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Evaluation of energy values of high-fiber dietary ingredients with different solubility fed to growing pigs using the difference and regression methods

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Animal Nutrition 2021年第2期7卷 569-575页

作者： Zhengqun Liu Ruqing Zhong Kai Li Liang Chen Bifeng Zhang Lei Liu Hongfu Zhang State Key Laboratory of Animal Nutrition Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193China Institute of Animal Science and Veterinary Tianjin Academy of Agricultural SciencesTianjin300381China

The objective of this study was to compare the energy values of high-fiber dietary ingredients with different solubility(sugar beet pulp[SBP]and defatted rice bran[DFRB])in growing pigs using the difference and the regression methods.A total of 21 barrows(initial BW,40.5±1.2 kg)were assigned to 3 blocks with BW as a blocking factor,and each block was assigned to a 7×2 incomplete Latin square design with 7 diets and two 13-d experimental *** 7 experimental diets consisted of a corn-soybean meal basal diet and 6 additional diets containing 10%,20%,or 30%SBP or DFRB in the basal diet,*** of the exper-imental periods lasted 12 d,with a 7 d dietary adaptation period followed by 5-d total fecal and urine *** showed that the digestible energy(DE)and metabolizable energy(ME)of the SBP determined by the difference method with different inclusion levels(10%,20%,or 30%)were 2,712 and 2,628 kcal/kg,2,683 and 2,580 kcal/kg,and 2,643 and 2,554 kcal/kg DM basis,*** DE and ME in the DFRB evaluated by the difference method with 3 different inclusion levels were 2,407 and 2,243 kcal/kg,2,687 and 2,598 kcal/kg,and 2,630 and 2,544 kcal/kg DM basis,*** inclusion levels had no effects on the energy values of each test ingredient estimated by the difference *** DE and ME of the SBP and the DFRB estimated by the regression method were 2,562 and 2,472 kcal/kg and 2,685 and 2,606 kcal/kg DM basis,*** energy values of each ingredient determined by the regression method were similar to the values estimated by the difference method with the 20%or 30%inclusion ***,the energy values of the SBP and DFRB estimated by the difference method with the 10%inclusion level were inconsistent with the values determined by the regression method(Pregression method was a robust indirect method to evaluate the energy values for high-fiber ingredients with different solubility in growing pi

关键词： High-fiber ingredient Energy value Difference method regression method Inclusion level Growing pigs

Machine Learning-Based Seismic Fragility Analysis of Large-Scale Steel Buckling Restrained Brace Frames

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Computer Modeling in Engineering & Sciences 2020年第11期125卷 755-776页

作者： Baoyin Sun Yantai Zhang Caigui Huang Key Laboratory of Earthquake Engineering and Engineering Vibration Institute of Engineering MechanicsChina Earthquake AdministrationHarbin150080China Faculty of Infrastructure Engineering Dalian University of TechnologyDalian116024China College of Civil Engineering Nanjing Forestry UniversityNanjing210037China School of Architecture and Civil Engineering Xiamen UniversityXiamen361005China

Steel frames equipped with buckling restrained braces(BRBs)have been increasingly applied in earthquake-prone areas given their excellent capacity for resisting lateral ***,special attention has been paid to the seismic risk assessment(SRA)of such structures,e.g.,seismic fragility *** approaches,e.g.,nonlinear finite element simulation(NFES),are computationally inefficient for SRA analysis particularly for large-scale steel BRB frame *** this study,amachine learning(ML)-based seismic fragility analysis framework is established to effectively assess the risk to structures under seismic loading *** optimal artificial neural network model can be trained using calculated damage and intensity measures,a technique which will be used to compute the fragility curves of a steel BRB frame instead of employing *** results show that a highly efficient instantaneous failure probability assessment can be made with the proposed framework for realistic large-scale building structures.

关键词： Machine learning Monte Carlo simulation regression method fragility analysis buckling restrained braces

National variability in soil organic carbon stock predictions:Impact of bulk density pedotransfer functions

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国际水土保持研究（英文） 2024年第4期12卷 868-884页

作者： May-Thi Tuyet Do Linh Nguyen Van Xuan-Hien Le Giang V.Nguyen Minho Yeon Giha Lee Department of Advanced Science and Technology Convergence Kyungpook National University2559 Gyeongsang-daeroSangju-si37224South Korea Disaster Prevention Emergency Management Institute Kyungpook National University2559 Gyeongsang-daeroSangju-si37224South Korea Thuyloi University 175 Tay SonDong DaHanoi10000Viet Nam

Accurate soil organic carbon storage(SOCS)estimation is crucial for sustaining ecosystem health and mitigating climate change *** study investigated the accuracy and variability of SOCS pre-dictions,focusing on the role of pedotransfer functions(PTFs)in estimating soil bulk density(BD).Uti-lizing a comprehensive dataset from the Korean Rural Development Administration(RDA database),which includes 516 soil horizons,we evaluated 36 widely-used BD PTFs,well-established formulas that estimate BD by considering soil properties,including soil organic carbon(SOC),soil organic matter(OM),sand,gravel,silt,and *** PTFs demonstrated varying levels of precision,with root mean squared errors(RMSE)ranging from 0.177 to 0.377 Mg m-3 and coefficients of determination(R2)from 0.176 to 0.658;hence,the PTFs have been classified into excellent,moderate,and poor-performing groups for predicting ***,a novel PTF based on an exponential function of SOC was developed,showing superior predictive power(R2=0.73)compared to existing PTFs,using an independent validation *** findings reveal significant differences in SOCS predictions and observations among the PTFs,with a p-value＜*** highest concentrations of SOCS were noted in forest soils,considerably above the national average,highlighting the importance of tailored soil management practices to enhance carbon *** findings are crucial for refining PTF precision to improve the accuracy of national SOCS estimates,supporting effective land management and climate change mitigation strategies.

关键词： RDA database Soil organic carbon stock prediction Pedotransfer function Bayesian model average regression method

Design and experiment of the double-seed hole seeding precision seed metering device for peanuts

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International Journal of Agricultural and Biological Engineering 2022年第3期15卷 107-114页

作者： Xiaoshun Zhao Wenjing Ran Jianjun Hao Wenjie Bai Xinlei Yang College of Mechanical and Electrical Engineering Hebei Agricultural UniversityBaoding 071001HebeiChina

A secondary seeding precision double-seed peanut hole seeding seed metering device was designed to improve the performance of the peanut planting equipment and provide a solution for problems on the high seed charge that can cause poor cavitation and uniformity *** main structure and operation parameters in terms of groove length,seed charge height,seed-bed belt speed,and rotation speed of the seed metering wheel were determined through theoretical ***-factor and orthogonal tests were carried out through the JPS-12 seed metering device test bench,and the peanut variety Jinonghua-3 was selected as the test *** single hole double-seed rate,qualified rate,the variation coefficient of hole spacing,and hole rate were chosen for evaluating the working *** results of the single-factor test showed that the seed metering performance is mainly affected by the groove length,the speed of the seed-bed belt and the rotation speed of the seed metering wheel,and the influence of the cavitation rate is *** optimal seeding height is determined to be 40 *** results of the orthogonal test showed that the groove length was 27.3 mm,the seed-bed belt speed was 1.51 km/h,and the rotation speed of the seed metering wheel was 14.11 r/***’s more,a regression model based on the orthogonal test results was established,the qualified rate of the number of holes obtained after optimizing the model was 98.84%,the variation coefficient of hole spacing was 9.74%,and the hole rate was 1.40%.Notably,the working performances of the device can meet the requirement of precision seeding.

关键词： peanut precision seed metering device orthogonal test regression method

Optimized design and performance evaluation of an electric cup-chain potato metering device

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International Journal of Agricultural and Biological Engineering 2017年第2期10卷 36-43页

作者： Niu Kang Fang Xianfa Liu Yangchun Lü Chengxu Yuan Yanwei College of Engineering China Agricultural UniversityBeijing 100083China State Key Laboratory of Soil-Plant-Machine System Technology Chinese Academy of Agricultural Mechanization SciencesBeijing 100083China

The cup-chain metering device is commonly used in potato planters despite its problems of missing-seeding,double-seeding and ground wheel sliding.A mechanical-electrical design was developed for planters to resolve these problems.A regression experiment was conducted with three factors(chain speed,chain tightening distance and cup tilting)and two indicators(missing-seeding rate and double-seeding rate).Based on the results of regression experiment,a numerical regression model was built and a multi-objective optimization method was used to get an optimal ***,the optimized device was tested in the *** device design presents a tilting seed cup with a guard plate and an electric control *** laboratory test showed that the missing-seeding rate increased with the chain *** initially decreases and then increases with the chain tightening distance and cup tilting *** double-seeding rate declines with chain *** increases initially and declines afterward with the chain tightening *** optimization resulted in a missing-seeding rate of 4.39%and a double-seeding rate of 8.78%under the parameters of 0.32 m/s seeding speed,0.94×10-3 m tightening distance,and 12.5°cup tilting *** field test demonstrated that electric control instead of ground wheel-driven chain enables fast seeding and precise intra-row seeding distance.

关键词： potato planter cup-chain metering device multi-objective optimization regression method

A novel stress-based formulation of finite element analysis

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2021年第6期22卷 481-491页

作者： Himanshu GAUR Lema DAKSSA Mahmoud DA WOOD Nitin Kumar SAMAIYA Institute of Structural Mechanics Bauhaus-Universitat WeimarMarienstrasse 15D-99423 WeimarGermany Department of Civil Engineering Middle East CollegeKnowledge Oasis Muscat(KOM)Al RusaylMuscat 124Oman Department of Civil Engineering Jaypee University of Engineering and TechnologyGuna(M.P.)-473226India

This paper demonstrates a novel formulation of structural analysis.A novel stress-based formulation of structural analysis for material nonlinear problems was proposed in earlier *** this paper,this methodology is further extended for 3 D finite element *** approach avoids use of elastic moduli as the material input in the analysis *** utilizes the whole stress-strain curve of the *** can be shown that this analysis procedure solved the nonlinear or plasticity problem with relative *** paper solves a uniaxial bar,in which the results are compared with the solutions of Green-Lagrange strain and Piola-Kirchhoff *** uniaxial bar is also solved by a regression model in the‘scikit-learn’module in *** second problem solved is of a beam in pure bending for which the energy release rate is *** the beam in pure bending,the bending moment carrying capacity of the beam section is evaluated by this methodology as the crack propagates through the depth of the *** can be shown that the methodology is very simple,accurate,and clear in its physical steps.

关键词： Computational methods Machine learning regression method Material non-linear analysis Finite element analysis