small industrial cities. Heritage update. Tatiana Bystrova. Review by Mariya S. Frolova

“…The author shows the foundations of the stability of this system, the specifics of the architecture of industrial buildings and complexes, and the everyday culture of the region.The methods and cases of work with historical and cultural heritage introduced into scientific circulation in different regions of the world are selected taking into account the current economic, demographic, social processes in small Russian cities, which increases the efficiency of their possible use. …”
Get full text

PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems by Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, Huiting ZHOU, Hong LUO

“…Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model, a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed, and a system model of fusion technology was designed.Through simulation comparison with other literature methods, it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability, but the algorithm implementation complexity was too high.Therefore, a complementary SLM-Clipping fusion solution was proposed, and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method, the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system, and greatly improves the computational efficiency.…”
Get full text

PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems by Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, Huiting ZHOU, Hong LUO

“…Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model, a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed, and a system model of fusion technology was designed.Through simulation comparison with other literature methods, it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability, but the algorithm implementation complexity was too high.Therefore, a complementary SLM-Clipping fusion solution was proposed, and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method, the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system, and greatly improves the computational efficiency.…”
Get full text

AEQUAM: Accelerating Quantum Algorithm Validation Through FPGA-Based Emulation by Lorenzo Lagostina, Deborah Volpe, Maurizio Zamboni, Giovanna Turvani

“…This work presents AEQUAM (Area Efficient QUAntum eMulation), a toolchain that enables faster and more accessible quantum circuit verification. …”
Get full text

Estimation of sugarcane biomass from Sentinel-2 leaf area index using an improved SAFY model (SAFY-Sugar) by Jingyuan Xu, Xin Du, Taifeng Dong, Qiangzi Li, Yuan Zhang, Hongyan Wang, Miao Liu, Jiong Zhu, Jian Yang

“…The Simple Algorithm for Yield Estimation model (SAFY), a semi-physical crop growth model grounded in light use efficiency theory has been widely adopted for satellite-based biomass estimation in major field crops. …”
Get full text

Electrochemical Analysis of the Electrocatalytic Reduction of 5‐Hydroxymethylfurfural in Cu Electrodes by Jose Solera‐Rojas, David Carvajal, Antonio Guerrero, Carmen Mejuto, Elena Mas‐Marzá, Francisco Fabregat‐Santiago

“…However, achieving high selectivity in this process remains challenging due to the complexity of the reaction mechanisms involved. …”
Get full text

GPU-Accelerated Eclipse-Aware Routing for SpaceWire-Based OBC in Low-Earth-Orbit Satellite Networks by Hyeonwoo Kim, Heoncheol Lee, Myonghun Han

“…The approach first employs a Breadth-First Search (BFS)–based K-Shortest Paths (KSP) algorithm to generate candidate routes and then evaluates battery usage to select the most efficient path. In large-scale networks, the computational load of the KSP search increases substantially. …”
Get full text

Deep Learning Approaches for Morphological Classification of Intestinal Organoids by Giovanni Cicceri, Sebastiano Di Bella, Simone Di Franco, Giorgio Stassi, Matilde Todaro, Salvatore Vitabile

“…The use of deep learning (DL) in organoid image analysis becomes crucial to handle complexity, variability, and large amounts of data efficiently and accurately, overcoming the limitations of traditional image processing approaches. …”
Get full text

New challenges in point cloud visual quality assessment: a systematic review by Amar Tious, Toinon Vigier, Vincent Ricordel

“…We collected scientific papers from online libraries (IEEE Xplore, ACM DL, Scopus) and selected a set of relevant papers to analyze. From our observations, we discuss the progress and future challenges in PCQA toward efficient point cloud video coding and rendering for eXtended Reality. …”
Get full text

Blockade of αvβ6 and αvβ8 integrins with a chromogranin A-derived peptide inhibits TGFβ activation in tumors and suppresses tumor growth by Anna Maria Gasparri, Arianna Pocaterra, Barbara Colombo, Giulia Taiè, Chiara Gnasso, Alessandro Gori, Federica Pozzi, Andrew Smith, Fulvio Magni, Alessia Ugolini, Matteo Doglio, Maria Chiara Bonini, Anna Mondino, Angelo Corti, Flavio Curnis

“…Abstract Background The αvβ6- and αvβ8-integrins, two cell-adhesion receptors upregulated in many solid tumors, can promote the activation of transforming growth factor-β (TGFβ), a potent immunosuppressive cytokine, by interacting with the RGD sequence of the latency-associated peptide (LAP)/TGFβ complex. We have previously described a chromogranin A-derived peptide, called “peptide 5a”, which recognizes the RGD-binding site of both αvβ6 and αvβ8 with high affinity and selectivity, and efficiently accumulates in αvβ6- or αvβ8-positive tumors. …”
Get full text

Exploring the relationship between data sample size and traffic flow prediction accuracy by Jianhu Zheng, Minghua Wang, Mingfang Huang

“…Efficiently extracting and analyzing large urban traffic data, accurately predicting traffic conditions, and improving urban traffic management require careful selection of an appropriate data sample size. …”
Get full text

Overlapping community-based fair influence maximization under a multi-transformation optimization algorithm by Chunfeng Jiang, Zegang Niu, Jingru Qu, Yulan Zhao, Amin Rezaeipanah

“…The algorithm adapts to different transformations without the need for manual selection, allowing it to efficiently explore the solution space. …”
Get full text

Calculation of Weighted Geometric Dilution of Precision by Chien-Sheng Chen, Yi-Jen Chiu, Chin-Tan Lee, Jium-Ming Lin

“…The proposed formulae can reduce the computational complexity required for computing the matrix inversion. …”
Get full text

Development of a hybrid adaptive control system for pyrolysis plants: A comparative study of conventional and intelligent approaches by Rysbek Aitolkyn, Sergazin Gani, Zhetenbayev Nursultan

“…The analysis focuses on key performance indicators such as reliability, adaptability, integration complexity, and predictive capability. Due to the nonlinear and dynamic nature of pyrolysis, selecting an appropriate control architecture is essential for improving efficiency, product quality, and environmental safety. …”
Get full text

Spectrum‐sensing algorithm based on graph feature fusion by Shanshan Wu, Guobing Hu, Bin Gu

“…Thus, compared to existing algorithms, except block range‐ and energy‐detection‐based methods, the proposed algorithm demonstrates the best spectrum‐sensing performance under low SNRs and channel‐fading conditions, while achieving the lowest computational complexity. The proposed approach enables more efficient and accurate spectrum sensing, fostering advancements in communication technologies and defence applications.…”
Get full text

Research on bearing fault feature transfer diagnosis based on balanced distribution adaptation under feature fusion by Lulu Wang, Yongqi Li, Chunyi Zhang, Ralph Gerard Sangalang

“…Firstly, time-domain features of the bearing signals are extracted to comprehensively reflect the operational state of the bearings. Principal Component Analysis (PCA) is then utilized to reduce the dimensionality of the high-dimensional features, preserving the main information while reducing computational complexity. …”
Get full text

Optimization of Sparse Concentric Ring Arrays for Low Sidelobe by Kesong Chen, Yafei Li, Jiajia Shi

“…The MGA uses real number to code the optimization variable, and it reduces the complexity of coding and improves the search efficiency. …”
Get full text

Recent Advances in Understanding the Keys Factors Influencing Pressurized Liquid Extraction of Secondary Metabolites: A Comprehensive Review by Pauline Donn, Sepidar Seyyedi-Mansour, Franklin Chamorro, Paula Garcia-Oliveira, Javier Echave, Ana Perez-Vazquez, Paula Barciela, Lucia Cassani, Miguel Angel Prieto

“…This communication provides an overview of recent advancements in understanding the key factors influencing the efficiency and selectivity of the PLE of these bioactive compounds. …”
Get full text

A network traffic classification method based on random forest and improved convolutional neural network by Bensheng YUN, Xiaoya GAN, Yaguan QIAN

“…In order to improve the efficiency and reduce the complexity of network traffic classification model, a classification method based on random forest and improved convolutional neural network was proposed.Firstly, the random forest was used to evaluate the importance of each feature of network traffic, and the feature was selected according to the importance ranking.Secondly, AdamW optimizer and triangular cyclic learning rate were adopted to optimize the convolutional neural network classification model.Then, the model was built on Spark cluster to realize the parallelization of model training.Adopting triangular cyclic learning rate with constant cycle amplitude, the experimental results of selecting 1 024, 400, 256 and 100 most important features as input show that the model accuracy is improved to 97.68%, 95.84%, 95.03% and 94.22%, respectively.The 256 most important features were selected and the experimental results based on adopting different learning rates show that the learning rate with half the cycle amplitude works best, the accuracy of the model is improved to 95.25%, and training time of the model is reduced by nearly half.…”
Get full text

Evaluation of Intrusion Detection Systems in Cyber Security using Fuzzy OffLogic and MCDM Approach by Zhengrui Yang

“…In this study, thirteen widely used IDS models are assessed using a multi-criteria evaluation framework across four key dimensions: detection accuracy, resource efficiency, scalability, and false positive rate. The goal is to support informed, datadriven decision-making for stakeholders such as policymakers, IT administrators, and security analysts when selecting an appropriate IDS. …”
Get full text