Formation of Economically Sound Tax Consequences on Purchase and Sale of Foreign Goods (Case Study on Customs Procedure of Customs Warehouse) by E. Yu. Sidorova

“…The methodological basis was economic methods, a generalization method, and a comparison method to study the approaches in Russia and abroad to the formation of the institutional structure of the customs procedure of the customs warehouse. …”
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Biopreservative in Foods: Nisin (E234) by Başar Uymaz, Pınar Şanlıbaba

“…Nisin, defined as GRAS (Generally Recognized as Safe) by FDA and named the E234 code 'Nisin-protective' or 'natural protective' located in the food additives list, first used in 1988 as a natural preservative by prohibiting of antibiotics using in food in the US. …”
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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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Аlternative local stratigraphical scales of the Upper Miocene of the Rostov Dome by D. A. Ruban

“…The question of creating an automatic system for generalizing information about stratigraphical units is discussed.Conclusion. …”
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Feature selection for helpfulness prediction of online product reviews: An empirical study. by Jiahua Du, Jia Rong, Sandra Michalska, Hua Wang, Yanchun Zhang

“…Also, the current works tend to concentrate on domain- and/or platform-dependent feature curation, lacking wider generalization. Moreover, the issue of result comparability and reproducibility occurs due to frequent data and source code unavailability. …”
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The formal demography of kinship VI: Demographic stochasticity and variance in the kinship network by Hal Caswell

“…That limitation is now removed; both means and variances are easily calculated with minimal modification of code. …”
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The interplay between PolyQ and protein context delays aggregation by forming a reservoir of protofibrils. by Donatella Bulone, Laura Masino, David J Thomas, Pier Luigi San Biagio, Annalisa Pastore

“…Polyglutamine (polyQ) diseases are inherited neurodegenerative disorders caused by the expansion of CAG codon repeats, which code for polyQ in the corresponding gene products. …”
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Method for synthesizing a logic element that implements several functions simultaneously by S. I. Sovetov, S. F. Tyurin

“…While in canonical normal form LUTs generally implement only one logical function for a given configuration, in this case, there is always an inactive pass transistor element. …”
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Improved Correlation of Oil Recovery Factor for Water Driven Reservoirs in the Niger Delta by Ayodele Daniel, Faisal Olasubomi Olanipekun, Sunday Oloruntoba Isehunwa

“…The results obtained showed better model performance and generalization than any previously existing model. …”
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Extreme Gradient Boosting Beats In-Silico Identification of Proteins Potentially Associated With Alzheimer’s by Sadia Khalil, Wajid Arshad Abbasi, Syed Ali Abbas, Maryum Bibi, Saiqa Andleeb, Amsa Shabir

“…Through a series of simulation studies, we have shown that our proposed model by using protein sequence information only gives state-of-the-art generalization performance with an area under the precision-recall curve of 0.93 verified through various ML-centric and biologically relevant techniques and metrics. …”
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MicroRNA-200b suppresses the invasion and migration of hepatocellular carcinoma by downregulating RhoA and circRNA_000839 by Ben-gang Wang, Jun-shuai Li, Yong-feng Liu, Qian Xu

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Duodenal Adenocarcinoma Is Characterized by Acidity, High Infiltration of Macrophage, and Activated Linc01559–GRSF1 Axis by Xinxin Huang, Ying Shi, Zekun Liu, Yihang Wu, Xiaotong Luo, Dongwen Chen, Zhengyu Wei, Chong Chen, Huaiqiang Ju, Xiaojian Wu, Xuanhui Liu, Zhanhong Chen, Peishan Hu

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Circulating miR-1826 in plasma correlates with circulating tumor cells and is a prognostic marker in colorectal cancer by Zhihua Xu, Tianyi Xi, Ye Han, Xiaobo Guo, Fei Liu, Min Jiang, Daiwei Wan, Xiaofeng Xue, Songbing He, Rui Ren, Wei Li, Qiaoming Zhi

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Final year medical students’ expectations for medical education on climate change and planetary health – a qualitative study by Charlotte Flock, Rebecca Boekels, Alina Herrmann, Ilsa Beig, Lisa Lamkemeyer, Hans-Christoph Friederich, Christoph Nikendei, Till Johannes Bugaj

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Effect of SB Addition on Mechanical, Electronic and Thermodynamic Properties of Intermetallic B2-Nial: First Principles Study by Bouchentouf Mohamed Amine, Abdiche Ahmed, Ghaffor Djamel, Mokadem Azzeddine, Beloufa Nabil, Bekheira Samir

“…Generalized Gradient Approximation (GGA) was employed to approximate the exchange-correlation energy. …”
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Risk factors of 180-day rebleeding after management of blunt splenic injury without surgery and embolization: a national database study by Chung-Yen Chen, Hung-Yu Lin, Pie-Wen Hsieh, Yi-Kai Huang, Po-Chin Yu, Jian-Han Chen

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Machine learning classification meets migraine: recommendations for study evaluation by Igor Petrušić, Andrej Savić, Katarina Mitrović, Nebojša Bačanin, Gabriele Sebastianelli, Daniele Secci, Gianluca Coppola

“…This paper presents a framework of six essential recommendations for evaluating ML-based classification in migraine research: (1) group homogenization by clinical phenotype, attack frequency, comorbidity, therapy, and demographics; (2) defining adequate sample size; (3) quality control of collected and preprocessed data; (4) transparent training, testing, and performance evaluation of ML models, including strategies for data splitting, overfitting control, and feature selection; (5) interpretability of results with clinical relevance; and (6) open data and code sharing to facilitate reproducibility. These recommendations aim to balance the trade-off between model generalization and precision while encouraging collaborative standardization across the ML and headache communities. …”
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Non-ideal MHD analysis of pedestal scans of AUG and JET by F. Stefanelli, M.G. Dunne, J. Puchmayr, H. Zohm

“…The extended MHD code CASTOR3D is used to perform the MHD stability analysis of predictive pedestal scans of standard ASDEX Upgrade and JET-ILW scenarios. …”
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Rugularizing generalizable neural radiance field with limited-view images by Wei Sun, Ruijia Cui, Qianzhou Wang, Xianguang Kong, Yanning Zhang

“…Moreover, our reconstructed radiance field can be effectively optimized by fine-tuning the target scene to achieve higher quality results with reduced optimization time. The code will be released at https://github.com/dsdefv/nerf .…”
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Bayesian Neural Networks With Robust Feature Interpretation for Enhanced Compressive Strength Prediction of Ultra‐High‐Performance Concrete by Tao Zhang, Ji Hao, Jie Zhang, Lina Du, Yunhao Zhang, Wenbin Jiao

“…The complete implementation and source code are openly available at https://github.com/sean‐jiao/UHPC‐prediction.…”
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