Cuproptosis genes in predicting the occurrence of allergic rhinitis and pharmacological treatment. by Ting Yi

“…<h4>Background</h4>While drug therapy and allergen immunotherapy are useful for alleviating symptoms of seasonal allergic rhinitis (AR), existing therapeutic options remain limited. …”
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Cell-TRACTR: A transformer-based model for end-to-end segmentation and tracking of cells. by Owen M O'Connor, Mary J Dunlop

“…Our results demonstrate that Cell-TRACTR exhibits strong performance in tracking and division accuracy compared to state-of-the-art algorithms, while also meeting traditional benchmarks in detection accuracy. …”
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Journalistic Ethics in the Age of Artificial Intelligence: Towards an Update of Deontological Codes in the Ibero-American Context by Ingrid Viviana Estrella Tutivén, Cristina Garde Cano

“…Additionally, it highlights the need for balanced regulation that does not allow media abuses through AI while also respecting press freedom. …”
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Evaluating the Effectiveness of Various Small RNA Alignment Techniques in Transcriptomic Analysis by Examining Different Sources of Variability Through a Multi-Alignment Approach by Xinwei Zhao, Eberhard Korsching

“…This framework can be used to compare results from different alignment programs and algorithms on the same dataset, allowing for a comprehensive analysis of subtle to significant differences. …”
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PROACTIVE APPROACH IN TAX RISK MANAGEMENT: DATA ANALYSIS TECHNIQUES TO IDENTIFY HIGH-RISK TAXPAYERS by Funda KARAKOYUN

“…With this process, which has been accelerating for decades, statistical models that will reduce tax loss and evasion of states and increase efficiency in collection have been diversified in the field of machine learning. While innovations in software programs with digitalisation transformation reduce the manual workload of the tax administration, machine learning algorithms are used with experts employed in the field in continuously developing risk analysis studies. …”
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Ethical Challenges of Using the Internet of Behavior in the Medical and Healthcare Practice by Zahra Sadeqi-Arani, Esmaeil Mazroui Nasrabadi

“…Additionally, reliance on algorithms for IoB data analysis should not diminish human oversight in healthcare decision-making. …”
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Color correction methods for underwater image enhancement: A systematic literature review. by Yong Lin Lai, Tan Fong Ang, Uzair Aslam Bhatti, Chin Soon Ku, Qi Han, Lip Yee Por

“…However, challenges persist across all categories, including algorithmic limitations, data dependency, computational complexity, and performance variability across diverse underwater environments. …”
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Understanding Precipitation Moisture Sources and Their Dominant Factors During Droughts in the Vietnamese Mekong Delta by Keke Zhou, Xiaogang Shi

“…Results of the causal inference algorithms indicate that the humidity and wind speed in the upwind area are the dominant factors for driving moisture transport and determining the amount of VMD precipitation in dry and wet seasons, respectively. …”
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Instagram and #Wellness: Uncovering Gender and Body Patterns by Ana Marta M. Flores, Rita Sepúlveda

“…Alternative or counter-narratives, while they exist, often face challenges in gaining visibility due to both algorithmic biases and cultural predispositions. …”
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A new temporal locality-based workload prediction approach for SaaS services in a cloud environment by Wiem Matoussi, Tarek Hamrouni

“…The method will be implemented in order to simultaneously achieve a twofold benefit: obtain precise forecast results while optimizing response time. In this regard, we have chosen to control the computation time by dynamizing the size of the sliding window associated to the recent history to be analyzed, since the larger the size of the entry in the prediction model, the more the algorithmic complexity increases. …”
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Biased perceptions of public opinion don't define echo chambers but reveal systematic differences in political awareness. by Crispin H V Cooper, Kevin Fahey, Regan Jones

“…Echo chambers both feed and are fed by the false consensus effect, whereby people overestimate the degree to which others share their views, with algorithmic filtering of social media also a contributing factor. …”
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Machine learning-based predictive analysis of energy efficiency factors necessary for the HIFU treatment of adenomyosis by Ziyan Liu, Ziyi Liu, Yuan Wang, Xiyao Wan, Xiaohua Huang

“…Predictive features were selected using minimum redundancy maximum relevance (MRMR) and least absolute shrinkage and selection operator (LASSO) methods, and two joint—based on decision tree and random forest algorithms—models were developed for EEF prediction.ResultsThe decision tree model achieved a mean absolute error (MAE) of 8.095 on the test set, while the random forest model exhibited an MAE of 8.231. …”
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Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning by Qingli Liu, Yongjie Ma

“…The simulation results show that the system spectrum efficiency is improved by 19.1% on average compared with the centralized DDPG, MADDPG, MAPPO and FL-DuelingDQN algorithms in the Vehicle Networking scenario, while the transmission success rate of the V2V link is improved by 9.3% on average, and the total capacity of the V2I link is increased by 16.1% on average.…”
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Behavioral Economics and Online Donation Behavior on TikTok by Rukiah Rukiah, Ahmad Salman Farid

“…The role of influencers, algorithmic exposure, and real-time donation tracking fosters a community-driven donation culture that encourages both impulse and sustained giving. …”
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Comparison of Deep Learning Techniques in Detection of Sickle Cell Disease. by Mabirizi, Vicent, Kawuma, Simon, Kyarisiima, Addah, Bamutura, David, Atwiine, Barnabas, Nanjebe, Deborah, Oyesigye, Adolf Mukama

“…Results from our study will aid researchers and industry practitioners in making decisions on the best deep-learning model to use while detecting SCD.…”
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Defending CNN Against FGSM Attacks Using Beta-Based Personalized Activation Functions and Adversarial Training by Hanen Issaoui, Asma Eladel, Ahmed Zouinkhi, Mourad Zaied, Lazhar Khriji, Sarvar Hussain Nengroo

“…Machine learning algorithms based on deep neural networks have been widely used in many fields especially in computer vision, with impressive results. …”
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Model Based Control System Design Using SysML, Simulink, and Computer Algebra System by Takashi Sakairi, Eldad Palachi, Chaim Cohen, Yoichi Hatsutori, Junya Shimizu, Hisashi Miyashita

“…The integration with Simulink enables users to perform systems engineering process in a SysML model, while designing continuous control algorithms and plant behavior in Simulink, and to validate the behavior by simulating the overall composition in Simulink. …”
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The Development and Application of Multi-Cell Elliptical Superconducting Cavity Pre-Tuning Equipment by Ahong Li, Lin Meng, Huachang Liu, Yao Yang, Qiang Chen, Bo Li, Xiaolei Wu, Peihua Qu, Mengxu Fan, Wenzhong Zhou, Cong Zhang

“…This platform integrates three main components: real-time electric field measurements, data analysis based on tuning algorithms, and automated mechanical adjustment systems. …”
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Prediction of canopy mean traits in herbaceous plants by the UAV multispectral data: The quest for a better leaf-to-canopy upscaling method by Yuanqi Shan, Yunlong Yao, Lei Wang, Zhihui Wang, Huaihu Yi, Yi Fu, Weineng Li, Xuguang Zhang, Wenji Wang, Zhongwei Jing

“…These findings contribute to advancing the prediction accuracy of plant functional traits through remote sensing techniques, while future studies may explore the integration of deep learning methods.…”
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High-efficiency sparse convolution operator for event-based cameras by Sen Zhang, Fusheng Zha, Fusheng Zha, Xiangji Wang, Mantian Li, Wei Guo, Pengfei Wang, Xiaolin Li, Lining Sun

“…However, despite their inherent sparsity, most existing visual processing algorithms are optimized for conventional standard cameras and dense images captured from them, resulting in computational redundancy and high latency when applied to event-based cameras. …”
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