Macroscale Chemotaxis from a Swarm of Bacteria-Mimicking Nanoswimmers

Inspired by the dynamics of bacterial swarming, we report a swarm of polymer‐brush‐grafted, glucose‐oxidase‐powered Janus gold nanoswimmers with a positive, macroscale chemotactic behavior. These nanoswimmers are prepared through the grafting of polymer brushes onto one side of gold nanoparticles, followed by functionalization with glucose oxidase on the other side. The resulting polymer‐brush‐functionalized Janus gold nanoswimmers exhibit efficient propulsion with a velocity of up to approximately 120 body lengths s−1 in the presence of glucose. The comparative analysis of their kinematic behavior reveals that the grafted polymer brushes significantly improve the translational diffusion of Janus gold nanoswimmers. Particularly, these bacteria‐mimicking Janus gold nanoswimmers display a collectively chemotactic motion along the concentration gradient of a glucose resource, which could be observed at the macroscale

Application of EMD Technology in Leakage Acoustic Characteristic Extraction of Gas-Liquid, Two-Phase Flow Pipelines

Nowadays, the exploitation and transportation of marine oil and gas are mainly achieved using multiphase flow pipelines. Leakage detection of multiphase flow pipelines has always been the most difficult problem regarding the pipeline safety. Compared to other methods, acoustic detection technology has many advantages and high adaptability. However, multiphase flow pipelines are associated with many noise sources that affect the extraction and recognition of leakage signals. In this study, the mechanism of leakage acoustic source generation in gas-liquid, two-phase pipelines is analyzed. First, an acoustic leakage detection experiment in the multiphase pipelines is conducted. The acoustic signals are divided into two classes in accordance with whether leakage occurs or not. The original signals are processed and analyzed based on empirical mode decomposition (EMD) processing technology. Based on the use of signal processing, this study shows that EMD technology can accurately identify the leakage signal in the gas-liquid, two-phase pipeline. Upon increases in the leakage aperture sizes, the entropy of the EMD information of the acoustic signals gradually increases. Finally, the method of the normalized energies characteristic value of each IMF component is also applied in leakage signal processing. When the liquid flow is maintained constant, the energy values of the IMF components change in a nonlinear manner when the gas flow rate increases. This verifies the feasibility of use of the acoustic wave sensing technology for leak detection in multiphase flow pipelines, which has important theoretical significance for promoting the development of safe and efficient operation in two-phase flow pipelines

A review on progress of lithium-rich manganese-based cathodes for lithium ion batteries

With the increasing demand for energy, layered lithium-rich manganese-based (Li-rich Mn-based) materials have attracted extensive attention because of their high capacity and high voltage. However, the Li-rich Mn-based materials suffer from a series of problems of oxygen release, transition metal (TM) migration, and structural transformation, which results in serious voltage and capacity decay. In this review, the lithium storage mechanism of the materials is systematically and critically summarized, in terms of the electrochemical performance problems such as large initial irreversible capacity, voltage decay, voltage hysteresis, inferior cycling performance, and electrolyte corrosion. We also summarize in detail the various modifications conducted in recent years, including component improvement, coating, doping, and surface treatment. Lastly, challenges and perspectives on future research directions for the development of high performance Li-rich Mn-based materials are also presented and discussed

GeneSegNet: a deep learning framework for cell segmentation by integrating gene expression and imaging

When analyzing data from in situ RNA detection technologies, cell segmentation is an essential step in identifying cell boundaries, assigning RNA reads to cells, and studying the gene expression and morphological features of cells. We developed a deep-learning-based method, GeneSegNet, that integrates both gene expression and imaging information to perform cell segmentation. GeneSegNet also employs a recursive training strategy to deal with noisy training labels. We show that GeneSegNet significantly improves cell segmentation performances over existing methods that either ignore gene expression information or underutilize imaging information.ISSN:1474-760

Surface LiMn1.4Ni0.5Mo0.1O4 Coating and Bulk Mo Doping of Li-Rich Mn-Based Li1.2Mn0.54Ni0.13Co0.13O2 Cathode with Enhanced Electrochemical Performance for Lithium-Ion Batteries

To improve the initial Coulombic efficiency, cycling stability, and rate performance of the Li-rich Mn-based Li1.2Mn0.54Ni0.13Co0.13O2 cathode, the combination of LiMn1.4Ni0.5Mo0.1O4 coating with Mo doping has been successfully carried out by the sol-gel method and subsequent dip-dry process. This strategy buffers the electrodes from the corrosion of electrolyte and enhances the lattice parameter, which could inhibit the oxygen release and maintain the structural stability, thus improving the cycle stability and rate capability. After LiMn1.4Ni0.5Mo0.1O4 modification, the initial discharge capacity reaches 272.4 mAh g(-1) with a corresponding initial Coulombic efficiency (ICE) of 84.2% at 0.1C (1C = 250 mAh g(-1)), far higher than those (221.5 mAh g(-1) and 68.9%) of the pristine sample. Besides, the capacity retention of the coated sample is enhanced by up to 66.8% after 200 cycles at 0.1C. Especially, the rate capability of the coated sample is 95.2 mAh g(-1) at 5C. XRD, SEM, TEM, XPS, and Raman spectroscopy are adopted to characterize the morphologies and structures of the samples. This coating strategy has been demonstrated to be an effective approach to construct high-performance energy storage devices

Enhancing the overcharged performance of Li(Ni0.8Co0.15Al0.05)O-2 electrodes by CeO2-Al2O3 surface coating

The nickel-rich cathode materials (LiNi0.8Co0.15Al0.05O2, NCAs) in Lithium ion batteries often suffer from oxygen loss problems under partially overcharged conditions (> 4.3 V), leading to capacity fading and safety problem. Herein, we utilize a facile ball-milling method to coat the NCAs with a shell of cerium aluminum composite oxide (CeO2-Al2O3), which is commonly used as oxygen storage material. Proved by in situ X-ray diffraction results, the coating CeO2-Al2O3 layer is capable to suppress the lattice volume change and irreversible phase transition of NCAs. The CeO2-Al2O3 coating layer can adsorb released oxygen under overcharged conditions and replenish lattice oxygen of NCAs under oxygen-leaned conditions. The protective layer can also prevent dissolution of the transition metals caused by HF attack in electrolytes. As a result, the as prepared electrode presents high specific capacity of 186.4 mA h g(-1) and excellent cycle stability with capacity retention of 94.1% after 300 cycles at a rate of 0.5 C under overcharged conditions (3.0-4.5 V). Coating CeO2-Al2O3 is an efficient strategy to solve capacity fading problem and safety problem caused by partially overcharge, and such strategy shows significant promise for practical applications. (c) 2021 Elsevier B.V. All rights reserved

Faba Bean (<i>Vicia faba</i> L.) Yield Estimation Based on Dual-Sensor Data

Faba bean is an important member of legumes, which has richer protein levels and great development potential. Yield is an important phenotype character of crops, and early yield estimation can provide a reference for field inputs. To facilitate rapid and accurate estimation of the faba bean yield, the dual-sensor (RGB and multi-spectral) data based on unmanned aerial vehicle (UAV) was collected and analyzed. For this, support vector machine (SVM), ridge regression (RR), partial least squares regression (PLS), and k-nearest neighbor (KNN) were used for yield estimation. Additionally, the fusing data from different growth periods based on UAV was first used for estimating faba bean yield to obtain better estimation accuracy. The results obtained are as follows: for a single-growth period, S2 (12 July 2019) had the best accuracy of the estimation model. For fusion data from the muti-growth period, S2 + S3 (12 August 2019) obtained the best estimation results. Furthermore, the coefficient of determination (R2) values for RF were higher than other machine learning algorithms, followed by PLS, and the estimation effects of fusion data from a dual-sensor were evidently better than from a single sensor. In a word, these results indicated that it was feasible to estimate the faba bean yield with high accuracy through data fusion based on dual-sensor data and different growth periods

A crucial role in osmoregulation against hyperosmotic stress: Carbohydrate and inositol metabolism in Nile tilapia (Oreochromis niloticus)

The purpose of this study was to explore the relationship between inositol metabolism and carbohydrate metabolism in Nile tilapia (Oreochromis niloticus) under acute hyperosmotic stress. 50 mg/mL glucose solution and PBS was injected to the fish of experimental group and the control group, respectively. The fish were then transferred to 16 psu brackish water for hyperosmotic stress immediately, and sampled at 0, 1, 3, 6, 12, 24, and 48 h post stress. The hyperosmotic stress significantly increased the osmotic pressure, glucose content of serum, the process of glycolysis and gluconeogenesis in the liver of fish in both groups over time. The expression of genes involved in myo-inositol (MI) synthesis and transport was all induced by hypertonicity in gill, kidney and liver of fish in both groups. The injection of glucose solution significantly decreased MI synthesis in gill, kidney and liver, and relieved the apoptosis of liver under acute hyperosmotic stress. However, glucose injection significantly increased Na+K+-ATPase activity in the gill, as well as serum osmotic pressure, and the decomposition of carbohydrate, indicating that additional glucose promoted osmoregulation ability of fish. The results of this research suggested that during the hyperosmotic stress, the injection of exogenous glucose could not only provide energy that required for osmoregulation, but also participate in the osmoregulation by acting as an osmolyte itself