Interspecific Chromosome Substitution Lines as Genetic Resources for Improvement,Trait Analysis and Genomic Inference

The genetic base that cotton breeders commonly use to improve Upland cultivars is very narrow.The AD-genome species Gossypium barbadense,G.tomentosum,and G.mustelinum are part of

An improved modal pushover analysis procedure for estimating seismic demands of structures

The pushover analysis （POA） procedure is difficult to apply to high-rise buildings, as it cannot account for the contributions of higher modes. To overcome this limitation, a modal pushover analysis （MPA） procedure was proposed by Chopra et al. （2001）. However, invariable lateral force distributions are still adopted in the MPA. In this paper, an improved MPA procedure is presented to estimate the seismic demands of structures, considering the redistribution of inertia forces after the structure yields. This improved procedure is verified with numerical examples of 5-, 9- and 22-story buildings. It is concluded that the improved MPA procedure is more accurate than either the POA procedure or MPA procedure. In addition, the proposed procedure avoids a large computational effort by adopting a two-phase lateral force distribution..

Approach for improving precision of regression analysis of single-replication fertilization experiments in rice

The field experiment designs with single replication were frequently used for factorial experiments in which the numbers of field plots were limited, but the experimental error was difficult to be estimated. To study a new statistical method for improving precision of regression analysis of such experiments in rice, 84 fertilizer experiments were conducted in 15 provinces of China, including Zhejiang, Jiangsu, Anhui, Hunan, Sichuan, Heilongjiang, etc. Three factors with 14 treatments (N: 0—225kg/ha, P: 0 —112. 5kg/ha, K: 0—150kg/ha) and two replications were employed using approaching optimun design. There were 2352 (84×14×2=2352) Yield deviations (d) between the individual treatment yields and its arithmetic mean. The results indicated that:

A genetic diversity assessment of starch quality traits in rice landraces from the Taihu basin,China

There are nearly 1 000 rice landrace varieties in the Taihu basin, China. To assess the genetic diversity of the rice, 24 intragenic molecular markers（representing 17 starch synthesis-related genes） were investigated in 115 Taihu basin rice landraces and 87 improved cultivars simultaneously. The results show that the average genetic diversity and polymorphism information content values of the landraces were higher than those of improved cultivars. In total, 41 and 39 allele combinations（of the 17 genes） were derived from the landraces and improved cultivars, respectively; only two identical allele combinations were found bet ween the two rice variety sources. Cluster analysis, based on the molecular markers, revealed that the rice varieties could be subdivided into five groups and, within these, the japonica improved rice and japonica landrace rice varieties were in two separate groups. According to the quality reference criteria to classify the rice into grades, some of the landraces were found to perform we ll, in terms of starch quality. For example, according to NY /T595-2002 criteria from the Ministry of Agriculture of China, 25 and 33 landraces reached grade 1, in terms of their apparent amylose content and gel consistency. Th e varieties that had outstanding quality could be used as breeding materials for rice quality breeding programs in the future. Our study is useful for future applications, such as genetic diversity studies, the protection of rice variety and improvment of rice quality in breeding programs.

A preliminary study on the effects of line and selective thinning on bird communities in Hokkaido, northern Japan

In Japan, selective thinning is a common thinning method, though line thinning receives much attention because of its economic merits. In this study, we examined effects of the two thinning methods on bird communities in Todo fir （Abies sachalinensis） plantations in Hok- kaido, Japan. We surveyed bird species in forests under four different management types - unthinned, selectively thinned, line-thinned planta- tion, and naturally regenerated forest （here after referred to as natural forest） stands - using a line-transect method. We also investigated vege- tation structure （canopy tree and understory） of these stands. Bird species richness did not differ between natural forests and plantations, while bird total abundance was greater in plantations than in natural forests. Bird species richness and total abundance were comparable among the three management types for plantations. Abundances of 10 bird species were different among the four management types, and five species were more abundant in line-thinned plantations. However, two species were more abundant in selectively thinned stands than in line-thinned stands, and they frequently appeared in natural forests. There were no distinct differ- ences in vegetation structure among the management types for planta- tions. Our results suggest that line thinning could be beneficial for some bird species in plantations.

IoT Information Status Using Data Fusion and Feature Extraction Method

The Internet of Things(IoT)role is instrumental in the technological advancement of the healthcare industry.Both the hardware and the core level of software platforms are the progress resulted from the accompaniment of Medicine 4.0.Healthcare IoT systems are the emergence of this foresight.The communication systems between the sensing nodes and the processors;and the processing algorithms to produce output obtained from the data collected by the sensors are the major empowering technologies.At present,many new technologies supplement these empowering technologies.So,in this research work,a practical feature extraction and classification technique is suggested for handling data acquisition besides data fusion to enhance treatment-related data.In the initial stage,IoT devices are gathered and pre-processed for fusion processing.Dynamic Bayesian Network is considered an improved balance for tractability,a tool for CDF operations.Improved Principal Component Analysis is deployed for feature extraction along with dimension reduction.Lastly,this data learning is attained through Hybrid Learning Classifier Model for data fusion performance examination.In this research,Deep Belief Neural Network and Support VectorMachine are hybridized for healthcare data prediction.Thus,the suggested system is probably a beneficial decision support tool for multiple data sources prediction and predictive ability enhancement.

Application of Improved Matter-element Extension Method in Comprehensive Assessment of Shallow Groundwater

Taking shallow groundwater in Jinjiang City,Fujian Province for example,it was found that the classical element-matter analysis shows deficiency in calculation of correlation function,so the improved matter-element method was applied for the comprehensive assessment of shallow groundwater in Jinjiang City,and the spatial distribution was shown in maps.The assessment results demonstrated that ground water quality of most regions in the study area belonged to Grade I and II,thus the overall quality of shallow groundwater was good.The groundwater of Grade IV and V(relatively poor and extremely poor) was mainly distributed in Dongshi Town,Chendi Town,Zimao Town,and Shenhu Town,major exceeding-standard factors that influence shallow groundwater quality in the local area included TDS,Mn^(2+),NO_3,NO_2,NH_4^+ and Cl^-,which mainly owed to invasion of seawater,original geological conditions,industrial and agricultural discharge,and human life.

Application of Improved SPA Method in the Comprehensive Assessment of Groundwater Environment Quality:A Case Study of Jinjiang, Fujian Province

This paper applied the set pair analysis with improved five-element connection degree to assess shallow groundwater quality of Jinjiang City, Fujian Province, and used map to show the spatial distribution. The assessment results showed that most groundwater in the district was in the grade I and II, i.e. the overall groundwater environment in this area was favorable; groundwater of grade III(poorer level) was mainly distributed in Dongshi Town in the coastal region, and the total area was smaller. Major out-of-limit factors are TDS, nitrate, nitrite, ammonia nitrogen, and chloride, therefore, industrial and agricultural development, human activities and seawater invasion were major causes for the aggravation of water quality.

Identification of key factors affecting the failure of aviation piston engine turbochargers based on an improved correspondence analysis-polar angle-based classification

Turbocharging is an efficient approach for addressing power reduction and oil consumption increase in aviation piston engines during high-altitude flights.However,a turbocharger significantly increases the complexity of a power system,and its considerably complex matching relation with the engine results in a coupling of failure modes.Conventional analytical methods are hard to identify failure-inducing factors.Consequently,safety issues are becoming increasingly prominent.This study focuses on methods for identifying failure-inducing factors.A whole-machine system model is established and validated through experimentation.The response surface method is employed to further abstract the system simulation model to a surrogate model(average error:~3%)in order to reduce the computational cost while ensuring accuracy.On this basis,an improved Correspondence Analysis(CA)-Polar Angle(PA)-based Classification(PAC)is proposed to identify the key factors affecting the failure mode of turbochargers.This identification method is based on the row profile coordinates G varying with the numerical deviations of the key factors,and is capable of effectively identifying the key factors affecting the failure.In a validation example,this method identifies the diameter of the exhaust valve(e_(2))as the primary factor affecting the safety margin for each work boundary.

An improved series expansion method on the multi-frequency analysis of acoustic boundary element

For the multi-frequency acoustic analysis, a series expansion method has been introduced to reduce the computation time of the frequency-independent parts, but the Runge phenomenon will arise when this method is employed in high frequency band. Therefore, this method is improved by analyzing the application condition and proposing the selection principle of the series truncation number. The argument interval can be adjusted with the wavenumber factor. Therefore, the problem of unstable numeration and poor precision can be solved, and the application scope of this method is expanded. The numerical example of acoustic radiation shows that the improved method is correct for acoustic analysis in wider frequency band with less series truncation number and computation amount.

A simple data assimilation method for improving the MODIS LAI time-series data products based on the object analysis and gradient inverse weighted filter

A simple data assimilation method for improving estimation of moderate resolution imaging spectroradiometer （MODIS） leaf area index （LAI） time-series data products based on the gradient inverse weighted filter and object analysis is proposed. The properties and quality control （QC） of MODIS LAI data products are introduced. Also, the gradient inverse weighted filter and object analysis are analyzed. An experiment based on the simple data assimilation method is performed using MODIS LAI data sets from 2000 to 2005 of Guizhou Province in China.

A two-dimensional numerical model for eutrophication in Baiyangdian Lake

Hydrodynamic, physical, and biochemical processes in the Baiyangdian Lake water environment were analyzed comprehensively. An eutrophication eco- dynamics model including the effects of reed resistance on flow was coupled with the hydrodynamics governing equations. An improvement on the Water Quality Analysis Simulation Program （WASP, a modeling system intro- duced by the US Environmental Protection Agency） is established, which uses the zooplankton kinetic equation. The model simulates water quality constituents associated with eutrophication in the lake, including phytoplankton, zooplankton, nitrogen, phosphorus, dissolved oxygen, and others. Various kinetic coefficients were calibrated using measured data or information from relevant literature, to study eutrophication in the lake. The values calculated by the calibrated model agree well with field data, including ammonia nitrogen, total nitrogen, total phosphorus and dissolved oxygen. Changes related to nutrition and dissolved oxygen during the processes were simulated. The present model describes the temporal variation of water quality in Baiyangdian Lake with reasonable accuracy. Deviations between model-simulated and observed values are discussed. As an ideal tool for environmental management of the lake, this model can be used to predict its water quality, and be used in research to examine the eutrophication process.