Membrane decorated with biocides is an effective way to suppress biofilm growth. However, their immediate biocidal effect usually suffers from a significant decline due to the irreversible consumption of the biocides. Here, a smart nanofiltration membrane is reported with rechargeable antibacterial capability that is fabricated by a facile interfacial polymerization via 3-aminophenylboronic acid and trimesoyl chloride on a polysulfone substrate. Biocides bearing diol groups can be grafted onto the membrane surface under neutral/alkaline condition and then released from the surface under acidic environment, due to the pH-responsive feature of boronate ester complexes. The resultant membrane exhibits integrated properties of fast bacterial inactivating efficiency, rechargeable antibacterial capability, and impressive stability. In addition, the achieved membrane shows remarkable separation efficiency to dye/monovalent salt system. The successful fabrication of the membrane with rechargeable anti-bacterial property provides new insights into the development of pH-responsive and sustainable antibacterial membranes. 相似文献
Using time-series data analysis for stock-price forecasting (SPF) is complex and challenging because many factors can influence stock prices (e.g., inflation, seasonality, economic policy, societal behaviors). Such factors can be analyzed over time for SPF. Machine learning and deep learning have been shown to obtain better forecasts of stock prices than traditional approaches. This study, therefore, proposed a method to enhance the performance of an SPF system based on advanced machine learning and deep learning approaches. First, we applied extreme gradient boosting as a feature-selection technique to extract important features from high-dimensional time-series data and remove redundant features. Then, we fed selected features into a deep long short-term memory (LSTM) network to forecast stock prices. The deep LSTM network was used to reflect the temporal nature of the input time series and fully exploit future contextual information. The complex structure enables this network to capture more stochasticity within the stock price. The method does not change when applied to stock data or Forex data. Experimental results based on a Forex dataset covering 2008–2018 showed that our approach outperformed the baseline autoregressive integrated moving average approach with regard to mean absolute error, mean squared error, and root-mean-square error. 相似文献
This study aims to propose a more efficient hybrid algorithm to achieve favorable control performance for uncertain nonlinear systems. The proposed algorithm comprises a dual function-link network-based multilayer wavelet fuzzy brain emotional controller and a sign(.) functional compensator. The proposed algorithm estimates the judgment and emotion of a brain that includes two fuzzy inference systems for the amygdala network and the prefrontal cortex network via using a dual-function-link network and three sub-structures. Three sub-structures are a dual-function-link network, an amygdala network, and a prefrontal cortex network. Particularly, the dual-function-link network is used to adjust the amygdala and orbitofrontal weights separately so that the proposed algorithm can efficiently reduce the tracking error, follow the reference signal well, and achieve good performance. A Lyapunov stability function is used to determine the adaptive laws, which are used to efficiently tune the system parameters online. Simulation and experimental studies for an antilock braking system and a magnetic levitation system are presented to verify the effectiveness and advantage of the proposed algorithm.
The efficiency of sodium sulfide-assisted alkaline pulping for cellulose preparation from Oryza sativa L. rice straw in Vietnam for enzymatic saccharification was investigated. The response surface methodology was used for the determination of optimal technological parameters of alkaline pulping such as active alkali dosage, temperature and time. The optimal technological parameters were established to be active alkali dosage of 7%, treatment temperature of 100 °C and treatment time of 120 min. At these regimes, a maximal sugar yield of 51.8% (over dry rice straw) was obtained. It meant that the saccharification efficiency up to 97.1% could be achieved by using sodium sulfide-assisted alkaline pretreatment method. Addition of sodium sulfide into alkaline pretreatment resulted in higher sugar yield, higher level of depolymerization of lignin and less loss of cellulose. Moreover, liquid hydrolyzate after enzymatic hydrolysis was analyzed by HPLC to determine the compositions of sugar mixture. The fiber morphology in pretreated biomass solid was also revealed by SEM. 相似文献
Mutations in a gene encoding a multitransmembrane protein, termed presenilin 1 (PS1), are causative in the majority of early-onset cases of AD. To determine the topology of PS1, we utilized two strategies: first, we tested whether putative transmembranes are sufficient to export a protease-sensitive substrate across a lipid bilayer; and second, we examined the binding of antibodies to specific PS1 epitopes in cultured cells selectively permeabilized with the pore-forming toxin, streptolysin-O. We document that the "loop," N-terminal, and C-terminal domains of PS1 are oriented toward the cytoplasm. 相似文献
Salient structural elements are ubiquitous in natural textures, and their distribution exhibits some stochastic distribution features. Current texture synthesis algorithms can neither preserve the integrity of the elements nor capture this distributive information. We present an algorithm to treat this high-level visual information. Here, we address the issue by taking specific care of the structural elements. Our texture synthesis process grows the target texture one structural element at a time. A Markov ... 相似文献