Search

Persistent infection and prolonged shedding of human bocavirus 1 (HBoV1) in children have been reported, and the role of HBoV1 as a sole causative pathogen in acute respiratory infection (ARI) is yet to be established. While the reported prevalence of HBoV infection varies due to different detection methods and sampling criteria, determining the viral and bacterial etiology of HBoV infection using multiplex real-time PCR is yet to be reported. Herein, we aimed to further explore the pathogenicity of HBoV in patients with ARI by screening the viral and bacterial infections in children with ARI in Qingdao and comparing the epidemiological, clinical characteristics, and etiological results. Human bocavirus was identified in 28.1% of the samples, and further sequencing analysis of the detected HBoV confirmed 96.4% as HBoV1. The rate of HBoV as a single viral infection was 75%, and the rate of coinfection with bacteria was 66.1%, suggesting the need for continued monitoring of HBoV in children with ARIs. Clinical characterization suggested that HBoV infection may affect the function of organs, such as the liver, kidney, and heart, and the blood acid–base balance. Additionally, it is essential to promote awareness about the importance of disinfection and sterilization of the hospital environment and standardizing operations. The interactions between HBoV and other pathogens remain to be investigated in further detail in the future.

The recent observation of cyclotron resonance in optimally-doped La$_{2-x}$Sr$_x$CuO$_4$ using time-domain THz spectroscopy in high magnetic field has given new possibilities for the study of cuprate superconductors. One can measure the cyclotron mass in more disordered cuprates possesing short scattering times therefore expanding the study to materials and dopings in which quantum oscillations have not been observed. Here we present the measurement of the carrier mass of the hole doped cuprate La$_{2-x}$Sr$_x$CuO$_4$ across a a range of dopings spanning the slightly underdoped ($x=0.13$) to highly overdoped ($x=0.26$), near to the termination of the superconducting dome. These results reveal a systematic increase of $m_c$ with doping, up to values greater than thirteen times the bare electron mass. This is in contrast with those masses extracted from the heat capacity, which show a peak near the pseudogap critical point $p^*$ and/or Lifshitz transition. The cyclotron frequency is linear in field up to 31 T for all dopings giving no evidence for field induced Fermi surface reconstructions. The cyclotron mass is found to be positive for all dopings, but with a magnitude systematically below the heat capacity mass for under and optimally doped samples, while exceeding it for overdoped samples. Among other aspects, these results are surprising as photoemission reveals a Lifshitz transition in the middle of our doping range and the sign of the cyclotron mass determined from a finite frequency resonance is -- in conventional theories -- a {\it topological quantity} only sensitive to whether or not the Fermi surface is closed around holes or electrons. We see no sign of a divergence of the mass near $p^*$ nor near the Lifshitz transition, showing that any singularity -- if it exists -- is not strong enough to affect the cyclotron mass., Comment: 9 pages, 4 figures

Aims Continuous cropping leads to the decreasing of soil nutrients and microbial diversity. This study aims to explore the effects of chitosan application on soil nutrient, enzyme activity, root exudates, and bacterial diversity in cotton field.Methods Topsoils were collected from four treatments (continuous cotton cropping (Ct), continuous cotton cropping with chitosan application (CtC), rotation (Rt) (cotton-corn-wheat), and rotation with chitosan application (RtC)) to determine the effects of chitosan on soil nutrients, enzyme activity, root exudates, and bacterial diversity under different cultivation patterns. The structure and functions of bacterial communities were analyzed using Illumina MiSeq sequencing and PICRUSt approach.Results Root exudates in CtC, Rt, and RtC treatments were higher than that in Ct treatment, while soil nutrients were lower. Soil enzyme activities were higher in Rt treatment than in Ct treatment, while only catalase activity was higher in CtC treatment. The abundance of Actinomycetes, Proteobacteria, Chloroflexi, and Bacteroidetes in Rt and CtC treatments, Firmicutes in Rt treatment, and Gemmatimonadetes in CtC treatment were higher than those in Ct treatment. PICRUSt analysis showed that the abundance of functional genes for soil microbial metabolism, environmental information processing, and organismal systems were higher in Rt, CtC, and RtC treatments than in Ct treatment, while that of genes for genetic information processing, cellular processes, and human diseases were slightly higher. Conclusions Chitosan application in cotton fields under different cultivation patterns could improve nutrient availability in continuous-cropping soils by reducing root exudates and improving soil bacterial community diversity, to reduce continuous cropping obstacles.

The number of panicles per unit area is a common indicator of rice yield and is of great significance to yield estimation, breeding, and phenotype analysis. Traditional counting methods have various drawbacks, such as long delay times and high subjectivity, and they are easily perturbed by noise. To improve the accuracy of rice detection and counting in the field, we developed and implemented a panicle detection and counting system that is based on improved region-based fully convolutional networks, and we use the system to automate rice-phenotype measurements. The field experiments were conducted in target areas to train and test the system and used a rotor light unmanned aerial vehicle equipped with a high-definition RGB camera to collect images. The trained model achieved a precision of 0.868 on a held-out test set, which demonstrates the feasibility of this approach. The algorithm can deal with the irregular edge of the rice panicle, the significantly different appearance between the different varieties and growing periods, the interference due to color overlapping between panicle and leaves, and the variations in illumination intensity and shading effects in the field. The result is more accurate and efficient recognition of rice-panicles, which facilitates rice breeding. Overall, the approach of training deep learning models on increasingly large and publicly available image datasets presents a clear path toward smartphone-assisted crop disease diagnosis on a global scale.

Influx and loss are the two most common downhole complexities. They not only cause the reservoir damage, increase the exploration cost, reduce the drilling efficiency; but also induce major malignancy. Therefore accurate and early detection of influx and loss during drilling is of great significance. Traditional influx and loss detection methods have the shortcoming of monitoring time lagging and high costs. As the rapid development of artificial intelligence techniques, researchers start to detect influx and loss using artificial intelligence method. This work adopted two machine learning algorithms(Random forests and Support vector machine) according to their characteristics to detect influx and loss during drilling in real-time. The detection methods includes four steps: 1) Generating raw influx/loss raw data set by combining real-time drilling data and drilling history data; 2) Pre-processing raw data set to obtain training data set; 3) Training classification model of random forests and SVM by training data set and algorithms; 4) Predicting influx/loss by the trained model according to the new real-time data. The case study shows that influx and loss can be detected accurately in early stage by both random forests method and SVM method after proper pre-processing the raw data and optimizing algorithm parameters. The detection accuracy of the sample data from four wells exceeds 90%. This work demonstrate a new way to detect influx and loss by utilizing huge drilling data and machine-learning algorithms, and the detection results are satisfying.

With the continuous development of science and technology, industrial production technology is also constantly developing, and production efficiency is also constantly improving. Greenhouse electric working robots are industrial production tools with automatic control technology as the core, which affects the quality of industrial products and thus affects the profitability of the factory. According to the set programming work, the greenhouse electric working robot can realize the reproduction production and reduce the workload of the workers. In today’s era, the industrial production steps are more complicated, the production process is more flexible, and the robot’s unchanging posture and movement cannot meet the needs of modern industry, which restricts the development of the factory. In order to better complete the work of industrial robots, it is necessary to study the geometric positioning and color recognition of industrial robots based on machine vision to improve the working efficiency of industrial robots. This paper established an active positioning machine vision system for precise positioning of robot parts greenhouse electric working stations. The matching method using image processing and feature recognition area based on the shape of the binding phase combines the threshold shape criterion to identify object features. The experiments prove that the method can quickly and accurately obtain the object boundaries and centroid calculations and identification data, the robot kinematics combined with real-time motion control of the robot in order to eliminate this error, meet the requirements of the industrial robot self-aligned.

The Radio Frequency (RF) relative measurement is a novel and compelling technology in the spacecraft formation flying aimed at detecting, acquiring, and tracking the relative position and attitude between spacecrafts. In the development of RF relative measurement sensors, it has been found that the locations of antennas affect the measurement accuracy of the relative position and attitude to a large extend. Thus, in this study, the selection of antenna location is modeled as a function optimization problem and an adaptive genetic algorithm-based optimization method is proposed to solve it. This method can adaptively optimize the locations of antennas on the spacecraft to improve the accuracy of RF relative measurement. The experimental results demonstrate that the proposed method can indeed improve the measurement accuracy and can be adapted for different mission requirements.

Non-orthogonal multiple access (NOMA) is an interesting concept to provide higher capacity for future wireless communications. In this article, we consider the feasibility and benefits of combining full-duplex operation with NOMA for modern communication systems. Specifically, we provide a comprehensive overview on application of full-duplex NOMA in cellular networks, cooperative and cognitive radio networks, and characterize gains possible due to full-duplex operation. Accordingly, we discuss challenges, particularly the self-interference and inter-user interference and provide potential solutions to interference mitigation and quality-of-service provision based on beamforming, power control, and link scheduling. We further discuss future research challenges and interesting directions to pursue to bring full-duplex NOMA into maturity and use in practice., Comment: Revised, IEEE Wireless Communication Magazine

Selective catalytic reduction of NO with NH3(NH3-SCR) is a well-proven technique for the removal of NOx from stationary sources such as coal-fired power plants,and is also one of the most promising techniques for the NOx elimination from diesel exhaust under oxygen-rich conditions. Due to some inevitable disadvantages of the present V2O5-WO3(MoO3) /TiO2 catalyst for industrial use,many researchers focus on the development of novel,highly efficient,stable,environmental-friendly and vanadium-free NH3-SCR catalysts. The research progress in the field of vanadium-free NH3-SCR catalysts is reviewed,including zeolite catalysts(such as Fe-zeolite catalysts and Cu-zeolite catalysts) and oxide catalysts(such as Fe-based oxide catalysts,Mn-based oxide catalysts,and other vanadium-free oxide catalysts) . Several aspects in this field,including the evaluation of catalytic performance,the structure analysis of active sites,the improvement of low temperature activity,the study of NH3-SCR reaction mechanism,the enhancement of H2O/SO2 durability,and the feasibility analysis for industrial use,have been discussed in detail. The possible developing orientation and research interests in the field of vanadium-free NH3-SCR catalysts are previewed.

The reduction of magnetite from slags plays an important role in many metallurgical operations. It has been found that the losses of copper metals generally increase with the increasing magnetite content in the slag. The main objective of the current article was to study the reduction process of iron oxides by mixed CO-CH4-Ar gas from commercial copper slags. The magnetite content decreased gradually, while fayalite phase increased during the reduction process. The reduction rates of the oxides were found to be of the first-order kinetics. The rate-limiting step was the interfacial mass transfer between the gas and liquid phase which fitted the penetration model. The effects of reduction temperature and injection gas flow on the deoxidation rate are also mentioned in the study.

A low-frequency resistance noise study in highly underdoped thick films of La$_{2-x}$Sr$_{x}$CuO$_{4}$ ($x=0.07$ and 0.08) reveals slow, correlated dynamics and breaking of ergodicity near the superconducting transition of the Berezinskii-Kosterlitz-Thouless type. The observed correlated behavior is strongly suppressed by disorder., Comment: 6 pages, 5 figures

The control of the slag properties has become very essential in improving (1) the separation between the slag and the matte and (2) the operation of electric smelting furnaces in the copper pyrometallurgical process. The viscosities and electrical conductivities of FeOt-SiO2-CaO-Cu2O copper smelting slags were measured using the rotational spindle method and the standard direct-current (DC) four-probe method, respectively, in this article. The influences of the common constituents of CaO, Fe3O4, Cu2O in the basic slag system of FeO-SiO2 on the viscosity and conductivity have been investigated. The results showed that the effects of these three compositions on viscosity and conductivity were much more complicated due to the transition of the basic slag compositions. The apparent activity energy of viscosity and the relationship between viscosity and electrical conductivity are also mentioned in the study.

sol-gel method for NH3-SCR. Nevertheless, the reported CeTi based catalysts still have some problems in practical use, such as the narrow operation temperature window and poor activity in the low temperature range. Previous studies have shown that catalyst preparation meth- ods can significantly influence the catalytic performance of CeTi based catalysts, and a good dispersion of active compo- nent CeO2 on TiO2 is very important for the improvement of NH3-SCR activity. (8-10) Homogeneous precipitation, characterized by a highly uniform increase in the pH of metal salts solution achieved by thermal decomposition of some organic alkali, is a suitable catalyst preparation method that can produce highly dispersed mixed metal oxides. In this study, we report a signifi- cant improvement of CeTi based catalyst prepared by a ho- mogeneous precipitation method using urea as precipitator. NOx conversions and N2 selectivity over CeaTiOx(500) (a = 0.1, 0.2, 0.5, 1.0) are presented in Figure 1. Ce0.1TiOx(500) showed

As the rapid development of drilling techniques and data acquiring techniques, more and more drilling data are available. Storing, managing and effective using of these massive data are crucial to optimized drilling engineering design and strategic decision. This article is to research and design an integrated drilling database, and then further explore the innovative usage of the available drilling data. Based on the detail analysis of drilling database requirement, this article researched and designed drilling database by three phases: conceptual design, logical design and physical design. In the conceptual stage, the requirements of drilling design data, real-time drilling data and drilling construction data are extracted and analyzed, then E-R model is constructed. In the logical design stage, data tables and table relationship are designed and refined based on the E-R model. In the physical design stage, physical structure is selected for the logical data model to satisfy the application requirement. The designed drilling database is targeted data storage and management basis for drilling engineering design and craft software, real-time drilling software and drilling history management software; it conforms to drilling business process, contains comprehensive and detailed content and has high performance and refined data table structure. The construction of unified drilling database enables the efficient storage of mass drilling data and further data mining and analysis of drilling information. This work further researched the algorithms of automatic drilling engineering design, especially for automatic wellbore geometry design, based on the available data in the database. This article introduced a systematic method to design an integrated drilling database, which supports design data, real-time data and drilling management data. It also proposed an innovative way of drilling engineering design: automated drilling engineering design based on the data in the integrated drilling database and pre-installed rules.

The nature of the superconducting transition in highly underdoped thick films of La$_{2-x}$Sr$_x$CuO$_4$ ($x=0.07$ and 0.08) has been investigated using the in-plane transport measurements. The contribution of superconducting fluctuations to the conductivity in zero magnetic field, or paraconductivity, was determined from the magnetoresistance measured in fields applied perpendicular to the CuO$_2$ planes. Both the temperature dependence of the paraconductivity above the transition and the nonlinear current-voltage ($I-V$) characteristics measured across it, exhibit the main signatures of the Berezinskii-Kosterlitz-Thouless (BKT) transition. The quantitative comparison of the superfluid stiffness, extracted from the $I-V$ data, with the renormalization-group results for the BKT theory, reveals a large value of the vortex-core energy. This finding is confirmed by the analysis of the paraconductivity obtained using different methods. The results strongly suggest that the characteristic energy scale controlling the BKT behavior in this layered system corresponds to the superfluid stiffness of a few layers., Comment: 15 pages, 6 figures; v2: expanded discussion, added references and an Appendix; v3: fixed typos; to appear in Phys.. Rev. B

Real-time kinematic GPS precise positioning has been playing an increasing role in both surveying and navigation. Based on the city's fibre LAN network, Shenzhen Continuous Operating Reference Stations (SZCORS) system has been established and consists of GPS reference stations, system control center, user's data center, and real-time datacom network. The SZCORS system provides users the real-time centimeter positioning or post-processing millimeter positioning. This paper makes discussion on the structure of SZCORS system. Some experiments have been made to test the usablity, and then the data has been analyzed.

A geometric algorithm for Tilted-Camera Perspective (TCP) projection is proposed in this paper based on the principle of perspective projection. According to that, the difference between TCP projection and External Perspective (EXP) projecton is analyzed. It is put forward prerequisites making these two projections were compatible, and some examples are given.

Ce—Ti mixed oxide catalysts are prepared by precipitation from aqueous solutions of Ce(NO3)3 and Ti(SO4)2 with molar Ce/Ti ratios of 0.1, 0.2, 0.5, and 1.0 using excessive aqueous solution of urea (90 °C, 8 h), followed by calcination of the precipitate at 400, 500, or 600 °C for 5 h in air.

In this study, the efforts to reduce NOx and particulate matter (PM) emissions from a diesel engine using both ethanol-selective catalytic reduction (SCR) of NOx over an Ag/Al2O3 catalyst and a biodiesel-ethanol-diesel fuel blend (BE-diesel) on an engine bench test are discussed. Compared with diesel fuel, use of BE-diesel increased PM emissions by 14% due to the increase in the soluble organic fraction (SOF) of PM, but it greatly reduced the Bosch smoke number by 60%-80% according to the results from 13-mode test of European Stationary Cycle (ESC) test. The SCR catalyst was effective in NOx reduction by ethanol, and the NOx conversion was approximately 73%. Total hydrocarbons (THC) and CO emissions increased significantly during the SCR of NOx process. Two diesel oxidation catalyst (DOC) assemblies were used after Ag/Al2O3 converter to remove CO and HC. Different oxidation catalyst showed opposite effect on PM emission. The PM composition analysis revealed that the net effect of oxidation catalyst on total PM was an integrative effect on SOF reduction and sulfate formation of PM. The engine bench test results indicated that the combination of BE-diesel and a SCR catalyst assembly could provide benefits for NOx and PM emissions control even without using diesel particle filters (DPFs).