Rapid Resilience Assessment and Weak Link Analysis of Power Systems Considering Uncertainties of Typhoon by Wenqing Ma, Xiaofu Xiong, Jian Wang

“…Second, for the resilience assessment process, the impact increment method is used to reduce the dimensionality of multiple fault state analysis in the power system, and resilience indexes are calculated by screening the contingency set based on depth-first traversal through a backtracking algorithm. …”
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Few-Shot Intelligent Anti-Jamming Access with Fast Convergence: A GAN-Enhanced Deep Reinforcement Learning Approach by Tianxiao Wang, Yingtao Niu, Zhanyang Zhou

“…The method constructs a Generative Adversarial Network (GAN) to learn the time–frequency distribution characteristics of short-period jamming and to generate high-fidelity mixed samples. Furthermore, it screens qualified samples using the Pearson correlation coefficient to form a sample set, which is input into the DQN network model for pre-training to expand the experience replay buffer, effectively improving the convergence speed and decision accuracy of DQN. …”
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Comparative assessment of line probe assays and targeted next-generation sequencing in drug-resistant tuberculosis diagnosisResearch in context by Giovanna Carpi, Marva Seifert, Andres De la Rossa, Swapna Uplekar, Camilla Rodrigues, Nestani Tukvadze, Shaheed V. Omar, Anita Suresh, Timothy C. Rodwell, Rebecca E. Colman

“…Interpretation: LPAs demonstrated lower sensitivity and more limited drug resistance detection compared to tNGS workflows, underscoring the advantages of tNGS for improving DR-TB diagnostic algorithms. …”
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An EfficientNet integrated ResNet deep network and explainable AI for breast lesion classification from ultrasound images by Kiran Jabeen, Muhammad Attique Khan, Ameer Hamza, Hussain Mobarak Albarakati, Shrooq Alsenan, Usman Tariq, Isaac Ofori

“…Explainable artificial intelligence‐based analysed the performance of trained models. After that, a new feature selection technique is proposed based on the cuckoo search algorithm called cuckoo search controlled standard error mean. …”
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Leveraging automated time-lapse microscopy coupled with deep learning to automate colony forming assay by Anusha Klett, Anusha Klett, Dennis Raith, Dennis Raith, Paula Silvestrini, Paula Silvestrini, Paula Silvestrini, Matías Stingl, Jonas Bermeitinger, Avani Sapre, Avani Sapre, Avani Sapre, Martin Condor, Roman Melachrinos, Mira Kusterer, Alexandra Brand, Guido Pisani, Guido Pisani, Evelyn Ullrich, Evelyn Ullrich, Evelyn Ullrich, Evelyn Ullrich, Marie Follo, Marie Follo, Jesús Duque-Afonso, Roland Mertelsmann, Roland Mertelsmann

“…Brightfield images were used to train a YOLOv8 object detection network, achieving a mAP50 score of 86% for identifying single cells, clusters, and colonies, and 97% accuracy for Z-stack colony identification with a multi-object tracking algorithm. The detection model accurately identified the majority of objects in the dataset.ResultsThis AI-assisted CFA was successfully applied for density optimization, enabling the determination of seeding densities that maximize plating efficiency (PE), and for IC50 determination, offering an efficient, less labor-intensive method for testing drug concentrations. …”
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TikTok and Sound: Changing the ways of Creating, Promoting, Distributing and Listening to Music by Bojana Radovanović

“…In this article I will explore the ways in which TikTok has made an “aural turn” (Abidin and Kaye 2021), and thus changed and influenced the processes of music-making, music listening and music promotion. …”
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Rapid Detection of Antibiotic Mycelial Dregs Adulteration in Single-Cell Protein Feed by HS-GC-IMS and Chemometrics by Yuchao Feng, Yang Li, Wenxin Zheng, Decheng Suo, Ping Gong, Xiaolu Liu, Xia Fan

“…In addition, the feasibility of quantitative analysis of the AMDs content in adulterated SCPF based on partial least squares regression (PLSR) algorithm. In total, 88 volatile organic compounds (VOCs) were detected. …”
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La Inteligencia Artificial en la educación: Big data, cajas negras y solucionismo tecnológico / Artificial Intelligence in Education: Big Data, Black Boxes, and Technological Solut... by Xavier Giró-Gracia, Juana María Sancho-Gil

“…Educators, educational researchers, and policymakers, in general, lack the knowledge and expertise to understand the underlying logic of these new systems, and there is insufficient research based evidence to fully understand the consequences for learners’ development of both the extensive use of screens and the increasing reliance on algorithms in educational settings. …”
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In the Refractory Hypertension “Labyrinth”. Focus on Primary Hyperaldosteronism by O. V. Tsygankova, T. I. Batluk, L. D. Latyntseva, E. V. Akhmerova, N. M. Akhmedzhanov

“…It should not only have made the diagnosis easy, but it could have also absolutely justified the surgical tactics. …”
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Automated whole animal bio-imaging assay for human cancer dissemination. by Veerander P S Ghotra, Shuning He, Hans de Bont, Wietske van der Ent, Herman P Spaink, Bob van de Water, B Ewa Snaar-Jagalska, Erik H J Danen

“…Moreover, RNA interference establishes the metastasis-suppressor role for E-cadherin in this model. This automated quantitative whole animal bio-imaging assay can serve as a first-line in vivo screening step in the anti-cancer drug target discovery pipeline.…”
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DEVELOPMENT OF SOFTWARE SYSTEM FOR MONITORING OF STRESS CORROSION CRACKING OF THE PIPELINE UNDER TENSION by Z. K. Abaev, B. A. Bachiev

“…The working algorithm of developed program and the screen forms are presented.…”
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Evaluation of liver fibrosis in patients with metabolic dysfunction-associated steatotic liver disease using ultrasound controlled attenuation parameter combined with clinical feat... by LIU Chunyu, TANG Jingkuan, ZHAO Wei

“…Features were selected using the Boruta algorithm, and a predictive model combining CAP and clinical features was constructed. …”
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AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

“…Existing gaps include data quality, algorithmic transparency, and ethical concerns around privacy, among others. …”
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ATP6AP1 drives pyroptosis-mediated immune evasion in hepatocellular carcinoma: a machine learning-guided therapeutic target by Lei Tang, Xiyue Wang, Zhengzheng Xia, Jiayu Yan, Shanshan Lin

“…Results Through a rigorous multi-algorithm screening process, ATP6AP1 was found to be a highly reliable biomarker with an area under the curve (AUC) of 0.979. …”
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Digital mapping of peat thickness and extent in Finland using remote sensing and machine learning by Jonne Pohjankukka, Timo A. Räsänen, Timo P. Pitkänen, Arttu Kivimäki, Ville Mäkinen, Tapio Väänänen, Jouni Lerssi, Aura Salmivaara, Maarit Middleton

“…We carefully split the reference data into training and test sets, allowing for independent and robust model validation. Feature selection included an initial screening for multicollinearity using correlation-based feature pruning, followed by final selection using a genetic algorithm. …”
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Postpartum depression in Northeastern China: a cross-sectional study 6 weeks after giving birth by XuDong Huang, LiFeng Zhang, ChenYang Zhang, Jing Li, ChenYang Li

“…Feature importance was ranked via a random forest model based on the change in ROC-AUC after predictor removal. …”
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Drug–target interaction prediction by integrating heterogeneous information with mutual attention network by Yuanyuan Zhang, Yingdong Wang, Chaoyong Wu, Lingmin Zhan, Aoyi Wang, Caiping Cheng, Jinzhong Zhao, Wuxia Zhang, Jianxin Chen, Peng Li

“…DrugMAN uses a graph attention network-based integration algorithm to learn network-specific low-dimensional features for drugs and target proteins by integrating four drug networks and seven gene/protein networks collected by a certain screening conditions, respectively. …”
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Machine Learning for Predicting Zearalenone Contamination Levels in Pet Food by Zhenlong Wang, Wei An, Jiaxue Wang, Hui Tao, Xiumin Wang, Bing Han, Jinquan Wang

“…Other algorithms showed moderate accuracy, ranging from 77.1% to 84.8%. …”
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Interpretable machine learning for depression recognition with spatiotemporal gait features among older adults: a cross-sectional study in Xiamen, China by Shaowu Lin, Sicheng Li, Ya Fang

“…The developed machine learning models with high predictive accuracy, suggest the potential of Kinect-based gait assessment as a real-time and cost-effective screening tool for older adults with depressive symptoms.…”
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Detection of Undiagnosed Liver Cirrhosis via Artificial Intelligence-Enabled Electrocardiogram (DULCE): Rationale and design of a pragmatic cluster randomized clinical trial by Amy Olofson, Ryan Lennon, Blake Kassmeyer, Kan Liu, Zacchi I. Attia, David Rushlow, Puru Rattan, Joseph C. Ahn, Paul A. Friedman, Alina Allen, Patrick S. Kamath, Vijay H. Shah, Peter A. Noseworthy, Douglas A. Simonetto

“…A novel electrocardiogram (ECG)-enabled deep learning model trained for detection of advanced chronic liver disease (CLD) has demonstrated promising results and it may be used for screening of advanced CLD in primary care. …”
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