Biofortification with selenium and lithium improves nutraceutical properties of major winery grapes in the Midwestern United States

Enriching the micronutrients, selenium (Se) and lithium (Li), in grapes to improve their nutraceutical properties were implemented by foliar application of organic fertiliser rich in Se and Li onto five grape cultivars. The effects of this biofortification on vine vigour, fruit quality, overall micronutrients and phenolic compounds also were investigated. Agronomic biofortification was found greatly increased the Se and Li content in the whole grape by multiple times, meanwhile it did not significantly affect the vine vigour and fruit quality of grapes. However, the biofortification did impact the Ionome (including all the mineral nutrients and trace elements) and phenolic compounds in grapes and this varied among cultivars. This study demonstrated foliar spray of organic Se/Li fertiliser was a very effective strategy to biofortify these micronutrients in grape berries, particularly in the skin, and therefore might be a promising strategy to increase the consumption and awareness of these grapes.     

Disturbance Observer-based Adaptive Fault-tolerant Dynamic Surface Control of Nonlinear System with Asymmetric Input Saturation

International Journal of Control, Automation and Systems - In this paper, a composite fault-tolerant control problem is studied for a class of uncertain nonlinear system with asymmetric input...     

Chromium evaporation and oxidation characteristics of alumina-forming austenitic stainless steels for balance of plant applications in solid oxide fuel cells

The chromium (Cr) evaporation behavior of several different types of iron (Fe)-based AFA alloys and benchmark Cr₂O₃-forming Fe-based 310 and Ni-based 625 alloys was investigated for 500 h exposures at 800 °C to 900 °C in air with 10% H₂O. The Cr evaporation rates from alumina-forming austenitic (AFA) alloys were ~5 to 35 times lower than that of the Cr₂O₃-forming alloys depending on alloy and temperature. The Cr evaporation behavior was correlated with extensive characterization of the chemistry and microstructure of the oxide scales, which also revealed a degree of quartz tube Si contamination during the test. Long-term oxidation kinetics were also assessed at 800 to 1000 °C for up to 10,000 h in air with 10% H₂O to provide further guidance for SOFC BOP component alloy selection.     

In situ Raman spectroscopic study towards the growth and excellent HER catalysis of Ni/Ni(OH)2 heterostructure

The electrochemical water splitting to produce H₂ in high efficiency with earth-abundant-metal catalysts remains a challenge. Here, we describe a simple “cyclic voltammetry + ageing” protocol at room temperature to activate Ni electrode (AC-Ni/NF) for hydrogen evolution reaction (HER), by which Ni/Ni(OH)₂ heterostructure is formed at the surface. In situ Raman spectroscopy reveals the gradual growth of Ni/Ni(OH)₂ heterostructure during the first 30 min of the aging treatment and combined with polarization measurements, it suggests a positive relation between the Ni/Ni(OH)₂ amount and HER performance of the electrode. The obtained AC-Ni/NF catalyst, with plentiful Ni–Ni(OH)₂ interfaces, exhibits remarkable performance towards HER, with the low overpotential of only 30 mV at a H₂-evolving current density of 10 mA/cm² and 153 mV at 100 mA/cm², as well as a small Tafel slope of 46.8 mV/dec in 1 M KOH electrolyte at ambient temperature. The excellent HER performance of the AC-Ni/NF could be maintained for at least 24 h without obvious decay. Ex situ experiments and in situ electrochemical-Raman spectroscopy along with density functional theory (DFT) calculations reveal that Ni/Ni(OH)₂ heterostructure, although partially reduced, can still persist during HER catalysis and it is the Ni–Ni(OH)₂ interface reducing the energy barrier of H1 adsorption thus promoting the HER performance.     

选煤机排料系统中刮板结构的优化研究

针对选煤机排料系统的刮板易出现磨损、弯曲等问题,通过对刮板结构、受力情况进行详细分析,并提出了相应的优化设计方案.仿真结果表明,该设计方案可满足煤矿安全高效的生产需求,对实际生产中的刮板结构设计有一定应用价值.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

Traffic identification method based on multiple probabilistic neural network model

Neural Computing and Applications - Traffic identification is currently an important challenge for network management and security. In this paper, we propose a novel application identification...     

Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.     

Torsional statics of two-dimensionally functionally graded microtubes

A size-dependent governing equation is derived to investigate the torsional static behaviors of two-dimensionally functionally graded microtubes based on the modified couple stress theory. The shear modulus is assumed to vary along the tube’s length direction according to an exponential distribute function, and varies along the tube’s radius direction according to a power-law function. A generalized differential quadrature method is developed to determine the rotational angle and shear stresses. Some illustrative examples are given to investigate the effects of applied torques, the length scale parameter and various material compositions on the torsional angle and shear stresses.