SGK1 upregulation in GFAP+ neurons in the frontal association cortex protects against neuronal apoptosis after spinal cord injury by Anbiao Wu, Guang Yang, Genyu Liu, Jiyan Zhang

“…The introduction of SGK1 silencing vectors confirmed that SGK upregulation in these FrA neurons exerted anti-apoptotic effects through NRF2/HO-1 signaling. …”
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Adaptation of the Legal System of Ukraine in the Era of Digitalization: Challenges, Threats and Possible Ways to Overcome Them by Serhii ABLAMSKYI, Anna KAVUNSKA, Oleksandr PEREDERII, Oleksandr TYMOFIIV, Achmad ZUHDI

“… Modern processes related to the digitalization of legal relations significantly affect the development of society and the state as a whole. …”
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Study of purinosome assembly in cell-based model systems with de novo purine synthesis and salvage pathway deficiencies. by Veronika Baresova, Vaclava Skopova, Olga Souckova, Matyas Krijt, Stanislav Kmoch, Marie Zikanova

“…<h4>Background</h4>The enzymes involved in de novo purine synthesis (DNPS), one of the basic processes in eukaryotic cells, transiently and reversibly form a dynamic multienzyme complex called the purinosome in the cytoplasm. …”
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The Reaction of Monetary-Credit and Budget-Taxation Policy of Russia on the Challenges of Globalization by Mikhail Yu. Golovnin, Lyudmila N. Lykova, Irina S. Bukina

“…There were highlighted the general vectors of response of monetary-credit policy to the both crises: support of the rouble exchange rate, assistance to the banking system, expanding the toolkit of monetary and credit policy.However, one of the specific features of the crisis 2014–2016 was the transition to a floating exchange rate of the rouble and resulting instability in the currency sphere. …”
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A loss of function analysis of host factors influencing Vaccinia virus replication by RNA interference. by Philippa M Beard, Samantha J Griffiths, Orland Gonzalez, Ismar R Haga, Tali Pechenick Jowers, Danielle K Reynolds, Jan Wildenhain, Hille Tekotte, Manfred Auer, Mike Tyers, Peter Ghazal, Ralf Zimmer, Jürgen Haas

“…This advancement in our understanding of the VACV life cycle provides a reliable knowledge base for the improvement of poxvirus-based vaccine vectors and development of anti-viral theraputics.…”
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GLOBAL LIQUIDITY AS AN INSTITUTIONAL PHENOMENON by T. Е. Gorodetska, V. O. Kornivska

“… The content of present day contradictory processes in the world economy plays an important role in choosing the strategy of social and economic development of Ukraine. …”
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Improving the Energy Efficiency of the Use of Oil Jet Pumps by D. A. Panevnyk

“…The magnitude of the angle between the velocity vectors of the mixed flows directly affects the intensity of vortex formation in the mixing chamber, the amount of energy loss and the efficiency of the jet pump; however, the simplicity of their manufacture remains the determining condition for choosing the design variant of the elements of ejection systems. …”
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A Dual-Encoder Contrastive Learning Model for Knowledge Tracing by Yanhong Bai, Xingjiao Wu, Tingjiang Wei, Liang He

“…Furthermore, an adversarial training mechanism applies perturbations to embedding vectors, enhancing model robustness and generalization. …”
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Fusion Text Representations to Enhance Contextual Meaning in Sentiment Classification by Komang Wahyu Trisna, Jinjie Huang, Hengyu Liang, Eddy Muntina Dharma

“…The classification process using deep learning models is closely tied to text representation. …”
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Using Machine Learning to Propose a Qualitative Classification of Risk of Soil Erosion by Dione Pereira Cardoso, Paulo Cesar Ossani, Marcelo Angelo Cirillo, Marx Leandro Naves Silva, Junior Cesar Avanzi

“…Accordingly, the aims were to apply Machine Learning methods, specifically cluster analysis, to categorize soil erosion risk in the Peixe Angical Basin, in addition to using a discriminant analysis to propose a discriminant classifier vectors for current and future predictions of soil loss risks. …”
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Toxic metals in pregnancy and congenital heart defects. Insights and new perspectives for a technology-driven reduction in food sources by Francesca Gorini, Alessandro Tonacci

“…Additionally, being diet the major source of these elements in the general population, after having identified the main vectors of toxic metals in food, possible remediation strategies to reduce diet-related risks are also described. …”
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Ecology of Gene Drives: The Role of Density‐Dependent Feedbacks on the Efficacy and Dynamics of Two‐Locus Underdominance Gene Drive Systems by Ziqian Xu, Michael B. Bonsall

“…ABSTRACT Density dependence describes the regulation of population growth rate by population density. This process is widely observed in insect populations, including vectors such as mosquitoes and agricultural pests that are targets of genetic biocontrol using gene drive technologies. …”
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Text2SQL Business Intelligence System Based on Retrieval‐Augmented Generation (RAG) by Jie Liu, Shiwei Chu

“…Advances in natural language processing, particularly deep learning generative models, have enabled text‐to‐SQL (text2SQL) conversion, making database interaction more intuitive. …”
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Predicting specific wear rate of laser powder bed fusion AlSi10Mg parts at elevated temperatures using machine learning regression algorithm: Unveiling of microstructural morpholog... by Vijaykumar S. Jatti, R. Murali Krishnan, A. Saiyathibrahim, V. Preethi, Suganya Priyadharshini G, Abhinav Kumar, Shubham Sharma, Saiful Islam, Dražan Kozak, Jasmina Lozanovic

“…However, to accurately predict the wear rate at high temperatures, six different machine learning regression algorithms were used, namely Support Vector Machine (SVM), Linear Regression (LR), Random Forest Regression (RFR), Gaussian Process Regression (GPR), XGBoost regression (XGB) and Decision Tree (DT). …”
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Machine learning-based real-time prediction of duodenal stump leakage from gastrectomy in gastric cancer patients by Jae Hun Chung, Jae Hun Chung, Jae Hun Chung, Yushin Kim, Dongjun Lee, Dongwon Lim, Dongwon Lim, Dongwon Lim, Sun-Hwi Hwang, Sun-Hwi Hwang, Sun-Hwi Hwang, Si-Hak Lee, Si-Hak Lee, Si-Hak Lee, Woohwan Jung

“…Six ML algorithms were evaluated: Logistic Regression (LR), K-nearest neighbors (KNN), Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGB), and Neural Network (NN). …”
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Manufacturing of CD19 Specific CAR T-Cells and Evaluation of their Functional Activity in Vitro by AV Petukhov, VA Markova, DV Motorin, AK Titov, NS Belozerova, PM Gershovich, AV Karabel’skii, RA Ivanov, EK Zaikova, EYu Smirnov, PA Butylin, AYu Zaritskey

“…Human T-lymphocytes were transduced by the lentiviral vector containing anti-CD19-CAR, RIAD, and GFP genes. …”
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Suppression of METTL3 expression attenuated matrix stiffness-induced vaginal fibroblast-to-myofibroblast differentiation and abnormal modulation of the extracellular matrix in pelv... by Xiuqi Wang, Tao Guo, Xiaogang Li, Zhao Tian, Linru Fu, Zhijing Sun, Jinjiao Li

“…METTL3 small interfering RNA and an overexpression vector were transfected into vaginal fibroblasts to evaluate the effects of METTL3 silencing and overexpression on matrix stiffness-induced vaginal fibroblast-to-myofibroblast differentiation and abnormal modulation of the ECM. …”
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Hyperspectral and LiDAR space-borne data for assessing mountain forest volume and biomass by Rodolfo Ceriani, Sebastian Brocco, Monica Pepe, Silvio Oggioni, Giorgio Vacchiano, Renzo Motta, Roberta Berretti, Davide Ascoli, Matteo Garbarino, Donato Morresi, Francesco Bassi, Francesco Fava

“…We compared EMIT with Sentinel-2 (S2) multispectral data as model inputs, with and without GEDI data integration, using five Machine Learning (ML) algorithms: Partial Least Squares Regression (PLSR), Boosted Regression Trees (BRT), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Gaussian Process Regression (GPR). …”
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Predicting climate-driven shift of the East Mediterranean endemic Cynara cornigera Lindl by Heba Bedair, Heba Bedair, Yehia Hazzazi, Asmaa Abo Hatab, Marwa Waseem A. Halmy, Mohammed A. Dakhil, Mohammed A. Dakhil, Mubaraka S. Alghariani, Mubaraka S. Alghariani, Mari Sumayli, A. El-Shabasy, Mohamed M. El-Khalafy

“…Our analysis involved inclusion of bioclimatic variables, in the SDM modeling process that incorporated five algorithms: generalized linear model (GLM), Random Forest (RF), Boosted Regression Trees (BRT), Support Vector Machines (SVM), and Generalized Additive Model (GAM).Results and discussionThe ensemble model obtained high accuracy and performance model outcomes with a mean AUC of 0.95 and TSS of 0.85 for the overall model. …”
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A concept of natural genome reconstruction. Part 2. Effect of extracellular double-stranded DNA fragments on hematopoietic stem cells by V. S. Ruzanova, S. G. Oshikhmina, A. S. Proskurina, G. S. Ritter, S. S. Kirikovich, E. V. Levites, Y. R. Efremov, T. V. Karamysheva, M. I. Meschaninova, A. L. Mamaev, O. S. Taranov, A. S. Bogachev, S. V. Sidorov, S. D. Nikonov, O. Y. Leplina, A. A. Ostanin, E. R. Chernykh, N. A. Kolchanov, E. V. Dolgova, S. S. Bogachev

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