检索结果-南通市图书馆

Microstructure design using graphs

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

npj Computational Materials 2018年第1期4卷 239-245页

作者： Pengfei Du Adrian Zebrowski Jaroslaw Zola baskar ganapathysubramanian Olga Wodo Department of Mechanical Engineering Iowa State UniversityAmesIAUSA Department of Mechanical and Aerospace Engineering University at BuffaloBuffaloNYUSA Department of Computer Science and Engineering University at BuffaloBuffaloUSA Department of Materials Design and Innovation University at BuffaloBuffaloNYUSA

Thin films with tailored microstructures are an emerging class of materials with applications such as battery electrodes,organic electronics,and *** thin film devices typically exhibit a multi-phase microstructure that is confined,and show large *** approaches to microstructure design focus on optimizing bulk properties,by tuning features that are statistically averaged over a representative ***,we report a tool for morphogenesis posed as a graph-based optimization problem that evolves microstructures recognizing confinement and anisotropy *** illustrate the approach by designing optimized morphologies for photovoltaic applications,and evolve an initial morphology into an optimized morphology exhibiting substantially improved short circuit current(68% improvement over a conventional bulk-heterojunction morphology).We show optimized morphologies across a range of thicknesses exhibiting self-similar *** suggest that thicker films(250 nm)can be used to harvest more incident *** graph based morphogenesis is broadly applicable to microstructure-sensitive design of batteries,biosensors and related applications.

关键词： microstructure Microstructure evolve

Interpretable deep learning for guided microstructure-property explorations in photovoltaics

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

npj Computational Materials 2019年第1期5卷 302-312页

作者： Balaji Sesha Sarath Pokuri Sambuddha Ghosal Apurva Kokate Soumik Sarkar baskar ganapathysubramanian Department of Mechanical Engineering Iowa State UniversityAmesIAUSA Department of Computer Science Iowa State UniversityAmesIAUSA

The microstructure determines the photovoltaic performance of a thin film organic semiconductor *** relationship between microstructure and performance is usually highly non-linear and expensive to evaluate,thus making microstructure optimization ***,we show a data-driven approach for mapping the microstructure to photovoltaic performance using deep convolutional neural *** characterize this approach in terms of two critical metrics,its generalizability(has it learnt a reasonable map?),and its intepretability(can it produce meaningful microstructure characteristics that influence its prediction?).A surrogate model that exhibits these two features of generalizability and intepretability is particularly useful for subsequent design *** illustrate this by using the surrogate model for both manual exploration(that verifies known domain insight)as well as automated microstructure *** envision such approaches to be widely applicable to a wide variety of microstructure-sensitive design problems.

关键词： microstructure property meaningful

Using Machine Learning to Develop a Fully Automated Soybean Nodule Acquisition Pipeline(SNAP)

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Plant Phenomics 2021年第1期3卷 197-208页

作者： Talukder Zaki Jubery Clayton N.Carley Arti Singh Soumik Sarkar baskar ganapathysubramanian Asheesh K.Singh Department of Mechanical Engineering Iowa State UniversityAmesIAUSA Department of Agronomy Iowa State UniversityAmesIAUSA

Nodules form on plant roots through the symbiotic relationship between soybean(Glycine max ***.)roots and bacteria(Bradyrhizobium japonicum)and are an important structure where atmospheric nitrogen(N2)is fixed into bioavailable ammonia(NH3)for plant growth and *** quantification on soybean roots is a laborious and tedious task;therefore,assessment is frequently done on a numerical scale that allows for rapid phenotyping,but is less informative and suffers from *** report the Soybean Nodule Acquisition Pipeline(SNAP)for nodule quantification that combines RetinaNet and UNet deep learning architectures for object(i.e.,nodule)detection and *** was built using data from 691 unique roots from diverse soybean genotypes,vegetative growth stages,and field locations and has a good model fit(R2=0:99).SNAP reduces the human labor and inconsistencies of counting nodules,while acquiring quantifiable traits related to nodule growth,location,and distribution on *** ability of SNAP to phenotype nodules on soybean roots at a higher throughput enables researchers to assess the genetic and environmental factors,and their interactions on nodulation from an early development *** application of SNAP in research and breeding pipelines may lead to more nitrogen use efficiency for soybean and other legume species cultivars,as well as enhanced insight into the plant-Bradyrhizobium relationship.

关键词： soybean breeding cultivar

Soybean Root System Architecture Trait Study through Genotypic,Phenotypic,and Shape-Based Clusters

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Plant Phenomics 2020年第1期2卷 149-171页

作者： Kevin G.Falk Talukder Zaki Jubery Jamie A.O’Rourke Arti Singh Soumik Sarkar baskar ganapathysubramanian Asheesh K.Singh Department of Agronomy Iowa State UniversityAmesIowaUSA Department of Mechanical Engineering Iowa State UniversityAmesIowaUSA USDA-Agricultural Research Service Corn Insects and Crop Genetics Research UnitAmesIowaUSA

We report a root system architecture(RSA)traits examination of a larger scale soybean accession set to study trait genetic *** from the limitation of scale,scope,and susceptibility to measurement variation,RSA traits are tedious to *** 35,448 SNPs with an imaging phenotyping platform,292 accessions(replications=14)were studied for RSA traits to decipher the genetic *** on literature search for root shape and morphology parameters,we used an ideotypebased approach to develop informative root(iRoot)categories using root *** RSA traits displayed genetic variability for root shape,length,number,mass,and *** accessions clustered into eight genotype-and phenotype-based clusters and displayed ***-based clusters correlated with geographical *** profiles indicated that much of US origin genotypes lack genetic diversity for RSA traits,while diverse accession could infuse useful genetic variation for these ***-based clusters were created by integrating convolution neural net and Fourier transformation methods,enabling trait cataloging for breeding and research *** combination of genetic and phenotypic analyses in conjunction with machine learning and mathematical models provides opportunities for targeted root trait breeding efforts to maximize the beneficial genetic diversity for future genetic gains.

关键词： neural breeding Root

Deep Multiview Image Fusion for Soybean Yield Estimation in Breeding Applications

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Plant Phenomics 2021年第1期3卷 286-297页

作者： Luis GRiera Matthew ECarroll Zhisheng Zhang Johnathon MShook Sambuddha Ghosal Tianshuang Gao Arti Singh Sourabh Bhattacharya baskar ganapathysubramanian Asheesh K.Singh Soumik Sarkar Department of Mechanical Engineering Iowa State UniversityAmesIowaUSA Department of Agronomy Iowa State UniversityAmesIowaUSA Department of Computer Science Iowa State UniversityAmesIowaUSA

Reliable seed yield estimation is an indispensable step in plant breeding programs geared towards cultivar development in major row *** objective of this study is to develop a machine learning(ML)approach adept at soybean(Glycine max L.(Merr.))pod counting to enable genotype seed yield rank prediction from in-field video data collected by a ground *** meet this goal,we developed a multiview image-based yield estimation framework utilizing deep learning *** images captured from different angles were fused to estimate the yield and subsequently to rank soybean genotypes for application in breeding *** used data from controlled imaging environment in field,as well as from plant breeding test plots in field to demonstrate the efficacy of our framework via comparing performance with manual pod counting and yield *** results demonstrate the promise of ML models in making breeding decisions with significant reduction of time and human effort and opening new breeding method avenues to develop cultivars.

关键词： breeding soybean cultivar

Detection of the Progression of Anthesis in Field-Grown Maize Tassels:A Case Study

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Plant Phenomics 2021年第1期3卷 43-56页

作者： Seyed Vahid Mirnezami Srikant Srinivasan Yan Zhou Patrick SSchnable baskar ganapathysubramanian Department of Mechanical Engineering Iowa State UniversityAmesIowa 50011USA Department of Agronomy Iowa State UniversityAmesIowa 50011USA School of Computing and Electrical Engineering Indian Institute of Technology MandiKamandH.P.India

The tassel of the maize plant is responsible for the production and dispersal of pollen for subsequent capture by the silk(stigma)and fertilization of the *** the amount and timing of pollen shed are physiological traits that impact the production of a hybrid *** study describes an automated end-to-end pipeline that combines deep learning and image processing approaches to extract tassel flowering patterns from time-lapse camera images of plants grown under field *** lines from the SAM and NAM diversity panels were grown at the Curtiss farm at Iowa State University,Ames,IA,during the summer of *** a set of around 500 pole-mounted cameras installed in the field,images of plants were captured every 10 minutes of daylight hours over a three-week *** data from imaging performed under field conditions is challenging due to variabilities in weather,illumination,and the morphological diversity of *** address these issues,deep learning algorithms were used for tassel detection,classification,and *** processing approaches were then used to crop the main spike of the tassel to track reproductive *** results demonstrated that deep learning with well-labeled data is a powerful tool for detecting,classifying,and segmenting *** sequential workflow exhibited the following metrics:mAP for tassel detection was 0.91,F1 score obtained for tassel classification was 0.93,and accuracy of semantic segmentation in creating a binary image from the RGB tassel images was *** workflow was used to determine spatiotemporal variations in the thickness of the main spike—which serves as a proxy for anthesis progression.

关键词： mounted illumination segmentation

A Weakly Supervised Deep Learning Framework for Sorghum Head Detection and Counting

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Plant Phenomics 2019年第1期1卷 1-14页

作者： Sambuddha Ghosa Bangyou Zheng Scott Chapman Andries B.Potgieter David R.Jordan Xuemin Wang Asheesh K.Singh Arti Singh Masayuki Hirafuji Seishi Ninomiya baskar ganapathysubramanian Soumik Sarkar Wei Guo Department of Mechanical Engineering Iowa State UniversityAmesIAUSA Department of Computer Science Iowa State UniversityAmesIAUSA CSIRO Agriculture and Food St.LuciaQLDAustralia School of Agriculture and Food Sciences The University of QueenslandGattonQLD 4343Australia Queensland Alliance for Agriculture and Food Innovation(QAAFI) The University of QueenslandGattonQLDAustralia Queensland Alliance for Agriculture and Food Innovation(QAAFI) The University of QueenslandWarwickQLDAustralia Department of Agronomy Iowa State UniversityAmesIAUSA International Field Phenomics Research Laboratory Institute for Sustainable Agro-Ecosystem Services

The yield of cereal crops such as sorghum(Sorghum bicolor ***)depends on the distribution of crop-heads in varying branching ***,counting the head number per unit area is critical for plant breeders to correlate with the genotypic variation in a specific breeding ***,measuring such phenotypic traitsmanually is an extremely labor-intensive process and suffers from low efficiency and human ***,the process is almost infeasible for large-scale breeding plantations or *** learning-based approaches like deep convolutional neural network(CNN)based object detectors are promising tools for efficient object detection and ***,a significant limitation of such deep learningbased approaches is that they typically require a massive amount of hand-labeled images for training,which is still a tedious ***,we propose an active learning inspired weakly supervised deep learning framework for sorghum head detection and counting from UAV-based *** demonstrate that it is possible to significantly reduce human labeling effort without compromising final model performance(R^(2)between human count and machine count is 0.88)by using a semitrained CNN model(i.e.,trained with limited labeled data)to perform synthetic *** addition,we also visualize key features that the network *** improves trustworthiness by enabling users to better understand and trust the decisions that the trained deep learning model makes.

关键词： Unmanned aerial vehicles (UAV)

Development of Optimized Phenomic Predictors for Efficient Plant Breeding Decisions Using Phenomic-Assisted Selection in Soybean

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Plant Phenomics 2019年第1期1卷 106-120页

作者： Kyle Parmley Koushik Nagasubramanian Soumik Sarkar baskar ganapathysubramanian Asheesh K.Singh Department of Agronomy Iowa StateUniversityAmesIAUSA Department of Electrical Engineering Iowa State UniversityAmesIAUSA Department of Mechanical Engineering Iowa State UniversityAmesIAUSA

The rate of advancement made in phenomic-assisted breeding methodologies has lagged those of genomic-assisted techniques,which is now a critical component of mainstream cultivar development ***,advancements made in phenotyping technologies have empowered plant scientists with affordable high-dimensional datasets to optimize the operational efficiencies of breeding *** and seed yield data was collected across six environments for a panel of 292 soybean accessions with varying genetic *** forest,a machine learning(ML)algorithm,was used to map complex relationships between phenomic traits and seed yield and prediction performance assessed using two cross-validation(CV)scenarios consistent with breeding *** develop a prescriptive sensor package for future high-throughput phenotyping deployment to meet breeding objectives,feature importance in tandem with a genetic algorithm(GA)technique allowed selection of a subset of phenotypic traits,specifically optimal *** results illuminated the capability of fusingML and optimization techniques to identify a suite of in-season phenomic traits that will allow breeding programs to decrease the dependence on resource-intensive end-season phenotyping(e.g.,seed yield harvest).While we illustrate with soybean,this study establishes a template for deploying multitrait phenomic prediction that is easily amendable to any crop species and any breeding objective。

关键词： breeding soybean forest

Shaped 3D microcarriers for adherent cell culture and analysis

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Microsystems & Nanoengineering 2018年第1期4卷 199-207页

作者： Chueh-Yu Wu Daniel Stoecklein Aditya Kommajosula Jonathan Lin Keegan Owsley baskar ganapathysubramanian Dino Di Carlo Department of Bioengineering University of CaliforniaLos AngelesCAUSA Department of Mechanical and Aerospace Engineering University of CaliforniaLos AngelesCAUSA California NanoSystems Institute University of CaliforniaLos AngelesCAUSA Jonsson Comprehensive Cancer Center University of CaliforniaLos AngelesCAUSA Department of Mechanical Engineering Iowa State UniversityAmesIAUSA

Standard tissue culture of adherent cells is known to poorly replicate physiology and often entails suspending cells in solution for analysis and sorting,which modulates protein expression and eliminates intercellular *** allow adherent culture and processing in flow,we present 3D-shaped hydrogel cell microcarriers,which are designed with a recessed nook in a first dimension to provide a tunable shear-stress shelter for cell growth,and a dumbbell shape in an orthogonal direction to allow for self-alignment in a confined flow,important for processing in flow and imaging flow *** designed a method to rapidly design,using the genetic algorithm,and manufacture the microcarriers at scale using a transient liquid molding optofluidic *** ability to precisely engineer the microcarriers solves fundamental challenges with shear-stress-induced cell damage during liquid-handling,and is poised to enable adherent cell culture,in-flow analysis,and sorting in a single format.

关键词： culture sorting analysis