Effect of Hematopoietic Stem Cell Transplantation Regimen on Tacrolimus Pharmacokinetics by Haruno Oku, BS, Saki Yoshida, BS, Takumi Hotta, BS, Hirohito Muroi, BS, Keizo Fukushima, PhD, Kei Irie, PhD, Tatsuya Hirano, BS, Yoshimitsu Shimomura, MD, Takayuki Ishikawa, MD, PhD, Hiroaki Ikesue, PhD, Nobuyuki Muroi, PhD, Tohru Hashida, PhD, Nobuyuki Sugioka, PhD

“…Whole-blood tacrolimus concentrations were accurately captured (n = 1,658 measurements) using a one-compartment and additive error model. The conditioning regimen and donor source did not have an impact on the pharmacokinetics of tacrolimus. …”
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Ensemble Computational Intelligent for Insomnia Sleep Stage Detection via the Sleep ECG Signal by Pragati Tripathi, M. A. Ansari, Tapan Kumar Gandhi, Rajat Mehrotra, Md Belal Bin Heyat, Faijan Akhtar, Chiagoziem C. Ukwuoma, Abdullah Y. Muaad, Yasser M. Kadah, Mugahed A. Al-Antari, Jian Ping Li

“…The traditional insomnia detection methods are time-consuming, cumbersome, and more expensive because they demand a long time from a trained neurophysiologist, and they are prone to human error, hence, the accuracy of diagnosis gets compromised. …”
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Accelerated discovery and testing of Fe–Co–Cr–Ni–Mo ferrous medium-entropy alloys: advanced in-situ alloying via direct energy deposition by Jae Heung Lee, Ji Yeong Lee, Bon Woo Koo, Dae-Kyeom Kim, Jungwan Lee, Eun Seong Kim, Hyojeong Ha, Taek-Soo Kim, Hyoung Seop Kim

“…Traditional trial-and-error alloy design methods have reached their limitations due to the growing complexity of alloy systems such as high-entropy alloys (HEAs). …”
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Comparing sparse inertial sensor setups for sagittal-plane walking and running reconstructions by Eva Dorschky, Marlies Nitschke, Matthias Mayer, Ive Weygers, Heiko Gassner, Heiko Gassner, Thomas Seel, Bjoern M. Eskofier, Bjoern M. Eskofier, Anne D. Koelewijn, Anne D. Koelewijn

“…Mean RMSDs were highest for the setup with two foot-worn inertial sensors (largest error in knee angle during running: 18 deg vs. 11 deg for the full lower-body setup), and ranged between 4.8–18 deg for the joint angles, between 1.0–5.4 BW BH% for the joint moments, and between 0.03 BW–0.49 BW for the ground reaction forces. …”
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Detecting Anomalies in Attributed Networks Through Sparse Canonical Correlation Analysis Combined With Random Masking and Padding by Wasim Khan, Mohammad Ishrat, Ahmad Neyaz Khan, Mohammad Arif, Anwar Ahamed Shaikh, Mousa Mohammed Khubrani, Shadab Alam, Mohammed Shuaib, Rajan John

“…Approaches utilizing the reconstruction error rely on straightforward, simple mappings, which introduce a substantial risk of overfitting in high-dimensional data, wherein the model acquires patterns that are exclusive to the training data and fails to generalize to new data. …”
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Adversarial denoising of EEG signals: a comparative analysis of standard GAN and WGAN-GP approaches by Imad Eddine Tibermacine, Samuele Russo, Francesco Citeroni, Giuseppe Mancini, Abdelaziz Rabehi, Amal H. Alharbi, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Christian Napoli, Christian Napoli, Christian Napoli

“…Specifically, WGAN-GP achieved an SNR of up to 14.47 dB (compared to 12.37 dB for the standard GAN) and exhibited greater training stability, as evidenced by consistently lower relative root mean squared error (RRMSE) values. In contrast, the conventional GAN model excelled in preserving finer signal details, reflected in a PSNR of 19.28 dB and a correlation coefficient exceeding 0.90 in several recordings. …”
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Nanoscale Organic Contaminant Detection at the Surface Using Nonlinear Bond Model by Hendradi Hardhienata, Muhammad Ahyad, Fasya Nabilah, Husin Alatas, Faridah Handayasari, Agus Kartono, Tony Sumaryada, Muhammad D. Birowosuto

“…Our simulations show good agreement with rotational anisotropy (RA) SHG intensity experimental data across all polarization angles, with a total error estimate of 3%. We find for the first time that the SBHM not only identifies the different organic pollutant dyes on the surface, as in conventional SHG detection, but can also determine their relative orientation and different concentrations on the surface. …”
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Development and Validation of a Brain Aging Biomarker in Middle-Aged and Older Adults: Deep Learning Approach by Zihan Li, Jun Li, Jiahui Li, Mengying Wang, Andi Xu, Yushu Huang, Qi Yu, Lingzhi Zhang, Yingjun Li, Zilin Li, Xifeng Wu, Jiajun Bu, Wenyuan Li

“…Model performance was evaluated using mean absolute error (MAE) against benchmark models, while generalization capability was further validated on an external UK Biobank dataset. …”
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Modeling the compressive strength behavior of concrete reinforced with basalt fiber by Kennedy C. Onyelowe, Ahmed M. Ebid, Shadi Hanandeh, Viroon Kamchoom, Paul Awoyera, Siva Avudaiappan

“…Abstract This research investigates the compressive strength behavior of basalt fiber-reinforced concrete (BFRC) using machine learning models to optimize predictions and enhance its practical applications. The study incorporates various modeling techniques, including Artificial Neural Networks (ANN), k-Nearest Neighbors (KNN), Support Vector Machines (SVM), Decision Trees, and Random Forest (RF), to evaluate their predictive capabilities. …”
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Evaluating Degenerative Lumbar Disease with Markerless 3D Motion Capture: Reliability and Validity in Sit-to-Stand Test by Yi-Ting Huang, Szu-Hua Chen, Chao-Ying Chen, Shiu-Min Wang, Pei-Yuan Wu, Dar-Ming Lai, Wei-Li Hsu

“…Concurrent validity and agreement between VICON and MediaPipe were evaluated via Pearson/Spearman correlation coefficients, systematic bias, and the root mean square error (RMSE). Movement time, joint excursions, and angular velocities were also analyzed and compared across two groups. …”
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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

“…Although MAE was slightly higher, the overall error control remained within an acceptable range, validating the model’s stability and effectiveness. …”
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A 3×3 Antenna Beamforming Network Based on Waveguide Nolen Matrix for Ka-Bands by Hatem Oday Hanoosh, Mohamad Kamal A. Rahim, Noor Asniza Murad, Yaqdhan Mahmood Hussein

“…Therefore, this beamforming has a greater impact on the mm wave beamforming networks and applications.…”
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Nonlinear Dynamical Model and Analysis of Emotional Propagation Based on Caputo Derivative by Liang Hong, Lipu Zhang

“…The numerical accuracy of the fractional system is further verified through L1 discretization, with observed error convergence consistent with theoretical expectations for <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>μ</mi><mo>=</mo><mn>0.5</mn></mrow></semantics></math></inline-formula>. …”
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On the hydrostatic approximation in rotating stratified flow by A. Wirth

“…</p> <p>Calculating the difference of the two projection-evolution operators, the expression of the error, scaling and prefactors done by the hydrostatic approximation is obtained. …”
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Inverse Dynamic Parameter Identification for Remote Sensing of Soil Moisture From SMAP Satellite Observations by Runze Zhang, Adam Watts, Mohamad Alipour

“…The results demonstrated that the incorporation of dynamic <italic>h</italic> and &#x03C9; parameters, derived on a daily scale, markedly enhanced the soil moisture retrieval performance with an average unbiased root-mean-square error (ubRMSE) of 0.01 (0.02) m³&#x002F;m³ and Pearson correlation (<italic>R</italic>) of 0.95 (0.90) for the SCA (RDCA) algorithms, indicating that dynamic parameterization holds significant promise for improving retrieval accuracy. …”
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Fitts’ law-based identification of motor development stages for the upper limb: proof of concept in three age groups by Cristina Sanchez, Eloy Urendes, Alejandra Aceves, María Martínez-Olagüe, Rafael Raya

“…From an Information Theory perspective, throughput (TP) reflects processing speed in reaching tasks, while error rate (ER) quantifies incorrect selections. …”
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Can we rely on artificial intelligence to guide antimicrobial therapy? A systematic literature review by Sulwan AlGain, Alexandre R. Marra, Takaaki Kobayashi, Pedro S. Marra, Patricia Deffune Celeghini, Mariana Kim Hsieh, Mohammed Abdu Shatari, Samiyah Althagafi, Maria Alayed, Jamila I Ranavaya, Nicole A. Boodhoo, Nicholas O. Meade, Daniel Fu, Mindy Marie Sampson, Guillermo Rodriguez-Nava, Alex N. Zimmet, David Ha, Mohammed Alsuhaibani, Boglarka S. Huddleston, Jorge L. Salinas

“…Six studies focused on large language models to guide antimicrobial therapy; they had higher prescribing error rates, patient safety risks, and needed precise prompts to ensure accurate responses. …”
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Fading Evaluation in Standardized 5G Millimeter-Wave Band by Tiago Reis Rufino Marins, Andre Antonio Dos Anjos, Carlos Rafael Nogueira Da Silva, Vicent Miquel Rodrigo Penarrocha, Lorenzo Rubio, Juan Reig, Rausley Adriano Amaral De Souza, Michel Daoud Yacoub

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Scalable estimation of speciated volatile organic compound composition in the upstream natural gas sector by Sebastian T Rowland, Jeremy K Domen, Jasmine Lee, Quintin Munoz, Jessie M Jaeger, Sofia Bisogno, Chowdhury Moniruzzaman, Nick Heath, Christos Efstathiou, Seth B C Shonkoff, Lee Ann L Hill, Kelsey R Bilsback

“…Our models of non-flash benzene:methane molar ratios empirically demonstrated low bias (normalized mean error <10%) and moderate precision (24%–45% variance explained) when infrastructure and unspeciated gas composition (methane and C6+ fraction) data were available, with lower precision when facility-specific unspeciated composition data is unavailable. …”
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Handling of missing component information for common composite score outcomes used in axial spondyloarthritis research when complete-case analysis is unbiased by Christos Polysopoulos, Stylianos Georgiadis, Lykke Midtbøll Ørnbjerg, Almut Scherer, Daniela Di Giuseppe, Merete Lund Hetland, Michael John Nissen, Gareth T. Jones, Bente Glintborg, Anne Gitte Loft, Johan Karlsson Wallman, Karel Pavelka, Jakub Závada, Ayten Yazici, Maria José Santos, Adrian Ciurea, Burkhard Möller, Brigitte Michelsen, Pawel Mielnik, Johanna Huhtakangas, Heikki Relas, Katja Perdan Pirkmajer, Ziga Rotar, Ross MacDonald, Bjorn Gudbjornsson, Irene van der Horst-Bruinsma, Marleen van de Sande, Myriam Riek

“…However, since MI is susceptible to incorrect implementation and its performance may become questionable with increasing missingness, we consider the implementation of an error-free CC approach a valid and valuable option. …”
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