Mapping soil organic matter in cultivated land based on multi-year composite images on monthly time scales

Rapid and accurate acquisition of soil organic matter(SOM)information in cultivated land is important for sustainable agricultural development and carbon balance management.This study proposed a novel approach to predict SOM with high accuracy using multiyear synthetic remote sensing variables on a monthly scale.We obtained 12 monthly synthetic Sentinel-2 images covering the study area from 2016 to 2021 through the Google Earth Engine(GEE)platform,and reflectance bands and vegetation indices were extracted from these composite images.Then the random forest(RF),support vector machine(SVM)and gradient boosting regression tree(GBRT)models were tested to investigate the difference in SOM prediction accuracy under different combinations of monthly synthetic variables.Results showed that firstly,all monthly synthetic spectral bands of Sentinel-2 showed a significant correlation with SOM(P<0.05)for the months of January,March,April,October,and November.Secondly,in terms of single-monthly composite variables,the prediction accuracy was relatively poor,with the highest R^(2)value of 0.36 being observed in January.When monthly synthetic environmental variables were grouped in accordance with the four quarters of the year,the first quarter and the fourth quarter showed good performance,and any combination of three quarters was similar in estimation accuracy.The overall best performance was observed when all monthly synthetic variables were incorporated into the models.Thirdly,among the three models compared,the RF model was consistently more accurate than the SVM and GBRT models,achieving an R^(2)value of 0.56.Except for band 12 in December,the importance of the remaining bands did not exhibit significant differences.This research offers a new attempt to map SOM with high accuracy and fine spatial resolution based on monthly synthetic Sentinel-2 images.

Classification of four distinct osteoarthritis subtypes with a knee joint tissue transcriptome atlas

The limited molecular classifications and disease signatures of osteoarthritis(OA)impede the development of prediagnosis and targeted therapeutics for OA patients.To classify and understand the subtypes of OA,we collected three types of tissue including cartilage,subchondral bone,and synovium from multiple clinical centers and constructed an extensive transcriptome atlas of OA patients.By applying unsupervised clustering analysis to the cartilage transcriptome,OA patients were classified into four subtypes with distinct molecular signatures:a glycosaminoglycan metabolic disorder subtype(C1),a collagen metabolic disorder subtype(C2),an activated sensory neuron subtype(C3),and an inflammation subtype(C4).Through ligand-receptor crosstalk analysis of the three knee tissue types,we linked molecular functions with the clinical symptoms of different OA subtypes.For example,the Gene Ontology functional term of vasculature development was enriched in the subchondral bone-cartilage crosstalk of C2 and the cartilage-subchondral bone crosstalk of C4,which might lead to severe osteophytes in C2 patients and apparent joint space narrowing in C4 patients.Based on the marker genes of the four OA subtypes identified in this study,we modeled OA subtypes with two independent published RNA-seq datasets through random forest classification.The findings of this work contradicted traditional OA diagnosis by medical imaging and revealed distinct molecular subtypes in knee OA patients,which may allow for precise diagnosis and treatment of OA.

An Exponential Chaotic Oscillator Design and Its Dynamic Analysis

After years of development, chaotic circuits have possessed many different mathematic forms and multiple realization methods. However, in most of the existing chaotic systems, the nonlinear units are composed of the product terms. In this paper, in order to obtain a chaotic oscillator with higher nonlinearity and complexity to meet the needs of utilization, we discuss a novel chaotic system whose nonlinear term is realized by an exponential term. The new exponential chaotic oscillator is constructed by adding an exponential term to the classical Lüsystem. To further investigate the dynamic characteristics of the oscillator, classical theoretical analyses have been performed, such as phase diagrams, equilibrium points, stabilities of the system,Poincaré mappings, Lyapunov exponent spectrums, and bifurcation diagrams. Then through the National Institute of Standards and Technology(NIST) statistical test, it is proved that the chaotic sequence generated by the exponential chaotic oscillator is more random than that produced by the Lü system. In order to further verify the practicability of this chaotic oscillator, by applying the improved modular design method, the system equivalent circuit has been realized and proved by the Multisim simulation. The theoretical analysis and the Multisim simulation results are in good agreement.

Incorporation of source contributions to improve the accuracy of soil heavy metal mapping using small sample sizes at a county scale

Estimating heavy metal(HM) distribution with high precision is the key to effectively preventing Chinese medicinal plants from being polluted by the native soil. A total of 44 surface soil samples were gathered to detect the concentrations of eight HMs(As, Hg, Cu, Cr, Ni, Zn, Pb, and Cd) in the herb growing area of Luanping County, northeastern Hebei Province, China. An absolute principal component score-multiple linear regression(APCS-MLR) model was used to quantify pollution source contributions to soil HMs. Furthermore, the source contribution rates and environmental data of each sampling point were simultaneously incorporated into a stepwise linear regression model to identify the crucial indicators for predicting soil HM spatial distributions. Results showed that 88% of Cu, 72% of Cr, and 72% of Ni came from natural sources;50% of Zn, 49% of Pb, and 59% of Cd were mainly caused by agricultural activities;and 44% of As and 56% of Hg originated from industrial activities. When three-type(natural, agricultural, and industrial) source contribution rates and environmental data were simultaneously incorporated into the stepwise linear regression model, the fitting accuracy was significantly improved and the model could explain 31%–86% of the total variance in soil HM concentrations. This study introduced three-type source contributions of each sampling point based on APCS-MLR analysis as new covariates to improve soil HM estimation precision, thus providing a new approach for predicting the spatial distribution of HMs using small sample sizes at the county scale.

Effect of polyethylene glycol on the crystallization,rheology and foamability of poly(lactic acid)containing in situ generated polyamide 6 nanofibrils

In this study,the rheological properties,crystallization and foaming behavior of poly(lactic acid)with polyamide 6 nanofibrils were examined with polyethylene glycol as a compatibilizer.Polyamide 6 particles were deformed into nanofibrils during drawing.For the 10%polyamide 6 case,polyethylene glycol addition reduced the polyamide 6 fibril diameter from 365.53 to 254.63 nm,owing to the smaller polyamide 6 particle size and enhanced interface adhesion.Rheological experiments revealed that the viscosity and storage modulus of the composites were increased,which was associated with the three-dimensional entangled network of polyamide 6 nanofibrils.The presence of higher aspect ratio polyamide 6 nanofibrils substantially enhanced the melt strength of the composites.The isothermal crystallization kinetics results suggested that the polyamide 6 nanofibrils and polyethylene glycol had a synergistic effect on accelerating poly(lactic acid)crystallization.With the polyethylene glycol,the crystallization half-time reduced from 103.6 to 62.2 s.Batch foaming results indicated that owing to higher cell nucleation efficiency,the existence of polyamide 6 nanofibrils led to a higher cell density and lower expansion ratio.Furthermore,the poly(lactic acid)/polyamide 6 foams exhibited a higher cell density and expansion ratio than that of the foams without polyethylene glycol.

Simulation study of integrated‐gate‐commutated‐thyristor based superconducting hybrid direct current circuit breaker

With the development of a distributed generation,direct current(DC)load and energy‐storage equipment,voltage‐source‐converter‐based medium‐voltage DC systems(VSC‐MVDC)have attracted more attention due to its low power consumption,high reliability,independent power control and so on.However,VSC‐MVDC has the problem of DC fault isolation,which requires the fast‐acting DC circuit‐breakers to isolate faulty lines and ensure low cost.This problem can be solved by coordinating resistive type superconducting‐fault‐current‐limiter(R‐SFCL)and integrated‐gate‐commutated‐thyristor(IGCT)based hybrid circuit breaker.Based on this,IGCT based superconducting DC circuit breaker(SDCCB)is proposed and analysed.Combining R‐SFCL with IGCT could realise large current limiting and interruption and ensure low cost.In addition,the IGCT based hybrid DC circuit breaker(IGCT‐HDCCB)is compared with the traditional insulated gate bipolar transistor(IGBT)based hybrid DC circuit breaker(IGBT‐HDCCB)to evaluate which circuit breaker is more suitable for VSC‐MVDC.The results show that,coordination based on R‐SFCL and SDCCB,the fault current is successfully limited from 17.6 to 2.1 kA,and then inter-rupted within 3.8 ms.In addition,IGCT‐HDCCB overcomes the disadvantage that IGCT has less interrupting capacity than IGBT,retains the advantage of low cost of IGCT and is more suitable for MVDC system.

口腔专科医院成功抢救老年候诊患者心脏骤停1例

目的:本文通过总结口腔专科医院老年候诊患者心脏骤停的抢救过程1例,希望为口腔医务人员处理类似情况提供参考。诊治经过:患者女性,85岁,在口腔门诊候诊时突发心脏骤停,医护人员第一时间进行心肺复苏、电除颤、启动应急预案、使用急救药物、建立静脉通道、气管插管、呼吸机控制通气等一系列急救措施。结果:经过62分钟急救,患者心跳逐渐恢复,顺利完成交接转院进行后续治疗。结论:口腔专科医院医务人员应熟练掌握各种常用的医学急救知识和技能,各科室需合理配置急救设备和药品,制定相应的抢救制度及流程,并定期进行急救演练。