High-throughput behavioral screening in Caenorhabditis elegans using machine learning for drug repurposing by Antonio García-Garví, Antonio-José Sánchez-Salmerón

“…However, these methods present certain limitations in detecting subtle and non-linear patterns. In this study, we propose a high-throughput screening method based on machine learning, using classifiers that provide a recovery percentage as a measure of treatment effect. …”
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The Evolution of the Idiolect over the Lifetime: A Quantitative and Qualitative Study of French 19th Century Literature by Olga Seminck, Philippe Gambette, Dominique Legallois, Thierry Poibeau

“…Using the Corpus for Idiolectal Research (CIDRE) that contains the dated works of 11 prolific 19th century French fiction writers, we propose new methods to identify, quantify and describe the grammatical-stylistic changes that take place using lexico-morphosyntactic patterns, also called motifs. To examine the strength of the chronological signal of change, we developed a method to calculate if a distance matrix of literary works contains a stronger chronological signal than expected by chance. …”
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Classification Modeling Method for Near-Infrared Spectroscopy of Tobacco Based on Multimodal Convolution Neural Networks by Lei Zhang, Xiangqian Ding, Ruichun Hou

“…In order to improve the accuracy of the tobacco origin classification, a near-infrared spectrum (NIRS) identification method based on multimodal convolutional neural networks (CNN) was proposed, taking advantage of the strong feature extraction ability of the CNN. Firstly, the one-dimensional convolutional neural network (1-D CNN) is used to extract and combine the pattern features of one-dimensional NIRS data, and then the extracted features are used for classification. …”
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GATOR1 gene variants in focal epilepsy by Kovačević Maša, Vojvodić Nikola, Novaković Ivana

“…Variants in GATOR1 genes have been detected in multiplex families with rare familial focal epilepsy syndromes where they demonstrate an autosomal dominant inheritance pattern with reduced penetrance. More recently, they have also been defined as major contributors in common nonacquired focal epilepsy in which they are detected in 3% of familial and 0.2% of sporadic cases and are particularly common in familial epilepsy associated with FCD where up to 11% of affected subjects carry gene variants. …”
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Advanced smart assistance with enhancing social interaction and daily activities for visually impaired individuals using deep learning with modified seagull optimization by Sana Alazwari, Hussah Nasser AlEisa, Mohammed Rizwanullah, Radwa Marzouk

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Patient-derived organoids as a model to study tubo-ovarian carcinoma: a pathologist’s perspective by Catarina Alves-Vale, Beatriz Galvão, Ana Rita Silvestre, José Silva Pereira, Li Bei, João Paulo Fernandes, Paula Borralho, Maria Carmo-Fonseca, Noélia Custódio

“…HGSC organoids exhibited limited growth and mostly irregular structures, while preserving the p53 immunostaining pattern of the original tumour. SBT/LGSC and FT organoids maintained features of architectural complexity and faithfully recapitulated the original immunoprofile. …”
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A multi-modal dataset of electroencephalography and functional near-infrared spectroscopy recordings for motor imagery of multi-types of joints from unilateral upper limb by Weibo Yi, Jiaming Chen, Dan Wang, Xinkang Hu, Meng Xu, Fangda Li, Shuhan Wu, Jin Qian

“…The validity of multi-modal data was verified both from the EEG/fNIRS activation patterns and the classification performance. It is expected that this dataset will facilitate the development and innovation of decoding algorithms for MI of multi-types of joints based on multi-modal EEG-fNIRS data.…”
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A Stepwise decision tree model for differential diagnosis of Kimura’s disease in the head and neck by Rui Luo, Gongxin Yang, Huimin Shi, Yining He, Yongshun Han, Zhen Tian, Yingwei Wu

“…Demographic and magnetic resonance imaging (MRI) data were collected, with qualitative features (e.g., skin thickening, lesion morphology, lymphadenopathy, MRI signal intensity) and quantitative variables (e.g., age, lesion size, apparent diffusion coefficients (ADCs), wash-in rate, time to peak (TTP), time-signal intensity curve (TIC) patterns) examined. …”
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Fault diagnosis and inference of hoist main bearing based on transfer learning and ontology by Fei DONG, Di ZHANG, Kunpeng GE, Junjie CHEN, Xinyue XU

“…Firstly, the collected bearing vibration signals are processed, and it uses continuous wavelet transform to decompose the original vibration signals and extract two-dimensional time-frequency images; secondly, to adaptively extract deep features from both the source and target domains, the pre-trained and fine-tuning approaches are employed for convolutional neural networks transfer learning, and it constructs a transfer convolutional neural network model to achieve adaptive extraction of deep features from both domains; then, a new supervised domain adaptation method is proposed, integrating dynamic joint distribution adaptation with enhanced separability, to further reduce the distribution differences between deep feature sets of the source and target domains while effectively enhancing the separability of feature data; finally, a patterns recognition classifier is trained based on the source domain features after domain adaptation, which achieves fault patterns recognition in the target domain. ② Hoist main bearing fault knowledge reasoning based on ontology. …”
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Modeling the partial equilibrium in the milk and dairy market in Ukraine by S. Kvasha, N. Davydenko, A. Ivanko, Z. Titenko

“…Specifics of establishing the state of partial equilibrium in that market were characterized relative to the main groups of its participants as producers and consumers. Development of methodological and practical aspects of features of establishing the state of market equilibrium in the dairy market, unlike existing, is based on a model basis is still actual. …”
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Impact of Coenzyme Q10 on Mitochondrial Metabolism: A Complementary Study Using Fluorescence Lifetime Imaging and Electron Microscopy by Johannes Georg Wieland, Nilanjon Naskar, Kirsten Reess, Daniela Nobre Sarmento dos Santos, Julia M. Weise, Thomas Blatt, Sebastian Kordes, Paul Walther, Angelika Rück

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A Novel Technique for Facial Recognition Based on the GSO-CNN Deep Learning Algorithm by Rana H. Al-Abboodi, Ayad A. Al-Ani

“…Face recognition is one of the important elements that can be used for securing the facilities, emotion recognition, sentiment exploration, fraud analysis, and traffic pattern analysis. Intelligent face recognition has yielded excellent accuracy in a controlled environment whereas vice versa in an uncontrolled environment. …”
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Graph-informed convolutional autoencoder to classify brain responses during sleep by Sahar Zakeri, Somayeh Makouei, Sebelan Danishvar

“…The accuracy of the SlS-GICA classifier is 99.92% on the significant feature set. This achievement could be considered in real-time and automatic applications to develop new therapeutic strategies for sleep-related disorders.…”
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Data quality and uncertainty issues in flood prediction: a systematic review by Jinhui Yu, Yichen Li, Xiao Huang, Xinyue Ye

“…These datasets often suffer from issues such as incompleteness, inconsistency, and accuracy deficits, further complicated by uncertainties arising from complex spatial features and environmental changes. The literature proposes a range of solutions, including the development of innovative methodologies, model construction, and comparative analysis, to address these challenges. …”
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Technical innovations and their representations in post-modern arts (Op art as a model) by Hussein Jabbar Mohammad

“…All aspects of science, including human approaches, are affected by technological development. This prompted the artist to search for what art is and its new patterns, which depend on the link between the elements of space, light and movement in order to create the new kinetic beauty that evokes sensations at the same time.          …”
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Resilience of the transit-oriented built environment against COVID-19 transmission: Evidence from major urban communities in Wuhan city by Yangguang Xiao, Hsi-Chuan Wang, Kojiro Sho

“…This study investigates how features of the built environment within transit-oriented development-guided (TOD-guided) communities influenced COVID-19 transmission patterns in Wuhan. …”
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A novel flexible near-infrared endoscopic device that enables real-time artificial intelligence fluorescence tissue characterization. by Gareth Gallagher, Ra'ed Malallah, Jonathan P Epperlein, Jeffrey Dalli, Niall Hardy, Abhinav Jindal, Pol G MacAonghusa, Ronan A Cahill

“…Here, to close this technical gap, we present our development of a colonoscope-compatible flexible imaging probe for NIR-ICG visualization combined with a full field of view machine learning (ML) algorithm for fluorescence quantification and perfusion pattern cross-correlation (including first in human testing). …”
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Sedimentary Model of Sublacustrine Fans in the Shahejie Formation, Nanpu Sag by Zhen Wang, Zhihui Ma, Lingjian Meng, Rongchao Yang, Hongqi Yuan, Xuntao Yu, Chunbo He, Haiguang Wu

“…Inverse fault-step architectures formed by underlying faults control sandbody distribution patterns, restricting primary deposition locations for sublacustrine fan development. …”
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Video-Assisted Thoracoscopic Lung Biopsy as a Possible Cause of Acute Interstitial Pneumonia in a Patient with Nonspecific Interstitial Pneumonia by D Jeffrey Moore, Colm P McParland, Martin J Bullock, Yannick Cartier, Paul Hernandez

“…High-resolution computed tomography showed features of usual interstitial pneumonia, but the lung biopsy obtained by video-assisted thoracoscopy was consistent with a histological pattern of nonspecific interstitial pneumonia. …”
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Profiling antivaccination channels in Telegram: early efforts in detecting misinformation by Aelita Skarzauskiene, Monika Maciuliene, Aiste Dirzyte, Gintare Guleviciute

“…This study addresses the methodological gap in capturing and analysing misinformation on Telegram, with a particular focus on the anti-vaccination community.MethodsThe research was conducted in three phases: (1) a structured review of literature on misinformation dissemination via Telegram, (2) development of a conceptual framework incorporating features of message creators, message content, intended targets and broader social context, and (3) application of this framework to anti-vaccination Telegram channels using latent profile analysis (LPA). …”
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