Multi-channel broadband optical chaos generation assisted by phase modulation and CFBG feedback.

In this paper, we propose a novel and simple multi-channel broadband optical chaos generation scheme based on phase modulation and chirped fiber Bragg grating (CFBG). Firstly, phase modulation is introduced to generate more new frequency components to broaden the spectrum of the phase chaos. Meanwhile, the accumulated dispersion from CFBG distorts the intensity chaos, converts phase chaos to intensity chaos, and weakens the laser relaxation oscillation. This process would lead to energy redistribution in the power spectrum, effectively increasing the chaotic bandwidth. Then, the wavelength detuning between CFBG and the semiconductor laser is introduced to enhance the chaotic bandwidth further. The experiment results show that the 10 dB bandwidths of the five channels are up to 31.0 GHz, 34.3 GHz, 36.3 GHz, 40 GHz, and 40 GHz, respectively. Note that the maximum bandwidth of the PD in our experiment is limited to 40 GHz. In addition, the multi-channel chaotic signals obtained from the experiment system are used to generate multi-channel physical random numbers. After the post-processing operations, the total rate of five parallel high-speed physical random number generation channels is 4.64 Tbit/s (160 GSa/s × 5bit × 1 channel + 160 GSa/s × 6bit × 4 channels). As far as we know, this is the highest record of using external cavity feedback semiconductor lasers to generate random numbers, which has great potential to meet the security requirements of next-generation Tbit/s optical communication systems.

Can three-dimensional nitrate structure be reconstructed from surface information with artificial intelligence? - A proof-of-concept study.

Nitrate is one of the essential variables in the ocean that is a primary control of the upper ocean pelagic ecosystem. Its three-dimensional (3D) structure is vital for understanding the dynamic and ecosystem. Although several gridded nitrate products exist, the possibility of reconstructing the 3D structure of nitrate from surface data has never been exploited. In this study, we employed two advanced artificial intelligence (AI) networks, U-net and Earthformer, to reconstruct nitrate concentration in the Indian Ocean from surface data. Simulation from an ecosystem model was utilized as the labeling data to train and test the AI networks, with wind vectors, wind stress, sea surface temperature, sea surface chlorophyll-a, solar radiation, and precipitation as the input. We compared the performance of two networks and different pre-processing methods. With the input features decomposed into climatology and anomaly components, the Earthformer achieved optimal reconstruction results with a lower normalized mean square error (NRMSE = 0.1591), spatially and temporally, outperforming U-net (NRMSE = 0.2007) and the climatology prediction (NRMSE = 0.2089). Furthermore, Earthformer was more capable of identifying interannual nitrate anomalies. With a network interpretation technique, we quantified the spatio-temporal importance of every input feature in the best case (Earthformer with decomposed inputs). The influence of different input features on nitrate concentration in the adjacent Java Sea exhibited seasonal variation, stronger than the interannual one. The feature importance highlighted the role of dynamic factors, particularly the wind, matching our understanding of the dynamic controls of the ecosystem. Our reconstruction and network interpretation technique can be extended to other ecosystem variables, providing new possibilities in studies of marine environment and ecology from an AI perspective.

Enhancing the Enantioselectivity and Catalytic Efficiency of Esterase from Bacillus subtilis for Kinetic Resolution of l-Menthol through Semirational Design.

Enzymatic kinetic resolution is a promising way to produce l-menthol. However, the properties of the reported biocatalysts are still unsatisfactory and far from being ready for industrial application. Herein, a para-nitrobenzylesterase (pnbA) gene from Bacillus subtilis was cloned and expressed to produce l-menthol from d,l-menthyl acetate. The highest enantiomeric excess (ee) value of the product generated by pnbA was only approximately 80%, with a high conversion rate (47.8%) of d,l-menthyl acetate with the help of a cosolvent, indicating high catalytic activity but low enantioselectivity (E = 19.95). To enhance the enantioselectivity and catalytic efficiency of pnbA to d,l-menthyl acetate in an organic solvent-free system, site-directed mutagenesis was performed based on the results of molecular docking. The F314E/F315T mutant showed the best catalytic properties (E = 36.25) for d,l-menthyl acetate, with 92.11% ee and 30.58% conversion of d,l-menthyl acetate. To further improve the properties of pnbA, additional mutants were constructed based on the structure-guided triple-code saturation mutagenesis strategy. Finally, four mutants were screened for the best enantioselectivity (ee > 99%, E > 300) and catalytic efficiency at a high substrate concentration (200 g/L) without a cosolvent. This work provides several generally applicable biocatalysts for the industrial production of l-menthol.

Experimental demonstration of 201.6-Gbit/s coherent probabilistic shaping QAM transmission with quantum noise stream cipher over a 1200-km standard single mode fiber.

A probabilistic shaping (PS) quadrature amplitude modulation (QAM) based on Y-00 quantum noise stream cipher (QNSC) has been proposed. We experimentally demonstrated this scheme with data rate of 201.6Gbit/s over a 1200-km standard single mode fiber (SSMF) under a 20% SD-FEC threshold. Accounting for the 20% FEC and 6.25% pilot overhead, the achieved net data rate is ∼160Gbit/s. In the proposed scheme, a mathematical cipher (Y-00 protocol) is utilized to convert the original low-order modulation PS-16 (22 × 22) QAM into ultra-dense high-order modulation PS-65536 (28 × 28) QAM. Then, the physical randomness of quantum (shot) noise at photodetection and amplified spontaneous emission (ASE) noise from optical amplifiers are employed to mask the encrypted ultra-dense high-order signal for further improving the security. We further analyze the security performance by two metrics known in the reported QNSC systems, namely the number of masked signals (NMS) of noise and the detection failure probability (DFP). Experimental results show it is difficult or even impossible to extract transmission signals from quantum or ASE noise for an eavesdropper (Eve). We believe that the proposed PS-QAM/QNSC secure transmission scheme has the potential to be compatible with existing high-speed long-distance optical fiber communication systems.

In Situ Encapsulated Moiré Perovskite for Stable Photodetectors with Ultrahigh Polarization Sensitivity.

Nanostructures provide a simple, effective, and low-cost route to enhance the light-trapping capability of optoelectronic devices. In recent years, nano-optical structures have been widely used in perovskite optoelectronic devices to greatly enhance the device performance. However, the inherent instability of perovskite materials hinders the practical application of these nanostructured optoelectronic devices. Here, in situ encapsulated moiré lattice perovskite photodetectors (PDs) by two nanograting-structured soft templates with relative rotation angles is fabricated. The confinement growth of the two nanograting templates leads to crystal growth with moiré lattice structure, which improves the light-harvesting ability of the perovskite crystal, thereby improving the device performance. The PD exhibits responsivity to 1026.5 A W-1 . The Moiré lattice-perovskite-based PD maintained 95% of the initial performance after 223 days. After being continuously sprayed with water moist for 180 min, the performance is maintained at 95.7% of its initial level. The nanograting structure endows the device with high polarization sensitivity of Imax /Imin as high as 9.1.

Modeling of a multi-parameter chaotic optoelectronic oscillator based on the Fourier neural operator.

A model construction scheme of chaotic optoelectronic oscillator (OEO) based on the Fourier neural operator (FNO) is proposed. Different from the conventional methods, we learn the nonlinear dynamics of OEO (actual components) in a data-driven way, expecting to obtain a multi-parameter OEO model for generating chaotic carrier with high-efficiency and low-cost. FNO is a deep learning architecture which utilizes neural network as a parameter structure to learn the trajectory of the family of equations from training data. With the assistance of FNO, the nonlinear dynamics of OEO characterized by differential delay equation can be modeled easily. In this work, the maximal Lyapunov exponent is applied to judge whether these time series have chaotic behavior, and the Pearson correlation coefficient (PCC) is introduced to evaluate the modeling performance. Compare with long and short-term memory (LSTM), FNO is not only superior to LSTM in modeling accuracy, but also requires less training data. Subsequently, we analyze the modeling performance of FNO under different feedback gains and time delays. Both numerical and experimental results show that the PCC can be greater than 0.99 in the case of low feedback gain. Next, we further analyze the influence of different system oscillation frequencies, and the generalization ability of FNO is also analyzed.

Application of nanoarchitectonics in moist-electric generation.

The consumption of energy is an important resource that cannot be ignored in modern society. Non-renewable forms of energy, such as coal, natural gas, and oil, have always been important strategic resources and are always facing a crisis of shortage. Therefore, there is an urgent need for green renewable forms of energy. As an emerging green energy source, the moist-electric generator (MEG) has been studied in recent years and may become an energy source that can be utilized in daily life. Along with the advancement of technological means, nanoarchitectonics play an important role in MEG devices. This review aims to provide a comprehensive summary of the fundamentals of the MEG from the perspective of different material classifications and to provide guidance for future work in the field of MEGs. The effects of various parameters and structural designs on the output power, recent important literature and works, the mechanism of liquid-solid interactions at the nanoscale, and the application status and further potential of MEG devices are discussed in this review. It is expected that this review may provide valuable knowledge for future MEG research.

Mechanical Properties and Coagulation Characteristics of Flue Gas Desulfurization Gypsum-Based Polymer Materials.

To resolve problems caused by the accumulation of flue gas desulfurization gypsum (FGDG) in the environment, a polymer material was prepared using FGDG, granulated blast furnace slag (GBFS), fly ash (FA), and solid sodium silicate (SSS). The compressive strength of these polymer specimens cured for 3, 28, and 60 d was regularly measured, and their condensation behavior was analyzed. Both the formation behavior of mineral crystals and microstructure characteristics were analyzed further using X-ray diffraction and scanning electron microscopy. The compressive strength of pure FGDG polymer specimen (whose strength is generated by particle condensation crystallization) is insufficient and the condensation is slow. The addition of appropriate amounts of GBFS, FA, and SSS can continuously and considerably improve the compressive strength and shorten the setting time. The optimal proportions of FGDG, GBFS, and FA are 50%, 20%, and 30%, respectively, with the SSS addition amount of 20 g. The incorporation of GBFS, FA, and SSS can promote the polymerization of calcium, silicon, and aluminum in FGDG to form silicate and aluminosilicate minerals. Their formation is the main reason for the increased compressive strength and accelerated coagulation.

Coagulation Mechanism and Compressive Strength Characteristics Analysis of High-Strength Alkali-Activated Slag Grouting Material.

In deep coal mining, grouting reinforcement and water blockage are the most effective means for reinforcing the rock mass of extremely broken coal. However, traditional cement grouting materials are not suitable for use in complex strata because of their insufficient early mechanical strength and slow setting time. This study innovatively proposes using alkali-activated grouting material to compensate for the shortcomings of traditional grouting materials and strengthen the reinforcement of extremely unstable broken coal and rock mass. The alkali-activated grouting material was prepared using slag as raw material combined with sodium hydroxide and liquid sodium silicate activation. The compressive strength of specimens cured for 1 d, 3 d, and 28 d was regularly measured and the condensation behavior was analyzed. Using X-ray diffraction and scanning electron microscopy, formation behavior of mineral crystals and microstructure characteristics were further analyzed. The results showed that alkali-activated slag grouting material features prompt and high strength and offers the advantages of rapid setting and adjustable setting time. With an increase in sodium hydroxide content, the compressive strength first increased (maximum increase was 21.1%) and then decreased, while the setting time continued to shorten. With an increase in liquid sodium silicate level, the compressive strength increased significantly (and remained unchanged, maximum increase was 35.9%), while the setting time decreased significantly (and remained unchanged). X-ray diffraction analysis identified the formation of aluminosilicate minerals as the main reason for the excellent mechanical properties and accelerated coagulation rate.

Preparation and Properties of Municipal Solid Waste Incineration Alkali-Activated Lightweight Materials through Spontaneous Bubbles.

A self-foaming alkali-activated lightweight material was prepared by the pretreatment of municipal solid waste incineration bottom ash (BA). The low weight could be achieved without adding a foaming agent by using the low-density and self-foaming expansion characteristics of BA in combination with a strong alkali. The effects of BA, liquid sodium silicate (LSS), and calcium hydroxide (CH) on dry and wet densities, as well as water absorption, are discussed. The results show that increasing the BA content can significantly improve the foaming effect and reduce the dry and wet densities of specimens. However, it also leads to a sudden decrease in compressive strength and a significant increase in water absorption. LSS and CH can significantly improve the ability to seal bubbles by accelerating condensation, and they further reduce dry and wet densities without significantly improving water absorption. It is most effective at BA, LSS, and CH contents of 60, 20, and 2%, respectively.

Chaotic optical communications at 56 Gbit/s over 100-km fiber transmission based on a chaos generation model driven by long short-term memory networks.

Chaotic optical communication technology is considered as an effective secure communication technology, which can protect information from a physical layer and is compatible with the existing optical networks. At present, to realize long-distance chaos synchronization is still a very difficult problem, mainly because well-matched hardware cannot always be guaranteed between the transmitter and receiver. In this Letter, we introduce long short-term memory (LSTM) networks to learn a nonlinear dynamics model of an opto-electronic feedback loop, and then apply the trained deep learning model to generate a chaotic waveform for encryption and decryption at the transmitter and receiver. Furthermore, to improve the security, we establish a deep learning model pool which consists of different gain trained models and different delay trained models, and use a digital signal to drive chaos synchronization between the receiver and transmitter. The proposed scheme is experimentally verified in chaotic-encrypted 56-Gbit/s PAM-4 systems, and a decrypted performance below 7%FEC threshold (BER = 3.8×10-3) can be achieved over a 100-km fiber transmission.

Trading off security and practicability to explore high-speed and long-haul chaotic optical communication.

Recent demonstrations of chaos-based secure communication have proven the feasibility of secured transmission of high-speed (tens of Gbit/s) signals over certain distances (∼100-km), which bring hope for secure communication from theoretical analysis to practical applications. So far, the chaos-based secure communication system with chaos-masking (CMS) encryption is considered as one of the most important and feasible schemes. In this paper, an optical chaotic carrier generated by an opto-electronic oscillator is used to encrypt 112-Gbit/s message by CMS encryption for data transmission over a 1040-km single-mode-fiber. The message is successfully decrypted by combining coherent detection and our proposed blind decryption algorithms, which can successfully separate the chaotic carrier and the message with the bit-error-rate (BER) below the forward error correction (FEC) threshold. Experimental results show that the coherent detection combined digital signal processing algorithms may be a possible way to promote the practical applications of chaotic optical communication in the future. In addition, this paper reveals that the security of the CMS encryption may be not high enough for those systems requiring rigorous confidentiality. Subsequently, we further discuss the bottlenecks encountered in current high-speed chaotic optical communication systems and analyze how to improve and weight the security and practicability.

[Construction and Application Optimization of the Chl-a Forecast Model ARIMA for Lake Taihu].

As an important indicator of phytoplankton biomass in lakes, the chlorophyll-a (Chl-a) concentration reflects the abundance and variation of phytoplankton in the water. Based on the monthly monitoring data of Chl-a and environmental factors in Lake Taihu from December 1999 to August 2019, key environmental factors related to Chl-a and their relationships were found using the principal component analysis (PCA) method. A multiple linear stepwise regression model and an auto-regressive integrated moving average (ARIMA) model were developed to predict the monthly Chl-a concentrations. The results showed that the Chl-a concentrations in Lake Taihu exhibited clear seasonal change characteristics and an overall trend of a gradual increase. The changes in total phosphorus (TP), the permanganate index, monthly average temperature (MAT), and monthly rainfall (MR) matched the Chl-a concentrations relatively well, whereas the changes in total nitrogen (TN) and ammonium nitrogen (NH4+-N) lagged significantly. The PCA results showed that the increased phytoplankton biomass and consequent algae outbreaks in Lake Taihu were not limited to the effect of a single factor such as TN or TP, but were comprehensively affected by multiple factors such as TN, NH4+-N, TP, the permanganate index, MR, and MAT. Through further validation, the ARIMA model of Chl-a concentrations was proved to be significantly better than the multiple linear stepwise regression model, especially when considering the key environmental factors as independent variables and optimizing their values. The established ARIMA (0,1,1) (0,1,1) model would be helpful for forecasting algae blooms in Lake Taihu and provide useful suggestions for water environmental management, such as water resources dispatch and regulation.

Experimentally validated full-vectorial model of wavelength multicasting via four-wave mixing in straight waveguides.

We derive full-vectorial nonlinear propagation equations of dual-pumped four-wave mixing in straight waveguides, which are valid in characterizing the one-to-six wavelength multicasting. Special attention is paid to the resulting idler wavelengths and their conversion efficiency, which enables the optimization of the experimental designs, including the incident wavelength and the power of pumps and signal. We validate the model by comparing the numerical simulation to the experimental measurement in a silicon-on-insulator waveguide, for the first time to our best knowledge, and achieve a good agreement. We further derive the general form of the proposed model for the case of using multiple,pumps, which holds a potential to numerically predict the performance of complex wavelength multicasting, and essentially guide the waveguide designs.

[Effect of specific immunotherapy on GM-CSF and IL-5 in the tissues of recurrent nasal polyps].

OBJECTIVE: To study the mechanism and clinical significance of specific immunotherapy (SIT) on the expression changes of GM-CSF and IL-5 in the tissue samples of recurrent nasal polyps. METHOD: Perennial allergic rhinitis patients with recurrent nasal polyps were randomly divided into 2 groups. The experimental group of 19 patients was treated by SIT and standardized treatment (glucocorticoid nasal spray) , and the control group of 17 patients was only treated by standardized treatment (glucocorticoid nasal spray). We measured the expression levels of GM-CSF and IL-5 in the tissue samples of the nasal polyps by ELISA, and compared the results obtained before treatment with expression levels detected at 6 months and 1 year after the treatment. RESULT: The expression of GM-CSF and IL-5 in the recurrent nasal polyps reduced significantly (P < 0.05) in both groups after 6 months and 1 year post-treatment compared with pre-treatment, and the expression of GM-CSF and IL-5 in the experimental group was much lower than that of the control group. CONCLUSION: SIT decreases the expression of GM-CSF and IL-5 and reduces the inflammatory reaction in the tissue samples of recurrent nasal polyps.

Endoscopic therapy of colonic liver flexure mucocele.

Colorectal mucoceles usually arise in the appendix, and colonic disease is very rare. We report the first case of a mucocele of the colonic liver flexure that was treated successfully with endoscopy. A 36-year-old man was admitted to our hospital because of abdominal distension persisting for 3 days. Colonoscopic examination revealed a round polyp in the hepatic flexure, and we performed hot snare polypectomy with argon plasma coagulation. Histologically, the polypectomy specimen was confirmed to be a mucocele, with no neoplastic changes. Follow-up examinations at 6 and 12 months showed no evidence of recurrence.