Removing Excess Iron from Sewage and Natural Waters: Selecting Optimal Sorbent by Ludmila A. Ivanova, Irina V. Timoshchuk, Alena K. Gorelkina, Ekaterina S. Mikhaylova, Nadezhda S. Golubeva, Evgeny N. Neverov, Tamara A. Utrobina

“…Initial concentration, flow velocity, and loading layer height were studied in dynamics, i.e., during continuous operation of the adsorption column. …”
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The mechanism of stability of fault system inducing roof water-inrush by Ma Zhijing, Li Yanheng, Bian Kai, Yang Zhibin, Gao Lijun, Liu Bo, Pang Yu, Balaji Panchal

“…Mining couses costant stress on the fault zone, which is a loading process on the system composed of fault material and surrounding medium. …”
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Network quality and user perception improvement of high-speed rail scene by Songbai LIANG, Yingwu GUO, Xinwei LI

“…In view of the difficulty in improving the quality of mobile network in high-speed railway scenes and the poor efficiency of conventional methods, a methodology system for improving the perception of mobile communication users was explored in traffic trunk lines, especially in high-speed railway scenes.The methodology system was based on handover chain optimization with the core idea of “primary covering, reasonable reselection and orderly switching”.It adopted a three-layer theoretical structure include covering control firstly, then parameter optimization, and feature loading last.It used idle state and service state data pull graph correlation to determine problem road sections and cells, match the delay parameters of high-speed mobile scenes, load service quality and perception characteristics, and greatly improved the high-speed railway network quality and user perception.This method started from the principle analysis, with practical application, it could effectively solve the network problems, which could be fully extended to other linear scenes.…”
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Topology Optimization of Spinal Cage Designs for Improved Stress Distribution and Bone Graft Window by Meltem Eryıldız

“…In this study, a topology optimization approach was employed to develop distinct spinal cages featuring a bone graft window. The mechanical behavior of the spinal cages under loading conditions was simulated and evaluated using finite element analysis. …”
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The mechanosensitive adhesion G protein-coupled receptor 133 (GPR133/ADGRD1) enhances bone formation by Juliane Lehmann, Hui Lin, Zihao Zhang, Maren Wiermann, Albert M. Ricken, Franziska Brinkmann, Jana Brendler, Christian Ullmann, Luisa Bayer, Sandra Berndt, Anja Penk, Nadine Winkler, Franz Wolfgang Hirsch, Thomas Fuhs, Josef Käs, Peng Xiao, Torsten Schöneberg, Martina Rauner, Jin-Peng Sun, Ines Liebscher

“…This is demonstrated in vitro through stretch assays and in vivo via a mechanical loading experiment. Further in vitro analysis shows that GPR133/ADGRD1-mediated osteoblast differentiation is driven by cAMP-dependent activation of the β-catenin signaling pathway. …”
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Development and study of mucoadhesive microcapsules for the nasal levodopa delivery by D. S. Gordeeva, V. V. Khutoryanskiy, R. I. Moustafine

“…The encapsulation efficiency, % (EE%) and loading capacity, % (LC%) of levodopa loaded MC were assessed using UV spectrophotometry on an Evolution™ 220 device (Thermo Fisher Scientific, USA) at a wavelength of 202 nm. …”
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Evaluation of the Occurrence of Initial Failures from Stress Concentrators in Welded Joints and Structural Elements by K. А. Molokov, V. V. Novikov, M. Dabalez

“…The literature on the topic was analyzed. The features of proven physical models and patterns of behavior of materials were taken into account. …”
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MGAT1-Guided complex N-Glycans on CD73 regulate immune evasion in triple-negative breast cancer by Junlong Jack Chi, Ping Xie, Mary Hongying Cheng, Yueming Zhu, Xin Cui, Joshua Watson, Lidan Zeng, Amad Uddin, Hoang Nguyen, Lei Li, Kelley Moremen, April Reedy, Megan Wyatt, Adam Marcus, Mingji Dai, Chrystal M. Paulos, Massimo Cristofanilli, William J. Gradishar, Shaying Zhao, Kevin Kalinsky, Mine-Chie Hung, Ivet Bahar, Bin Zhang, Yong Wan

“…Spatial transcriptomic profiling reveals spatially resolved features of interacting malignant and immune cells pertaining to expression levels of MGAT1 and CD73. …”
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Fault Diagnosis for Bearing Based on 1DCNN and LSTM by Haibin Sun, Shichao Zhao

“…Second, one-dimensional convolutional neural network (1DCNN) is used for self-adaptively extracting robust features from the original bearing signal, and more features are extracted while ensuring the validity and saliency of the extracted features by combining maximum pooling and average pooling layers to downsample features. …”
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Intelligent fault prediction method of telecom system by Heng CAI, Lei GE

“…Some approaches based on deep learning would be used to analyze the process and port network on a server cluster.Specifically,the features of nodes were carefully selected in server cluster network,by combining the prior knowledge from actual operations,and the abnormal state of processes or ports on the cluster was predicted.According to the research,the running information such as loads of CPU and memory,communications between processes and the structural features in the process network was valuable in predicting the states of processes and ports; furthermore,the changes of features mentioned above in the time dimension reflected the states of processes or ports,too.…”
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A deep learning-based algorithm for the detection of personal protective equipment. by Bo Tong, Guan Li, Xiangli Bu, Yang Wang, Xingchen Yu

“…A Multi-Scale Feature Diffusion Pyramid Network (MFDPN) was developed, which aggregates multi-scale features through the Multiscale Feature Focus (MFF) module and diffuses them across scales, providing each scale with detailed contextual information. …”
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Multi scale convolutional neural network combining BiLSTM and attention mechanism for bearing fault diagnosis under multiple working conditions by Zhao Dengfeng, Tian Chaoyang, Fu Zhijun, Zhong Yudong, Hou Junjian, He Wenbin

“…A deep learning network framework for diagnosing bearing faults under multiple load conditions is proposed to address the problems of extracting a single feature scale from bearing vibration timing signals, inability to simultaneously utilize spatial and bidirectional time features, and difficulty in obtaining sufficient training data under multiple working conditions. …”
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Algorithm for Constructing the Hazard Function of the Extended Cox Model and its Application to the Prostate Cancer Patient Database by I. I. Mikulik, G. M. Zharinov, A. Yu. Kneev

“…To solve the problem using the optimization method, a fitness function was constructed that evaluated the results of prognosis, the number of features, and the degree of overtraining of the model — the complexity and load of the compiled hazard function. …”
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Land Use Patch Generalization Based on Semantic Priority by Jun Yang, Fanqiang Kong, Jianchao Xi, Quansheng Ge, Xueming Li, Peng Xie

“…This effectively deletes narrow features and meets the area requirements, better generalizes land use features, and guarantees simple and attractive maps with appropriate loads. (4) We simplify the feature sidelines using the Douglas-Peucker algorithm to effectively eliminate nodes having little impact on overall shapes and characteristics. …”
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Bearing fault diagnosis for variable operating conditions based on KAN convolution and dual branch fusion attention by Qibing Wang, Chuanjie Yin, Kun She, Qinfeng Tong, Guoxiong Lu, Hongbing Zhang, Jiawei Lu

“…Subsequently, context-aware features and non-local aggregation features are combined with the objective of obtaining global features. …”
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Study on pore structure and gas adsorption characteristics of coals with different burst liability by Zhao LI, Guanhua NI, Wei YANG, Yongzan WEN, Gang WANG, Zhen LIU, Zhenyang WANG

“…With the increase of mining depth, the features of high geopathic stress, low permeability and strong disturbance of coal seams gradually appear, and the form of underground disasters becomes more and more complicated, among which impact ground pressure and gas protrusion is the most important form of composite disaster manifestation. …”
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A Lightweight Transformer Edge Intelligence Model for RUL Prediction Classification by Lilu Wang, Yongqi Li, Haiyuan Liu, Taihui Liu

“…To address this issue, we propose TBiGNet, a lightweight Transformer-based classification network model for RUL prediction. TBiGNet features an encoder–decoder architecture that outperforms traditional Transformer models by achieving over 15% higher accuracy while reducing computational load, memory access, and parameter size by more than 98%. …”
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AI-Driven Adaptive Security for Sensor Networks: Next-Generation Firewalls for Attack Detection by Niranjan W. Meegammana, Harinda Fernando

“…This study proposes an adaptive next-generation firewall (NGFW) that dynamically switches between shallow and deep AI models based on real-time network load and resource availability. Four neural network models were trained using 20 and 40-feature subsets of the UNSW-NB15 dataset. …”
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A visual SLAM loop closure detection method based on lightweight siamese capsule network by Yuhan Zhou, Mingli Sun

“…Traditional loop closure detection algorithms rely on the bag-of-words model, which involves a complex process, has slow loading speeds, and is sensitive to changes in illumination or viewing angles. …”
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Automatic Condition Monitoring of Industrial Rolling-Element Bearings Using Motor’s Vibration and Current Analysis by Zhenyu Yang

“…In order to test the flexibility and robustness, the monitoring performance is extensively studied under diverse operating conditions: different sensor locations, motor speeds, loading conditions, and data samples from different time segments. …”
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