Changes in the activities of key enzymes and the abundance of functional genes involved in nitrogen transformation in rice rhizosphere soil under different aerated conditions

Soil microorganisms play important roles in nitrogen transformation. The aim of this study was to characterize changes in the activity of nitrogen transformation enzymes and the abundance of nitrogen function genes in rhizosphere soil aerated using three different methods(continuous flooding(CF), continuous flooding and aeration(CFA), and alternate wetting and drying(AWD)). The abundances of amoA ammonia-oxidizing archaea(AOA) and ammonia-oxidizing bacteria(AOB), nirS, nirK, and nifH genes, and the activities of urease, protease, ammonia oxidase, nitrate reductase, and nitrite reductase were measured at the tillering(S1), heading(S2), and ripening(S3) stages. We analyzed the relationships of the aforementioned microbial activity indices, in addition to soil microbial biomass carbon(MBC) and soil microbial biomass nitrogen(MBN), with the concentration of soil nitrate and ammonium nitrogen. The abundance of nitrogen function genes and the activities of nitrogen invertase in rice rhizosphere soil were higher at S2 compared with S1 and S3 in all treatments. AWD and CFA increased the abundance of amoA and nifH genes, and the activities of urease, protease, and ammonia oxidase, and decreased the abundance of nirS and nirK genes and the activities of nitrate reductase and nitrite reductase, with the effect of AWD being particularly strong. During the entire growth period, the mean abundances of the AOA amoA, AOB amoA, and nifH genes were 2.9, 5.8, and 3.0 higher in the AWD treatment than in the CF treatment, respectively, and the activities of urease, protease, and ammonia oxidase were 1.1, 0.5, and 0.7 higher in the AWD treatment than in the CF treatment, respectively. The abundances of the nirS and nirK genes, and the activities of nitrate reductase and nitrite reductase were 73.6, 84.8, 10.3 and 36.5% lower in the AWD treatment than in the CF treatment, respectively. The abundances of the AOA amoA, AOB amoA, and nifH genes were significantly and positively correlated with the activities of urease, protease, and ammonia oxidase, and the abundances of the nirS and nirK genes were significantly positively correlated with the activities of nitrate reductase. All the above indicators were positively correlated with soil MBC and MBN. In sum, microbial activity related to nitrogen transformation in rice rhizosphere soil was highest at S2. Aeration can effectively increase the activity of most nitrogen-converting microorganisms and MBN, and thus promote soil nitrogen transformation.

Review of intelligent diagnosis methods for imaging gland cancer based on machine learning

Gland cancer is a high-incidence disease that endangers human health,and its early detection and treatment require efficient,accurate,and objective intelligent diagnosis methods.In recent years,the advent of machine learning techniques has yielded satisfactory results in intelligent gland cancer diagnosis based on clinical images,significantly improving the accuracy and efficiency of medical image interpretation while reducing the workload of doctors.The focus of this study is to review,classify,and analyze intelligent diagnosis methods for imaging gland cancer based on machine learning and deep learning.This paper briefly introduces some basic imaging principles of multimodal medical images,such as the commonly used computed tomography(CT),magnetic resonance imaging(MRI),ultrasound(US),positron emission tomography(PET),and pathology.In addition,the intelligent diagnosis methods for imaging gland cancer were further classified into supervised learning and weakly supervised learning.Supervised learning consists of traditional machine learning methods,such as K-nearest neighbor algorithm(KNN),support vector machine(SVM),and multilayer perceptron,and deep learning methods evolving from convolutional neural network(CNN).By contrast,weakly supervised learning can be further categorized into active learning,semisupervised learning,and transfer learning.State-of-the-art methods are illustrated with implementation details,including image segmentation,feature extraction,and optimization of classifiers.Their performances are evaluated through indicators,such as accuracy,precision,and sensitivity.In conclusion,the challenges and development trends of intelligent diagnosis methods for imaging gland cancer were addressed and discussed.

Machine learning-enabled MIMO-FBMC communication channel parameter estimation in IIoT: A distributed CS approach

Compressed Sensing(CS)is a Machine Learning(ML)method,which can be regarded as a single-layer unsupervised learning method.It mainly emphasizes the sparsity of the model.In this paper,we study an ML-based CS Channel Estimation(CE)method for wireless communications,which plays an important role in Industrial Internet of Things(IIoT)applications.For the sparse correlation between channels in Multiple Input Multiple Output Filter Bank MultiCarrier with Offset Quadrature Amplitude Modulation(MIMO-FBMC/OQAM)systems,a Distributed Compressed Sensing(DCS)-based CE approach is studied.A distributed sparse adaptive weak selection threshold method is proposed for CE.Firstly,the correlation between MIMO channels is utilized to represent a joint sparse model,and CE is transformed into a joint sparse signal reconstruction problem.Then,the number of correlation atoms for inner product operation is optimized by weak selection threshold,and sparse signal reconstruction is realized by sparse adaptation.The experiment results show that the proposed DCS-based method not only estimates the multipath channel components accurately but also achieves higher CE performance than classical Orthogonal Matching Pursuit(OMP)method and other traditional DCS methods in the time-frequency dual selective channels.

Active disturbance rejection control for hydraulic width control system for rough mill

The highly nonlinear behavior of the system limits the performance of classical linear proportional and integral （PI） controllers used for hot rolling. An active disturbance rejection controller is proposed in this paper to deal with the nonlinear problem of hydraulic servo system in order to preserve last response and small overshoot of control system. The active disturbance rejection （ADR） controller is composed of nonlinear tracking differentiator （TD）, extended state observer （ESO） and nonlinear feedback （NF） law. An example of the hydraulic edger system case study is investigated to show the effectiveness and robustness of the proposed nonlinear controller, especially, in the circumstance of foreign disturbance and working condition variation, compared with classic PI controller.

Origin Distribution Patterns and Floating Population Modeling:Yiwu City as a Destination

Existing quantitative migration studies are mainly at the inter-region or inter-province level for lacking of detailed geo-referenced migration data.Meanwhile,few of them integrate explorative spatial data analysis and spatial regression model into migration analysis.Based on aggregated registered floating population data from 2005 to 2008,the phenomena that population floating to Yiwu City in Zhejiang Province is analyzed at the provincial and county levels.The spatial layout of Yiwu's pull forces is proved as a V-shaped pattern excluding Sichuan Province based on map visualization method.Using the migration ratio in 2007 as an explanatory variable,two models are compared using ordinary least square,spatial error model and spatial lag model methods for county-level data in Jiangxi and Anhui provinces.The model with migration stock provides an improved fitting over the model without migration stock according to the model fitting results.The floating population flocking into Yiwu City from Jiangxi is determined mostly by migration stock while the determinant factors are migration stock and distance to Yiwu City for Anhui.The distance-decay effect is true for migration flow from Anhui to Yiwu City while the distance rule is not confirmed in Jiangxi with the best fitting model.The correlation between per capita net income of rural labor forces and migration ratio is not significant in Jiangxi and significant but at the 0.1 level only in Anhui.Further analysis shows that the distance,income and man-land ratio are important factors to explain population floating at earlier stage.However,as the dynamic population floating process evolves,the determinant factor would be migration stock.

Gastrointestinal bleeding caused by extrahepatic arterioportal fistula associated with portal vein thrombosis

An extrahepatic arterioportal fistula(APF) involving the gastroduodenal artery and superior mesenteric vein is rare and mostly results from iatrogenic injuries.The clinical symptoms associated with APFs may include abdominal pain,gastrointestinal bleeding,ascites,nausea,vomiting,diarrhea,or even congestive heart failure.We present the case of a 70-year-old man who presented with chronic abdominal pain and gastrointestinal bleeding secondary to APF and portal vein thrombosis.The endovascular embolization of APF was accomplished successfully,and symptoms of portal hypertension resolved immediately after intervention.Unfortunately,the patient did not respond well to anticoagulation therapy with warfarin.Therefore,the patient underwent implantation of a transjugular intrahepatic portosystemic shunt,and the complications of portal hypertension resolved.In conclusion,the embolization of APF is technically feasible and effective and can be considered the first-choice therapy in selected patients.

Typical Surface Seasonal Circulation in the Indian Ocean Derived from Argos Floats

This study investigates the surface circulation in the Indian Ocean using Argos float data over the period 1979-2011.The Argos observations manifest some new phenomena.The climatological annual mean circulation shows that the surface current becomes much stronger after turning around in shore in the western Indian Ocean.In the tropical Indian Ocean,the Great Whirl(GW) to the east of Somalia develops quickly in spring(April-May) as the monsoon reverses to move northward,becoming strongest in summer(June-September) and disappearing in autumn(October-November).The west end of the Agulhas retroflection can reach 18°E,and it exhibits a seasonal variation.At approximately 90°E,the Agulhas Return Current combines with the eastward South Atlantic Current and finally joins the Antarctic Circumpolar Current.

In-situ Moissanite in Dunite of the Luobusa Ophiolite, Tibet: Implications for Deep Mantle Origin

We report the discovery of an in-situ natural moissanite in Cr-spinel hosted by dunite of the Luobusa ophiolite, Tibet. The dunite envelopes a poditbrm chromitite, separating it from the harzburgite in which the chromitite occurs （Fig. 1）. The moissanite occurs as a twinned grain,

Optimization of critical medium components for enhancing antibacterial thiopeptide nocathiacin I production with significantly improved quality

Nocathiacin I, a glycosylated thiopeptide antibiotic, displays excellent antibacterial activities against multidrug resistant bacterial pathogens. Previously, a novel nocathiacin I formulation for intravenous administration has been successfully developed and its aqueous solubility is greatly enhanced for clinical application. The purpose of the present study was to increase the fermentation titer of nocathiacin I and reduce or eliminate analogous impurities by screening the medium ingredients using response surface methodology. After a sysmatic optimization, a water-soluble medium containing quality-controllable components was developed and validated, resulting in an increase in the production of nocathiacin I from 150 to 405.8 mg·L-1 at 150-L scale. Meanwhile, the analogous impurities existed in reported processes were greatly reduced or eliminated. Using optimized medium for fermentation, nocathiacin I with pharmaceutically acceptable quality was easily obtained with a recovery of 67%. In conclusion, the results from the present study offer a practical and efficient fermentation process for the production of nocathiacin I as a therapeutic agent.

Recent Progress on 2D Transition Metal Compounds-based Electrocatalysts for Efficient Nitrogen Reduction

Ammonia is a commodity chemical with high added value.Electrochemical reduction of nitrogen has great promise for the sustainable synthesis of ammonia in recent vears.Because of its rich resources and unique electronic structure and characteristics,2D transition metal compounds have been used as electrocatalysts for electro-chemical reduction of nitrogen for clean and sustainable production of ammonia,This review outlines the latest development in the use of 2D transition metal compounds as high-efficiency electrocatalysts for nitrogen reduction.reaction(NRR).First,we introduce the N,reduction mechanism,and briefly summarize the performance indicators ofthe catalyst.Then,we focused on the functionalization of unique 2D materials to design high-performance 2D electrocatalysts in respect of simulation calculation and experimental development.Finally,the current challenges and future opportunities for NRR electrocatalvsts are introduced.

Use of breakthrough experiment to evaluate the performance of hydrogen isotope separation for metal-organic frameworks M-MOF-74(M=Co, Ni, Mg, Zn)

The unique adsorption performance of metal-organic frameworks(MOFs) indicates a new direction for gas separation and purification. The low-temperature distillation, as a traditional technique for hydrogen isotope separation, is limited as it is a high energy-and cost-intensive process. Instead of utilizing such a conventional separation route, we use ordered microporous frameworks based on a physical adsorption mechanism to solve the challenge of hydrogen isotope separation. Herein we analyze M-MOF-74(M=Co, Ni, Mg, Zn), featuring a hexagonal channel about 11 ? and high density of open metal sites, for their ability to separate and purify deuterium from the hydrogen isotope mixture by dynamic column breakthrough experiments. Our results show that the combination of the strength of binding sites, density of coordinatively unsaturated metal sites and hydrogen isotope adsorption capacity of materials renders Co-MOF-74 as an optimal adsorbent for the capture of deuterium from hydrogen isotope mixtures in a simulated industrial process.

Performance analysis of multi-hop parallel FSO system over double generalized gamma distribution considering two transmission beams

The performances of multi-hop parallel free space optical(FSO) communication system are investigated over double generalized gamma(double GG) distribution for plane and spherical waves considering path loss and pointing errors(PE). Specifically, the closed-form expressions of outage probability and average bit error rate(ABER) are derived with Meijer-G function and further confirmed by Monte Carlo(MC) simulation. Subsequently, the outage performances of this system are analyzed in detail with the influence of PE, turbulence strengths, structure parameters and weather conditions for plane and spherical waves. Moreover, cyclic coding is used in this work to further optimize system performance.