The Application of Continuous Wavelet Transform Based Foreground Subtraction Method in 21 cm Sky Surveys

We propose a continuous wavelet transform based non-parametric foreground subtraction method for the detection of redshifted 21 cm signal from the epoch of reionization. This method works based on the assumption that the foreground spectra are smooth in frequency domain, while the 21 cm signal spectrum is full of saw-tooth-like structures, thus their characteristic scales are significantly different. We can distinguish them in the wavelet coefficient space easily and perform the foreground subtraction. Compared with the traditional spectral fitting based method, our method is more tolerant to complex foregrounds. Furthermore, we also find that when the instrument has uncorrected response error, our method can also work significantly better than the spectral fitting based method. Our method can obtain similar results with the Wp smoothing method, which is also a non-parametric method, but our method consumes much less computing time.Comment: Accepted by Ap

Revealing the Mechanical Properties of Metal Pillars Using Experimental Methods and Molecular Dynamic Simulations

The mechanical properties of nano-crystalline copper pillars were investigated by both experimental methods and Molecular Dynamic Simulations in this study. Electron beam lithography and electroplating were used to fabricate the nano-crystalline copper pillars with various cross-sectional geometries, namely solid core, hollow, c-shaped, and x-shaped. These as-fabricated copper pillars possess three different average grain sizes, which were achieved by changing the compositions of the plating solution. Uniaxial micro-compression tests were applied to deform these nano-crystalline columnar structures. Classical Hall-Petch relationship was observed between the large-grain specimens and medium-grain specimens. An inversed Hall-Petch relationship emerged as the grain size continued to go down to the small grain size region. The mechanical behavior exhibited no signs of sensitivity to the cross-sectional geometries. To understand the deformation mechanisms, Molecular Dynamic Simulations were performed on nano- crystalline copper pillars with different dimensions. The as-constructed models displayed different mechanical behaviors under compressive and tensile deformation. This so-called compression-tension asymmetry was believed to be associated with free surface alongside the nano-crystalline pillars, where the free surface energy made opposite contributions under compression and tension. An inversed Hall-Petch trend was also observed between the nano-crystalline copper columnar structure with the grain size of 13 and 6 nm

Chandra Observation of a Weak Shock in the Galaxy Cluster A2556

Based on a 21.5 ks \chandra\ observation of A2556, we identify an edge on the surface brightness profile (SBP) at about 160$h_{71}^{-1}$ kpc northeast of the cluster center, and it corresponds to a shock front whose Mach number $\mathcal{M}$ is calculated to be $1.25_{-0.03}^{+0.02}$. No prominent substructure, such as sub-cluster, is found in either optical or X-ray band that can be associated with the edge, suggesting that the conventional super-sonic motion mechanism may not work in this case. As an alternative solution, we propose that the nonlinear steepening of acoustic wave, which is induced by the turbulence of the ICM at the core of the cluster, can be used to explain the origin of the shock front. Although nonlinear steepening weak shock is expected to occur frequently in clusters, why it is rarely observed still remains a question that requires further investigation, including both deeper X-ray observation and extensive theoretical studies.Comment: 15 pages, 4 figures, accepted by Ap

Pruning convolutional neural networks with an attention mechanism for remote sensing image classification

Despite the great success of Convolutional Neural Networks (CNNs) in various visual recognition tasks, the high computational and storage costs of such deep networks impede their deployments in real-time remote sensing tasks. To this end, considerable attention has been given to the filter pruning techniques, which enable slimming deep networks with acceptable performance drops and thus implementing them on the remote sensing devices. In this paper, we propose a new scheme, termed Pruning Filter with Attention Mechanism (PFAM), to compress and accelerate traditional CNNs. In particular, a novel correlation-based filter pruning criterion, which explores the long-range dependencies among filters via an attention module, is employed to select the to-be-pruned filters. Distinct from previous methods, the less correlated filters are first pruned after the pruning stage in the current training epoch, and they are reconstructed and updated during the next training epoch. Doing so allows manipulating input data with the maximum information preserved when executing the original training strategy such that the compressed network model can be obtained without the need for the pretrained model. The proposed method is evaluated on three public remote sensing image datasets, and the experimental results demonstrate its superiority, compared to state-of-the-art baselines. Specifically, PFAM achieves a 0.67% accuracy improvement with a 40% model-size reduction on the Aerial Image Dataset (AID) dataset, which is impressive

Direct parameter inference from global EoR signal with Bayesian statistics

In the observation of sky-averaged HI signal from Epoch of Reionization (EoR), model parameter inference can be a computation-intensive work, which makes it hard to perform a direct one-stage model parameter inference by using Markov Chain Monte Carlo (MCMC) sampling method in Bayesian framework. Instead, a two-stage inference is usually used, i.e. the parameters of some characteristic points on the EoR spectrum model are first estimated, which are then used as the input to estimate physical model parameters further. However, some previous works had noticed that this kind of method could bias results, and it could be meaningful to answer the question of whether it is feasible to perform direct one-stage MCMC sampling and obtain unbiased physical model parameter estimations. In this work, we studied this problem and confirmed the feasibility. We find that unbiased estimations to physical model parameters can be obtained with a one-stage direct MCMC sampling method. We also study the influence of some factors that should be considered in practical observations to model parameter inference. We find that a very tiny amplifier gain calibration error (10−5 relative error) with complex spectral structures can significantly bias the parameter estimation; the frequency-dependent antenna beam and geographical position can also influence the results, so that should be carefully handled

One-step of tryptophan attenuator inactivation and promoter swapping to improve the production of L-tryptophan in Escherichia coli

<p>Abstract</p> <p>Background</p> <p>L-tryptophan is an aromatic amino acid widely used in the food, chemical and pharmaceutical industries. In <it>Escherichia coli</it>, L-tryptophan is synthesized from phosphoenolpyruvate and erythrose 4-phosphate by enzymes in the shikimate pathway and L-tryptophan branch pathway, while L-serine and phosphoribosylpyrophosphate are also involved in L-tryptophan synthesis. In order to construct a microbial strain for efficient L-tryptophan production from glucose, we developed a one step tryptophan attenuator inactivation and promoter swapping strategy for metabolic flux optimization after a base strain was obtained by overexpressing the <it>tktA</it>, mutated <it>trpE </it>and <it>aroG </it>genes and inactivating a series of competitive steps.</p> <p>Results</p> <p>The engineered <it>E. coli </it>GPT1002 with tryptophan attenuator inactivation and tryptophan operon promoter substitution exhibited 1.67 ~ 9.29 times higher transcription of tryptophan operon genes than the control GPT1001. In addition, this strain accumulated 1.70 g l^-1L-tryptophan after 36 h batch cultivation in 300-mL shake flask. Bioreactor fermentation experiments showed that GPT1002 could produce 10.15 g l^-1L-tryptophan in 48 h.</p> <p>Conclusions</p> <p>The one step inactivating and promoter swapping is an efficient method for metabolic engineering. This method can also be applied in other bacteria.</p

Asynchronous switching control for fuzzy Markov jump systems with periodically varying delay and its application to electronic circuits

This article focuses on addressing the issue of asynchronous H∞ control for Takagi-Sugeno (T-S) fuzzy Markov jump systems with generally incomplete transition probabilities (TPs). The delay is assumed to vary periodically, resulting in one monotonically increasing interval and one monotonically decreasing interval during each period. Meanwhile, a new Lyapunov-Krasovskii functional (LKF) is devised, which depends on membership functions (MFs) and two looped functions formulated for the monotonic intervals. Since the modes and TPs of the original system are assumed to be unavailable, an asynchronous switching fuzzy controller on the basis of hidden Markov model is proposed to stabilize the fuzzy Markov jump systems (FMJSs) with generally incomplete TPs. Consequently, a stability criterion with improved practicality and reduced conservatism is derived, ensuring the stochastic stability and H∞ performance of the closed-loop system. Finally, this technique is employed to the tunnel diode circuit system, and a comparison example is given, which verifies the practicality and superiority of the method