Leveraging large language models for automated detection of velopharyngeal dysfunction in patients with cleft palate by Myranda Uselton Shirk, Catherine Dang, Jaewoo Cho, Hanlin Chen, Lily Hofstetter, Jack Bijur, Claiborne Lucas, Andrew James, Ricardo-Torres Guzman, Andrea Hiller, Noah Alter, Amy Stone, Maria Powell, Matthew E. Pontell, Matthew E. Pontell

“…BackgroundHypernasality, a hallmark of velopharyngeal insufficiency (VPI), is a speech disorder with significant psychosocial and functional implications. Conventional diagnostic methods rely heavily on specialized expertise and equipment, posing challenges in resource-limited settings. …”
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Physics-Informed Neural Networks in Aerospace: A Structured Taxonomy with Literature Review by Yurii Tkachov, Oleh Murashko

“…The methodology involves grouping tasks into four distinct tiers—Physical Modeling, Dynamic Analysis, Functional Assessment, and System-Level Assessment—based on their physical, operational, and systemic characteristics. …”
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Task-Driven Real-World Super-Resolution of Document Scans by Maciej Zyrek, Tomasz Tarasiewicz, Jakub Sadel, Aleksandra Krzywon, Michal Kawulok

“…In this study, we introduce a task-driven, multi-task learning framework for training a super-resolution network specifically optimized for optical character recognition tasks. …”
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Technology for the development and use of electronic educational resources in the educational process of a university by M. V. Makhmutova, E. I. Senicheva, O. A. Akimova

“…The study was conducted in accordance with the pedagogical conditions of student learning and the methodological requirements for the educational product. …”
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TopoRSNet: A Unique Approach to Maintaining Topological Features for Digital Rock Image Rescaling With Minimal Quality Degradation by Kunning Tang, Yufu Niu, Ying DaWang, Vanessa Robins, Peyman Mostaghimi, Mark Lindsay, Ryan T. Armstrong

“…Feature preservation is ensured by introducing three feature‐based loss functions: adversarial loss, a new feature consistency loss, and a novel persistent homology loss (PH loss). …”
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Concept «EDUCATION» and its Subconcepts in the Consciousness of Ukrainian managers by Наталія Михальчук, Наталія Харченко, Георгій Калмиков, Ернест Івашкевич, Едуард Івашкевич, Наталія Хупавцева, Інна Мисан

“…The first synonym series with a dominant subconcept “The process of teaching and training people” of the concept EDUCATION is characterized by seven synonyms: teaching; learning; instruction; schooling; tuition. Learning is a dominant. …”
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A Hybrid Method Combining Variational Mode Decomposition and Deep Neural Networks for Predicting PM2.5 Concentration in China by Senlin Li, Bo Tang, Xiaowu Deng

“…The VMD algorithm, which can decompose signals adaptively and possesses a certain level of robustness to noise and interference, decomposes complex time series into intrinsic mode functions (IMFs), which are then used as inputs for training a deep neural network prediction model. …”
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Simultaneous Mental Fatigue and Mental Workload Assessment With Wearable High-Density Diffuse Optical Tomography by Jianan Chen, Huixin Yang, Yunjia Xia, Tingchen Gong, Alexander Thomas, Jia Liu, Wei Chen, Tom Carlson, Hubin Zhao

“…To address this, high-density diffuse optical tomography (HD-DOT), an emerging form of functional near-infrared spectroscopy (fNIRS) was employed in this study, which provides higher spatial resolution for hemodynamic measurements and enables the reconstruction of 3D brain images. …”
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High-throughput sequencing metabarcoding and network analysis elucidate the effects of soil fumigation and biostimulant on potato yield, rhizoctonia canker, and fungal community by Honoré Tekeu, Honoré Tekeu, Honoré Tekeu, Joël D’Astous-Pagé, Thomas Jeanne, Richard Hogue

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Integration of Microarray Data and Single-Cell Sequencing Analysis to Explore Key Genes Associated with Macrophage Infiltration in Heart Failure by Rao J, Wang X, Wang Z

“…Additionally, we employed four integrated machine learning algorithms to identify macrophage-related genes with diagnostic value, and in vivo validation was performed. …”
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Performance exploration of multi-gene panels of alopecia areata susceptibility and drug-binding targets by Hongye Liu, Yang Li, Ling Ren, Xiaofeng Yang, Shuo Zhang, Hongmei Bi, Hongxia He, Jingyu Ren, Xiaoqing Lang, Shuping Guo

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Multi-omics identification of a polyamine metabolism related signature for hepatocellular carcinoma and revealing tumor microenvironment characteristics by Yuexi Yu, Huiru Liu, Kaipeng Liu, Meiqi Zhao, Yiyan Zhang, Runci Jiang, Fengmei Wang

“…Further analysis revealed significant differences in clinical features, biological functions, mutation profiles, and immune cell infiltration between high-risk and low-risk groups. …”
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Harnessing single-cell and multi-omics insights: STING pathway-based predictive signature for immunotherapy response in lung adenocarcinoma by Yang Ding, Dingli Wang, Dali Yan, Jun Fan, Zongli Ding, Lei Xue

“…We developed a STING pathway-related signature (STINGsig) using 101 machine learning frameworks. The functional significance of ERRFI1, a key component of STINGsig, was validated through mouse models and multicolor flow cytometry, particularly examining its role in enhancing antitumor immunity and potential synergy with α-PD1 therapy.ResultsOur single-cell analysis identified and characterized 15 distinct cell populations, including epithelial cells, macrophages, fibroblasts, T cells, B cells, and endothelial cells, each with unique marker gene profiles. …”
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Remotely Sensed Variables Predict Grassland Diversity Better at Scales Below 1,000 km as Opposed to Abiotic Variables That Predict It Better at Larger Scales by Yujin Zhao, Bernhard Schmid, Zhaoju Zheng, Yang Wang, Jin Wu, Yao Wang, Ziyan Chen, Xia Zhao, Dan Zhao, Yuan Zeng, Yongfei Bai

“…Here we used vegetation survey data from 1,609 field sites (>4,000 plots of 1 m2), remotely sensed data (ecosystem productivity and phenology, habitat heterogeneity, functional traits and spectral diversity), and abiotic data (water‐ and energy‐related, characterizing climate‐dominated environment) together with machine learning and spatial autoregressive models to predict and map grassland species richness per 100 m2 across the Mongolian Plateau at 500 m resolution. …”
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Research on bearing fault diagnosis of reciprocating compressors based on GMDE and MFO-MKELM algorithms by LI Yanyang, WANG Jindong, NING Liuyang, MA Lei

“…A generalized multiscale entropy algorithm spread, application of the reciprocating compressor vibration signals of bearing clearance for fault feature extraction was proposed; then, the polynomial kernel function and the improved Gaussian kernel function were linearly combined to construct the multiple kernel extreme learning machine intelligent recognition algorithm, and the fault diagnosis research was carried out on the extracted feature vector set.ResultsSimulation results show that the recognition accuracy of the fault diagnosis method is as high as 98.6%, which effectively realizes the intelligent diagnosis of different types of bearing faults.…”
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DHS-CNN: A Defect-Adaptive Hierarchical Structure CNN Model for Detecting Anomalies in Contact Lenses by Sung-Hoon Kim, Seong-Jong Joo, Kwan-Hee Yoo

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Dual-Branch Diffusion Detection Model for Photovoltaic Array and Hotspot Defect Detection in Infrared Images by Ruide Li, Wenjun Yan, Chaoqun Xia

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A resource allocation algorithm based on improved salp swarm algorithm in cognitive smart grid by SHEN Hongting

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Application of Support Vector Machines in High Power Device Technology by RAO Wei, LI Yong, YAN Ji

“…As a machine learning algorithm, support vector machine(SVM) has the advantages of good nonlinear processing ability, theoretical global optimum and overcoming the curse of dimensionality. …”
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Novel algorithm for multifocus image fusion: integration of convolutional neural network and partial differential equation by Gargi J Trivedi, Rajesh Sanghvi

“…Furthermore, we aim to enhance our approach by incorporating machine learning techniques to optimize the parameters of the image fusion algorithm. …”
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