Preliminary insights into the effects of spinal manipulation therapy of different force magnitudes on blood biomarkers of oxidative stress and pro-resolution of inflammation mediat... by Felipe C. K. Duarte, Martha Funabashi, David Starmer, Wania A. Partata

“…Conclusion Despite the small sample size, which elevates the risk of type II error (false negatives), and the interruption of recruitment caused by the pandemic, our findings appeared to indicate that different single SMT force-time characteristics presented contrasting effects on the systemic redox signalling biomarkers and pro-resolution of inflammation mediators in healthy participants. …”
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TREATMENT OF SPASTICITY AND DEGENERATIVE-DYSTROPHIC CHANGES IN MUSCLES IN CHILDREN WITH CEREBRAL PALSY by О. Данилов, О. Шульга

“…Quantitative data were statistically processed using the mean ± standard error (M±m), and statistical significance was determined using Student’s t-test. …”
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Risk coupling analysis of underground gas storage leakage accidents based on dynamic Bayesian network and N-K model by Yao Hu, Zhilong Ding, Liguang Qiao, Feng Gu, Mengqi Yang

“…Additionally, the validation of the proposed model is proven utilizing a three-axiom-based technique.ResultsBy integrating the N-K model’s mutual information metric with DBN’s temporal modeling, the approach achieves a mean absolute error (MAE) of 0.032 in predicting coupling probabilities and enables risk reduction of up to 17.4% through targeted interventions, enhancing the accuracy and actionable insights for UGS safety management. …”
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Lower-Complexity Multi-Layered Security Partitioning Algorithm Based on Chaos Mapping-DWT Transform for WA/SNs by Tarek Srour, Mohsen A. M. El-Bendary, Mostafa Eltokhy, Atef E. Abouelazm, Ahmed A. F. Youssef, Ali M. El-Rifaie

“…The resource limitations of Low-Power Wireless Networks (LP-WNs), such as Wireless Sensor Networks (WSNs), Wireless Actuator/Sensor Networks (WA/SNs), and Internet of Things (IoT) outdoor applications, restrict the utilization of the error-performance-enhancing techniques and the use of the powerful and robust security tools. …”
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A Novel Approach to Generate Large-Scale InSAR-Derived Velocity Fields: Enhanced Mosaicking of Overlapping InSAR Data by Xupeng Liu, Guangyu Xu, Yaning Yi, Tengxu Zhang, Yuanping Xia

“…In addition, a significant improvement of 30% in RMSE reduction was achieved for some tracks.…”
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Evaluation of the influence of hydrodynamic cavitation treatment of dark petroleum products on the yield of fractions with boiling points up to 400°C by B. V. Peshnev, E. V. Burlyaeva, V. B. Terenteva, D. V. Nikishin, A. I. Nikolaev, K. S. Andronov

“…Objectives. The reduction of the anthropogenic burden on the environment is generally associated with the transition to alternative energy sources. …”
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Prediction of moisture content of hummus peach based on multi-burr hyperspectral data by GAO Aidi, QIAO Fengzhang, ZHU Wenxuan, ZHONG Xiaopin, DENG Yuanlong

“…The coefficient of determination (<i>R</i>²) was 0.928, and the root mean square error (RMSE) was 0.008 4 on the training set. The <i>R</i>² was 0.926, and the RMSE was 0.009 2 on the testing set. …”
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Dynamic Simulation of Ground Braking Force Control Based on Fuzzy Adaptive PID for Integrated ABS-RBS System with Slip Ratio Consideration by Pinjia Shi, Yongjun Min, Hui Wang, Liya Lv

“…The proposed control strategy achieves remarkable precision improvements, reducing integral time absolute error (<i>ITAE</i>) by 8.3–52.8% compared to conventional methods. …”
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Research on Newton-Krylov Method for Multi-component Flow Heat Transfer Coupled System of High-temperature Gas-cooled Reactor by TANG Huanran, ZHANG Han, LIU Lixun, PENG Xinru, WU Yingjie, GUO Jiong, LI Fu

“…The correctness of this program was verified by comparison with the high-temperature gas-cooled reactor analysis program TINTE. The maximum error between this program and TINTE is less than 0.1%. …”

On the parametric analytics to investigate hole quality characteristics during helical milling of carbon fiber reinforced plastics stacks by Mehdi Tlija, Nimra Naeem, Mohammad Pervez Mughal, Kiran Mughal, Saad Ullah, Muhammad Sana, Anamta Khan

“…Analysis of variance is used to study the impact of input variables on the hole quality aspects that include delamination damage, length of uncut fiber, circularity error, and surface roughness by using the Taguchi design of experiment. …”
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Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

“…Specifically, it has been demonstrated to achieve a 22.6% reduction in root-mean-square error (RMSE) and a 16.7% decrease in training time when compared to traditional models. …”
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Estimation of the air conditioning energy consumption of a classroom using machine learning in a tropical climate by Liliana Ortega-Diaz, Julian Jaramillo-Ibarra, German Osma-Pinto

“…The evaluation of the models was performed using RMSE, MAE and R2 metrics, to different characteristics and approaches to error measurement. During the training phase, the RFR model achieved a coefficient of determination (R2) of 0.97, while the SVR obtained an R2 of 0.78 in the test phase. …”
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A wavelet-guided transformer approach for autofocus in brightfield biological microscopy by Wangka Yang, Meini Lv, Zhenming Yu, Jiawei Deng

“…Experiments conducted on a locally collected dataset demonstrate that WGT-Net achieves a mean absolute error (MAE) of 0.0869 and a root mean square error (RMSE) of 0.101, achieving 28.69% and 32.39% reductions in MAE and RMSE, respectively, compared with state-of-the-art methods, and completing predictions within milliseconds. …”
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A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm. by Jingnan Yan, Yue Wu, Kexin Ji, Cheng Cheng, Yili Zheng

“…Experimental results demonstrate that, compared to the traditional Gaussian Mixture Model approach, the proposed method improves trajectory accuracy by more than 15%, as shown by reductions in both the Mean Absolute Error and the Root Mean Square Error. …”
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Process-driven strength enhancement and progressive damage analysis of three-dimensional woven composites traction rods by Hao Huang, Zhongde Shan, Yanming Xing, Zitong Guo, Chunguang Yang, Jianhua Liu, Zheng Sun, Xiaohui Ao, Dong Wang, Chenchen Tan, Weihao Wang, Juncheng Luo

“…Experimental validation demonstrated significant performance improvements, including an 18.56% increase in stiffness, a 40.69% enhancement in strength, and a 6.1% reduction in mass. The surrogate model achieved high accuracy across multiple metrics, and the predictive capabilities of the damage model showed a relative error of 13.5% for stiffness and 10.7% for strength. …”
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A Regional Gravimetric and Hybrid Geoid Model in Northern Greece from Dedicated Gravity Campaigns by Georgios S. Vergos, Dimitrios A. Natsiopoulos, Elisavet G. Mamagiannou, Eleni A. Tzanou, Anastasia I. Triantafyllou, Ilias N. Tziavos, Dimitrios Ramnalis, Vassilios Polychronos

“…The final hybrid geoid model, i.e., after the stochastic treatment of the adjusted residuals, gave a std of the difference to the GNSS/leveling data of 1.1 cm, with 99.8% and 99.9% of the height difference being smaller than the 1 cm and 2 cm standard errors, thus achieving a 1 cm accuracy regional geoid.…”
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Mind the HAP: an initiative to improve the diagnosis, management and prevention of hospital-acquired pneumonia on the RBH elderly care wards by Charles McLaren, Apurba Chatterjee, Shabnam Iyer, Thanuja Nanayakkara, Patricia Knight, Tanya Demonne, Oscar Amarille, Amanda Adkins, Ruhel Miah

“…Methods: Retrospective audits revealed diagnostic and coding errors, alongside a dearth of structured preventative measures across the five wards. …”
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Bias Mitigation in Primary Health Care Artificial Intelligence Models: Scoping Review by Maxime Sasseville, Steven Ouellet, Caroline Rhéaume, Malek Sahlia, Vincent Couture, Philippe Després, Jean-Sébastien Paquette, David Darmon, Frédéric Bergeron, Marie-Pierre Gagnon

“…However, these approaches sometimes exacerbated prediction errors across groups or led to overall model miscalibrations. …”
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Perception and Reality of Robotic Microsurgery: A Cross-sectional Comparative User and Nonuser Survey Study by Maximilian Mayrhofer-Schmid, MD, Martin Aman, MD, PhD, Floris V. Raasveld, MD, Wen-Chih Liu, MD, Felix Struebing, MD, Ulrich Kneser, MD, Kyle R. Eberlin, MD, Leila Harhaus, MD, Arne Hendrik Boecker, MD

“…For future indications, users saw significant importance in the role of RMSs in reducing human error. Conclusions:. Our findings underscore the potential of RMSs, drawing a realistic picture of real user experiences and nonuser expectations and highlighting key areas for further technological advancement before broader adoption.…”
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Adaptive Nonlinear Proportional–Integral–Derivative Control of a Continuous Stirred Tank Reactor Process Using a Radial Basis Function Neural Network by Joo-Yeon Lee, Gang-Gyoo Jin, Gun-Baek So

“…For disturbance changes, the proposed method reduced the peak magnitude (<i>M_peak</i>) by 4.9%, recovery time (<i>t_rcy</i>) by 23.6%, and integral absolute error by 16.2%. Similarly, for parameter changes, the reductions were 3.0% (<i>M_peak</i>), 26.4% (<i>t_rcy</i>), and 24.4% (<i>IAE</i>).…”
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