Liver developmental microenvironment promotes iHSC generation from human iPSCs by Di Ye, Min Ding, Yu-Mu Song, Heng-Xing Meng, Wen-Hao Chen, Jian-Yun Ge, Yun-Wen Zheng

“…The generation of highly functional iHSCs may make it more feasible to accurately simulate the liver-specific multicellular microenvironments, thus providing new perspectives on the modeling of physiological regenerative processes and disease progression in the liver, as well as useful tools for creating of new therapeutic strategies.…”
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SSA-GAN: Singular Spectrum Analysis-Enhanced Generative Adversarial Network for Multispectral Pansharpening by Lanfa Liu, Jinian Zhang, Baitao Zhou, Peilun Lyu, Zhanchuan Cai

“…We designed SSA modules within the generator, enabling more effective extraction and utilization of spectral features. …”
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A Novel Technique for Secure Data Cryptosystem Based on Chaotic Key Image Generation by Mustafa Dhiaa Al-Hassani

“…The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given control parameters, which is then processed by converting the fractional parts of them through a function into a set of non-repeating numbers that leads to a vast number of unpredicted probabilities (the factorial of rows times columns). …”
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Two-stage voltage control partitioning method for distribution network containing distributed generation by Aigang YANG, Miaoran YANG, Lijun XIE, Jianwei SHAO

“…Aiming at the characteristics of large-scale data in the distribution network with distributed generation, as well as the limitations of the traditional grid partitioning method based on complex network theory, such as irrational partitioning and insufficient reactive power regulation capability, a two-stage division method based on complex network theory is proposed in this paper. …”
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A Study on an Improved Generative Adversarial Network Model for Super-Resolution Image Reconstruction by Ximin Qu, Cheng Peng

“…The SRGAN model based on Generative Adversarial Networks (GANs) has achieved breakthroughs in perceptual quality for image super-resolution reconstruction. …”
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Radar Echo Extrapolation Based on Translator Coding and Decoding Conditional Generation Adversarial Network by Xingang Mou, Yuan He, Wenfeng Li, Xiao Zhou

“…Lastly, a composite multi-loss function is proposed to enhance the network’s capability to model intricate spatiotemporal evolving radar echo data, facilitating a more comprehensive assessment of the quality of the generated images, which in turn fortifies the network’s robustness. …”
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Bio-inspired generative design of contact interfaces subjected to time-dependent loading conditions by David Hernandez-Aristizabal, Santiago Arroyave-Tobón, Kalenia Marquez-Florez, Jean-Marc Linares

“…The results demonstrate that the growth principles lead to almost uniform contact pressure under time-independent loads, up to 34.7% more uniform than reference shapes. Under time-dependent loads, it generates shapes with reduced maximum shear stress and contact pressure (up to 73%) with respect to initial shapes. …”
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Imbalanced Power Spectral Generation for Respiratory Rate and Uncertainty Estimations Based on Photoplethysmography Signal by Soojeong Lee, Mugahed A. Al-antari, Gyanendra Prasad Joshi, Yeong Hyeon Gu

“…Thus, accurate estimation of RRs for cardiopulmonary function is essential for home health monitoring systems. …”
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Identification of diversity-generating retroelements in host-associated and environmental genomes: prevalence, diversity, and roles by Mariela Carrasco-Villanueva, Chaoxian Wang, Chaochun Wei

“…Abstract Background The diversity-generating retroelements (DGRs) are a family of genetic elements that can produce mutations in target genes often related to ligand-binding functions, which possess a C-type lectin (CLec) domain that tolerates massive variations. …”
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Microservices-Driven Automation in Full-Stack Development: Bridging Efficiency and Innovation With FSMicroGenerator by Samira Khalfaoui, Hafida Khalfaoui, Abdellah Azmani

“…FSMicroGenerator also stands out for its ability to create a catalog of ready-to-use functional blocks, enabling their reuse and integration into other solutions. …”
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Appliances of Generative AI-Powered Language Tools in Academic Writing: A Scoping Review by Lilia Raitskaya, Елена Тихонова

“…The potential of AI language tools embraces many functions (text generation, proofreading, editing, text annotation, paraphrasing and translation) and provides for assistance in research and academic writing, offers strategies for hybrid AI-powered writing of various assignments and genres and improvements in writing quality. …”
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Model generation and parametric study of stick-slip induced vibration for mechanics under friction by Jitendra Yadav, Roushan Kumar, Adesh Kumar, Brijesh Gangil, Lalit Ranakoti, Shubham Sharma, Kuldeep Sharma, Rakesh Kumar, S Rajkumar, Krishnaraj Ramaswamy

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Generator Rescheduling Based Congestion Management in Power System Deregulation Using the Cheetah Optimization by Sajal Debbarma, Dipu Sarkar

“…Congestion management (CM), which takes into account the inherent uncertainties of the restructured power system, is essential to the functioning and security of DPM. This article demonstrates how to control congestion with generation rescheduling. …”
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Digital Architectural Form Generation Through Pixel System-Driven Image Feature Information by Hee-Sung An, You-Chang Jeon, Sung-Wook Kim

“…This study analyzes valuable information (image feature information) from pixel-based images to systematize the form generation process utilizing this information. Information in architecture is mainly used as an analytical tool for functional design optimization. …”
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Potentials of integrating generative artificial intelligence technologies into formative assessment processes in higher education by A. A. Paskova

“…The use of generative artificial intelligence technologies in education has the potential to revolutionize learning and educational assessment by personalizing the learning experience, providing immediate feedback, and improving the overall learning experience.The relevance of the research is due to the spread of artificial intelligence technologies and the lack of practices for formative assessment of educational achievements in higher education.The problem statement: existing domestic e-learning systems have limited functionality, which makes them difficult to use in the process of formative testing.The goal of the research is to study the possibility and effectiveness of using generative artificial intelligence technologies in formative assessment in higher education.The objectives of the research are to consider the theoretical foundations of using generative artificial intelligence tools in assessing knowledge, skills and abilities, and to analyze our own experience of using large language models in formative testing at a university.The methodological basis of the research is analysis of Internet resources and literary sources, methods of mathematical statistics, and synthesis.The research results: the possibilities of using and the effectiveness of generative artificial intelligence technologies in formative testing of university students have been studied, our own experience of using large language models in formative testing have been analyzed, the main limitations of introducing these technologies into the educational process have been identified, recommendations have been given for organizing formative testing using large language models.Key conclusions: Large language models can be integrated into the learning process to assess formative and summative tests, which will significantly reduce the workload of teachers, provide more objective results and, ultimately, increase the effectiveness of the learning process.…”
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Innovative Guardrails for Generative AI: Designing an Intelligent Filter for Safe and Responsible LLM Deployment by Olga Shvetsova, Danila Katalshov, Sang-Kon Lee

“…AVI provides a scalable and adaptable architectural template for the responsible deployment of generative AI in high-stakes domains such as finance, healthcare, and education, promoting safer and more ethical use of AI technologies.…”
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Summarizing Online Patient Conversations Using Generative Language Models: Experimental and Comparative Study by Rakhi Asokkumar Subjagouri Nair, Matthias Hartung, Philipp Heinisch, Janik Jaskolski, Cornelius Starke-Knäusel, Susana Veríssimo, David Maria Schmidt, Philipp Cimiano

“…ConclusionsTaken together, our results suggest that state-of-the-art pretrained language models are a valuable tool to provide qualitative insights about the patient experience to better understand unmet needs, patient priorities, and how a disease impacts daily functioning and quality of life to inform processes aimed at improving health care delivery and ensure that drug development focuses more on the actual priorities and unmet needs of patients. …”
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eidos: A modular approach to external function integration in LLMs by José F. Aldana-Martín, Antonio Benítez-Hidalgo, José F. Aldana-Montes

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circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data by Petr Ryšavý, Alikhan Anuarbekov, Michaela Dostálová Merkerová, Jiří Kléma

“…To address this issue, we propose an extended algorithm named circGPAcorr, which uses expression data to weight the interactions, resulting in more precise functional annotation. To assess the significance of the results, the p-value is calculated using reduction to circGPA, a generating-polynomial-based method. …”
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The detection of distributional discrepancy for language GANs by Xingyuan Chen, Peng Jin, Ping Cai, Hongjun Wang, Xinyu Dai, Jiajun Chen

“…Different from the above-mentioned methods, we adopted the most recent metric functions, which measure the distributional discrepancy between real and generated text. …”
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