All-optical image transmission through a dynamically perturbed multimode fiber and a ring-core fiber using diffractive deep neural networks.

In this study, we present an all-optical image reconstruction technique leveraging a diffractive deep neural network (D2NN) within a ring-core fiber (RCF) architecture. Orbital angular momentum (OAM) modes are employed to facilitate imaging transmission. We experimentally validate the efficacy of our approach for complex field diffractive image reconstruction through a multimode fiber (MMF) and RCF at a 1550 nm operating wavelength.

Spectral analysis based blind frequency offset estimation for digital subcarrier multiplexing systems with adjustable roll-off factors and various modulation formats.

We proposed a blind frequency offset estimation (FOE) method for digital subcarrier multiplexing (DSM) signals. By utilising spectral information from the DSM signal and analysing the correlation between the frequency offset (FO) and the summed power of the signal spectrum, the proposed FOE method can accurately and effectively handle various modulation schemes assigned to each subcarrier. The proposed FOE method exhibits a flexibility to the roll-off factor of the root raised cosine (RRC) spectral shaping and can achieve a high level of accuracy in FOE under different roll-off factors and subcarrier numbers, with an FOE error of less than 30 MHz under a fast Fourier transform (FFT) size of 2048.

Mechanistic insight of fungal-microalgal pellets in photobioreactor for heavy-metal wastewater bioremediation.

The high cost of harvesting microalgae limits their industrial application. Fungal-microalgal pellets can efficiently harvest microalgae and enhance heavy-metal adsorption. However, the molecular response mechanism of fungal-microalgal pellets under heavy-metal stress remains unclear.

Multifunctional carbonyl-rich compounds for constructing "corrosion-resistant electrodes and electrolyte interface" in high-voltage sodium-metal batteries.

In recent years, there has been notable advancement in the development of high-performance materials for sodium-ion batteries, particularly in layered oxide cathodes. However, research on enhancing the interface between electrolytes and cathodes remains nascent. One promising approach involves the addition of electrolyte additives, recognized for their cost-effectiveness and efficiency in bolstering the electrode/electrolyte interface to enhance material stability during high-voltage cycling.

Moderate-intensity continuous training and high-intensity interval training alleviate glycolipid metabolism through modulation of gut microbiota and their metabolite SCFAs in diabetic rats.

Glucose and lipid metabolism disorders are typical of diabetic patients and are important factors leading to macrovascular and microvascular complications. The aim of this study was to understand the effects of different exercises on glycolipid metabolism in diabetic rats and the role of gut flora in metabolic maintenance. We measured glycolipid metabolic indices and short-chain fatty acids (SCFAs) content and sequenced and analyzed gut microbes after 8 weeks of moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT) programs in type 2 diabetic rats(T2DM).

Three-dimensional rattan-derived electrodes with directional channels and large mass loadings for high-performance aqueous zinc-ion batteries.

Aqueous zinc-ion batteries (AZIBs) have emerged as prospective candidates for wide-scale energy storage, benefiting from their exceptional reliability and budget-friendliness. To tackle the challenge of limited energy density of AZIBs, it is pivotal to explore cathodes with substantial mass loadings. In this study, rattan is converted into a three-dimensional (3D) current collector with directional channels, high compressive strength, good electrolyte affinity, and superior electrochemical stability through a process involving ultraviolet light irradiation-assisted delignification followed by high-temperature carbonization.

Knowledge of and attitude towards depression among urban and rural residents in Beijing: a cross-sectional study.

Objectives: To compare the level of knowledge of depression, recognition ability and attitudes towards depression among urban and rural residents in Beijing.

Design: A cross-sectional study.

Setting: Six districts in Beijing, China, 2021.

Combining metabolomics and transcriptomics to analyze key response metabolites and molecular mechanisms of Aspergillus fumigatus under cadmium stress.

The co-cultivation of fungi with microalgae facilitates microalgae harvesting and enhances heavy metal adsorption. However, the mechanisms of fungal tolerance to cadmium (Cd) have not yet been studied in detail. In this study, functional groups of fungi were analyzed under Cd stress using Fourier transform infrared spectrometer (FTIR), X-ray photoelectron spectroscopy (XPS), scanning electron microscope (SEM), and transmission electron microscope (TEM) to explore their morphology.

Association of exposure to multiple perfluoroalkyl and polyfluoroalkyl substances and glucose metabolism in National Health and Nutrition Examination Survey 2017-2018.

Objective: To investigate the relationships between perfluoroalkyl and polyfluoroalkyl substances (PFASs) exposure and glucose metabolism indices.

Methods: Data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 waves were used. A total of 611 participants with information on serum PFASs (perfluorononanoic acid (PFNA); perfluorooctanoic acid (PFOA); perfluoroundecanoic acid (PFUA); perfluorohexane sulfonic acid (PFHxS); perfluorooctane sulfonates acid (PFOS); perfluorodecanoic acid (PFDeA)), glucose metabolism indices (fasting plasma glucose (FPG), homeostasis model assessment for insulin resistance (HOMA-IR) and insulin) as well as selected covariates were included.

16QAM optical signal generation scheme based on weighted optimal Euclidean distance.

A two-dimensional signal constellation scheme for binary uniform memoryless source transmission in optical fiber channels is studied in this paper. In geometric shaping (GS), optimization algorithms are usually used to change the overall position of constellation points while maintaining the probability of constellation points unchanged. Different optimization functions are used to allocate the position of constellation symbols, thereby improving constellation performance.

DACNN-aided nonlinear equalizer for a probabilistic shaping coherent optical communication system.

The probabilistic shaping (PS) technique is a key technology for fiber optic communication systems to further approach the Shannon limit. To solve the problem that nonlinear equalizers are ineffective for probabilistic shaping optical communication systems with non-uniform distribution, a distribution alignment convolutional neural network (DACNN)-aided nonlinear equalizer is proposed. The approach calibrates the equalizer using the probabilistic shaping prior distribution, which reduces the training complexity and improves the performance of the equalizer simultaneously.

Poly (lactic-co-glycolic acid)-encapsulated Endostar-loaded calcium phosphate cement as anti-tumor bone cement for the treatment of bone metastasis in lung cancer.

Lung cancer is one of the most common malignant tumors in the world. In approximately 30%-40% of lung cancer patients, bone metastases ensues with osteolytic destruction. Worse still, intractable pain, pathological fracture, and nerve compression caused by bone metastases are currently the bottleneck of research, diagnosis, and treatment of lung cancer.

OAM mode-division multiplexing IM/DD transmission at 4.32 Tbit/s with a low-complexity adaptive-network-based fuzzy inference system nonlinear equalizer.

Stochastic nonlinear impairment is the primary factor that limits the transmission performance of high-speed orbital angular momentum (OAM) mode-division multiplexing (MDM) optical fiber communication systems. This Letter presents a low-complexity adaptive-network-based fuzzy inference system (LANFIS) nonlinear equalizer for OAM-MDM intensity-modulation direct-detection (IM/DD) transmission with three OAM modes and 15 wavelength division multiplex (WDM) channels. The LANFIS equalizer could adjust the probability distribution functions (PDFs) of the distorted pulse amplitude modulation (PAM) symbols to fit the statistical characteristics of the WDM-OAM-MDM transmission channel.

Physiological regulation of microalgae under cadmium stress and response mechanisms of time-series analysis using metabolomics.

The investigation of heavy metal wastewater treatment utilizing microalgae adsorption has been extensively demonstrated. However, the response mechanism based on metabolomics to analyze the time-series changes of microalgae under Cd stress has not been described in detail. In this study, SEM/TEM demonstrated that Cd accumulated on the cell surface of microalgae and was bioconcentrated in the cytoplasm, vesicles, and chloroplasts.

Secure key real-time update and dynamic DNA encryption for CO-OFDM-PON based on a hybrid 5-D chaos.

A double key (DK) real-time update and hybrid five-dimensional (5-D) hyperchaotic deoxyribonucleic acid (DNA) dynamic encryption scheme is proposed, which can ensure the security in the orthogonal frequency division multiplexing passive optical network (OFDM-PON). Chaotic sequences for DNA dynamic encryption are produced using a four-dimensional (4-D) hyperchaotic Lü system and a one-dimensional (1-D) logistic map. In this scheme, the DK consists of an external key set, which is stored locally, and an internal key, which is associated with the plaintext and external key.

Study of molecular patterns associated with ferroptosis in Parkinson's disease and its immune signature.

Parkinson's disease is the second most common neurodegenerative disease in the world. We downloaded data on Parkinson's disease and Ferroptosis-related genes from the GEO and FerrDb databases. We used WCGAN and Random Forest algorithm to screen out five Parkinson's disease ferroptosis-related hub genes.

Identification of potential immune-related hub genes in Parkinson's disease based on machine learning and development and validation of a diagnostic classification model.

Background: Parkinson's disease is the second most common neurodegenerative disease in the world. However, current diagnostic methods are still limited, and available treatments can only mitigate the symptoms of the disease, not reverse it at the root. The immune function has been identified as playing a role in PD, but the exact mechanism is unknown.

Scalable fabrication of free-standing and integrated electrodes with commercial level of areal capacity for aqueous zinc-ion batteries.

Aqueous zinc-ion batteries (AZIBs) present a highly promising avenue for the deployment of grid-scale energy storage systems. However, the electrodes fabricated through conventional methodologies not only suffer from insufficient mass loadings, but also are susceptible to exfoliation under deformations. Herein, a scalable and cost-effective freezing-thawing method is developed to construct free-standing and integrated electrode, comprising HAlVO, carboxymethyl cellulose, and carbon nanotubes.

Bayesian generative adversarial network emulator based end-to-end learning strategy of the probabilistic shaping for OAM mode division multiplexing IM/DD transmission.

Orbital angular momentum (OAM) mode division multiplexing (MDM) has emerged as a new multiplexing technology that can significantly increase transmission capacity. In addition, probabilistic shaping (PS) is a well-established technique that can increase the transmission capacity of an optical fiber to close to the Shannon limit. However, both the mode coupling and the nonlinear impairment lead to a considerable gap between the OAM-MDM channel and the conventional additive white Gaussian noise (AWGN) channel, meaning that existing PS technology is not suitable for an OAM-MDM intensity-modulation direct-detection (IM-DD) system.

Low-complexity characterized-long-short-term-memory-aided channel modeling for optical fiber communications.

In this work, a low-complexity data-driven characterized-long-short-term-memory (C-LSTM)-aided channel modeling technique is proposed for optical single-mode fiber (SMF) communications. To fully utilize the sequence correlation learning ability of traditional long short-term memory (LSTM) networks and solve the gradient explosion problem, the feature information is introduced into the traditional LSTM input layer to better characterize the intersymbol interference caused by dispersion in SMF modeling. The simulation results show that the proposed C-LSTM can effectively alleviate the gradient explosion problem with a stable and ultimately lower mean square error (MSE) than traditional LSTM.

Salting-Out Effect Realizing High-Strength and Dendrite-Inhibiting Cellulose Hydrogel Electrolyte for Durable Aqueous Zinc-Ion Batteries.

Aqueous zinc-ion batteries are limited by poor Zn stripping/plating reversibility. Not only can hydrogel electrolytes address this issue, but also they are suitable for constructing flexible batteries. However, there exists a contradiction between the mechanical strength and the ionic conductivity for hydrogel electrolytes.

Hidden conditional random field-based equalizer for the 3D-CAP-64 transmission of OAM mode-division multiplexed ring-core fiber communication.

As a key technique for achieving ultra-high capacity optical fiber communications, orbital angular momentum (OAM) mode-division multiplexing (MDM) is affected by severe nonlinear impairments, including modulation related nonlinearities, square-law nonlinearity and mode-coupling-induced nonlinearity. In this paper, an equalizer based on a hidden conditional random field (HCRF) is proposed for the nonlinear mitigation of OAM-MDM optical fiber communication systems with 20 GBaud three-dimensional carrierless amplitude and phase modulation-64 (3D-CAP-64) signals. The HCRF equalizer extracts the stochastic nonlinear feature of the OAM-MDM 3D-CAP-64 signals by estimating the conditional probabilities of the hidden variables, thereby enabling the signals to be classified into subclasses of constellation points.

High-performance Si@C anode for lithium-ion batteries enabled by a novel structuring strategy.

Si anode has drawn growing attention because of its features of large specific capacity, low electrochemical potential, and high natural abundance. However, it suffers from severe electrochemical irreversibility due to its large volume change during cycling. In spite of the achievement of improved electrochemical performance after compositing with carbon materials, most of the reported Si/C composite anodes lack a simple preparation process.