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Switchgrass sward establishment selection is consistent across multiple environments and fertilization levels

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Grassland Research 2022年第4期1卷 252-261页

作者： neal W.Tilhou Michael D.Casler Department of Agronomy University of WisconsinMadisonWisconsinUSA USDA-ARS US Dairy Forage Research CenterMadisonWisconsinUSA

Background Strong selection can occur during switchgrass sward *** in establishment selection due to environment or management could provide information on genotype-by-environment variation and could influence strategies for breeding perennial *** Leaf samples were collected before sward establishment and from 3-year-old swards for two breeding groups(lowland and hybrid)at three *** two locations,samples were collected from paired fertilized(112 kg N ha−1)and unfertilized *** frequencies from pooled DNA samples were studied through multivariate analysis of variance,genomewide trait predictions(heading date and winter survivorship),and genomically estimated breeding values(GEBVs)for individual sward survival within an independent data *** This study found only minor variations in selection due to location or *** heading dates of the hybrid population had significant changes due to fertilization and *** were strong correlations among sward establishment survival GEBVs between growing environments(hybrid r=0.77;gulf r=0.97).Interestingly,this study found a small number of genotypes that were over-represented in established swards across all growing environments.

关键词： genomic prediction grassland establishment Panicum virgatum polygenic traits selection

Safety Analysis of Riding at Intersection Entrance Using Video Recognition Technology

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Computers, Materials & Continua 2022年第9期72卷 5135-5148页

作者： Xingjian Xue Linjuan Ge Longxin Zeng Weiran Li Rui Song neal N.Xiong College of Landscape Architecture Central South University of Forestry and TechnologyChangshaHunan410004China College of Logistics and Transportation Central South University of Forestry and TechnologyChangshaHunan410004China Department of Mathematics and Computer Science Northeastern State UniversityTahlequahOK74464United States

To study riding safety at intersection entrance,video recognition technology is used to build vehicle-bicycle conflict models based on the Bayesian *** is analyzed the relationship among the width of nonmotorized lanes at the entrance lane of the intersection,the vehicle-bicycle soft isolation form of the entrance lane of intersection,the traffic volume of right-turning motor vehicles and straight-going non-motor vehicles,the speed of right-turning motor vehicles,and straight-going non-motor vehicles,and the conflict between right-turning motor vehicles and straight-going nonmotor *** to the traditional statistical methods,to overcome the discreteness of vehicle-bicycle conflict data and the differences of influencing factors,the Bayesian random effect Poisson-log-normal model and random effect negative binomial regression model are *** results show that the random effect Poisson-log-normal model is better than the negative binomial distribution of random effects;The width of non-motorized lanes,the form of vehicle-bicycle soft isolation,the traffic volume of right-turning motor vehicles,and the coefficients of straight traffic volume obey a normal *** them,the type of vehicle-bicycle soft isolation facilities and the vehicle-bicycle traffic volumes are significantly positively correlated with the number of vehicle-bicycle *** width of non-motorized lanes is significantly negatively correlated with the number of vehicle-bicycle *** periods and flat periods,the average speed of right-turning motor vehicles,and the average speed of straight-going non-motor vehicles have no significant influence on the number of vehicle-bicycle conflicts.

关键词： Video recognition technology vehicle-bicycle conflict intersection entrance random effect poisson-log-normal model random effect negative binomial regression model

Deep Neural Network-based Speaker-Aware Information Logging for Augmentative and Alternative Communication

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Journal of Artificial Intelligence and Technology 2021年第2期1卷 138-143页

作者： Gang Hu Szu-Han Kay Chen neal Mazur Department of Computer Information State University of New York Buffalo StateBuffaloNY 14222 USA Department of Communication Disorders and Sciences State University of New YorkFredoniaNY 14063 USA

People with complex communication needs can use a high-technology augmentative and alternative communication device to communicate with ***,researchers and clinicians often use data logging from high-tech augmentative and alternative communication devices to analyze augmentative and alternative communication user ***,existing automated data logging systems cannot differentiate the authorship of the data log when more than one user accesses the *** issue reduces the validity of the data logs and increases the difficulties of performance ***,this paper presents a solution using a deep neural network-based visual analysis approach to process videos to detect different augmentative and alternative communication users in practice *** approach has significant potential to improve the validity of data logs and ultimately to enhance augmentative and alternative communication outcome measures.

关键词： augmentative and alternative communication(AAC) outcome measures visual logs hand tracking deep learning

A Fully Convolutional Neural Network-based Regression Approach for Effective Chemical Composition Analysis Using Near-infrared Spectroscopy in Cloud

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Journal of Artificial Intelligence and Technology 2021年第1期1卷 74-82页

作者： Daiyu Jiang Gang Hu Guanqiu Qi neal Mazur College of Automation Chongqing University of Posts and TelecommunicationsChongqing 400065China Computer Information Systems Department State University of New York at Buffalo StateBuffaloNY 14222 USA

As one chemical composition,nicotine content has an important influence on the quality of tobacco *** and nondestructive quantitative analysis of nicotine is an important task in the tobacco ***-infrared(NIR)spectroscopy as an effective chemical composition analysis technique has been widely *** this paper,we propose a one-dimensional fully convolutional network(1D-FCN)model to quantitatively analyze the nicotine composition of tobacco leaves using NIR spectroscopy data in a cloud *** 1D-FCN model uses one-dimensional convolution layers to directly extract the complex features from sequential spectroscopy *** consists of five convolutional layers and two full connection layers with the max-pooling layer replaced by a convolutional layer to avoid information *** computing techniques are used to solve the increasing requests of large-size data analysis and implement data sharing and *** results show that the proposed 1D-FCN model can effectively extract the complex characteristics inside the spectrum and more accurately predict the nicotine volumes in tobacco leaves than other *** research provides a deep learning foundation for quantitative analysis of NIR spectral data in the tobacco industry.

关键词： nicotine tobacco leaves near-infrared spectroscopy fully convolutional network cloud computing

Prediction of impedance responses of protonic ceramic cells using artificial neural network tuned with the distribution of relaxation times

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Journal of Energy Chemistry 2023年第3期78卷 582-588,I0016页

作者： Xuhao Liu Zilin Yan Junwei Wu Jake Huang Yifeng Zheng neal PSullivan Ryan O'Hayre Zheng Zhong Zehua Pan School of Science Harbin Institute of TechnologyShenzhen 518055GuangdongChina School of Materials Engineering Harbin Institute of TechnologyShenzhen 518055GuangdongChina Department of Metallurgical and Materials Engineering Colorado School of Mines1500 Illinois St.Golden 80401ColoradoUSA College of Materials Science and Engineering Nanjing Tech UniversityNo.30 Puzhu Road(S)Nanjing 211816JiangsuChina Department of Mechanical Engineering Colorado School of Mines1500 Illinois St.Golden 80401ColoradoUSA

A deep-learning-based framework is proposed to predict the impedance response and underlying electrochemical behavior of the reversible protonic ceramic cell(PCC) across a wide variety of different operating *** impedance spectra(EIS) of PCCs were first acquired under a variety of opera ting conditions to provide a dataset containing 36 sets of EIS spectra for the *** artificial neural network(ANN) was then trained to model the relationship between the cell operating condition and EIS ***,ANN model-predicted EIS spectra were analyzed by the distribution of relaxation times(DRT) and compared to DRT spectra obtained from the experimental EIS data,enabling an assessment of the accumulative errors from the predicted EIS data vs the predicted *** show that in certain cases,although the R^(2)of the predicted EIS curve may be> 0.98,the R^(2)of the predicted DRT may be as low as~*** can lead to an inaccurate ANN prediction of the underlying time-resolved electrochemical response,although the apparent accuracy as evaluated from the EIS prediction may seem *** adjustment of the parameters of the ANN framework,the average R^(2)of the DRTs derived from the predicted EIS can be improved to ***,we demonstrate that a properly tuned ANN model can be used as an effective tool to predict not only the EIS,but also the DRT of complex electrochemical systems.

关键词： Protonic ceramic fuel cell/electrolysis cell Electrochemical impedance spectroscopy Distribution of relaxation times Artiﬁcial neural network

Review of the current targeted therapies for non-small-cell lung cancer

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World Journal of Clinical Oncology 2014年第4期5卷 576-587页

作者： Kim-Son H Nguyen Joel W neal Heather Wakelee Division of Oncology Department of Medicine Stanford University School of MedicineStanford CA 94305 United States Division of Oncology Department of Medicine Stanford University School of Medicine StanfordCA 94305 United States

The last decade has witnessed the development of oncogene-directed targeted therapies that have significantly changed the treatment of non-small-cell lung cancer(NSCLC). In this paper we review the data demonstrating efficacy of gefitinib, erlotinib, and afatinib, which target the epidermal growth factor receptor(EGFR), and crizotinib which targets anaplastic lymphoma kinase(ALK). We discuss the challenge of acquired resistance to these small-molecular tyrosine kinase inhibitors and review promising agents which may overcome resistance, including the EGFR T790 Mtargeted agents CO-1686 and AZD9291, and the ALKtargeted agents ceritinib(LDK378), AP26113, alectinib(CH/RO5424802), and others. Emerging therapies directed against other driver oncogenes in NSCLC including ROS1, HER2, and BRAF are covered as well. The identification of specific molecular targets in a significant fraction of NSCLC has led to the personalized deployment of many effective targeted therapies, with more to come.

关键词： Lung cancer Non-small cell lung cancer Targeted therapies Epidermal growth factor receptor Epidermal growth factor receptor Anaplastic lymphoma kinase Anaplastic lymphoma kinase Acquired resistance

Aortic Dissection Diagnosis Based on Sequence Information and Deep Learning

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Computers, Materials & Continua 2022年第11期73卷 2757-2771页

作者： Haikuo Peng Yun Tan Hao Tang Ling Tan Xuyu Xiang Yongjun Wang neal N.Xiong Central South University of Forestry and Technology Changsha410004China The Second Xiangya Hospital of Central South University Changsha410011China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464USA

Aortic dissection(AD)is one of the most serious diseases with high mortality,and its diagnosis mainly depends on computed tomography(CT)*** existing automatic diagnosis methods of AD are only suitable for AD recognition,which usually require preselection of CT images and cannot be further classified to different *** this work,we constructed a dataset of 105 cases with a total of 49021 slices,including 31043 slices expertlevel annotation and proposed a two-stage AD diagnosis structure based on sequence information and deep *** proposed region of interest(RoI)extraction algorithm based on sequence information(RESI)can realize high-precision for RoI identification in the first *** DenseNet-121 is applied for further ***,the proposed method can judge the type of AD without preselection of CT *** experimental results show that the accuracy of Stanford typing classification of AD is 89.19%,and the accuracy at the slice-level reaches 97.41%,which outperform the state-ofart *** can provide important decision-making information for the determination of further surgical treatment plan for patients.

关键词： Aortic dissection deep learning sequence information RoI

Risk Prediction of Aortic Dissection Operation Based on Boosting Trees

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Computers, Materials & Continua 2021年第11期69卷 2583-2598页

作者： Ling Tan Yun Tan Jiaohua Qin Hao Tang Xuyu Xiang Dongshu Xie neal N.Xiong The Second Xiangya Hospital of Central South University Changsha410011HunanChina Central South University of Forestry&Technology Changsha410004HunanChina Northeastern State University Tahlequah74464OKUSA

During the COVID-19 pandemic,the treatment of aortic dissection has faced additional *** necessary medical resources are in serious shortage,and the preoperative waiting time has been significantly prolonged due to the requirement to test for COVID-19 *** this work,we focus on the risk prediction of aortic dissection surgery under the influence of the COVID-19 pandemic.A general scheme of medical data processing is proposed,which includes five modules,namely problem definition,data preprocessing,data mining,result analysis,and knowledge *** on effective data preprocessing,feature analysis and boosting trees,our proposed fusion decision model can obtain 100%accuracy for early postoperative mortality prediction,which outperforms machine learning methods based on a single model such as LightGBM,XGBoost,and *** results reveal the critical factors related to the postoperative mortality of aortic dissection,which can provide a theoretical basis for the formulation of clinical operation plans and help to effectively avoid risks in advance.

关键词： Risk prediction aortic dissection COVID-19 postoperative mortality boosting tree

Soil carbon sequestration,carbon markets,and conservation agriculture practices:A hypothetical examination in Mozambique

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International Soil and Water Conservation Research 2017年第3期5卷 167-179页

作者： Timoteo E.Simone Dayton M.Lambert Ivan Cuvaca neal S.Eash Department of Agricultural&Resource Economics 321 Morgan Hall2621 Morgan CircleKnoxvilleTN 37996-4518USA Department Biosystems Engineering&Soil Science 2506 EJ Chapman DriveKnoxvilleTN 37996-4531USA

Payments for Environmental Services(PES)are relatively novel mechanisms whereby the adoption of sustainable management practices by a stakeholder is rewarded by incentives linked to external *** of PES for conservation agricultural practices(CAPS)by smallholder farmers may provide opportunities to increase household income or cover the technology costs of adoption if the carbon sequestration benefits of CAPS are quantifiable,adoption rates are accelerated and maintained,a mechanism exists whereby carbon sequestration services can be compensated,and carbon offset exchange markets are *** research suggests a methodology to examine a PES market for carbon offsets generated by the adoption of CAPS by farmers in *** a cumulative adoption of 60%over a 20-year period,revenue from PES market participation to CA adopters was two times higher than revenue earned when disadoption occurred midway through the *** adoption targets are associated with higher per household returns when fertilizer rates typical to the region are *** and maintaining a sustainable PES system in the study region would require significant investment in time and *** lack of on-the-ground institutions or local support for such a program would also challenge successful ***,the programs where participant success depends on external markets,such as the hypothetical one suggested here,are subject to the ebb and flow of foreign demand for carbon *** these three broad constraints to a PES/CAPS program in the region would require grass-roots driven policy initiatives with buy-in at multiple social,economic,and political levels.

关键词： Payment for environmental services Conservation agriculture adoption Carbon sequestration