Differentiating biomarker features and familial characteristics of B-SNIP psychosis Biotypes by David A. Parker, Rebekah L. Trotti, Jennifer E. McDowell, Sarah K. Keedy, Matcheri S. Keshavan, Godfrey D. Pearlson, Elliot S. Gershon, Elena I. Ivleva, Ling-Yu Huang, Kodiak Sauer, S. Kristian Hill, John A. Sweeney, Carol A. Tamminga, Brett A. Clementz

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Towards gridded nighttime aerosol optical thickness retrievals using VIIRS day–night band observations over regions with artificial light sources by J. Zhang, J. S. Reid, B. T. Sorenson, S. D. Miller, M. O. Román, Z. Wang, Z. Wang, R. J. D. Spurr, S. Jaker, T. F. Eck, T. F. Eck, J. I. Rubin

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Diagnostic informative value of liquid-based cytology optimized with genetic methods for the differential diagnosis of precancerous and malignant diseases of the cervix by O. I. Kit, A. Yu. Maksimov, M. Yu. Timoshkova, E. A. Lukbanova, N. A. Petrusenko, D. S. Potemkin, E. V. Verenikina, A. N. Shevchenko, M. M. Kecheryukova

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Modeling Wetland Biomass and Aboveground Carbon: Influence of Plot Size and Data Treatment Using Remote Sensing and Random Forest by Tássia Fraga Belloli, Diniz Carvalho de Arruda, Laurindo Antonio Guasselli, Christhian Santana Cunha, Carina Cristiane Korb

“…Larger plots produced smaller prediction errors with S2 models, indicating the influence of plot size on the reliability of the estimate. …”
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Improving Electrical Stimulation Effectiveness and Versatility for Non-Invasive Transdermal Monitoring Applications via an Innovative Mixed-Signal Electronic Interface by Alessandro Zompanti, Davide Ciarrocchi, Simone Grasso, Riccardo Olivieri, Giuseppe Ferri, Marco Santonico, Giorgio Pennazza

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Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer by J.-S. Chou, H.-M. Nguyen, H.-P. Phan, K.-L. Wang

“…The AEIO–MobileNet model precisely predicts imminent deep-seated landslide displacement with a mean absolute percentage error (MAPE) of 2.81 %. These advancements significantly enhance geohazard informatics by providing reliable and efficient tools for landslide risk assessment and management. …”
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Analysis of Reaction between α-Lipoic Acid and 2-Chloro-1-methylquinolinium Tetrafluoroborate Used as a Precolumn Derivatization Technique in Chromatographic Determination of α-Lip... by Magdalena Godlewska, Angelika Odachowska, Monika Turkowicz, Joanna Karpinska

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Effects of internal tides on GNSS-A seafloor crustal deformation observation by Yusuke Yokota, Tadashi Ishikawa, Shun-ichi Watanabe, Koya Nagae, Yuto Nakamura, Eiji Masunaga

“…Abstract Internal tides are crucial in ocean dynamics and are a source of error in marine acoustic measurements. In Global Navigation Satellite System-Acoustic combination technique (GNSS-A) seafloor crustal deformation observations, which contribute to earthquake and plate subduction sciences, the effect of internal tides has never been estimated, even though it has been predicted. …”
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Design of Online Electric Power Monitoring For Street Vendors by Endang Sri Rahayu, Puteri Nurul Magfirah, Reza Diharja

“…The objective of this research is to develop an online power monitoring system for street vendors based on RFID sensors and Telegram. …”
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Bridge Cable Performance Warning Method Based on Temperature and Displacement Monitoring Data by Yan Shi, Yan Wang, Lu-Nan Wang, Wei-Nan Wang, Tao-Yuan Yang

“…Correlation analysis revealed a strong linear correlation between air temperature and quasi-static tower-girder displacements. This research proposes to use the tower-girder distance (effective cable length) to represent the length of the cable, take the thermal expansion coefficient of the effective length of the cable as the quantitative index for long-term monitoring, and take its error as the performance early warning indicator. …”
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Targeted Data Augmentation for Improving Model Robustness by Mikołajczyk-Bareła Agnieszka, Ferlin Maria, Grochowski Michał

“…By randomly inserting identified biases into training samples, we demonstrated that TDA significantly reduced bias measures by two times to more than 50 times, with only a negligible increase in the error rate. We performed our research on three model families: EfficientNet, DenseNet and Vision Transformer.…”
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Design and Construction of IoT-Based Overvoltage and Undervoltage Detection Devices by Luki Septya Mahendra, Putu Agus Mahadi Putra, Agus Dinantya Dwi Kurniawan, Hendik Eko Hadi Suharyanto, Lucky Pradigta Setiya Raharja, Yahya Chusna Arif

“…The data displayed by the monitoring system is compared with the Fluke 43B measuring instrument to be calibrated, with an average error of 1.2%. Monitoring data can be accessed via gadgets. …”
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Analysis of double side ironless permanent magnet linear synchronous machine with low normal force by Xinghua He, Qixin Sun, Liang Yan, Pengjie Xiang, Tao Zheng

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On QoS evaluation for ZigBee incorporated Wireless Sensor Network (IEEE 802.15.4) using mobile sensor nodes by Vishal Kumar Arora, Vishal Sharma, Monika Sachdeva

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Validation of Depth-Averaged Flow Model Using Flat-Bottomed Benchmark Problems by Il Won Seo, Young Do Kim, Chang Geun Song

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An Affordable Low-Cost Wearable Solution for Object Detection in Visual Impairment by Swami Siddharth, Singh Rajesh, Dhyani Saurabh, Rathi Garima, Kumar Shah Sanjeev, Ghalwan Manish, Yamsani Nagendar

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Nonlinear Decoupling Study of Six-Axis Acceleration Sensor Based on Improved BP Neural Network by Jialin Zhang, Chunzhan Yu, Chengxin Du, Zhe Hao, Zhibo Sun

“…Aiming at the problem of nonlinear coupling error in the measurement of parallel six-axis accelerometers, this study improves the back propagation (BP) neural network and proposes an improved BP neural network decoupling model that introduces the gradient descent with momentum and the Levenberg–Marquardt (LM) algorithm. …”
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Hyperparameter Optimization of Neural Networks Using Grid Search for Predicting HVAC Heating Coil Performance by Yosef Jaber, Pasidu Dharmasena, Adam Nassif, Nabil Nassif

“…The best-performing model achieved a mean squared error of 0.469 and featured 17 hidden layers, a left-triangle architecture trained for 500 epochs with a learning rate of 5 × 10⁻⁵, and Adam as the optimizer. …”
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Unravelling urban carbon dynamics: a multi-source data study on Nanchang city's carbon dioxide emissions by Lingyun Yao, Li Wang, Ke Wang, Zheng Niu

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Reconstruction of U.S. Regional-Scale Soybean SIF Based on MODIS Data and BP Neural Network by YAO Jianen, LIU Haiqiu, YANG Man, FENG Jinying, CHEN Xiu, ZHANG Peipei

“…Leveraging these inherent nonlinear relationships, compared and analyzed the effects of different combinations of explanatory variables on SIF reconstruction, mainly analyzing the three indicators of goodness of fit R2, root mean square error RMSE, and mean absolute error MAE, and then selecting the best SIF reconstruction model, generate a regional scale, spatially continuous, and high temporal resolution (500 m, 8 d) soybean SIF reconstruction dataset (BPSIF).…”
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