Effects of Different Cultivation Modes on the Storage Quality and Flavor of Harvested Chinese Leek by ZHOU Xinyuan, TAO Jiejie, LIU Mingchi, ZUO Jinhua, WU Zhanhui, ZHENG Yanyan, KANG Xinna, LIANG Hao, MU Jianlou, CHEN Jie, JI Yanhai

Subjects: “…different cultivation methods; chinese leek; storage quality; volatile flavor substances…”
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Influence of Unloading Conditions of Confining Pressure on the Compressive Strength and Permeability of Deep Mudstone by Tianyu Xin, Yashengnan Sun, Junguang Wang, Weiji Sun

“…To investigate the compressive strength and permeability of deep mudstone under stress disturbance, a triaxial rheometer is used to conduct seepage experiments on mudstone specimens with different buried depths under triaxial compression and unloading conditions. …”
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Comparative Cranial Joint Variation in Three Different Lizards: Impact of Feeding Habit by Elif Yıldırım Caynak, Kamil Candan, Yusuf Kumlutaş, Ahmet Gökay Korkmaz, Sezen Birlik, Dudu Mertgenç Yoldaş, Serkan Gül, Çetin Ilgaz

“…The skull structure in vertebrates is closely related to feeding mode. This study examines the relationship between the cranial joint morphology variation among different lizard species [<i>Eumesces schneideri</i> (Daudin, 1802), <i>Anguis colchica</i> (Nordmann, 1840), and <i>Eremias suphani</i> (Başoğlu & Hellmich 1968)] and their feeding habit. …”
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A method of processing mechanical mixtures using vortex set of deep separation by V. I. Kuznetsov, O. A. Sharikov

“…There is described a new method of processing mechanical mixtures using a vortex set of deep separation – VCGS and experimental model of a new vortex separator in the form of cyclone nozzles. …”
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Integrating manual annotation with deep transfer learning and radiomics for vertebral fracture analysis by Jing Wang, Zhirui Dong, Huanxin He, Zhiyang Gao, Yukai Huang, Guangcheng Yuan, Libo Jiang, Mingdong Zhao

Subjects: “…Deep transfer learning…”
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To Achieve that Have Been Gradually Worked out the Criteria of Correct Treatment of the History by A. V. Torkunov

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Blacklegged Tick or Deer Tick, Ixodes scapularis Say (Arachnida: Acari: Ixodidae) by Michael R. Patnaude, Thomas N. Mather

“…EENY-143/IN300: Blacklegged Tick or Deer Tick, Ixodes scapularis Say (Arachnida: Acari: Ixodidae) (ufl.edu) …”
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Quantitative Evaluation for the Threat Degree of a Thermal Reservoir to Deep Coal Mining by Yun Chen, Xinyi Wang, Yanqi Zhao, Haolin Shi, Xiaoman Liu, Zhigang Niu

“…The area above the medium-threat zone accounts for 71.82% of the total study area, indicating that deep coal mining is affected by multiple factors and that roof water and heat disasters are more likely to occur.…”
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How Much Does Bad Hay Cost a Beef Cattle Producer? by Matthew J. Hersom, Todd A. Thrift

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Deer Flies, Yellow Flies and Horse Flies, Chrysops, Diachlorus, and Tabanus spp. by Jason M. Squitier

“… The family Tabanidae, commonly known as horse flies, and deer flies, contains pests of cattle, horses and humans. …”
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Enhancing Maternal Knowledge and Practices in Complementary Feeding through Emotional Demonstration Methods by Ani Intiyati, Imam Sarwo Edi, Inne Soesanti, Juliana Christianingsih, Kusmini Suprihatin, Luluk Widarti

Subjects: “…complementary feeding…”
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Homogenized Point Mutual Information and Deep Quantum Reinforced Wind Power Prediction by W. G. Jency, J. E. Judith

“…Deep learning-based methods are referred to as straightforward, and robust, and have been utilized in the recent few years for wind power prediction with a certain level of success. …”
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Exploring Deep Learning–Based Models for Sociocultural African Food Recognition System by Grace Ataguba, Mona Alhasani, James Daniel, Emeka Ogbuju, Rita Orji

“…We present the design and evaluation of a sociocultural app for African food recognition using deep learning models such as transfer learning. Deep learning models have multiple processing layers that make them robust in image recognition. …”
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Mood Detection from Physical and Neurophysical Data Using Deep Learning Models by Zeynep Hilal Kilimci, Aykut Güven, Mitat Uysal, Selim Akyokus

“…Another novelty is that the emotion classification task is performed by both conventional machine learning algorithms and deep learning models. For this purpose, Feedforward Neural Network (FFNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) neural network are employed as deep learning methodologies. …”
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UTR-Insight: integrating deep learning for efficient 5′ UTR discovery and design by Saichao Pan, Hanyu Wang, Hang Zhang, Zan Tang, Lianqiang Xu, Zhixiang Yan, Yong Hu

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Deep Learning Based Proactive Caching for Effective WSN-Enabled Vision Applications by Fangyuan Lei, Jun Cai, Qingyun Dai, Huimin Zhao

“…Firstly, based on Software Defined Network (SDN) and Network Function Virtualization (NFV) technologies, a distributed deep learning network SSAE is constructed in the sink nodes and control nodes of the WSN network. …”
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An Intelligent Framework Based on Deep Learning for SMS and e-mail Spam Detection by Umair Maqsood, Saif Ur Rehman, Tariq Ali, Khalid Mahmood, Tahani Alsaedi, Mahwish Kundi

“…To counter this problem, in this paper, multiple classifiers of ML and a classifier of deep learning (DL) were applied to the SMS and e-mail dataset for spam detection with higher accuracy. …”
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Anti-Methanogenic Potential of Seaweeds and Impact on Feed Fermentation and Rumen Microbiome In Vitro by Pradeep Kumar Malik, Atul Purshottam Kolte, Shraddha Trivedi, Govindan Tamilmani, Archit Mohapatra, Shalini Vaswani, Johnson Belevendran, Artabandhu Sahoo, Achamveetil Gopalakrishnan, Raghavendra Bhatta

“…The results also demonstrated that the supplementation of <i>Kappaphycus alvarezii</i> and <i>Sargassum wightii</i> did not alter the feed fermentation pattern, and therefore, the reduction in CH₄ production in the present study could not be attributed to it. …”
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Unsupervised Hyperspectral Denoising Based on Deep Image Prior and Least Favorable Distribution by Keivan Faghih Niresi, Chong-Yung Chi

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Surveillance of Aflatoxin and Microbiota Related to Brewer's Grain Destined for Swine Feed in Argentina by Gisela A. Gerbaldo, Carina M. Pereyra, Lilia R. Cavaglieri, Francisco Ruiz, Liliana Pascual, Ana M. Dalcero, Isabel L. Barberis

“…Regular monitoring of feeds is required in order to prevent chronic and acute toxic syndromes related to this kind of contamination.…”
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