An integrative analysis reveals cancer risk associated with artificial sweeteners by Jumin Xie, Ying Zhu, Zixuan Yang, Zhang Yu, Mingzhi Yang, Qingzhi Wang

“…AS-cancer targets were identified through the intersection of these datasets. A network visualization (‘AS-targets-cancer’) was constructed using Cytoscape 3.9.0. …”
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Comparative miRNAome combined with transcriptome and degradome analysis reveals a novel miRNA-mRNA regulatory network associated with starch metabolism affecting pre-harvest sprout... by Longqing Sun, Ting Zhao, Dandan Qin, Jing Dong, Daorong Zhang, Xifeng Ren

“…Based on transcriptome data, a network associated with starch metabolism was systematically and completely reconstructed in wheat. …”
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Hourly Ozone and PM2.5 Prediction Using Meteorological Data – Alternatives for Cities with Limited Pollutant Information by Felipe Cifuentes, Angel Gálvez, Carlos M. González, Mauricio Orozco-Alzate, Beatriz H. Aristizábal

“…Abstract Using statistical models, the average hourly ozone (O3) concentration was predicted from seven meteorological variables (Pearson correlation coefficient, R = 0.87–0.90), with solar radiation and temperature being the most important predictors. …”
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Do digital influencers successfully contribute to reducing the gap between customers and companies? by Isaac Moreira, Paulo Stenzel, João M. Lopes, José Oliveira

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Identifying Significant Macroeconomic Indicators for Indian Stock Markets by Prakash K. Aithal, Acharya U. Dinesh, M. Geetha

“…In addition, the influence of these seven factors on the NSE Nifty and BSE SENSEX indices are analyzed using regression. …”
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Compound identification of Shuangxinfang and its potential mechanisms in the treatment of myocardial infarction with depression: insights from LC-MS/MS and bioinformatic prediction by Yize Sun, Yize Sun, Haibin Zhao, Zheyi Wang

“…All the targets were intersected to construct the Protein-Protein Interaction (PPI) network on Metascape platform and the herb-compound-target (HCT) network on Cytoscape, to identify the hub targets. …”
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Unsupervised Hyperspectral Denoising Based on Deep Image Prior and Least Favorable Distribution by Keivan Faghih Niresi, Chong-Yung Chi

“…Lately, it has been reported that the convolutional neural network (CNN), the core element used by deep image prior (DIP), is able to capture image statistical characteristics without the need of training, i.e., restore the clean image blindly. …”
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Machine Learning-Based Prediction of Ecosystem-Scale CO₂ Flux Measurements by Jeffrey Uyekawa, John Leland, Darby Bergl, Yujie Liu, Andrew D. Richardson, Benjamin Lucas

“…AmeriFlux is a network of hundreds of sites across the contiguous United States providing tower-based ecosystem-scale carbon dioxide flux measurements at 30 min temporal resolution. …”
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Eliciting Emotions: Investigating the Use of Generative AI and Facial Muscle Activation in Children’s Emotional Recognition by Manuel A. Solis-Arrazola, Raul E. Sanchez-Yanez, Ana M. S. Gonzalez-Acosta, Carlos H. Garcia-Capulin, Horacio Rostro-Gonzalez

“…In contrast, for AI-generated images, seven emotions were analyzed, including the previous five plus surprise and disgust. …”
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Globalisation as a factor of marketing concepts’ evolution by I. V. Alyoshina

“…In the context of the globalization processes development, a comparative description of seven marketing concepts has been given – from improving production to holistic marketing. …”
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Energy efficiency as a driver of the circular economy and carbon neutrality in selected countries of Southern Europe: a soft computing approach by Alma Ramčilović Jesih, Goran Šimić, Ljubiša Konatar, Zoran Brljak, Polona Šprajc

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Pasithea-1: An Energy-Efficient Sequential Reconfigurable Array With CPU-Like Programmability by Tobias Kaiser, Esther Gottschalk, Kai Biethahn, Friedel Gerfers

“…To reduce operand transfer energy, seven interconnect topologies are evaluated: a flat bus, five crossbar variants and a logarithmic network. …”
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Application of Computer Simulation in Exploring the Effects of <italic>Achyranthis Bidentatae Radix</italic> on Simultaneously Treating Wei Syndrome and Bi Syndrome of Osteoarthrit... by Chunsong ZHENG, Hongzhi YE, Jinxia YE, Changlong FU

“…Meanwhile, the Niuxi compound numbers of treating Bi syndrome and Wei syndrome were thirty-seven and twenty-six, respectively. Among them, twenty compounds could simultaneously treating Bi syndrome and Wei syndrome of OA. …”
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A COMPARATIVE STUDY OF DEEP LEARNING METHODS APPLIED FOR WASTEWATER pH NEUTRALIZATION PROCESS MODELLING by Mădălina Cărbureanu

“…The analysed DL methods are Feedforward Neural Networks (FNNs), Temporal Convolutional Networks (TCNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM), General Regression Neural Networks (GRNNs), Time Delay Neural Networks (TDNNs) and Deep Belief Networks (DBNs), being implemented using Python 3.9 software and Tensorflow. …”
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Multi-step Prediction of Monthly Sediment Concentration Based on WPT-ARO-DBN/WPT-EPO-DBN Model by GAO Xuemei, CUI Dongwen

“…Accurate multi-step sediment concentration prediction is of significance for regional soil erosion control,flood control and disaster reduction.To improve the multi-step prediction accuracy of sediment concentration and the prediction performance of the deep belief network (DBN),this paper proposes a multi-step prediction model of monthly sediment concentration by combining the artificial rabbit optimization (ARO) algorithm,eagle habitat optimization (EPO) algorithm,and DBN based on wavelet packet transform (WPT).The model is validated using time series data of monthly sediment concentration from Longtan Station in Yunnan Province.Firstly,WPT is employed to decompose the time series data of the monthly sediment concentration of the case in three layers,and eight more regular subsequence components are obtained.Secondly,the principles of ARO and EPO algorithms are introduced,and hyperparameters such as the neuron number in the hidden layer of DBN are optimized by ARO and EPO.Meanwhile,WPT-ARO-DBN and WPT-EPO-DBN prediction models are built,and WPT-PSO (particle swarm optimization)-DBN and WPT-DBN are constructed for comparative analysis.Finally,four models are adopted to predict each subsequence component,and the predicted values are superimposed to obtain the multi-step prediction results of the final monthly sediment concentration.The results are as follows.① WPT-ARO-DBN and WPT-EPO-DBN models have satisfactory prediction effects on the monthly sediment concentration of the case from one step ahead to four steps ahead.This yields sound prediction results for five steps ahead.The prediction effect for six steps ahead and seven steps ahead is average,and the prediction accuracy for eight steps ahead is poor and cannot meet the prediction accuracy requirements.② The multi-step prediction performance of WPT-ARO-DBN and WPT-EPO-DBN models is superior to WPT-PSO-DBN models and far superior to WPT-DBN models,with higher prediction accuracy,better generalization ability,and larger prediction step size.③ ARO and EPO can effectively optimize DBN hyperparameters,improve DBN prediction performance,and have better optimization effects than PSO.Additionally,WPT-ARO-DBN and WPT-EPO-DBN models can give full play to the advantages of WPT,new swarm intelligence algorithms and the DBN network and improve the multi-step prediction accuracy of monthly sediment concentration,and the prediction accuracy decreases with the increasing prediction steps.…”
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Automating skin cancer screening: a deep learning by Nada M. Rashad, Noha MM. Abdelnapi, Ahmed F. Seddik, M. A. Sayedelahl

“…This model is able to recognize seven different kinds of skin lesions. On the ISIC dataset, an analysis has been done. …”
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Faculty Profile Management System Using IRINS for the Analysis of Research Performance in the Field of Science and Technology by S. Thanuskodi, P. Kannan

“…The study aims to develop a faculty profile management system using the Indian Research Information Network System (IRINS) for seven Indian Institute of Technology (IIT) and analyze the faculty members' research contributions through bibliometric indicators. …”
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Frequency and Texture Aware Multi-Domain Feature Fusion for Remote Sensing Scene Classification by Russo Ashraf, Kang-Hyun Jo

“…The proposed method yield the best results when trained from scratch, in all seven tested datasets:: ISL-RS50 (60%), Optimal-31 (86.55%), UC-Merced (94.52%), RSSCN7 (94.1%), SIRI-WHU (95%), WHU-RS19 (94.52%), AID (93.5%). …”
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Availability and use of institutional support programs for emergency department healthcare personnel during the COVID-19 pandemic. by Karin F Hoth, Patrick Ten Eyck, Karisa K Harland, Anusha Krishnadasan, Robert M Rodriguez, Juan Carlos C Montoy, Linder H Wendt, William Mower, Kelli Wallace, Scott Santibañez, David A Talan, Nicholas M Mohr, Project COVERED Emergency Department Network

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Mobile Localization Based on Received Signal Strength and Pearson's Correlation Coefficient by Huiyu Liu, Yunzhou Zhang, Xiaolin Su, Xintong Li, Ning Xu

“…Being applicable for almost every scenario, mobile localization based on cellular network has gained increasing interest in recent years. …”
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