hidden Markov model with robustness to phase difference ambiguity by fully exploiting the underlying property of slowly changing the time-delay difference over time. Thus, the phase difference measurements available for time-delay difference estimation are extended from that of low-frequency line-spectrum components in a single frame to that of all detected line-spectrum components in multiple frames. By jointly taking advantage of the phase difference measurements in both time and frequency dimensions, the proposed method can acquire enhanced time-delay difference estimates even in a low SNR case. Both simulation and at-sea experimental results have demonstrated the effectiveness of the proposed method.

Reliable and efficient sensing and tracking of multiple weak or time-varying frequency line components in underwater acoustic signals is the topic of this paper. We propose a method for automatic detection and tracking of multiple frequency lines in lofargram based on hidden Markov model (HMM). Instead of being directly subjected to frequency line tracking, the whole lofargram is first segmented into several sub-lofargrams. Then, the sub-lofargrams suspected to contain frequency lines are screened. In these sub-lofargrams, the HMM-based method is used for detection of multiple frequency lines. Using image stitching and statistical model method, the frequency lines with overlapping parts detected by different sub-lofargrams are merged to obtain the final detection results. The method can effectively detect multiple time-varying frequency lines of underwater acoustic signals while ensuring the performance under the condition of low signal-to-noise ratio (SNR). It can be concluded that the proposed algorithm can provide better multiple frequency lines sensing ability while greatly reducing the amount of calculations and providing potential techniques for feature sensing and tracking processing of unattended equipment such as sonar buoys and submerged buoys.

The sparse direct adaptive equalizer (DAE) has recently attracted much attention in underwater acoustic (UWA) communications for its improved performance compared with conventional non-sparse DAEs. The recursive least squares (RLS) type sparse DAEs were barely studied, mainly due to their high complexity despite fast convergence. This letter presents several low-complexity sparse RLS algorithms for multiple-input multiple-output UWA channel equalization. The resulting fast sparse RLS DAEs are tested to be effective and outperform their non-sparse counterpart by experimental results.

One of the major track issues in urban rail transit is the rail side wear, especially at the high rail on sharp curves. The mechanism of rail side wear is very complex and has not been fully understood. This study attempts to characterize the progressive development of high rail side wear in a transit track with heavy traffic. A numerical vehicle-track model is developed based on multi-body dynamics and the modified Archard wear formula and is used to perform a parametric analysis. The side wear development trend observed in the field is in good agreement with the results calculated from the numerical mode. According to the results obtained from this study, the side wear during the life-cycle of the high rail can be approximately characterized into three stages: 1) Stage I, rail wear initiates at the gauge side corner; 2) Stage II, side wear propagates linearly; 3) Stage III, side wear propagates exponentially. The parametric analysis suggests that three maintenance activities may ease the development rate of the high rail side wear in Stage III. These include increasing the rail inclination, adjusting the track gauge on time, and restoring the rail profile of the low rail.

For the passive detection of azimuth and frequency of azimuths and frequencies of line-spectrum signals radiated from underwater weak targets, a space-frequency joint detection and tracking method based on track-before-detect (TBD) technology is proposed. This method works directly with the time sequence of frequency-azimuth (FRAZ) spectra to estimate the frequency and azimuth of line-spectrum signals. And the change of the frequency and azimuth states of a line-spectrum signal is modeled as a first-order hidden Markov process. The distribution of the FRAZ spectra of linear array received signal are derived in this paper to set the parameters of Hidden Markov Models (HMM). The FRAZ spectra at different times is joint process using Viterbi algorithm to obtain the maximum a posteriori estimation of the azimuth and frequency of line-spectrum signal. A dynamic searching method based on region segmentation and merging similar line-spectrum is designed to solve the problem of large computation of Viterbi algorithm in the detection of line-spectrum. The proposed method can make full use of the correlation between the target's information in the multi-frame FRAZ spectra to distinguish the target from the background noise. The processing results of simulation data and actual data show that the method has excellent line-spectrum detection performance at low SNR and can adapt to the complex situation such as there are multiple targets and multiple line-spectrum signals.

The least mean squares (LMS) type direct adaptive equalization (DAE) has been a favored choice in underwater acoustic communications. As the equalizer size grows, however, conventional LMS DAEs face serious challenges in both performance and complexity, which has motivated the development of the sparsity-aware alternates. By taking advantage of the sparse (non-uniform) structure of the equalizer, the so-developed DAE achieves performance improvement and/or complexity reduction. There are two families of sparsity-aware DAEs in the literature, based on the proportionate-updating (PU) principle and the zero-attracting (ZA) theory, respectively. Even though, there is no consensus on which family is a preferred choice. In this paper, the improved proportionate normalized LMS (IPNLMS) DAE designed with the PU principle and the selective ZA (SZA) NLMS DAE based on the ZA theory are compared, aiming to gain preliminary insights on the choice of the sparsity-aware DAE for practical applications. Analytical studies show the two have comparable complexity, and experimental results indicate the IPNLMS-DAE is a better choice than the SZA-NLMS-DAE, in terms of performance and maneuverability.

Objectives: Psychological pain may be helpful in conceptualizing suicidal behavior, in that high motivation to avoid pain combined with painful feelings may contribute to an increased risk of suicide. However, no experimental study has tested this hypothesis. The aim of the present study is to provide empirical evidence for the relationship between anhedonia, pain avoidance motivation, and suicidal ideation. Method: The sample comprised 40 depressed outpatients and 20 healthy control subjects. All participants completed the Beck Scale for Suicide Ideation (BSS), Beck Depression Inventory, Psychache Scale, Three-Dimensional Psychological Pain Scale, the monetary incentive delay (MID), and affective incentive delay (AID) tasks. Based on BSS scores, clinical participants were divided into high suicidal ideation (HSI) and low suicidal ideation (LSI) groups. Results: In the AID task, the HSI group had longer response times (RTs) under the reward condition than those under the punishment condition (p = .002). The LSI and control groups had shorter RTs under the reward condition compared with those under the neural condition (p < .001 and p = .008, respectively). The LSI group also had shorter RTs under the reward condition than under the punishment condition (p = .003). Pain arousal (r = -.33, p < .01) and BSS scores were significantly negatively correlated with differences in RTs between neutral and reward conditions. Pain avoidance (r = .35, p < .01) and BSS scores were positively correlated with differences in RTs between neutral and punishment conditions. Conclusions: The AID task was more sensitive than the MID task for the detection of participants' motivation in approaching hedonic experiences and avoiding pain. A suicidal mindset is manifested as decreased motivation to experience hedonia and increased motivation to avoid pain, which could be strong predictors of suicidal behavior. (C) 2013 Wiley Periodicals, Inc.

Target dimension is important information in underwater target classification. An intrinsic mode characteristic extraction method in underwater cylindrical shell acoustic radiation was studied in this paper based on the mechanism of shell vibration to gain the information about its dimension instead of accurate inversion processing. The underwater cylindrical shell vibration and acoustic radiation were first analyzed using mode decomposition to solve the wave equation. The characteristic of acoustic radiation was studied with different cylindrical shell lengths, radii, thickness, excitation points and fine structures. Simulation results show that the intrinsic mode in acoustic radiation spectrum correlates closely with the geometry dimensions of cylindrical shells. Through multifaceted analysis, the strongest intrinsic mode characteristic extracted from underwater shell acoustic radiated signal was most likely relevant to the radiated source radius. Then, partial information about unknown source dimension could be gained from intrinsic mode characteristic in passive sonar applications for underwater target classification. Experimental data processing results verified the effectiveness of the method in this paper.

The analysis of underwater acoustic signals, especially ship-radiated noise received by passive sonar, is of great importance in theelds of defense, military, and scientic research. In this paper, we investigate multiple kernel learning graph embedding using auditory model features in the application of ship-radiated noise feature extraction. We use an auditory model to get auditory model features for each signal sample. In order to have more effective features, iterative multiple kernel learning methods are adopted to conduct dimensionality reduction. Validated by experiments, the proposed method outperforms ordinary kernel-based graph embedding methods. The experiments show that the multiple kernel learning method can automatically choose relatively appropriate kernel combinations in dimensionality reduction for ship-radiated noise using auditory model features. In addition, some worthwhile conclusions can be drawn from our experiments and analysis.