Neuro-Mimetic Developmental Architecture for Continual Learning Through Self-Organizing Multimodal Perception Coordination by Farhan Dawood, Naoki Masuyama, Chu Kiong Loo

“…This study presents a novel brain-inspired hierarchical autonomous framework, Cognitive Deep Self-Organizing Neural Network (CDSN), designed to enable autonomous agents to acquire object concepts dynamically. …”
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Exposure to hate in online and traditional media: A systematic review and meta‐analysis of the impact of this exposure on individuals and communities by Pablo Madriaza, Ghayda Hassan, Sébastien Brouillette‐Alarie, Aoudou Njingouo Mounchingam, Loïc Durocher‐Corfa, Eugene Borokhovski, David Pickup, Sabrina Paillé

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Exploring the antimicrobial potential of the articaine derivative in oral infections by Yongzhen Tan, Yihang Hao, Yihang Fu, Shilong Hu, Xi Yang, Yaling Tang, Bowen Ke, Xinhua Liang

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Host associations and genetic diversity of bat flies (Diptera: Nycteribiidae and Streblidae) in bats from Thailand by Dimas Novianto, Siwaporn Tuangpermsub, Thongchai Ngamprasertwong, Morakot Kaewthamasorn

“…Phylogenetic relationships were inferred using Maximum Likelihood methods, while genetic variation was assessed through TCS haplotype network analysis. Tripartite network analysis was employed to examine site-host-parasite associations. …”
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Hybrid LSTM–Transformer Architecture with Multi-Scale Feature Fusion for High-Accuracy Gold Futures Price Forecasting by Yali Zhao, Yingying Guo, Xuecheng Wang

“…Amidst global economic fluctuations and escalating geopolitical risks, gold futures, as a pivotal safe-haven asset, demonstrate price dynamics that directly impact investor decision-making and risk mitigation effectiveness. …”
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Tailored knowledge distillation with automated loss function learning. by Sheng Ran, Tao Huang, Wuyue Yang

“…Building upon our proposed generic loss networks for logits and intermediate features, we derive a dynamic optimization strategy to adjust losses based on the student models' changing states for enhanced performance and adaptability. …”
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Harnessing Transfer Learning for Rapid Malware Family Classification in Large-Scale Cyber Datasets by Mohan Rishabh, Gupta Himanshu

“…By utilizing pre-trained architectures such as Convolutional Neural Networks (CNNs) and Transformers, we exploit their ability to learn transferable features, minimizing the need for domain-specific knowledge. …”
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Synchronizability of Discrete Nonlinear Systems: A Master Stability Function Approach by Mohanasubha Ramasamy, Suresh Kumarasamy, Sakthi Kumar Sampathkumar, Anitha Karthikeyan, Karthikeyan Rajagopal

“…These findings greatly enhance our understanding of network dynamics, as discrete-time dynamical systems adeptly replicate the dynamics of continuous-time models, offering significant reductions in computational complexity.…”
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Form, Formats, and Forms of Informed Consent by Rune Larsen, Amanda Moller Rasmussen

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Recognition of chlorophyll rings using YOLOv8 by Guangjun Xu, Zhixia Lin, Yucheng Shi, Jialun Wu, Huabing Xu, Guancheng Wang, Tianyu Zhang

“…With the rapid advancement of deep learning technologies, the application of neural networks in ocean science has become increasingly prevalent. …”
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TSNetIQ: High-Resolution DOA Estimation of UAVs Using Microphone Arrays by Kequan Zhu, Tian Jin, Shitong Xie, Zixuan Liu, Jinlong Sun

“…The proposed TSNetIQ combines elaborately designed Transformer and convolutional neural networks (CNN) modules, and the raw in-phase (I) and quadrature (Q) components of the audio signals are used as input data. …”
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Quantifying the impact of external and internal factors and their interactions on thermal load behaviour of a building by Christoph Matschi, Isabell Nemeth

“…For this purpose, a parameter study is conducted using dynamic thermal building simulation software. …”
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Extending the forecasting horizon of daily new COVID-19 cases using non-pharmaceutical measures and the effective reproduction number (Rt): A deep learning-based framework by Tuga Mauritsius

“…Utilizing advanced Deep Learning (DL) methodologies, including Deep Feedforward Neural Networks (DFNN), Long Short-Term Memory (LSTM), one-dimensional convolutional neural networks (CONV1D), and Gated Recurrent Units (GRU), this research endeavors to predict daily confirmed Covid-19 cases in Indonesia. …”
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From accounting to accountability: social and relational accountability among civic humanitarian actors in Uganda by Emmanuel Viga, Hilde Refstie

“…Drawing on ethnographic fieldwork conducted between 2020 and 2023, it explores accountability as it emerges in diaspora networks, community leadership, familial and neighborly assistance, and communal practices. …”
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Drone Attitude and Position Prediction via Stacked Hybrid Deep Learning Model for Massive MIMO Applications by Abdullah Al-Ahmadi

“…This approach addresses limitations in traditional control methods, which struggle to maintain stability under noisy, dynamic environments. Extensive experiments were conducted to assess the model’s accuracy and robustness across diverse flight scenarios. …”
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RIS-based indoor wireless communication signal enhancement system by Kui TANG, Qi HU, Junming ZHAO, Ke CHEN, Yijun FENG

“…By utilizing the tunable performances of the reconfigurable intelligent surface (RIS) to manipulate the reflected electromagnetic waves, an indoor wireless communication signal enhancement system was constructed, which could improve the signal quality of the receiving terminal in where the initial wireless signals were weak.First, a RIS unit cell with dynamically tunable phase characteristics was designed, and the dynamic change of the 2 bit reflection phases was realized by switching the working states of the two active diodes.Then, experiments were conducted to verify that the proposed RIS could dynamically reshape the beam direction.Finally, a host computer and field programmable gate array (FPGA) were used to realize the intelligent control of the coding sequences applied onto the proposed RIS.By changing the spatial phase distribution on the RIS aperture, the output beam could be controlled in real-time.By traversing the pre-loaded coding sequences, the enhancement of received signal in indoor wireless environments had been experimentally demonstrated.Both simulation and experiment results verify that the proposed RIS system can effectively and dynamically improve the quality of the indoor wireless signals.The received signal is increased by an average of 8.9 dB, with a maximum of 22 dB.The proposed work may provide basic hardware technical support for the optimization of 5G and the next-generation communication networks.…”
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Supervised Semantic Segmentation of Urban Area Using SAR by Joanna Pluto-Kossakowska, Sandhi Wangiyana

“…Cyclical analyses of dynamic changes in urban areas are critical and necessary for policymakers and societies. …”
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Revolutionizing treatment for disorders of consciousness: a multidisciplinary review of advancements in deep brain stimulation by Yi Yang, Tian-Qing Cao, Sheng-Hong He, Lu-Chen Wang, Qi-Heng He, Ling-Zhong Fan, Yong-Zhi Huang, Hao-Ran Zhang, Yong Wang, Yuan-Yuan Dang, Nan Wang, Xiao-Ke Chai, Dong Wang, Qiu-Hua Jiang, Xiao-Li Li, Chen Liu, Shou-Yan Wang

“…Advances in computational models have also facilitated a deeper exploration of the neural dynamics associated with DOC, linking neuron-level dynamics with macroscopic behavioral changes. …”
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Understanding the Complexity of Business Information Dissemination in Social Media: A Meta-Analysis of Empirical Evidence from China by Jiawen Yan, Yuantao You, Yu Wang, Dongfang Sheng

“…With the development of social networks, the complexity of the factors affecting the users’ information dissemination is increasing and the complexity of online social networks and influencing factors of individual behaviors and attitudes make the development of online public opinion present a dynamic, complex, and multifactor evolution. …”
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Repetitive magnetic stimulation with iTBS600 induces persistent structural and functional plasticity in mouse organotypic slice cultures by Han Lu, Shreyash Garg, Maximilian Lenz, Andreas Vlachos

“…Despite the widespread electric field generated by rTMS, its effects were spatially and temporally precise, driving Hebbian plasticity and region-specific spine dynamics. Conclusions:: These findings provide mechanistic insights into how rTMS-induced LTP promotes targeted plasticity while preserving network stability. …”
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