Titanium oxide and chitosan nanoparticles loaded in methylene blue activated by photodynamic therapy on caries affected dentin disinfection, bond strength, and smear layer removal... by Amer M. Alanazi, Nabeel Ahmad Khan, Azmat Ali Khan, Kinza Bhutto, Syed Hussain Askary, Gulrukh Askary, Eisha Abrar, Syed Junaid Mahmood, Ambrina Qureshi

“…Aim: Effect of nanoparticles (NPs) loaded methylene blue (MB) mediated photodynamic therapy (PDT) on caries-affected dentin (CAD) against S.mutans, smear layer (SL) elimination, and shear bond strength (SBS) of single bottle 7th generation adhesive. …”
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Investigation of key performance metrics in TiOX/TiN based resistive random-access memory cells by Brandon R. Zink, William A. Borders, Advait Madhavan, Brian D. Hoskins, Jabez McClelland

“…Abstract Resistive random-access memory (RRAM) is a promising beyond-CMOS technology due to its non-volatility, scalability, and high ON/OFF ratio. …”
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Fuzzy Random Prediction Model of Frost Heave Characteristics of Horizontal Frozen Metro Contact Channel in Coastal Area by Yao Yafeng, Zhang Zhemei, Wang Wei, Li Yongheng, Li Siqi, Wei Chenguang

“…With the aim of improving the deficiency of traditional BP neural network algorithms in solving fuzzy random engineering problems, random factor and mean square error between layers are used to modify the evaluation function of the network model. …”
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The Sloping Mire Soil-Landscape of Southern Ecuador: Influence of Predictor Resolution and Model Tuning on Random Forest Predictions by Mareike Ließ, Martin Hitziger, Bernd Huwe

“…The sloping mire landscape of the investigation area, in the southern Andes of Ecuador, is dominated by stagnic soils with thick organic layers. The recursive partitioning algorithm Random Forest was used to predict the spatial water stagnation pattern and the thickness of the organic layer from terrain attributes. …”
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ACD-ML: Advanced CKD detection using machine learning: A tri-phase ensemble and multi-layered stacking and blending approach by Mir Faiyaz Hossain, Shajreen Tabassum Diya, Riasat Khan

“…The investigation reveals that, for the Discrete Merged dataset, the novel Tri-phase Ensemble and Multi-layer Stacking with layers interchanged achieves an accuracy of 99.5%. …”
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An Empirical Evaluation of Lightweight Random Walk Based Routing Protocol in Duty Cycle Aware Wireless Sensor Networks by Adnan Noor Mian, Mehwish Fatima, Raees Khan, Ravi Prakash

“…In this paper we first present a three messages exchange Lightweight Random Walk Routing (LRWR) protocol and then evaluate its performance in WSNs for routing low data rate packets. …”
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Comparison of barbed suture and nonbarbed suture for laparoscopic cholecystoduodenostomy in rabbits: a randomized controlled trial by Yuan Li, Xiaofeng Yang, Chuang Zhang, Lixia Zhou, Chi Sun, Suolin Li

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Effects of Dandelion Flavonoid Extract on the Accumulation of Flavonoids in Layer Hen Meat, Slaughter Performance and Blood Antioxidant Indicators of Spent Laying Hens by Yuyu Wei, Jingwen Zhang, Yiming Zhang, Dingkuo Liu, Chunxue You, Wenjuan Zhang, Chaoqi Ren, Xin Zhao, Liu’an Li, Xiaoxue Yu

“…The results showed that dietary supplementation with DFE can increase the content of dandelion flavonoids in layer hen meat. The contents of rutin in layer hen breast meat of groups T1, T2, T3, and T4 were 1.37, 4.41, 16.26, and 36.03 ng/g, respectively, and the contents of quercetin was 2.58, 1.36, 4.98, 12.48 ng/g. …”
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Collaborative opportunistic routing in wireless sensor networks by HU Hai-feng, YANG Zhen

“…Based on the region-based routing, rendezvous scheme and sleep discipline, the protocal allowed for routing solution to be improved by cross layer design for wireless sensor networks. The routing objective was to provide robustness to the random variations in network con-nectivity while ensuring better data forwarding efficiency in an energy efficient manner. …”
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Scheme for identifying malware traffic with TLS data based on machine learning by Ziming LUO, Shubin XU, Xiaodong LIU

“…Based on analyzing the characteristics of transport layer security (TLS) protocol,a distributed automation malicious traffic detecting system based on machine learning was designed.The characteristics of encrypted malware traffic from TLS data,observable metadata and contextual flow data was extracted.Support vector machine,random forest and extreme gradient boosting were used to compare the performance of the mainstream malicious encryption traffic identification which realized the efficient detection of malicious encryption traffic,and verified the validity of the detection system of malicious encryption traffic.…”
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Deep Learning for Connectivity Identification in Random Subsurface Flows: A Methodological Workflow for Early Solute Arrival Time Quantification by A. Manzoni, F. P. J. deBarros, G. M. Porta, M. Riva, A. Guadagnini

“…The effectiveness of the approach is exemplified on synthetic two‐dimensional (randomly) heterogeneous hydraulic conductivity fields. …”
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WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches by Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, Adeel Akram, Muhammad Awais Azam

“…Then, we use three deep learning techniques, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), to classify the attacks. …”
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Hybrid Darknet53-SVM model with random grid search optimization for enhanced colorectal cancer histological image classification by Pragati Patharia, Prabira Kumar Sethy, K. Lakshmipathi Raju, Anita Khanna, Ashoka Kumar Ratha, Santi Kumari Behera, Aziz Nanthaamornphong

“…To enhance the classification performance, Darknet53 was hybridized with a SVM by replacing the dense layer, and hyperparameters were optimized using a Random Grid Search algorithm. …”
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Network Embedding Algorithm for Vulnerability Assessment of Power Transmission Lines Using Integrated Structure and Attribute Information by Xianglong Lian, Tong Qian, Zepeng Li, Xingyu Chen, Wenhu Tang, Q. H. Wu

“…Based on a structure and attribute network embedding (SANE) algorithm, a novel quantitative vulnerability analysis method is proposed to identify vulnerable lines in this research. First, a two-layered random walk network with topological and electrical properties of transmission lines is established. …”
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Local Diversity-Guided Weakly Supervised Fine-Grained Image Classification Method by Yuebo Meng, Xianglong Luo, Hua Zhan, Bo Wang, Shilong Su, Guanghui Liu

“…We designed a Multi-Attention Semantic Fusion Module (MASF) to build multi-layer attention maps and channel–spatial interaction, which can effectively enhance the semantic representation of the attention maps. …”
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Ultra-Narrowband High-Transmissivity Guided-Mode Resonance Filter Based on Dual Dielectric Film Structure and High Refractive Index Waveguide Layer by Min Gao, Yu Zhang, Xinmiao Lu, Xiaoli Gong, Lei Zheng

“…Additionally, a double-layer dielectric film structure composed of SiO₂ and Al₂O₃ is employed on the Ag grating to suppress random scattering leakage in the short wavelength range, resulting in reduced sidebands and improved transmittance of the resonant peak. …”
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Investigating Tropical Cyclone Warm Core and Boundary Layer Structures with Constellation Observing System for Meteorology, Ionosphere, and Climate 2 Radio Occultation Data by Xiaoxu Qi, Shengpeng Yang, Li He

“…The aim of this study is to obtain a more accurate COSMIC-2 radio occultation (RO) dataset through quality control (QC) and use this dataset to validate warm core structures and explore the planetary boundary layer (PBL) structures of TCs. In this study, COSMIC-2 data are used to analyze the distribution of the relative local spectral width (LSW) and the confidence parameter characterizing the random error of the bending angle. …”
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Block Encryption LAyer (BELA): Zero-Trust Defense Against Model Inversion Attacks for Federated Learning in 5G/6G Systems by Sunder A. Khowaja, Parus Khuwaja, Kapal Dev, Keshav Singh, Xingwang Li, Nikolaos Bartzoudis, Ciprian R. Comsa

“…The BELA module mimics the Batch normalization (BN) layer in the deep neural network architecture that considers the random sequence. …”
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A novel prediction of the PV system output current based on integration of optimized hyperparameters of multi-layer neural networks and polynomial regression models by Hussein Mohammed Ridha, Hashim Hizam, Seyedali Mirjalili, Mohammad Lutfi Othman, Mohammad Effendy Ya’acob, Noor Izzri Bin Abdul Wahab, Masoud Ahmadipour

“…The IMGO is employed to determine the appropriate hyperparameters of the model, ranging from the number of neurons in the hidden layers and learning rate. The Bayesian regularization backpropagation procedure is applied to update the weights and bias of the network. …”
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SMRFR: A global multilayer soil moisture dataset generated using Random Forest from multi-source data by Yuhan Liu, Yuanyuan Zha, Gulin Ran, Yonggen Zhang, Liangsheng Shi

“…In this study, we present a novel machine learning (ML) based framework for generating a continuously updated, multilayer global SM dataset: SMRFR (Soil Moisture via Random Forest Regression). Leveraging publicly available reanalysis and remote sensing data, SMRFR provides daily SM estimates at five soil layers (0–5, 5–10, 10–30, 30–50 and 50–100 cm) with a spatial resolution of 9 km, covering the period from 2000 to 2023. …”
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