A long tail of truth and beauty: A zigzag pattern of feather formation determines the symmetry, complexity, and beauty of the peacock’s tail [version 2; peer review: 1 approved, 2... by Santosh Jagadeeshan, Rama Singh

“…Background Darwin assumed that the peacock’s long train was maladaptive and was the indirect effect of selection by female mate choice based on the train’s beauty. …”
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EnviScan+: AI-driven plant identification and eco-system management for sustainable agriculture by Stitini Oumaima, Lachgar Mohamed, Bouleknadel Abderrahmane, Mandour Iyass

“…EnviScan+ is an interactive mobile and web application that facilitates plant recognition and preservation through AI-based image identification and a chatbot-oriented recommendation system. …”
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New concepts of magnetohydrodynamics and entropy rate for radiative nanofluid flow invoking artificial neural network approach by Aqsa Razzaq, T. Hayat, Sohail A. Khan, Aneeta Razaq

“…Subsequently the advanced computational technique (ANNs) based on Levenberg-Marquardt algorithm (LMA) is integrated to train the resulting datasets and facilitate predictions of advanced solutions. …”
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Typology of Results of Cooperation Between Russian Universities and Business by A. V. Melikyan

“…The cluster analysis identified 6 groups of universitates, each of which has specific features. Universities in the first two clusters are focused on commercializing income from R&D. …”
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Recognizing Special Art Pieces Through EEG: A Journey in Neuroaesthetics Classification by Maurizio Palmieri, Marco Avvenuti, Francesco Marcelloni, Alessio Vecchio

“…The first two methods exploit classical machine learning approaches based on various sets of features extracted using different techniques for EEG analysis. …”
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Synthesis and evaluation of seamless, large-scale, multispectral satellite images using Generative Adversarial Networks on land use and land cover and Sentinel-2 data by Torben Dedring, Andreas Rienow

“…Estimates of the spectral characteristics of LULC categories could enrich LULC forecasting models by providing necessary information to delineate vegetation indices or microclimatic parameters. We train two identical Conditional Generative Adversarial Networks (CGAN) to synthesize a multispectral Sentinel-2 image based on different combinations of open-source LULC data sets. …”
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A Method of Trackside Kilometer Post Identification Combined with YOLOv3 Model by QIU Xinhua, WANG Wenkun, JI Yuwen, LI Jia

“…Transfer learning is adopted to obtain possible rectangular region of kilometer post based on the trained network parameters. Then, pattern recognition is used to extract, segment and recognize character region of kilometer scale, and finally output digital information of kilometer scale to the control system. …”
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Academic major as a variable in EFL instructors’ speaking assessment preferences in preparatory programs by Berk İlhan

“…Data were collected via an electronic questionnaire featuring statements on different CEFR-based assessment types. …”
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POSITIVE INTERACTION IN AN INCLUSIVE EDUCATION: MANIFESTATION OF THE INTERNATIONAL CHILD DEVELOPMENT PROGRAMME (ICDP) by Farid Alamdar oglu Suleymanov

“…From this perspective International Child Development Programme (ICDP) functions as a resource-based communication and mediation approach which trains caregiver to develop a positive conception of their children and gain wider and deeper insight and confidence about their responsibilities and roles. …”
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An action decoding framework combined with deep neural network for predicting the semantics of human actions in videos from evoked brain activities by Yuanyuan Zhang, Manli Tian, Baolin Liu

“…However, it remains unclear whether it is possible to establish relationships between brain activities and semantic features of human actions in video stimuli. Here we construct a framework for decoding action semantics by establishing relationships between brain activities and semantic features of human actions.MethodsTo effectively use a small amount of available brain activity data, our proposed method employs a pre-trained image action recognition network model based on an expanding three-dimensional (X3D) deep neural network framework (DNN). …”
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Spatiotemporal Flood Hazard Classification in Bangkok Using Graph Convolutional Network and Temporal Fusion Transformer by Pakpoom Chaimook, Nirattaya Khamsemanan, Cholwich Nattee, Alice Sharp

“…The GCN component learns spatial dependencies from a graph constructed based on district relations, while the TFT learns temporal sequences based on spatiotemporal inputs. …”
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Construction of a novel online calculator for prediction of osteoporosis risk in Chinese type 2 diabetes patients by Xing Yu, Wenchi Liu, Xiaojun Chen, Yicheng Wang, Huibin Tang, Yunyun Su, Liangdi Xie, Li Luo

“…All patients were randomly divided into a training set (70 %) and a test set (30 %). Then, univariate and multivariate logistic regression analyses were used to screen independent risk factors for osteoporosis. …”
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Long-Range LiDAR Vehicle Detection Through Clustering and Classification for Autonomous Racing by Na-Young Lim, Tae-Hyoung Park

“…Additionally, a machine learning classifier trained on long-range vehicle features is incorporated to enhance detection accuracy at extended distances. …”
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Supervised optimal control in complex continuous systems with trajectory imitation and reinforcement learning by Yingjun Liu, Fuchun Liu, Renwei Huang

“…Firstly, behavior cloning (BC) is adopted to pre-train the policy model based on a small number of human demonstrations. …”
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Enhancing Detection of Control State for High-Speed Asynchronous SSVEP-BCIs Using Frequency-Specific Framework by Yufeng Ke, Jiale Du, Shuang Liu, Dong Ming

“…For an input EEG epoch, the FS framework first identified its potential SSVEP frequency using the TRCA-based method and then recognized its control state using one of the classifiers trained on the features specifically related to the identified frequency. …”
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Accurate segmentation of localized corrosion in structural alloys via deep learning by Liang Zhao, Jenifer Locke, Fei Xu, Tiankai Yao, Xiaolei Guo

“…The newly constructed dataset, alongside data from two public databases, are employed to jointly train a deep learning-based model modified with a texture refinement module. …”
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An open-source tool for analysis and automatic identification of dendritic spines using machine learning. by Michael S Smirnov, Tavita R Garrett, Ryohei Yasuda

“…Custom thresholding and binarization functions serve to "clean" fluorescent images, and a neural network is trained using features based on the relative shape of the spine perimeter and its corresponding dendritic backbone. …”
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CRGAN: A Context-Aware Clothing Design and Recommendation System for Young Sri Lankan Females Using Generative Adversarial Networks by Nethmi Pathirana, Azma Imtiaz, Shakir Saheel, Kasun Karunanayaka, Adrian David Cheok

“…This shift is driven by the desire for personalized clothing recommendations, especially among young females, who seek tailored suggestions based on their preferences, climate, and style. While traditional recommendation systems rely on existing databases to suggest predefined outfit options, this research takes a novel approach by integrating generative modeling techniques to create unique outfit designs based on contextual factors. …”
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Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks. by Petros-Pavlos Ypsilantis, Musib Siddique, Hyon-Mok Sohn, Andrew Davies, Gary Cook, Vicky Goh, Giovanni Montana

“…We report on a study that compares the performance of two competing radiomics strategies: an approach based on state-of-the-art statistical classifiers using over 100 quantitative imaging descriptors, including texture features as well as standardized uptake values, and a convolutional neural network, 3S-CNN, trained directly from PET scans by taking sets of adjacent intra-tumor slices. …”
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Distinguishing benign and malignant myxoid soft tissue tumors: Performance of radiomics vs. radiologists. by Joshua M Lawrenz, Can Cui, Samuel R Johnson, Katherine S Hajdu, Stephen W Chenard, Akhil Rekulapelli, Cullen P Moran, John J Block, Nicholson S Chadwick, Joanna L Shechtel, Brian Bingham, Leo Y Luo, Jennifer L Halpern, Herbert S Schwartz, Ginger E Holt, David S Smith, Benoit Dawant, Hakmook Kang

“…<h4>Introduction</h4>Benign and malignant myxoid soft tissue tumors have shared clinical, imaging, and histologic features that can make diagnosis challenging. The purpose of this study is comparison of the diagnostic performance of a radiomic based machine learning (ML) model to musculoskeletal radiologists.…”
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