Resveratrol contributes to NK cell-mediated breast cancer cytotoxicity by upregulating ULBP2 through miR-17-5p downmodulation and activation of MINK1/JNK/c-Jun signaling by Bisha Ding, Jie Li, Jia-Lin Yan, Chun-Yan Jiang, Ling-Bo Qian, Jie Pan

“…The target gene of miR-17-5p were predicted with different algorithms from five databases and further confirmed with dual-luciferase reporter assay. …”
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LogProb: Online Parsing Evolving Logs With Complex Parameters by Yan Li, Ziying Wang, Jiaming Mao, Zhimin Gu, Haitao Jiang

“…The extraction process includes two stages: identifying candidate templates with predicted static tokens, and using a fast matching algorithm to determine the final template. …”
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Artificial intelligence-based radiogenomics reveals the potential immunoregulatory role of COL22A1 in glioma and its induced autoimmune encephalitis by Bingchao Yan, Bingchao Yan, Qian Chen, Dacheng Wang, Leili Ding, Leili Ding, Jingfeng Qu, Renfei Du, Renfei Du, Wenjie Shi, Ulf D. Kahlert, Zhengquan Yu

“…Immune infiltration was evaluated using five algorithms (MCP-counter, EPIC, TIMER, QUANT and IPS). …”
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Application of deep learning reconstruction at prone position chest scanning of early interstitial lung disease by Ruijie Zhao, Yun Wang, Jiaru Wang, Zixing Wang, Ran Xiao, Ying Ming, Sirong Piao, Jinhua Wang, Lan Song, Yinghao Xu, Zhuangfei Ma, Peilin Fan, Xin Sui, Wei Song

“…Conclusion With 63.7% reduction of radiation dose, the overall image quality of LDCT DLR was comparable to HRCT HIR in prone scanning for early ILD patients. …”
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Microstate Co-Occurrence Matrices-Based Brain Activity Pattern Changes Analysis on Chronic Tinnitus Subjects by Yingying Wang, Gui Yang, Hongyu Liu, Xin Huang, Shuqing Han, Zhixiang Gu, Liyang Shao, Lei Zhang, Yuan Tao

“…Unlike healthy individuals, tinnitus patients exhibit minimal changes between OE and CE, indicating the reduction of brain flexibility. This study advances EEG microstate analysis by integrating co-occurrence matrix algorithms, offering a direct and comprehensive assessment of microstate stability and interactions. …”
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Digital-twin driven alignment control method for marine shafting with air spring vibration isolation system by Song Liu, Liang Shi, Wei Xu, ZeChao Hu

“…To obtain the optimal air spring pressures, the genetic algorithm is introduced to solve the optimization problem, fully exploiting its global search capacity. …”
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Optimalisasi Prediksi Harga Ihsg Menggunakan Hybrid Weighted Fuzzy Time Series Hidden Markov Model Dengan Algoritma Evolusi Differensial by Alya Fitri Syalsabilla, Suci Astutik, Agus Fachrur Rozy

“…Forecasting from the Hybrid WFTS-HMM Model with the DE Algorithm has lower prediction error (1.45%) compared to the model without DE (1.49%). …”
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Optimal design strategy of traditional courtyard based on performance and data-driven method—A case study of Yanshen ancient town, China by Zhixin Xu, Xin Zheng, Xiangfeng Li

“…Based on the learning rates and various evaluation indicators, XGBoost is ultimately selected to classify and predict the overall building performance. Results indicate that the model achieves an average prediction accuracy of 83.6%. …”
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Generative AI for drug discovery and protein design: the next frontier in AI-driven molecular science by Uddalak Das

“…Generative artificial intelligence (AI) has emerged as a disruptive paradigm in molecular science, enabling algorithmic navigation and construction of chemical and proteomic spaces through data-driven modeling. …”
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AI Innovations in Liver Transplantation: From Big Data to Better Outcomes by Eleni Avramidou, Dominik Todorov, Georgios Katsanos, Nikolaos Antoniadis, Athanasios Kofinas, Stella Vasileiadou, Konstantina-Eleni Karakasi, Georgios Tsoulfas

“…As a result, algorithms are being developed to assess steatosis in pre-implantation biopsies and predict liver graft function, with AI applications displaying great accuracy across various studies included in this review. …”
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Opportunities and limitations of introducing artificial intelligence technologies into reproductive medicine by V. A. Lebina, O. Kh. Shikhalakhova, A. A. Kokhan, I. Yu. Rashidov, K. A. Tazhev, A. V. Filippova, E. P. Myshinskaya, Yu. V. Symolkina, Yu. I. Ibuev, A. A. Mataeva, A. N. Sirotenko, T. T. Gabaraeva, A. I. Askerova

“…Studies show that machine learning algorithms can process images of embryos to assess their quality, thus facilitating the selection of the most viable among them for transfer. …”
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Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

“…AI technologies, including predictive modeling and ML algorithms such as random forests and convolutional neural networks (CNNs), can analyze diverse data sources—such as meteorological, environmental, and health records—to detect patterns and predict outbreaks. …”
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Artificial intelligence - finite element method - hybrids for efficient nonlinear analysis of concrete structures by Michael A. Kraus, Rafael Bischof, Walter Kaufmann, Karel Thoma

“…We successfully calibrated and evaluated k-nearest-neighbour, LGBM and ResNet algorithms and report their predictive capabilities. …”
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Phasic and periodic change of drought under greenhouse effect by Yang Li, Zhicheng Zheng, Yaochen Qin, Haifeng Tian, Zhixiang Xie, Peijun Rong

“…It can lead to crop reduction and even pose a threat to human survival in environmentally sensitive areas of China (ESAC). …”
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Low-Rank Tensor Fusion for Enhanced Deep Learning-Based Multimodal Brain Age Estimation by Xia Liu, Guowei Zheng, Iman Beheshti, Shanling Ji, Zhinan Gou, Wenkuo Cui

“…<b>Results:</b> Our prediction model achieved a desirable prediction accuracy on the independent test samples, demonstrating its robust performance. …”
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Machine Learning-Based Cost Estimation Models for Office Buildings by Guolong Chen, Simin Zheng, Xiaorui He, Xian Liang, Xiaohui Liao

“…This paper explores the application of algorithm-optimized back propagation neural networks and support vector machines in predicting the costs of office buildings. …”
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Machine Learning and Deep Learning-Based Atmospheric Duct Interference Detection and Mitigation in TD-LTE Networks by Rasendram Muralitharan, Upul Jayasinghe, Roshan G. Ragel, Gyu Myoung Lee

“…Our results show that the Random Forest algorithm achieves the highest prediction accuracy, while a convolutional neural network demonstrates the best mitigation performance with accuracy. …”
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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

“…Rate-distortion optimization (RDO) is a crucial technique in block based hybrid video encoders.However, the widely used independent RDO is far from obtaining optimal coding performance.To improve the rate-distortion (R-D) performance of high efficiency video coding (HEVC), a temporal dependent RDO algorithm was proposed.Firstly, the formula to calculate temporal distortion propagation factor was derived by using an exponential R-D function.Then, the coding distortion and motion compensation predicted error were obtained by pre-encoding, and the temporal distortion propagation factor was estimated by using distortion backward propagation.Finally, the Lagrange multiplier and quantization parameter of coding tree unit were adaptively adjusted to optimize bit resources allocation.Experimental results show that compared with the original RDO method in HEVC under the low-delay configuration, the proposed algorithm achieves an average 4.4% bit rate reduction for all test sequences, and up to 13.0% bit rate reduction for test sequence BasketballDrill, at the same reconstructed video quality.…”
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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

“…Rate-distortion optimization (RDO) is a crucial technique in block based hybrid video encoders.However, the widely used independent RDO is far from obtaining optimal coding performance.To improve the rate-distortion (R-D) performance of high efficiency video coding (HEVC), a temporal dependent RDO algorithm was proposed.Firstly, the formula to calculate temporal distortion propagation factor was derived by using an exponential R-D function.Then, the coding distortion and motion compensation predicted error were obtained by pre-encoding, and the temporal distortion propagation factor was estimated by using distortion backward propagation.Finally, the Lagrange multiplier and quantization parameter of coding tree unit were adaptively adjusted to optimize bit resources allocation.Experimental results show that compared with the original RDO method in HEVC under the low-delay configuration, the proposed algorithm achieves an average 4.4% bit rate reduction for all test sequences, and up to 13.0% bit rate reduction for test sequence BasketballDrill, at the same reconstructed video quality.…”
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Improving Accuracy and Calibration of Deep Image Classifiers With Agreement-Driven Dynamic Ensemble by Pedro Conde, Rui L. Lopes, Cristiano Premebida

“…Possible strategies to tackle this problem are two-fold: (i) models need to be highly accurate, consequently reducing this risk of failure; (ii) facing the impossibility of completely eliminating the risk of error, the models should be able to inform the level of uncertainty at the prediction level. As such, state-of-the-art DL models should be <italic>accurate</italic> and also <italic>calibrated</italic>, meaning that each prediction has to codify its confidence/uncertainty in a way that approximates the true likelihood of correctness. …”
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