Three-dimensional atomic-scale characterization of titanium oxyhydroxide nanoparticles by data-driven lattice correlation analysis by Kohei Aso, Koichi Higashimine, Masanobu Miyata, Hiroshi Kamio, Yoshifumi Oshima

“…Our findings reveal their anatase-like structure with alternating layers of titanium dioxide (TiO2) and titanium hydroxide (Ti(OH)4) planes. …”
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Airborne-Platform-Assisted Transmission and Control Separation for Multiple Access in Integrated Satellite–Terrestrial Networks by Chaoran Huang, Xiao Ma, Xiangren Xin, Weijia Han, Yanjie Dong

“…Currently, the primary random access protocol for satellite communications is Irregular Repetition Slotted ALOHA (IRSA). …”
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A novel approach towards the robustness of centrality measures in networks by Jens Dörpinghaus, Vera Weil, Robert Rockenfeller, Meetkumar Pravinbhai Mangroliya

“…We introduce a method with different removal strategies to analyze how additional or missing layers, nodes, or edges in a random network influence centrality measures. …”
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A first-in-human, prospective pilot trial of umbilical cord-derived mesenchymal stem cell eye drops therapy for patients with refractory non-Sjögren's and Sjögren's syndrome dry ey... by Di Zhang, Taige Chen, Qi Liang, Xuebing Feng, Jiaxuan Jiang, Zeying Chen, Yun Tang, Yiran Chu, Bin Wang, Kai Hu

“…Secondary assessments focused on the evaluation of lipid layer, meibomian gland function, and bulbar conjunctival redness. …”
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Bridging Classical Methodologies in <i>Salmonella</i> Investigation with Modern Technologies: A Comprehensive Review by Steven Ray Kitchens, Chengming Wang, Stuart B. Price

“…In addition to these sequencing approaches, machine learning techniques like decision trees and random forests provide powerful tools for pattern recognition and predictive modeling. …”
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Reliability Analysis of Anchored Geotechnical Structures for the Design Limit States by Sohaib K Al-Mamoori, Laheab A. Al-Maliki, Khaled El-Tawel

“… Reliability has been considered of magnificent importance in engineering design specially in geotechnical engineering due to the unpredictable conditions of soil layers. It is essential to establish well- designed failure modes that could guarantee safety and durability of the proposed structure. …”
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Preferences for student rental housing in Dehradun, India: Using TOPSIS technique by Dikchha Tiwari, Uttam Kumar Roy

“…A five-point Likert scale survey was administered to 425 students, selected through simple random sampling. The data were analysed using the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS), allowing for a comparative performance analysis of each attribute. …”
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MINI Logic 1-Bit Adder: A Comparison with Hybrid NMOS-Memristor-Logic Styles Using Ta2O5/Al2O3 Based RRAM Device by NITHYA, N., PARAMASIVAM, K.

“…As conventional CMOS technology faces scaling and efficiency limitations, integrating emerging memory technologies like Resistive Random Access Memory (RRAM), also known as memristor, offers a promising solution. …”
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iTAGPred: A Two-Level Prediction Model for Identification of Angiogenesis and Tumor Angiogenesis Biomarkers by Khalid Allehaibi, Yaser Daanial Khan, Sher Afzal Khan

“…The proposed work focuses on developing a two-layered prediction model using different classifiers like random forest (RF), neural network, and support vector machine. …”
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Stacked LSTM for Short-Term Wind Power Forecasting Using Multivariate Time Series Data by Manisha Galphade, V. B. Nikam, Biplab Banerjee, Arvind W. Kiwelekar, Priyanka Sharma

“…Among the various prediction models, deep learning models such as Long Short-Term Memory (LSTM) have demonstrated outstanding performance in the field of WPF. By adding multiple layers of LSTM networks, the model can capture more complex patterns. …”
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Optimization Algorithm of Neural Network Structure Based on Adaptive Genetic Algorithm by XILiang, WANGRui dong

“…The structural design of neural network is one of the hot issues in neural network research The number of hidden layers and nodes has a great influence on the convergence speed and generalization ability of neural network Genetic algorithm is an adaptive optimization probability search algorithm formed by simulating biological heredity and evolution Its core idea is derived from the natural law of biological genetics and survival of the fittest, and it is a search algorithm with the iterative process of “survival + detection” However, the selection of genetic algorithm parameters is subjective, slow convergence and easy to fall into premature convergence To solve these problems, an adaptive genetic algorithm is proposed to find the optimal neural network structure The adaptive genetic algorithm selects the first n optimal individuals and adds a certain amount of random individuals in the optimization process of each iteration to update the population, and selfadaptive optimization of the search step size of the population can ensure the diversity of the population and improve the convergence rate at the same time Then we code and the structure of neural network processing, adaptive genetic algorithm, neural network structure optimization, so as to make the neural network as soon as possible to find the optimal network structure and parameters, in order to improve the accuracy of neural network. …”
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A diffusion enhanced CRF and BiLSTM framework for accurate entity recognition by Yunfei Qiu, Libo Dong, Wenwen Zhang, Haoran Xing, Junwei Huang

“…To solve this, we suggest a diffusion model with Conditional Random Fields and Bidirectional Long Short-Term Memory layers. …”
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Anatomical entity recognition with a hierarchical framework augmented by external resources. by Yan Xu, Ji Hua, Zhaoheng Ni, Qinlang Chen, Yubo Fan, Sophia Ananiadou, Eric I-Chao Chang, Junichi Tsujii

“…Each of the NERs is implemented using the Conditional Random Fields (CRF) model, which use a range of external resources to generate features. …”
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Determining the Fisheries Consumption Preferences of Ege University Students by Hülya Saygı

“…Faculties in Ege University have been considered as layers. In the study, a 25-question questionnaire was conducted face-to-face to 381 students selected according to the random sampling method between February and March 2019, and the results were obtained. …”
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Probabilistic design strategy for improved Austin-Moore stem used in artificial cementless hip prosthesis considering material property uncertainty by G. Kharmanda, I. R. Antypas

“…Different material properties were generated randomly using Monte Carlo simulation (MCS). Monte Carlo sampling techniques were applied, and different von Mises stresses of the layers (bone and metal) were chosen as a performance indicator. …”
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Business Analysis of Probiotic Administration of Lactic Acid Bacteria on The Performance of Kampung Super Chicken by Gogik Satrio Margo Utomo, Sri Hidanah, Muhammad Anam Al Arif, Widya Paramita Lokapirnasari, Wiwik Misaco Yuniarti

“…Kampung super chicken is the result of a cross between a layer chicken and a superior kampung super chicken. …”
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Organic and mineral fertilization determining the agronomic performance of sunflower cultivars and soil chemical attributes by Weslian V. da Silva, José H. da S. Taveira, Patrick B. Fernandes, Patrícia C. Silva, Ana B. G. da Costa, Carolina M. Costa, Pedro R. Giongo, Níbia S. D. Corioletti, Antonio L. C. Gurgel

“…The experimental design used was randomized blocks in a 3 × 2 factorial scheme with six replicates, totaling 36 experimental units. …”
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Smart Defect Detection in Aero-Engines: Evaluating Transfer Learning with VGG19 and Data-Efficient Image Transformer Models by Samira Mohammadi, Vahid Rahmanian, Sasan Sattarpanah Karganroudi, Mehdi Adda

“…We focused on metrics such as accuracy, precision, recall, and loss to compare the performance of models VGG19 and DeiT (data-efficient image transformer). RandomSearchCV was used for hyperparameter optimization, and we selectively froze some layers during training to help better tailor the models to our dataset. …”
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Declining extent of fen peat deposits over the past 50 years in Ogre Municipality, central Latvia by Normunds Stivrins, Davis Matskins, Ilze Ozola

“…After a feasibility study using GIS tools, fen peat deposits were randomly selected and surveyed in the field to determine the type, thickness, and characteristics of the peat. …”
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Leaching of salts and production of sour passion fruit irrigated with low- and high-salinity water by Járisson C. Nunes, Antonio J. de Lima Neto, Lourival F. Cavalcante, Walter E. Pereira, Hans R. Gheyi, Geovani S. de Lima, Flaviano F. de Oliveira, Juliete A. da S. Nunes

“…Irrigation increased the electrical conductivity of the soil saturation extract, with higher values in the surface layer and at the end of the dry season. Rainfall during the rainy season reduced the saline character of soil from moderately saline and strongly saline, in treatments irrigated with water of low and high electrical conductivity, to non-saline and slightly saline, respectively. …”
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