Development of Cellulose Acetate Microcapsules with Cyanex 923 for Phenol Removal from Aqueous Media by Irma Pérez-Silva, Israel S. Ibarra, A. Castañeda-Ovando, C. A. Galán-Vidal, Ma. Elena Páez-Hernández

“…Microcapsules characterization demonstrated the extractant reagent encapsulation, while in a batch mode procedure, good adsorption of phenol (ca. 5.5 × 10−3 mol Kg−1) has been reached. …”
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Towards precision agriculture tea leaf disease detection using CNNs and image processing by Irfan Sadiq Rahat, Hritwik Ghosh, Suresh Dara, Shashi Kant

“…These blocks combine Conv2D layers, batch normalization, activation layers, and shortcut connections, ensuring robust and efficient feature extraction at various levels of abstraction. …”
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Detection: A convolutional network method for plant disease recognition by Enow Takang Achuo Albert, Ngalle Bille, Ngonkeu Mangaptche Eddy Leonard

“…Detection contains four convolutional layers, four batch normalization layers and two max-pooling layers. …”
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Radio Frequency Sensing–Based Human Emotion Identification by Leveraging 2D Transformation Techniques and Deep Learning Models by Najah AbuAli, Ihtesham Jadoon, Farman Ullah, Mohammad Hayajneh, Shayma Alkobaisi

“…These TFIs are then fed into pretrained deep learning models—AlexNet, ResNet18, and GoogleNet—to extract features for identifying eight emotions using varying batch sizes and optimizers. …”
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Evaluating the impact of hyperparameters on the performance of 1D CNN model for nutritional profiling of underutilized crops using NIRS data by Simardeep Kaur, Naseeb Singh, Amit Kumar, Philanim W S, Veerendra Kumar Verma, Amit Kumar Patil, Rakesh Bhardwaj, Amritbir Riar

“…Max pooling with smaller sizes provided optimal results by retaining essential features, whereas larger pooling sizes caused information loss. Smaller batch sizes were more effective at improving generalization, while larger batch sizes led to over-smoothing. …”
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Desalination and Treatment of Oilfield Produced Waters by Giovanni Campisi, Alice Sorrenti, Paulo B. Mofatto, Alessandro Cosenza, Serena Randazzo, Santo F. Corsino, Marco Capodici, Michele Torregrossa, Alessandro Tamburini, Giorgio Micale

“…Produced water is a salty and organic-polluted byproduct drilled out during the oil extraction. An annual production of 11.2 million of m3 is estimated, based on the production of at least 3 barrels of PW for every barrel of oil extracted. …”
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A human activity recognition model based on deep neural network integrating attention mechanism by Feng Xu, Xuchen Gao, Weigang Wang

“…With multi-scale feature extraction, residual and skip connections, and dual attention mechanisms, along with a series of optimization strategies like dropout, batch normalization, and AdamW optimizer, the model achieves an average accuracy of 99.03% in five-fold cross-validation. …”
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Production of biodiesel from dairy wastewater sludge: A laboratory and pilot scale study by R. Balasubramanian, Anirbid Sircar, P. Sivakumar, K. Anbarasu

“…Keywords: Activated sludge, Extraction, Biodiesel, Scale up…”
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Immobilization of Lead from Pb-Contaminated Soil Amended with Peat Moss by Seul-Ji Lee, Myoung-Eun Lee, Jae Woo Chung, Jin Hee Park, Keun Young Huh, Gee-Ill Jun

“…The immobilization properties of Pb in the contaminated soil were evaluated by a column leaching experiment, a microcosm test, and a batch incubation test. Peat moss significantly reduced the Pb leaching in all of the experiments and more effectively reduced mobility and toxicity of Pb in the column leaching and microcosm tests than bioavailability in the batch incubation test. …”
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Impact of nutrient deficiency and harvesting strategy on biomass and phycocyanin production in Spirulina cultures by Hooi Ren Lim, Hooi Ren Lim, Kuan Shiong Khoo, Pau Loke Show

“…Biomass productivity of 1-L and 10-L batch culture was found to be 0.23 g/L/d and 0.21 g/L/d, respectively. …”
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Advancing mango quality assurance: Non‐destructive detection of spongy tissue using visible near‐infrared spectroscopy and machine learning classification by Patil Rajvardhan Kiran, Md Yeasin, Pramod Aradwad, T. V. Arunkumar, Roaf Ahmad Parray

“…Unfortunately, the widespread issue of spongy tissue (ST) disorder in Alphonso mangoes results in a soft, corky texture, affecting up to 30% of mangoes in a single batch. This challenge leads to the outright rejection of affected mangoes during export due to delayed disorder identification. …”
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Development and validation of an LC–MS/MS method for quantitative determination of LXT-101 sustained-release suspension, a novel drug in treating prostate cancer, in beagle plasma... by Jinglai Li, Lan Yin, Yuexin Li, Yutao Xue, Xiaoying Wang, Wenxia Xu, Zhenqing Zhang, Shan Xiong

“…It showed good linearity over the range of 2–600 ng/mL (R2 = 0.9977). The intra- and inter-batch accuracy were within 93.36–93.94% and 95.61–99.27%, while the intra- and inter-batch precision were in the range of 3.23–14.26% and 5.03–11.10%, respectively. …”
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UPLC-MS/MS method for simultaneous determination of pyrantel, praziquantel, febantel, fenbendazole and oxfendazole in dog plasma and its application to a bioequivalence study by Fengyichi Zhang, Fanxi Guo, Xinyu Zhao, Chongyang Li, Junli Wang, Mengyun Wang, Ruixia Ma, Baochang Chen, Qiangqiang Miao, Yimeng Wang, Zihan Wang, Di Cao, Zugong Yu

“…The mean extraction recoveries for the analytes and IS were >90%. …”
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L’épave de Saint-Satur dans la Loire moyenne : un transport d’ardoises interrompu à la charnière du Moyen Âge et de la période moderne by Marion Foucher, Annie Dumont, Philippe Moyat, Catherine Lavier, Ronan Steinmann

“…In the light of contemporary accounting, these various aspects make it possible to discuss the existence of complex supply chains, integrating intermediaries between the places of extraction and those of implementation, and to evoke the standardisation of slate production.…”
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Aircraft Wake Vortex Recognition Method Based on Improved Inception-VGG16 Hybrid Network by Weijun Pan, Yuhao Wang, Leilei Deng, Yanqiang Jiang, Yuanfei Leng

“…This module comprises convolution, batch normalization, ReLU activation, and max pooling operations. …”
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Application of Quantum Recurrent Neural Network in Low-Resource Language Text Classification by Wenbin Yu, Lei Yin, Chengjun Zhang, Yadang Chen, Alex X. Liu

“…This architecture utilizes a pretrained multilingual bidirectional encoder representations from transformer (BERT) model to obtain vector representations of words and combines the proposed batch upload quantum recurrent neural network (BUQRNN) and parameter nonshared batch upload quantum recurrent neural network (PN-BUQRNN) as feature extraction models for sentiment analysis in Bengali. …”
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A novel strategy for controllable electrofabrication of molecularly imprinted polymer biosensors utilizing embedded Prussian blue nanoparticles by Bahareh Babamiri, Mohammadreza Farrokhnia, Mehdi Mohammadi, Amir Sanati Nezhad

“…Abstract The reproducibility of ultrasensitive biosensors is vital for clinical research, scalable manufacturing, commercialization, and reliable clinical decision-making, as batch-to-batch variations introduce significant uncertainty. …”
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An efficient parallel DCNN algorithm in big data environment by Yimin Mao, Yaser Ahangari Nanehkaran, Neelakandan Chandrasekaran, Ying Huo, Zhan Qing Wen, ke Gong, Miao Decheng

“…First, a parallel feature extraction strategy based on the Marr-Hildreth operator (PFE-MHO) is proposed to extract target features from data as inputs to the network, effectively solving the problem of high data redundancy. …”
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Research of clover-grater-and-scarificator KS-0.2 with oval type deck at seeds scarification by A. I. Burkov, M. V. Simonov, V. Ju. Mokiev

“…In 2017 in the Kirov region the clover-grater-and-scarificator KS-0.2 intended for extraction of seeds from wad of clover and other legumes and grasses as well as scarification of hard legume seeds was investigated. …”
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Design and Application of Reliability Calculation Program Based on Secondary Development of ABAQUS by ZOU Hong, WU Jian, XU Zhichun, YANG Li

“…As a kind of finite element analysis software,ABAQUS is widely used in nonlinear simulation field,but there is no universal and mature reliability calculation module.Therefore,it is necessary to establish a general reliability calculation program for Monte Carlo simulation based on finite element model to meet the automation requirements of reliability calculation of various structures in ABAQUS.This paper firstly puts forward the design idea and main functions of reliability calculation program in ABAQUS,including random number generation,model batch building,automatic result extraction and so on;then,develops the pre-processing and post-processing modules of ABAQUS with Python language for modularizing the main functions of the program;finally,introduces the application method of this reliability calculation program in detail taking the reliability calculation process of the finite element model of a simply supported steel truss bridge as an example.This reliability calculation program can effectively improve the degree of automation in the process of structural reliability calculation,and reduce the calculation time,which has great reference value in engineering application.…”
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