Optimizing In Vitro Metacyclogenesis: Strain-Specific Variability in <i>Trypanosoma cruzi</i> Responses to Nutritional and pH Stress by Virginia Perdomo, Victoria Boselli, Romina Manarin, Esteban Serra

“…Metacyclogenesis is a critical process in the <i>Trypanosoma cruzi</i> life cycle. …”
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IM- LTS: An Integrated Model for Lung Tumor Segmentation using Neural Networks and IoMT by Jayapradha J, Su-Cheng Haw, Naveen Palanichamy, Kok-Why Ng, Senthil Kumar Thillaigovindhan

“…In recent days, Internet of Medical Things (IoMT) and Deep Learning (DL) techniques are broadly used in medical data processing in decision-making. A lung tumour, one of the most dangerous medical diseases, requires early diagnosis with a higher precision rate. …”
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Design and Application of an Energy Management System Based on Artificial Intelligence Technology by Hongye Lin, Xuanying Bai, Chun Li, Shenghan Xu, Haibin Xu, Zne-Jung Lee, Yun Lin, Qunshan Zhou, Jingxun Cai

“…The system is functionally complete, completing the process from data collection to visualization, the cloud platform’s construction, and finally a full energy management platform. …”
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Acute myeloid leukemia-derived extracellular vesicles induced DNA methylation changes responsible for inflammatory program in normal hematopoietic stem progenitor cells by Daniela Lamorte, Giovanni Calice, Stefania Trino, Michele Santodirocco, Antonella Caivano, Luciana De Luca, Ilaria Laurenzana

“…This communication can be mediated by Extracellular Vesicles (EVs), small vectors carrying a range of tumor molecular information. …”
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Investigating the Triple Code Model in numerical cognition using stereotactic electroencephalography. by Alexander P Rockhill, Hao Tan, Christian G Lopez Ramos, Caleb Nerison, Beck Shafie, Maryam N Shahin, Adeline Fecker, Mostafa Ismail, Daniel R Cleary, Kelly L Collins, Ahmed M Raslan

“…According to the "Triple Code Model" in numerical cognition, distinct neural substrates encode the processing of visual, auditory, and non-symbolic numerical representations. …”
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An Efficient and Fast Model Reduced Kernel KNN for Human Activity Recognition by Zongying Liu, Shaoxi Li, Jiangling Hao, Jingfeng Hu, Mingyang Pan

“…Many classic machine learning algorithms, such as artificial neural network, feed forward neural network, K-nearest neighbors, and support vector machine, achieve good performance for detecting human activity. …”
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Key issues of patient safety during anticancer drug treatment in a day hospital and outpatient setting by A. A. Fedenko, A. A. Kolomeytseva, V. O. Artemova

“…The qualifications level of medical personnel involved in the treatment process should allow early monitoring of various adverse events development. …”
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Assessment of the accuracy of heavy aircraft control, taking into account the functioning of the indicator on the windshield and flight control actuators by A. A. Malchenko, P. S. Kostin, Ya. G. Khatuntsev

“…The features of the process of developing the elements of the indicator on the windshield, namely the indicators of the director ring and the velocity vector, their control law when the aircraft moves along an assigned flight path are presented.  …”
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Real-time fMRI pattern decoding and neurofeedback using FRIEND: an FSL-integrated BCI toolbox. by João R Sato, Rodrigo Basilio, Fernando F Paiva, Griselda J Garrido, Ivanei E Bramati, Patricia Bado, Fernanda Tovar-Moll, Roland Zahn, Jorge Moll

“…FRIEND is open-source and free for non-commercial use. Processing tutorials and extensive documentation are available.…”
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Application research and effectiveness evaluation mechanism of hybrid intelligent algorithm integrating cognitive computing and deep learning for dynamically adjusting employee per... by Zhenlin Luo, Kebin Lu

“…Simultaneously, hybrid intelligent algorithms outperform support vector machines (SVM) in terms of response speed, with a 61.9% reduction in response time compared to SVM, highlighting their advantages in processing large-scale datasets. …”
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Milling Tool Wear State Recognition by Vibration Signal Using a Stacked Generalization Ensemble Model by Yang Hui, Xuesong Mei, Gedong Jiang, Tao Tao, Changyu Pei, Ziwei Ma

“…However, the characteristics of milling process limit the accuracy and stability of tool condition monitoring (TCM) employing vibration signals. …”
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A Machine Learning Framework for Student Retention Policy Development: A Case Study by Sidika Hoca, Nazife Dimililer

“…While most previous work relies on wide-ranging data from numerous sources such as surveys, enrolment, and learning management systems, making the process complex and time-consuming, the current study uses minimal data that are readily available in any registration system. …”
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To Close is Impossible to Leave it: Where Should be Put a Comma? by E. A. Pleshkevich

“…It is noted that the basic social function determining the vector of domestic library construction was the function of educating a Soviet person, his ideological, cultural, scientific and technical enlightenment through the guidance of book reading in a specially selected library fund. …”
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PolyReg: Autoregressive Building Outline Regularization via Masked Attention Sequence Generation by Longfei Cui, Chao Li, Xin Chen, Xiao Wang, Haizhong Qian

“…Automatically extracting regularized building outline polygon vectors is crucial for improving vector mapping efficiency and geographic information system applications, but existing deep learning methods struggle to simultaneously achieve accurate detection, high pixel-level coverage, and geometric regularity. …”
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Optimized Identity Authentication via Channel State Information for Two-Factor User Verification in Information Systems by Chuangeng Tian, Fanjia Li, Xiaomeng Liu, Juanjuan Li

“…For classification, a kernel support vector machine (SVM) model is trained using a randomized hyperparameter search algorithm. …”
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Diagnosis and classification of neuromuscular disorders using Bi-LSTM optimized with grey Wolf optimizer for EMG signals by Ruth Keziah Mani, Balakrishnan Nagaraj

“…Existing approaches range from deep learning techniques such as Long Short-Term Memory (LSTM) and Bidirectional LSTM (Bi-LSTM) to conventional machine learning methods like Support Vector Machines (SVM) and Random Forest. Deep learning automates the process, reducing the dependency on manual feature extraction. …”
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Enhanced Medical Education for Physically Disabled People through Integration of IoT and Digital Twin Technologies by Abhishek Kumar, Abdul Khader Jilani Saudagar, Muhammad Badruddin Khan

“…A unique visual response algorithm has been developed to enhance the processing of visual vector data, resulting in a more efficient IoT service development process. …”
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Efficient Dynamic Performance Prediction of Railway Bridges Situated on Small-Radius Reverse Curves by Yumin Song, Bin Hu, Xiaoliang Meng

“…After identifying essential design parameters as data features using Fisher scores, we proceed to input these features into a support vector machine (SVM). Through supervised training with dynamic performance labels, this process empowers the SVM model to predict the dynamic performance of the bridge. …”
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Investigation of brain response to acquisition and learning the second languages based on EEG signals and machine learning techniques by Talal A. Aldhaheri, Sonali B. Kulkarni, Pratibha R. Bhise, Baraq Ghaleb

“…The data was pre-processed, cleaned, and analyzed to extract language learning-related features. …”
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An automatic approach to detect skin cancer utilizing active infrared thermography by Ricardo F. Soto, Sebastián E. Godoy

“…These features were implemented in a support-vector machine classifier to detect malignancy. Notably, our method addresses a common limitation in existing approaches—manual lesion selection—by automating the process using a U-Net convolutional neural network.We validated our system by comparing U-Net's performance with expert dermatologist segmentations, achieving a 17% improvement in the Jaccard index over a semi-automatic algorithm. …”
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