Essential Norms and Schatten(-Herz) Classes of Integration Operators from Bergman Spaces to Hardy Spaces

In this paper, we completely characterize the compactness of the Volterra type integration operators $J_b$ acting from weighted Bergman spaces $A_\alpha^p$ to Hardy spaces $H^q$ for all $0<p, q<\infty$. Furthermore, we give some estimates for the essential norms of $J_b: A_\alpha^p \rightarrow H^q$ in the case $0<p \leq q<\infty$. We finally describe the membership in the Schatten(-Herz) class of the Volterra type integration operators

Monolithically Integrated Optoelectronic Receivers Implemented in 0. 25μm MS/RF CMOS

A monolithically integrated optoelectronic receiver is presented. A silicon-based photo-diode and receiver circuits are integrated on identical substrates in order to eliminate the parasitics induced by hybrid packaging. Implemented in the present deep sub-micron MS/RF （mixed signal, radio frequency） CMOS,this monolithically OEIC takes advantage of several new features to improve the performance of the photo-diode and eventually the whole OEIC

Government Competition, Land Supply Structure and Semi-Urbanization in China

Population urbanization is crucial to establishing a harmonious society. However, the phenomenon of population semi-urbanization is becoming an issue of ever-increasing concern in China. More and more immigrants from rural areas work and live in the city, but their roots remain in the rural area. This paper aims to analyze the influence mechanism of government competition on population semi-urbanization through land supply structure. The study’s theoretical analysis and empirical analysis results are based on the panel data of 105 key prefecture-level cities in China from 2007 to 2017. The results demonstrate that: (1) land finance and land-motivated investment engendered by government competition lead to an imbalance in the land price structure, further increasing the rate of population semi-urbanization; (2) land finance does not lead to population semi-urbanization through the land area structure; and (3) land-motivated investment aggravates the imbalance in the land area structure, further leading to population semi-urbanization. It is found that government competition in terms of achieving performance indicators affects population semi-urbanization by adjusting the land supply structure. Efforts should be made to achieve the coordinated development of urbanization, given that the increasing rate of population semi-urbanization will almost certainly aggravate social instability

Effect of Working Temperature Conditions on the Autogenous Deformation of High-Performance Concrete Mixed with MgO Expansive Agent

Currently, mass concrete is increasingly utilized in various engineering projects that demand high physical properties of concrete. The water-cement ratio of mass concrete is comparatively smaller than that of the concrete used in dam engineering. However, the occurrence of severe cracking in mass concrete has been reported in numerous engineering applications. To address this issue, the incorporation of MgO expansive agent (MEA) in concrete has been widely recognized as an effective method to prevent mass concrete from cracking. In this research, three distinct temperature conditions were established based on the temperature elevation of mass concrete in practical engineering scenarios. To replicate the temperature increase under operational conditions, a device was fabricated that employed a stainless-steel barrel as the container for concrete, which was enveloped with insulation cotton for thermal insulation purposes. Three different MEA dosages were used during the pouring of concrete, and sine strain gauges were placed within the concrete to gauge the resulting strain. The hydration level of MEA was studied using thermogravimetric analysis (TG) to calculate the degree of hydration. The findings demonstrate that temperature has a significant impact on the performance of MEA; a higher temperature results in more complete hydration of MEA. The design of the three temperature conditions revealed that when the peak temperature exceeded 60 °C in two cases, the addition of 6% MEA was sufficient to fully compensate for the early shrinkage of concrete. Moreover, in instances where the peak temperature exceeded 60 °C, the impact of temperature on accelerating MEA hydration was more noticeable

State of Charge Estimation of Lithium-Ion Battery for Electric Vehicles under Extreme Operating Temperatures Based on an Adaptive Temporal Convolutional Network

The accurate estimation of state of charge (SOC) under various conditions is critical to the research and application of batteries, especially at extreme temperatures. However, few studies have examined the SOC estimation performance of estimation algorithms for several types of batteries under such conditions. In this study, a new method was derived for SOC estimation and a series of experiments were conducted covering five types of lithium-ion batteries with three kinds of cathode materials (i.e., LiFePO4, Li(Ni0.5Co0.2Mn0.3)O2, and LiCoO2), three test temperatures, and four real driving cycles to verify the proposed method. The test temperatures for battery operation ranges from −20 to 60 °C. Then, an adaptive machine learning (ML) framework based on the deep temporal convolutional network (TCN) and Coulomb counting method was proposed, and the structure of the estimation model was designed through the Taguchi method. The accuracy and generalizability of the proposed method were evaluated by calculating the estimation errors and their standard deviations (SDs), its average errors showed a decline of at least 49.66%, and its SDs showed a decline of at least 45.88% when compared to four popular ML methods. These traditional ML methods performed poor accuracy and stability at extreme temperatures (−20 and 60 °C) when compared to 25 °C, while the proposed adaptive method exhibited stable and high performances at different temperatures

EA-Net: Research on skin lesion segmentation method based on U-Net

Accurate segmentation of skin lesions is a challenging task because the task is highly influenced by factors such as location, shape and scale. In recent years, Convolutional Neural Networks (CNNs) have achieved advanced performance in automated medical image segmentation. However, existing CNNs have problems such as inability to highlight relevant features and preserve local features, which limit their application in clinical decision-making. This paper proposes a CNN with an added attention mechanism (EA-Net) for more accurate medical image segmentation.EA-Net is based on the U-Net network model framework. Specifically, we added a pixel-level attention module (PA) to the encoder section to preserve the local features of the image during downsampling, making the feature maps input to the decoder more relevant to the ground-truth. At the same time, we added a spatial multi-scale attention module (SA) after the decoding process to increase the spatial weight of the feature maps that are more relevant to the ground-truth, thereby reducing the gap between the output results and the ground-truth. We conducted extensive segmentation experiments on skin lesion images from the ISIC 2017 and ISIC 2018 datasets. The results demonstrate that, when compared to U-Net, our proposed EA-Net achieves an average Dice score improvement of 1.94% and 5.38% for skin lesion tissue segmentation on the ISIC 2017 and ISIC 2018 datasets, respectively. The IoU also increases by 2.69% and 8.31%, and the ASSD decreases by 0.3783 pix and 0.5432 pix, indicating superior segmentation performance. EA-Net can achieve better segmentation results when the original image of skin lesions has an obscure boundary and the segmentation area contains interference factors, which proves that the addition of attention mechanism in the encoder and the application of comprehensive attention mechanism can improve the performance of neural network in the field of skin lesions image segmentation

Effects and Mechanisms of Phosphate Activation in Paddy Soil by Phosphorus Activators

Phosphorus (P) build-up in agricultural soils as a consequence of excessive P fertilizer application necessitates the exploration of soil P pool for crop supply. We conducted a soil incubation experiment, pot experiments, and field experiments to study the effects of different P activators (Pas) (humic acid, lignosulfonate sodium, and biochemical humic acid) on soil phosphate fraction, rice yield, and P loss. Through chemical analyses and microbial community structure measurement, we found that Pas significantly increased paddy soil water-soluble P (WSP), available P, Fe-P, and relative abundances of P-mineralizing and P-solubilizing microorganisms, whereas they decreased Al-P and microbial alpha diversity. Our pot experiment results showed that the application of Pas significantly reduced soil P loss and resulted in grain yield comparable to those obtained by fertilization with P fertilizers, and significantly higher than those in the control plants. The results of the field experiment suggested that Pas are able to increase rice yield more significantly than P fertilizers and improve the P utilization efficiency of rice plants. We conclude that application of Pas was more effective in reducing P leaching, soil total P, WSP, and Olsen P than P fertilizers during rice harvest

Characteristics of surface layer protein from Lactobacillus kefiri HBA20 and the role in mediating interactions with Saccharomyces cerevisiae Y8

In this study, the surface layer protein (SLP) from Lactobacillus kefiri HBA20 was characterized. The SLP was extracted by 5M LiCl. The molecular mass of the SLP was approximately 64 kDa as analyzed via SDS-PAGE. The surface morphology and the adhesion potential of L. kefiri HBA20 in the absence and presence of SLP were measured by AFM. Moreover, the protein secondary structure was evaluated by using circular dichroism (CD) and Fourier transform infrared spectroscopy (FTIR), respectively. SLP had high β-sheet contents and low content of α-helix. Thermal analysis of SLP of Lactobacillus kefiri HBA20 exhibited one transition peak at 129.64 °C. Furthermore, SEM measurements were showed that after the SLP were removed from the cell surface, the coaggregation ability with Saccharomyces cerevisiae Y8 of the strain was significantly reduced. In conclusion, the SLP of Lactobacillus kefiri HBA20 has a stable structure and the ability of adhesion to yeast. Molecular docking study revealed that mannan bind with the hydrophobic residues of SLP. Our results will help further understanding of the new surface layer protein and the interaction between L. kefiri and S. cerevisiae

Simulation study on flow field characteristics of air flotation deoiling process

In order to solve the problems of low clarification efficiency and long subsequent processing steps in the extraction metallurgically dissolved air flotation(DAF) process, supported by the actual process with a domestic oil removal equipment, the Reynolds Average Navier-Stokes(RANS) turbulence transient numerical simulation method and the κ-ω turbulence model were used to analyze the flow characteristics of internal flow. The results are shown as follows. 1) With a constant air blowing volume, it is favorable for oil removal with the range of the liquid inlet volume from 45 m3/h to 55 m3/h because of the good flow properties; while the liquid inlet is lower than 40 m3/h or higher than 60 m3/h, the gas bubbles are concentrated in the surface of the reactor, which leads to the low efficiency of the oil separation. 2) With a constant liquid inlet volume, the wall velocity and gas volume fraction increase while the gas inlet increases, which shows unfavorable effects for the oil removal because of the gas distribution on the wall. 3) The lower position of the liquid inlet or the gas phase inlet and the lower height of the partition have obvious adverse effects on the separation of oil from liquid phases