scholarly journals An Efficient Method for Estimating Wheat Heading Dates Using UAV Images

2021 ◽  
Vol 13 (16) ◽  
pp. 3067
Author(s):  
Licheng Zhao ◽  
Wei Guo ◽  
Jian Wang ◽  
Haozhou Wang ◽  
Yulin Duan ◽  
...  
Keyword(s):  
High Throughput ◽  
Growth Curve ◽  
Large Scale ◽  
Agricultural Research ◽  
Heading Date ◽  
Absolute Error ◽  
Growth Cycle ◽  
Continuous Growth ◽  
Large Scale Field ◽  
Uav Images

Convenient, efficient, and high-throughput estimation of wheat heading dates is of great significance in plant sciences and agricultural research. However, documenting heading dates is time-consuming, labor-intensive, and subjective on a large-scale field. To overcome these challenges, model- and image-based approaches are used to estimate heading dates. Phenology models usually require complicated parameters calibrations, making it difficult to model other varieties and different locations, while in situ field-image recognition usually requires the deployment of a large amount of observational equipment, which is expensive. Therefore, in this study, we proposed a growth curve-based method for estimating wheat heading dates. The method first generates a height-based continuous growth curve based on five time-series unmanned aerial vehicle (UAV) images captured over the entire wheat growth cycle (>200 d). Then estimate the heading date by generated growth curve. As a result, the proposed method had a mean absolute error of 2.81 d and a root mean square error of 3.49 d for 72 wheat plots composed of different varieties and densities sown on different dates. Thus, the proposed method is straightforward, efficient, and affordable and meets the high-throughput estimation requirements of large-scale fields and underdeveloped areas.

scholarly journals Mesophilic Anaerobic Digestion of JUNCAO for Biogas Production: Structure and Functional Analysis of Microbial Communities Based on High-Throughput Sequencing

2021 ◽  
Author(s):  
Yuyang Qiu ◽  
Yating Lei ◽  
Hui Zhao ◽  
Xiaoyu He ◽  
Ying Huang ◽  
...  
Keyword(s):  
Anaerobic Digestion ◽  
High Throughput ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Biogas Production ◽  
Growth Cycle ◽  
Biomass Energy ◽  
Market Potential ◽  
Bacterial Phyla ◽  
New Energy

Abstract JUNCAO, as energy grass, was used in mesophilic anaerobic digestion (MAD) to produce methane, which has a huge market potential in biomass energy. This study was to investigate the characteristics of MAD of Arundo donax cv. Lvzhou No.1 (Lvzhou No.1) and Pennisetum giganteum z.x.lin (P. giganteum) (the growth cycle of 5 months), explore the relationship between microbial community structure and its function during MAD process. The results showed that the cumulative biogas production of Lvzhou No.1 and P. giganteum reached up to 370.37 mL/g VS and 313.04 mL/g VS, respectively. And the maximum methane concentration of both reached 75%. The volatile fatty acid (VFA) showed a trend of increasing at first then decreasing. Microbiota analysis based on high-throughput sequencing technology showed that the same microflora could differentiate into different microflora due to different fermentation materials. Firmicutes, Bacteroidetes and Proteobacteria were the dominant bacterial phyla with two predominant genera of Unidentified_Clostridiales and Romboutsia. In addition, Euryarchaeota and Methanosaeta were the dominant archaeal phyla and genus, respectively. Spearman correlation analysis showed that the production of acidic substances in this system was mainly the reaction effect of bacteria, and the methanogenic function was mainly associated with the dominant flora of archaea. In conclusion, this study would provide new evidence for MAD of JUNCAO as new energy resources, which would pave the way for large-scale MAD of energy plants in the future.

Biodata response elaboration: A large-scale field experiment

2010 ◽  
Author(s):  
Julia Levashina ◽  
Frederick P. Morgeson ◽  
Michael A. Campion
Keyword(s):  
Field Experiment ◽  
Large Scale ◽  
Scale Field ◽  
Large Scale Field

Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Mojtaba Haghighatlari ◽  
Sai Prasad Ganesh ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
Data Mining ◽  
Refractive Index ◽  
High Throughput ◽  
First Principles ◽  
High Throughput Screening ◽  
Large Scale ◽  
Computational Study ◽  
High Refractive Index ◽  
Structural Features ◽  
Learning Program

<div>We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches.</div>

Benchmark of Simplified Time-Dependent Density Functional Theory for UV-Vis Spectral Properties of Porphyrinoids

2019 ◽  
Author(s):  
Kamal Batra ◽  
Stefan Zahn ◽  
Thomas Heine
Keyword(s):  
Density Functional Theory ◽  
Density Functional ◽  
Large Scale ◽  
Absolute Error ◽  
Time Dependent ◽  
Basis Set ◽  
Basis Sets ◽  
Functional Theory ◽  
Framework Materials ◽  
Dependent Density

<p>We thoroughly benchmark time-dependent density- functional theory for the predictive calculation of UV/Vis spectra of porphyrin derivatives. With the aim to provide an approach that is computationally feasible for large-scale applications such as biological systems or molecular framework materials, albeit performing with high accuracy for the Q-bands, we compare the results given by various computational protocols, including basis sets, density-functionals (including gradient corrected local functionals, hybrids, double hybrids and range-separated functionals), and various variants of time-dependent density-functional theory, including the simplified Tamm-Dancoff approximation. An excellent choice for these calculations is the range-separated functional CAM-B3LYP in combination with the simplified Tamm-Dancoff approximation and a basis set of double-ζ quality def2-SVP (mean absolute error [MAE] of ~0.05 eV). This is not surpassed by more expensive approaches, not even by double hybrid functionals, and solely systematic excitation energy scaling slightly improves the results (MAE ~0.04 eV). </p>

Research on the Marketing Strategy of Online Education -- Taking New Oriental as an Example

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Jialu Chen ◽  
Yingxiao Han ◽  
An Li
Keyword(s):  
Online Learning ◽  
Online Education ◽  
Online Teaching ◽  
Large Scale ◽  
Target Market ◽  
Growth Trend ◽  
Continuous Growth ◽  
Financial Investment ◽  
Marketing Mode ◽  
Marketing Costs

In recent years, with the development of society and the progress of science and technology, online learning has penetrated into people's daily life, and people's demand for high-quality curriculum products is more and more strong. From a macro perspective, the continuous growth of national financial investment in education, the continuous upgrading of China's consumption structure, the development of 5G technology and the popularization of AI intelligence make online teaching less limited. The online education industry is showing an explosive growth trend. More and more online education institutions are listed for financing, and the market value is soaring. However, in 2019, except for GSX, the latest online learning platforms such as New Oriental, Speak English Fluently and Sunlands, have been in a state of loss. Most of these agencies seize the market by increasing advertising investment, but at the same time, they also bring huge marketing costs, which affect the financial performance of the company. With the enhancement of Matthew effect, large-scale educational institutions occupy a large market through free classes and low-price classes, while small and medium-sized institutions with weak capital strength are often unable to afford high sales costs, facing the risk of capital chain rupture. Taking new Oriental online as an example, this paper analyzes the problems existing in the marketing strategies of online education institutions. It also puts forward suggestions on four aspects, which are target market, differentiated value, marketing mix and marketing mode, so as to make sure that online education institutions can control marketing expenses and achieve profits by improving course quality, expanding marketing channels and implementing precise positioning.

Next-Generation Sequencing: An Emerging Tool for Drug Designing

2019 ◽  
Vol 25 (31) ◽  
pp. 3350-3357 ◽  
Author(s):  
Pooja Tripathi ◽  
Jyotsna Singh ◽  
Jonathan A. Lal ◽  
Vijay Tripathi
Keyword(s):  
Next Generation Sequencing ◽  
High Throughput ◽  
Large Scale ◽  
Massively Parallel Sequencing ◽  
Genomic Research ◽  
Biological Research ◽  
Next Generation ◽  
Human Welfare ◽  
Drug Designing ◽  
Generation Sequencing

Background: With the outbreak of high throughput next-generation sequencing (NGS), the biological research of drug discovery has been directed towards the oncology and infectious disease therapeutic areas, with extensive use in biopharmaceutical development and vaccine production. Method: In this review, an effort was made to address the basic background of NGS technologies, potential applications of NGS in drug designing. Our purpose is also to provide a brief introduction of various Nextgeneration sequencing techniques. Discussions: The high-throughput methods execute Large-scale Unbiased Sequencing (LUS) which comprises of Massively Parallel Sequencing (MPS) or NGS technologies. The Next geneinvolved necessarily executes Largescale Unbiased Sequencing (LUS) which comprises of MPS or NGS technologies. These are related terms that describe a DNA sequencing technology which has revolutionized genomic research. Using NGS, an entire human genome can be sequenced within a single day. Conclusion: Analysis of NGS data unravels important clues in the quest for the treatment of various lifethreatening diseases and other related scientific problems related to human welfare.

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