Analysis of Microbiome for AP and CRC Discrimination by Alessio Rotelli, Ali Salman, Leandro Di Gloria, Giulia Nannini, Elena Niccolai, Alessio Luschi, Amedeo Amedei, Ernesto Iadanza

“…After data validation, layer-wise relevance propagation (LRP) was performed on a deep learning classifier to extract important OTU features from the generated dataset, to discriminate between CRC patients and those affected by AP. …”
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Retinal Microvascular Characteristics—Novel Risk Stratification in Cardiovascular Diseases by Alexandra Cristina Rusu, Klara Brînzaniuc, Grigore Tinica, Clément Germanese, Simona Irina Damian, Sofia Mihaela David, Raluca Ozana Chistol

“…We evaluated the precision of several classification models in identifying patients with CHDs based on traditional risk factors and OCTA characteristics: a conventional logistic regression model and four machine learning algorithms: k-Nearest Neighbors (k-NN), Naive Bayes, Support Vector Machine (SVM) and supervised logistic regression. …”
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Uncertainty-Aware Earthquake Forecasting Using a Bayesian Neural Network with Elastic Weight Consolidation by Changchun Liu, Yuting Li, Huijuan Gao, Lin Feng, Xinqian Wu

“…Our experiments demonstrate that our SVGD-BNN model significantly outperforms traditional peak displacement (Pd)-based approaches. …”
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Dynamically Changing Parallelism with the Asynchronous Sequential Data Flows by Alexander I. Legalov, Ivan V. Matkovskii, Mariya S. Ushakova, Darya S. Romanova

“…It is assumed that on the data readiness a control signal is emitted to inform the processes about the occurrence of certain events. The special feature of our approach is that the model is extended with the special asynchronous containers that can generate events on their partial filling. …”
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Accurate Virtual Trial Assembly Method of Prefabricated Steel Components Using Terrestrial Laser Scanning by Yin Zhou, Daguang Han, Kaixin Hu, Guocheng Qin, Zhongfu Xiang, Chunli Ying, Lidu Zhao, Xingyi Hu

“…In this study, a general framework for VTA that is performed between a point cloud, a building information model (BIM), and the finite element method is proposed. …”
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Power System Transient Stability Assessment Based on Intelligent Enhanced Transient Energy Function Method by Tianxiao Mo, Jun Liu, Jiacheng Liu, Guangyao Wang, Yuting Li, Kaiwei Lin

“…Firstly, the ST-kmeans method is used to cluster the generator sets, and the S-transformation is performed on the power angle changes of the generator sets to extract features. …”
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Investigation of potential prognostic biomarkers for colorectal cancer by Hui Li, Jie Liu, WenHui Liu, Liang Zheng, JuHui Chen

“…Since CRC is largely asymptomatic until the alert features develop to an advanced stage, implementation of a screening program is important to reduce cancer morbidity and mortality. …”
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Optimizing the interaction of service robots in elderly care institutions using multi-modal emotion recognition system based on transfer learning by Yongguan Ai, Yuanjun Zhang, Juan Wang, Nianfang Xu

“…Initially, public emotion datasets such as AffectNet and IEMOCAP are utilised for pre-training convolutional neural networks (CNN) and bidirectional long short-term memory (Bi-LSTM) models to capture general emotional features. Subsequently, the system is fine-tuned using a home-grown nursing home dataset, employing a hierarchical fine-tuning strategy to optimise the model, with a particular emphasis on enhancing the facial expressions, speech and physiological signals of the elderly. …”
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Detecting unknown vulnerabilities in smart contracts using opcode sequences by Peiqiang Li, Guojun Wang, Xiaofei Xing, Xiangbin Li, Jinyao Zhu

“…Next, we employ an n-gram model and a vector weight penalty mechanism to extract the opcode sequence features. …”
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Incidence rate and clinical characteristics of seasonal affective disorders in senior medical students by I. I. Ukraintsev, E. D. Schastnyy, N. A. Bokhan

“…To study the incidence rate, clinical features, and prognosis of seasonal affective disorder (SAD) in senior (6th-year) medical students.Materials and methods. …”
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Single-cell sequencing combined with machine learning to identify glioma biomarkers and therapeutic targets by Yu Yan, Zhengmin Chu, Qi Zhong, Genghuan Wang

“…Characterizing these ubiquitination-associated features may elucidate the molecular mechanisms driving GBM progression and offer novel insights for its diagnosis and treatment. …”
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Social and Digital Entrepreneurship in Turkey: Content Analysis of Crowdfunding Platforms with Data Scraping Techniques by Murat Kılınç, Can Aydın, Çiğdem Tarhan

“…The crowdfunding (CF) model, which is presented as a new generation entrepreneurship model in the digitalizing world, provides great benefits in realizing business ideas. …”
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Epidemiological and clinical characteristics of children with pertussis: a 6-year retrospective cohort study in Chengdu, China by Qing Yang, Dong-Mei Wang, Qi An, Liang Huang

“…Univariate and multivariate Cox regression and the autoregressive integrated moving average model were used for identifying risk factors, and epidemiological trend analysis was performed.ResultsWe analyzed the data of 643 children with pertussis, 351 (54.59%) were younger than 6 months and 344 (53.50%) had a positive contact history. …”
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Properties of the SURE Estimates When Using Continuous Thresholding Functions for Wavelet Shrinkage by Alexey Kudryavtsev, Oleg Shestakov

“…This model is well studied in the literature, and various types of thresholding and parameter selection strategies adapted for specific applications have been proposed. …”
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Synergizing TabNet and SHAP for PM10 Forecasting: Insights From Makkah, Saudi Arabia by Abdulrazak H. Almaliki, Afaq Khattak

“…This study utilizes the TabNet model to estimate PM10 concentrations, taking advantage of its ability to perform sparse feature selection and sequential decision-making to uncover complex relationships among different environmental variables. …”
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Structural analysis of viral infectivity factor of HIV type 1 and its interaction with A3G, EloC and EloB. by Kauê Santana da Costa, Elcio Leal, Alberto Monteiro dos Santos, Anderson Henrique Lima e Lima, Cláudio Nahum Alves, Jerônimo Lameira

“…<h4>Methodology</h4>Fifty thousand Vif models were generated using the ab initio relax protocol of the Rosetta algorithm from sets of three- and nine-residue fragments using the fragment Monte Carlo insertion-simulated annealing strategy, which favors protein-like features, followed by an all-atom refinement. …”
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Siamese network with squeeze-attention for incomplete multi-view multi-label classification by Mengqing Wang, Jiarui Chen, Lian Zhao, Yinghao Ye, Xiaohuan Lu

“…Furthermore, considering the task-specific importance variation exhibited by each view, we apply the squeeze attention-weighted fusion (SWF) strategy, which performs feature dimensionality reduction to amplify the key characteristics from each view and enables the model to flexibly adjust the influence of each perspective. …”
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A Dynamic Kalman Filtering Method for Multi-Object Fruit Tracking and Counting in Complex Orchards by Yaning Zhai, Ling Zhang, Xin Hu, Fanghu Yang, Yang Huang

“…By optimizing the network structure, the improved YOLO detection model provides high-quality detection results for subsequent tracking tasks. …”
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On the issue of creating the optimal last stage of powerful steam turbines of nuclear power plants by T. V. Bogomolova, G. A. Ahmadzadeh

“…To estimate the most effective length of the working blade of the last stage of a powerful wet-steam turbine in terms of obtaining its maximum efficiency and to optimize the parameters of this stage in the design mode. For this stage, perform multi-mode optimization to select the main characteristics of the stage operating with maximum efficiency according to a given model daily load schedule.METHODS. …”
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Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation by Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen

“…AI assistance appears to improve sensitivity for lung nodule and cancer detection but can be accompanied by a decrease in specificity and an increase in false-positive findings per scan, as well as raising risk categorisation. The reported performance of AI-assisted reading varies substantially among published studies (for any nodules: per-person sensitivity 0.79–0.99, per-person specificity 0.81–0.97), possibly attributable to heterogeneous study and reader populations, other study design features and risk of bias in addition to potential differences in the performance of individual technologies. …”
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