Robust genetic codes enhance protein evolvability. by Hana Rozhoňová, Carlos Martí-Gómez, David M McCandlish, Joshua L Payne

“…By constructing low-dimensional visualizations of these landscapes, which each comprise more than 16 million mRNA sequences, we show that such alternative codes radically alter the topological features of the network of high-fitness genotypes. …”
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Machine learning-aided hybrid technique for dynamics of rail transit stations classification: a case study by Ahad Amini Pishro, Shiquan Zhang, Alain L’Hostis, Yuetong Liu, Qixiao Hu, Farzad Hejazi, Maryam Shahpasand, Ali Rahman, Abdelbacet Oueslati, Zhengrui Zhang

“…By employing mathematical models, clustering methods, and neural network techniques, the model enhances the precision of station classification, allowing for a refined evaluation of station attributes. …”
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An Interpretable Implicit-Based Approach for Modeling Local Spatial Effects: A Case Study of Global Gross Primary Productivity Estimation by S. Du, H. Huang, K. Shen, Z. Liu, S. Tang

“…While approaches like Geographically Weighted Regression (GWR) capture local variations, they fall short of uncovering global patterns and tracking the continuous evolution of spatial heterogeneity. Motivated by this limitation, we propose a novel perspective—that is, simultaneously modeling common features across different locations alongside spatial differences using deep neural networks. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…A temporal convolutional network processes the extracted action features. This network performs convolution operations on features at different instances, enabling the model to capture changes over time and identify long-term dependencies between action features. …”
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Morphometric and Morphotectonic characteristics of Sürgü and Çardak Faults (East Anatolian Fault Zone) by Musa Balkaya, Hüsnü Serdar Akyüz, Suha Ozden

“…Implemented morphotectonic investiga-tions and evaluations indicate that the Sürgü and Çardak faults play a key role in the morphotectonic evolution of the region.…”
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PISCFF-LNet: A Method for Autonomous Flight of UAVs Based on Lightweight Road Extraction by Yuanxu Zhu, Tianze Zhang, Aiying Wu, Gang Shi

“…The network employs a dual-branch encoder architecture to separately extract spatial and contextual features, thus obtaining multi-dimensional feature representations. …”
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An accurate approach to discriminate android colluded malware from single app malware using permissions intelligence by Roger Yiran Mawoh, Joan Beri Ali Wacka, Franklin Tchakounte, Claude Fachkha, Kolyang

“…Extensive experimentation is conducted using five ensemble classifiers: random forest, Extra Trees, AdaBoost, XGBoost, and LightGBM alongside our proposed custom Artificial Neural Network (ANN) and Deep Neural Network (DNN) architectures. …”
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The research on landslide detection in remote sensing images based on improved DeepLabv3+ method by Yong Li

“…Additionally, the model incorporates a dual attention mechanism from the lightweight Convolutional Block Attention Module to more accurately and efficiently detect landslide features. The model underwent dataset creation, training, detection, and accuracy evaluation. …”
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Rough-and-Refine Model for Scene Graph Generation by Li Junliang, Lv Shirong, Li Wei

“…In the Rough Part, image features are initially extracted using convolutional neural networks and a Transformer encoder. …”
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Enhanced SVM-based model for predicting cyberspace vulnerabilities: Analyzing the role of user group dynamics and capital influx. by Yicheng Long

“…By incorporating the dynamics of user behavioral changes and the logic of platform scaling driven by investment, two representative cybersecurity datasets are selected for analysis: the Canadian Institute for Cybersecurity Intrusion Detection System 2017 and the Network-Based Intrusion Detection Evaluation Dataset 2015. …”
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Automatic Recognition of Authors Identity in Persian based on Systemic Functional Grammar by Fatemeh Soltanzadeh, Azadeh Mirzaei, Mohammad Bahrani, Shahram Modarres Khiabani

“…Then, the relative frequency of function words in addition to systemic functional features were calculated in each document. Multilayer perceptron classifier, a type of neural network, was used for learning phase which resulted in a desirable accuracy in evaluation phase. …”
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SEM Deep Learning Multiclass Noise Level Classification With Data Augmentation by Kai Liang Lew, Kok Swee Sim, Shing Chiang Tan

“…Three different SEM datasets are used, namely the NFFA-EUROPE dataset, EPFL CVLab EM dataset, and Biofilms SEM dataset. The proposed network achieved the highest evaluation in accuracy (92.76%), precision (92.77%), recall (92.76%), and F1 score (92.74%), as well as the shortest training time in the NFFA-EUROPE dataset. …”
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Chinese medical named entity recognition based on multimodal information fusion and hybrid attention mechanism. by Zhen Luo, Jingping Che, Fan Ji

“…A Dual-Stream Network architecture is employed to extract multimodal features at both the character and word levels, followed by deep fusion to enhance the model's ability to recognize medical entities. …”
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Text Mining for Consumers’ Sentiment Tendency and Strategies for Promoting Cross-Border E-Commerce Marketing Using Consumers’ Online Review Data by Changting Liu, Tao Chen, Qiang Pu, Ying Jin

“…The research employs Python tools (Jupyter Notebook 7.0.8) to analyze the 14,078 pieces of review text data from the top four best-selling products in a certain product category on a certain cross-border e-commerce platform. By applying social network analysis, constructing LDA (Latent Dirichlet Allocation) topic models, and establishing LSTM (Long Short-Term Memory) sentiment classification models, the topics and sentiment distribution of the review set are obtained, and the evolution trends of topics and sentiments are analyzed according to different periods. …”
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Topology Unveiled: A New Horizon for Economic and Financial Modeling by Yicheng Wei, Junzo Watada, Zijin Wang

“…Given that the introduction of topology to economics is relatively new and presents features of being fragmented and non-systematic, this review aimed to provide scholars with a systematic evolution map to refine the characteristics of topology as a methodology applied in economics and finance, thereby aiding future potential interdisciplinary developments in these fields. …”
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Noise indicators for corona acoustic signal from power lines - estimation in intensified interference conditions by Tadeusz WSZOŁEK

“…Because of the above-mentioned features, in practice the best evaluation method of the negative environmental impact is a continuous signal monitoring. …”
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European Erasmus Programme: Main Stages and Results of Development (1987-2017) by O. N. Bogatyryova, N. V. Leskina

“…The article is devoted to the evolution of the flagship educational programmes of the European Union ERASMUS and its impact on the Europeanization of higher education. …”
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AS-TBR: An Intrusion Detection Model for Smart Grid Advanced Metering Infrastructure by Hao Ma, Yifan Fan, Yiying Zhang

“…Additionally, current approaches exhibit limitations in spatiotemporal feature extraction, failing to effectively capture the complex dependencies within network traffic data. …”
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Bladder lesion detection using EfficientNet and hybrid attention transformer through attention transformation by Poonam Sharma, Bhisham Sharma, Dhirendra Prasad Yadav, Deepti Thakral, Julian L. Webber

“…Our hybrid model contains two blocks of the inceptionV3 to extract spatial features. Furthermore, the global co-relation of the features is achieved using hybrid attention modules incorporated in the ViT encoder. …”
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Accurate disaster entity recognition based on contextual embeddings in self-attentive BiLSTM-CRF. by Noor E Hafsa, Hadeel Mohammed Alzoubi, Atikah Saeed Almutlq

“…These contextual word embedding features, combined with lexicon features, are encoded using a novel contextualized deep Bi-directional LSTM network augmented with self-attention and conditional random field (CRF) layers. …”
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