Supporting Young Children’s Self-Regulation Through Nature-Based Practices in Preschool by Julie Ernst, Hannah Stelley

Get full text

Fuzzy Adaptive Switching Control for an Uncertain Robot Manipulators with Time-Varying Output Constraint by Yongqing Fan, Wenqing Wang, Ying Liu, Minjuan Wang

“…The novel design method is used to reduce greatly the online learning computation burden compared with traditional fuzzy adaptive control. …”
Get full text

Differential Proteomic Analysis of the Hippocampus in Rats with Neuropathic Pain to Investigate the Use of Electroacupuncture in Relieving Mechanical Allodynia and Cognitive Declin... by Degui Gong, Xiangmei Yu, Menghong Jiang, Changzheng Li, Zhifu Wang

“…Abnormal changes in hippocampal function and neuroplasticity are involved in neuropathic pain, which induces hyperalgesia and learning and memory deficits. …”
Get full text

Elsinta radio’s social message to build the value of communication wisdom and citizens cultural identity by Eko Digdoyo, Mukhlish Muhammad Maududi

“…This study was to analyze the existence of radio as a type of electronic media that has a role and function as a medium of information, education, and entertainment for the community. …”
Get full text

A Hybrid Particle Swarm Optimizer for Curriculum Sequencing Problem by Xianjie Peng, Xiaonan Sun, Zhen He

“…Curriculum sequencing problem is crucial to e-learning system, which is a NP-hard optimization problem and commonly solved by swarm intelligence. …”
Get full text

Recognition Algorithm of AE Signal of Rock Fracture Based on Multiscale 1DCNN-BLSTM by Weihua Wang

“…This article constructs a deep learning algorithm model to identify acoustic emission signals released from rock fractures with different brittle mineral contents. …”
Get full text

Analysis of digital intelligent financial audit system based on improved BiLSTM neural network by Zhu Xincai

“…With the continuous advancement of deep learning and digital technology, new audit methods have been provided for computer auditing. …”
Get full text

Research and development of thick plate shape prediction system based on industrial big data by Yufei MA, Changxin LIU, Wei KONG, Jinliang DING

“…Thick plate shape is one of the important indicators to measure the quality of thick plate products.The timely prediction of the final plate shape in production is of great significance for adjusting the operation and control of thick plate production.In actual industrial production, thick plate data has many characteristics, such as multiple coupling information, large amount of redundant information, and multi-source heterogeneity of data.Combining the needs of thick plate shape prediction, a thick plate shape prediction system was designed and developed.The data dump function was used to filter and preprocess the industrial big data to remove the coupling information and redundant variables in the data.LSTM neural network, convolutional neural network and 3D convolutional neural network were used to extract data features from data of different dimensions, and the features were fused based on the maximum mutual information coefficient to establish an integrated learning prediction model, which effectively solved the modeling difficulties caused by multi-source heterogeneous data.The actual industrial data of a domestic thick plate production line was used for verification, and the results showed the effectiveness of the developed system.…”
Get full text

Critical biomarkers for responsive deep brain stimulation and responsive focal cortex stimulation in epilepsy field by Zhikai Yu, Binghao Yang, Penghu Wei, Hang Xu, Yongzhi Shan, Xiaotong Fan, Huaqiang Zhang, Changming Wang, Jingjing Wang, Shan Yu, Guoguang Zhao

“…The set of DFA exponents is employed as an intermediary variable in the machine learning process. The resultant model possesses the capability to function as a feedback trigger program for electrical stimulation systems of the feedback variety, specifically within the domain of neural modulation in epilepsy.…”
Get full text

Gravitational-wave Parameter Estimation in Non-Gaussian Noise Using Score-based Likelihood Characterization by Ronan Legin, Maximiliano Isi, Kaze W. K. Wong, Yashar Hezaveh, Laurence Perreault-Levasseur

“…Assuming only noise additivity, we employ score-based diffusion models to learn an empirical noise distribution directly from detector data and then combine it with a deterministic waveform model to provide an unbiased estimate of the likelihood function. …”
Get full text

Parental kynurenine 3-monooxygenase genotype in mice directs sex-specific behavioral outcomes in offspring by Snezana Milosavljevic, Maria V. Piroli, Emma J. Sandago, Gerardo G. Piroli, Holland H. Smith, Sarah Beggiato, Norma Frizzell, Ana Pocivavsek

“…WT-Kmo +/+ males had deficits in reversal learning but no sleep disturbances or anxiety-like behaviors. …”
Get full text

Relationship between retinol metabolism and hepatocellular carcinoma: a comprehensive analysis of Mendelian randomization, prognostic characteristic and experiment by Fuqing Chen, Yifan Cai, Jianyin Zhou

“…Methods We used transcriptomic data related to HCC in TCGA and GEO databases for a variety of machine learning, including differential gene expression analysis, functional enrichment analysis, protein–protein network interaction, ceRNA regulatory network, and single-cell sequencing analysis. …”
Get full text

Vulnerability-Based Economic Loss Rate Assessment of a Frame Structure Under Stochastic Sequence Ground Motions by Zheng Zhang, Yunmu Jiang, Zixin Liu

“…Coherence analysis shows that the function remains relatively stable between 0.3 and 0.6 across the 0–30 Rad/s frequency range. …”
Get full text

Neuron Network Modeling of Intensification of Isogumulone Extraction in a Rotary Pulse Generator by Anton V. Shafrai, Elena A. Safonova, Dmitry M. Borodulin, Yana S. Golovacheva, Sergey A. Ratnikov, Wasfie Barsoom Wasef Kerlos

“…The resulting model had the following parameters: two hidden layers, 30 neurons each; neuron activation function – GELU; loss function – MSELoss; learning step – 0.001; optimizer – Adam; L2 regularization at 0.00001; training set of four batches, 16 records each; 9,801 epochs. …”
Get full text

Treatment-Associated Neuroplastic Changes in People with Stroke-Associated Ataxia—An fMRI Study by Patricia Meier, Christian Siedentopf, Lukas Mayer-Suess, Michael Knoflach, Stefan Kiechl, Gudrun Sylvest Schönherr, Astrid E. Grams, Elke R. Gizewski, Claudia Lamina, Malik Galijasevic, Ruth Steiger

“…Coordination exercises, constituting a specific treatment of ataxic symptoms, indicate more consolidated brain activations, corresponding to a faster motor learning process. Activation within Brodmann Area 7 has been prominent among all paradigms, indicating a special importance of this region for coordinative functions. …”
Get full text

Infrared Aircraft Detection Algorithm Based on High-Resolution Feature-Enhanced Semantic Segmentation Network by Gang Liu, Jiangtao Xi, Chao Ma, Huixiang Chen

“…Finally, a dice loss function is introduced to calculate the overlap between the predicted results and the ground truth labels, facilitating deep excavation of foreground information for comprehensive learning of samples. …”
Get full text

Toward Model-Independent Separative Training for Deep Hyperspectral Anomaly Detection With Mask Guidance by Xi Su, Xiangfei Shen, Haijun Liu, Lihui Chen, Gemine Vivone, Xichuan Zhou

“…Based on this mask, we exploit a separative loss function that reconstructs the background and suppresses the anomalies, thus learning a pure background. …”
Get full text

Bipolar transurethral enucleation and resection of the prostate: Whether it is ready to supersede TURP? by Peng Xu, Abai Xu, Binshen Chen, Shaobo Zheng, Yawen Xu, Hulin Li, Haiyan Shen, Chunxiao Liu

“…An improvement in International Index of Erectile Function (IIEF-5) scores was witnessed in 17 patients preoperatively with normal sexual function during the first 6 months after surgery, and sustained throughout the 24-month period. …”
Get full text

The illness management and recovery program: a contribution to recovery-oriented secondary mental health services by Kristin B. Ørjasæter, Tone Winnem, Kristin Heiervang, Ottar Ness, Kim T. Mueser

Get full text

Optimizing brain tumor detection in MRI scans through InceptionResNetV2 and deep stacked Autoencoders with SwiGLU activation and sparsity regularization by Vishal Awasthi, Mamta Tiwari, Amit Yadav, Gesu Thakur, Mamata Mayee Panda, Hemant Kumar, Shivneet Tripathi

“…Future studies should address these limitations by enhancing interpretability, exploring domain-specific transfer learning, and validating on diverse datasets to strengthen the model's utility in real-world settings. …”
Get full text