Selection of the optimal medical waste incineration facility location: A challenge of medical waste risk management by Stanojević Kristina, Radovanović Goran, Makajić-Nikolić Dragana, Savić Gordana, Simeunović Barbara, Petrović Nataša

“…In the proposed methodology on the chosen scenario and analysing the criteria relevant for selecting the most suitable location, using the DEA method, seven efficient locations for MW incineration facility were obtained. …”
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Preparation and Characterization of Ternary Complexes to Improve the Solubility and Dissolution Performance of a Proteolysis-Targeting Chimera Drug by Heng Zhang, Hengqian Wu, Lili Wang, Laura Machín Galarza, Chuanyu Wu, Mingzhong Li, Zhengping Wang, Erpeng Zhou, Jun Han

“…<b>Methods:</b> Initially, sulfobutyl ether-β-cyclodextrin (SBE-β-CD) was selected to improve the solubility of LC001. The polymer TPGS was screened based on the phase solubility method to enhance the efficiency of complexation and solubilization capacity, and its ratio with SBE-β-CD was optimized. …”
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Enhancing PV power forecasting through feature selection and artificial neural networks: a case study by Mokhtar Ali, Abdelhalim Rabehi, Abdelkerim Souahlia, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem, Takele Ferede Agajie

“…For instance, integrating ReliefF with MLP reduced the normalized mean absolute error (nMAE) to 9.21% with an R2 of 0.9608, while the best LSTM configuration achieved an nMAE of 9.29% and an R2 of 0.946 when using Chi-square selected features. These findings confirm that careful feature selection enhances model performance, reduces complexity, and ensures better generalization, offering valuable insights for more efficient solar energy management and grid stability.…”
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Molecularly Woven Cationic Covalent Organic Frameworks for Highly Selective Electrocatalytic Conversion of CO2 to CO by Fentahun Wondu Dagnaw, Karim Harrath, Tao Zheng, Xu‐Dong Wu, Yu‐Ze Liu, Rui‐Qi Li, Luo‐Han Xie, Zhen Li, Xuezhong He, Qing‐Xiao Tong, Jing‐Xin Jian

“…After loading Pd nanoparticles, CuCOF‐Pd and CuCOF+‐Pd performed increased CO selectivity up to 84.97% and 95.45%, respectively. Combining the DFT theoretical calculations and experimental measurements, it is assumed that the molecularly woven cationic COF provides a catalytic microenvironment for CO2R and ensures efficient charge transfer from the electrode to the catalytic center, thereby achieving high electrocatalytic activity and selectivity. …”
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Selective Cleaning Enhances Machine Learning Accuracy for Drug Repurposing: Multiscale Discovery of MDM2 Inhibitors by Mohammad Firdaus Akmal, Ming Wah Wong

“…Quantum mechanical (ONIOM) optimizations and molecular dynamics simulations confirmed the stability and favorable interaction profiles of the selected protein–ligand complexes, resembling that of navtemadlin, a known MDM2 inhibitor. …”
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Tear replacement by cationic emulsion in complex therapy of superficial punctate keratitis in hypotensively medicated glaucoma patients by S. V. Trufanov, S. A. Malozhen, D. A. Krakhmaleva, E. A. Pivin

“…The testing procedures and efficiency monitoring included biomicroscopy, Schirmer test, Norn test and evaluation of tear film osmolarity. …”
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PLL-VO： An Efficient and Robust Visual Odometry Integrating Point-Line Features and Neural Networks by L. Zhao, Y. Yang, D. Ma, X. Lin, W. Wang

“…To overcome the impact of complex lighting conditions, a self-supervised learning method for interest point detection and a line detection algorithm that combines line optical flow tracking with cross-constraints is presented. …”
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Background of Data Envelopment Analysis Implementation in Moscow Healthcare System: International and Russian Experience by Yu. V. Budarina

“…The publications were selected using the PRISMA guidelines. A complex of modern general scientific methods of cognition was also used: system and structural approach, analytical method, comparison, and generalization.Results. …”
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An Efficient Large-Scale Sensor Deployment Using a Parallel Genetic Algorithm Based on CUDA by Jae-Hyun Seo, Yourim Yoon, Yong-Hyuk Kim

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Dynamics-based predictions of infinite-dimensional complex systems using dynamical system deep learning method by Hao Li, Jianping Li, Zixiang Wu, Mingyu Wang, Guangcan Liu, Ruipeng Sun, Ruize Li, Ning Wang, Houbin Song, Shixin Zhen

“…Predicting complex nonlinear chaotic dynamical systems constitutes a critical and formidable challenge across various disciplines. …”
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Adaptive Neuro-Fuzzy System for Detection of Wind Turbine Blade Defects by Lesia Dubchak, Anatoliy Sachenko, Yevgeniy Bodyanskiy, Carsten Wolff, Nadiia Vasylkiv, Ruslan Brukhanskyi, Volodymyr Kochan

“…For this purpose, the authors explored grid partitioning and subtractive clustering methods and selected the last one because it uses three rules only for fault detection, ensuring low computational costs and enabling the discovery of wind turbine defects quickly and efficiently. …”
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Insulator Defect Detection Algorithm Based on Improved YOLOv11n by Junmei Zhao, Shangxiao Miao, Rui Kang, Longkun Cao, Liping Zhang, Yifeng Ren

“…Ensuring the reliability and safety of electrical power systems requires the efficient detection of defects in high-voltage transmission line insulators, which play a critical role in electrical isolation and mechanical support. …”
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Intelligent Detection of Tomato Ripening in Natural Environments Using YOLO-DGS by Mengyuan Zhao, Beibei Cui, Yuehao Yu, Xiaoyi Zhang, Jiaxin Xu, Fengzheng Shi, Liang Zhao

“…To achieve accurate detection of tomato fruit maturity and enable automated harvesting in natural environments, this paper presents a more lightweight and efficient maturity detection algorithm, YOLO-DGS, addressing the challenges of subtle maturity differences between regular and cherry tomatoes, as well as fruit occlusion. …”
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Edge-Optimized Lightweight YOLO for Real-Time SAR Object Detection by Caiguang Zhang, Ruofeng Yu, Shuwen Wang, Fatong Zhang, Shaojia Ge, Shuangshuang Li, Xuezhou Zhao

“…Experimental results demonstrate that the proposed method achieves comparable detection performance to state-of-the-art YOLO variants while drastically reducing computational complexity (4.4 GFLOP) and parameter count (1.9 M). …”
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Contrastive Learning Algorithm for Low-Resource Cryptographic Attack Event Detection by Peng Luo, Rangjia Cai, Yuanbo Guo

“…Additionally, assigning appropriate weights to keywords of different event types and employing clustering methods for effective classification reduce reliance on manually labeled data, thereby facilitating the training of an efficient cryptographic attack event detection model. …”
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A Novel Approach to Speed Up Hampel Filter for Outlier Detection by Mario Roos-Hoefgeest Toribio, Alejandro Garnung Menéndez, Sara Roos-Hoefgeest Toribio, Ignacio Álvarez García

“…This paper proposes a novel Hampel filter variant that replaces the MAD with an original estimator (mMAD) that retains statistical robustness but is computationally more efficient. This reduces the filter’s computational complexity from <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>N</mi><mo>·</mo><mi>w</mi><mo form="prefix">log</mo><mi>w</mi><mo>)</mo></mrow></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>N</mi><mo>·</mo><mi>w</mi><mo>)</mo></mrow></semantics></math></inline-formula>, where <i>N</i> is the data length and <i>w</i> the window size. …”
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A Suggested Point Search Algorithm for Circle Detection in Binary Images by Sundus Ebraheem

“…The proposed algorithm was more efficient, where the average ratio of the running time for the proposed algorithm to HT method was 1:646, and the accuracy of the proposed algorithm was 100% for circles detection. …”
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Log Anomaly Detection Method Based on Transformer and Temporal Convolutional Networks by Niandong Liao, Zihan Liu

“…However, the rapid development of distributed technologies has led to the increasing scale and complexity of log data, resulting in existing methods facing difficulties in fully mining log features and information loss during parsing. …”
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Security anomaly detection for enterprise management network based on attention mechanism by Zhaohan You, Yucai Zheng

“…It is an enterprise management network security anomaly detection method based on deep learning, aiming to achieve efficient and intelligent monitoring and management of security anomaly data in enterprise management network. …”
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Enhancing Cybersecurity: Hybrid Deep Learning Approaches to Smishing Attack Detection by Tanjim Mahmud, Md. Alif Hossen Prince, Md. Hasan Ali, Mohammad Shahadat Hossain, Karl Andersson

“…Experimental results demonstrate that the proposed CNN-Bi-GRU model outperforms existing approaches, achieving an overall highest accuracy of 99.82% in detecting SMS phishing messages. This study provides an empirical analysis of the effectiveness of hybrid deep learning techniques for SMS phishing detection, offering a more precise and efficient solution to enhance cybersecurity in mobile communications.…”
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