Solanum tuberosum Leaf Extract Templated Synthesis of Co3O4 Nanoparticles for Electrochemical Sensor and Antibacterial Applications by Eneyew Tilahun Bekele, H. C. Ananda Murthy, Dhanalakshmi Muniswamy, Yeshaneh Adimasu Lemenh, Minale Shegaw Shume, Gezahegn Tadesse Ayanie, Avvaru Praveen Kumar, C. R. Ravikumar, R. Balachandran, Arpita Roy

“…Among three volume ratios (1 : 2, 1 : 1, and 2 : 1) of Co3O4 nanoelectrodes, 1 : 1 and 2 : 1 were identified as the best performing nanoelectrodes. This is possibly due to the high catalytic behavior and the more homogenized surface structure. …”
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Numerical simulation of an HTL-free carbon-based perovskite solar cell with graphitic carbon nitride doped zinc oxide as electron transport layers by Joseph Kariuki, Nicholas Rono, Chinedu Christian Ahia, Eric Kibagendi Osoro, Edson L. Meyer

“…The electron transport layer (ETL) was a blend with ZnO and graphitic carbon nitride, and named GT1, GT3 and GT5 materials in different ratios. The band gap values of the proposed ETL were 3.06, 3.06, 3.10, and 2.97 eV for pure ZnO, GT1, GT3 and GT5 respectively. …”
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Generalisation of EEG-Based Pain Biomarker Classification for Predicting Central Neuropathic Pain in Subacute Spinal Cord Injury by Keri Anderson, Sebastian Stein, Ho Suen, Mariel Purcell, Maurizio Belci, Euan McCaughey, Ronali McLean, Aye Khine, Aleksandra Vuckovic

“…EEG features were extracted based on either band power or Higuchi fractal dimension (HFD). Three levels of generalisability were tested: (1) classification PDP vs. …”
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Event segmentation in ADHD: neglect of social information and deviant theta activity point to a mechanism underlying ADHD by Christian Beste, Veit Roessner, Astrid Prochnow, Xianzhen Zhou, Foroogh Ghorbani, Bernhard Hommel

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Prediction of Winter Wheat Parameters with Planet SuperDove Imagery and Explainable Artificial Intelligence by Gabriele De Carolis, Vincenzo Giannico, Leonardo Costanza, Francesca Ardito, Anna Maria Stellacci, Afwa Thameur, Sergio Ruggieri, Sabina Tangaro, Marcello Mastrorilli, Nicola Sanitate, Simone Pietro Garofalo

“…A SHAP analysis highlighted that GNDVI, Cl1, and NDRE were the most important VIs for predicting RCC, while yellow and red bands were the most important for DM prediction, and yellow and nir bands for RWC prediction. …”
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Accurate estimation of Jujube leaf chlorophyll content using optimized spectral indices and machine learning methods integrating geospatial information by Nigela Tuerxun, Sulei Naibi, Jianghua Zheng, Renjun Wang, Lei Wang, Binbin Lu, Danlin Yu

“…Hyperspectral data enable precise LCC monitoring by extracting spectral indices through optimal band combination (OBC) and predicting LCC with machine learning. …”
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Periodically poled aluminum scandium nitride bulk acoustic wave resonators and filters for communications in the 6G era by Izhar, M. M. A. Fiagbenu, S. Yao, X. Du, P. Musavigharavi, Y. Deng, J. Leathersich, C. Moe, A. Kochhar, E. A. Stach, R. Vetury, R. H. Olsson

“…In the beyond-5G (potential 6G) era, high-frequency bands (>8 GHz) are expected to require resonators with high-quality factor (Q) and electromechanical coupling ( $${k}_{t}^{2}$$ k t 2 ) to form filters with low insertion loss and high selectivity. …”
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A study on the classification of coastal wetland vegetation based on the Suaeda salsa index and its phenological characteristics by Weicheng Huang, Xianyun Fei, Weiwei Yang, Zhen Wang, Yajun Gao, Hong Yan

“…Therefore, in this study, based on the analysis of the spectral separability of Suaeda salsa (S. salsa) and native vegetation, two new Red Suaeda salsa Indices (RSSI and RSSI(1)) were constructed by selecting the red, green and near-infrared bands of the Sentinel 2 multispectral band, and then, based on the sample points, we constructed the RSSI time series and fitted using Fourier function fitting, and extracted (a) Difference Of RSSI (DOR), (b) Sum Of RSSI (SOR), (c) Ratio Of Green-up RSSI (ROGR), and (d) Ratio Of Senescence RSSI (ROSR) from the phenological fitting curve. …”
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The Effect of Spatial Scale on the Prediction of Tropical Forest Attributes from Image Texture by J. Alberto Gallardo-Cruz, Jonathan V. Solórzano, Edgar J. González, Jorge A. Meave

“…The second best-predicted attribute was HSD, which peaked at the intermediate scale. …”
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Forecasting yield and market classes of Vidalia sweet onions: A UAV-based multispectral and texture data-driven approach by Marcelo Rodrigues Barbosa Júnior, Lucas de Azevedo Sales, Regimar Garcia dos Santos, Rônega Boa Sorte Vargas, Chris Tyson, Luan Pereira de Oliveira

“…Similar results appeared for the market class, presenting the best results 45 DBH, through the medium class. Furthermore, texture data emerged as important inputs for both yield and market class forecasting, particularly from NIR and RedEdge bands, respectively. …”
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Optical Properties of DMA-π-DCV Derivatives: A Theoretical Inspection under the DFT Microscope by Joaquín Calbo

“…The hybrid PBE0 (or a similar hybrid analogue) consolidates as the best choice for the prediction of CT excitations in the DMA-π-DCV push-pull family.…”
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A comparative analysis of autograft choices of anterior cruciate ligament reconstruction and their effects on muscle strength and joint biomechanics by Wiem Issaoui, Wiem Issaoui, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Hatem Ghouili, Abdelfatteh El Omri, Noomen Guelmami, Philippe Chomier, Mourad Ghrairi, Helmi Ben Saad, Helmi Ben Saad, Helmi Ben Saad, Wassim Moalla, Wassim Moalla

“…In this study, the effects of four autografts are investigated: Iliotibial band (ITB), combined ITB and hamstring tendon (ITB + HT), hamstring tendon (HT) and bone-tendon-bone (BTB) on quadriceps and hamstring peak torque (QPT and HPT) recovery and hamstring to quadriceps ratio (H:Q) to assess knee stability and function.MethodsForty-two active males (mean ± standard deviation of age: 31.5 ± 6.1 years, height: 177 ± 6 cm, weight: 76 ± 11 kg, body mass index: 24.5 ± 2.2 kg/m²) with primary ACL ruptures were allocated to the four graft groups (ITB: n = 16, ITB + HT: n = 12, HT: n = 7, BTB: n = 7) and underwent a standardized rehabilitation protocol. …”
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Agricultural Drought Assessment using Remote Sensing Data (Case study: Tuyserkan County) by Maedeh Malmir, Kamran Shayesteh, Iman Pazhouhan

“…As a result, the VCI was selected as the best index for monitoring agricultural droughts in the region. …”
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Removal of Fluoride from Aqueous Solutions Using Chitosan Cryogels by Anete Jessica Arcos-Arévalo, Rosa Elvira Zavala-Arce, Pedro Ávila-Pérez, Beatriz García-Gaitán, José Luis García-Rivas, María de la Luz Jiménez-Núñez

“…FTIR results show the characteristic bands of amino and hydroxyl groups, while in the XPS analysis, interactions between iron and oxygen with fluorine were observed. …”
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Applying Randomness Effectively Based on Random Forests for Classification Task of Datasets of Insufficient Information by Hyontai Sug

“…Hence, in this paper, some best classification accuracy based on clever application of random forests to predict the occurrence of cylinder bands in rotogravure printing is investigated. …”
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Monitoring Identification of salt crusts in dry areas by satellite data’s processing by fariba sfanyary, nader sarmasty, sid kazem alavipanah

“…Then , according to the salt crusts’ spectral reflections in different bands and spectral rationing, RSCI (ratio salt crust index) and NDSCI (normalized different salt crust index ) were described. …”
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Integrating Remote Sensing and Soil Features for Enhanced Machine Learning-Based Corn Yield Prediction in the Southern US by Sayantan Sarkar, Javier M. Osorio Leyton, Efrain Noa-Yarasca, Kabindra Adhikari, Chad B. Hajda, Douglas R. Smith

“…Results show that, using random forest method, the V14/VT stage had the best yield predictions (RMSE of 0.52 Mg/ha for a mean yield of 10.19 Mg/ha), and yield estimation at V6 stage was still feasible. …”
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Adsorption isotherms and kinetics of vanadium by shale and coal waste by George William Kajjumba, Serdar Aydın, Sinan Güneysu

“…The adsorption kinetics are best described by pseudo-second order, while Langmuir model fits the adsorption isotherm for both adsorbents. …”
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Gearbox Fault Identification and Classification with Convolutional Neural Networks by ZhiQiang Chen, Chuan Li, René-Vinicio Sanchez

“…Comparing with peer algorithms, the present method exhibits the best performance in the gearbox fault diagnosis.…”
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Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industry by Md Wadud Ahmed, Carlos A. Esquerre, Kristen Eilts, Dylan P. Allen, Scott M. McCoy, Sebastian Varela, Vijay Singh, Andrew D.B. Leakey, Mohammed Kamruzzaman

“…With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. …”
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