Theoretical analysis of low power optogenetic control of synaptic plasticity with subcellular expression of CapChR2 at postsynaptic spine by Nripesh Dixit, Gur Pyari, Himanshu Bansal, Sukhdev Roy

“…The analysis provides a new means of direct optogenetic control of $${Ca}^{2+}$$ -based synaptic plasticity, better understanding of learning and memory processes, and opens prospects for targeted therapeutic interventions to modulate synaptic function and address various neurological disorders.…”
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Intelligent decision-making for mine airflow on demand based on the improved artificial bee colony algorithm by ZHANG Lang, LEI Shuang, LI Wei, LIU Yanqing

“…The Lagrange relaxation method was used to optimize the model's constraint conditions, the conflict count method was used to optimize the objective function of the model, and random search methods combined with heuristic algorithms were used to optimize the search strategy of the model. …”
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Enhancing power transformer health assessment through dimensional reduction and ensemble approaches in Dissolved Gas Analysis by Abdelmoumene Hechifa, Saurabh Dutta, Abdelaziz Lakehal, Hazlee Azil Illias, Arnaud Nanfak, Chouaib Labiod

“…Various machine learning algorithms, including Decision Tree (DT), K‐Nearest Neighbours, Radial Basis Function Network, and Support Vector Machine, are employed in conjunction with Ensemble techniques. …”
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Quantitative evaluation and obstacle factor diagnosis of drug regulatory capacity in China. by Mingming Zhai, Liwen Huang, Shijie Sun, Liying Cao, Xueqiong Yue, Yuanxia Hu

“…<h4>Results</h4>The quantitative indicator system was constructed from five aspects: resource acquisition, function performance, learning and development, performance level and Internet application,and the relevant indicators of pharmacovigilance and risk response were analyzed at the national macro level. …”
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Hybrid chaotic firefly decision making model for Parkinson’s disease diagnosis by Sujata Dash, Ajith Abraham, Ashish Kr Luhach, Jolanta Mizera-Pietraszko, Joel JPC Rodrigues

“…In addition, four widely used classifiers such as Naïve Bayes classifier, k-nearest neighbor, decision tree, and radial basis function classifier are used to prove the generalization and stability of the logistic chaotic model. …”
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Ultra Short-Term Charging Load Forecasting Based on Improved Data Decomposition and Hybrid Neural Network by Shaoyang Yin, Zhaohui Chen, Wanyuan Liu, Zhiwen Su

“…First, an OOA incorporating an opposition-based learning strategy was introduced to optimize the key parameters of the VMD. …”
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Integrated Method of Future Capacity and RUL Prediction for Lithium‐Ion Batteries Based on CEEMD‐Transformer‐LSTM Model by Wangyang Hu, Chaolong Zhang, Laijin Luo, Shanhe Jiang

“…Considering nonlinear changes in the aging trajectory of lithium‐ion batteries, a method for predicting the RUL of lithium‐ion batteries was proposed in this study based on a complementary ensemble empirical mode decomposition (CEEMD) as well as transformer and long short‐term memory (LSTM) neural network dual‐drive machine learning model. First, the CEEMD algorithm was adopted to decompose the raw aging data of lithium‐ion batteries into intrinsic mode function (IMF) sequences and residual sequence, where the number of modal layers was produced by the proposed posterior feedback entropy and relevance (PFER) method. …”
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Advancing Traditional Dunhuang Regional Pattern Design with Diffusion Adapter Networks and Cross-Entropy by Yihuan Tian, Tao Yu, Zuling Cheng, Sunjung Lee

“…To promote the inheritance of traditional culture, a variety of emerging methods rooted in machine learning and deep learning have been introduced. Dunhuang patterns, an important part of traditional Chinese culture, are difficult to collect in large numbers due to their limited availability. …”
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Dual-Ascent-Inspired Transformer for Compressed Sensing by Rui Lin, Yue Shen, Yu Chen

“…Second, DAT exhibits enhanced robustness to variations in initial learning rates, as evidenced by loss function analysis during training.…”
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Differential effects of GPT-based tools on comprehension of standardized passages by Hudson K. Etkin, Kai J. Etkin, Ryan J. Carter, Camarin E. Rolle

“…Consistent with our pre-registered hypotheses, we found a differential effect of AI tools as a function of baseline reading comprehension ability. …”
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Physics-Informed Multi-Agent DRL-Based Active Distribution Network Zonal Balancing Control Strategy for Security and Supply Preservation by Bingxu Zhai, Yuanzhuo Li, Wei Qiu, Rui Zhang, Zhilin Jiang, Wei Wang, Tao Qian, Qinran Hu

“…The framework generates parameters through an upper-layer reinforcement learning algorithm, which are passed into the objective function of the lower-layer local physical model. …”
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Medical Image Hybrid Watermark Algorithm Based on Frequency Domain Processing and Inception v3 by Yu Fan, Jingbing Li, Uzair Aslam Bhatti, Saqib Ali Nawaz, Yenwei Chen

“…This article proposes a hybrid digital watermarking algorithm for medical images based on frequency domain transformation and deep learning convolutional neural networks. The algorithm combines the advantages of traditional frequency domain watermarking methods and deep learning techniques. …”
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A Rapid Artificial Intelligence-Based Computer-Aided Diagnosis System for COVID-19 Classification from CT Images by Hassaan Haider Syed, Muhammad Attique Khan, Usman Tariq, Ammar Armghan, Fayadh Alenezi, Junaid Ali Khan, Seungmin Rho, Seifedine Kadry, Venkatesan Rajinikanth

“…The proposed method includes four core steps: (i) preparing a database of three different classes such as COVID-19, pneumonia, and normal; (ii) modifying three pretrained deep learning models such as VGG16, ResNet50, and ResNet101 for the classification of COVID-19-positive scans; (iii) proposing an activation function and improving the firefly algorithm for feature selection; and (iv) fusing optimal selected features using descending order serial approach and classifying using multiclass supervised learning algorithms. …”
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ApoE receptor 2 regulates synapse and dendritic spine formation. by Sonya B Dumanis, Hyun-Jung Cha, Jung Min Song, Justin H Trotter, Matthew Spitzer, Ji-Yun Lee, Edwin J Weeber, R Scott Turner, Daniel T S Pak, G William Rebeck, Hyang-Sook Hoe

“…<h4>Background</h4>Apolipoprotein E receptor 2 (ApoEr2) is a postsynaptic protein involved in long-term potentiation (LTP), learning, and memory through unknown mechanisms. We examined the biological effects of ApoEr2 on synapse and dendritic spine formation-processes critical for learning and memory.…”
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Enhancing Power Quality in Grid-Integrated Hybrid Renewable Energy System using ANFIS-FBSO by Singh Manpreet, Singh Lakhwinder

“…The FBSO algorithm optimises the learning function of the ANFIS for optimal outcomes. …”
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Foundation Models and Fine-Tuning: A Benchmark for Out of Distribution Detection by Francesco Cappio Borlino, Lorenzo Lu, Tatiana Tommasi

“…We design an experimental framework to analyze specific choices in the model learning and use (which dataset, pretraining objective, OOD scoring function) and extensively evaluate the comparison to standard approaches that leverage a training phase on the available In Distribution (ID) data. …”
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A Coupled Adaptive Kriging Model and Generalized Subset Simulation Hybrid Reliability Analysis Method for Rare Failure Events by Yunhan Ling, Huajun Peng, Yong Sun, Chao Yuan, Zining Su, Xiaoxiao Tian, Peng Nie, Hengfei Yang, Shiyuan Yang

“…This updated strategy avoids the limitations of most current learning functions based on the prediction variance of Kriging models. …”
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Comparing UNet configurations for anthropogenic geomorphic feature extraction from land surface parameters. by Sarah Farhadpour, Aaron E Maxwell

“…The application of deep learning for semantic segmentation has revolutionized image analysis, particularly in the geospatial and medical fields. …”
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A Statistical Optimization Method for Sound Speed Profiles Inversion in the South China Sea Based on Acoustic Stability Pre-Clustering by Zixuan Zhang, Ke Qu, Zhanglong Li

“…Aiming at the problem of accuracy degradation caused by the mixing of spatiotemporal disturbance patterns in sound speed profile (SSP) inversion using the traditional geographic grid division method, this study proposes an acoustic stability pre-clustering framework that integrates principal component analysis and machine learning clustering. Disturbance mode principal component analysis is first used to extract characteristic parameters, and then a machine learning clustering algorithm is adopted to pre-classify SSP samples according to acoustic stability. …”
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A bibliometric analysis of studies on artificial intelligence in neuroscience by Ugur Tekin, Murat Dener, Murat Dener

“…The incorporation of artificial intelligence (AI) into neuroscience has the potential to significantly enhance our comprehension of brain function and facilitate more effective diagnosis and treatment of neurological disorders. …”
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