Cross-cultural adaptation of the Activities of Daily Living Questionnaire-Brazil in Parkinson’s disease by Walter Luis Teixeira ALVES, Iza de FARIA-FORTINI, Ana Carolina Daher Ribas GALVÃO, Francisco Eduardo Costa CARDOSO, Paula Luciana SCALZO

“…The limits of agreement were verified using the Bland-Altman plot. The standard error of measurement (SEM) and the minimum detectable change (MDC) were calculated. …”
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The use of modern long-acting hormonal contraceptives: relevance, demand and concerns. Debunking myths by Yu. A. Sorokin

“…At the same time, modern research leaves no doubt that the effectiveness of hormonal releasing systems reaches the highest level not only due to the active component, but also due to adherence to the method, eliminating the factor of ″unforced user error″, i.e. due to the lack of need for control over use by the woman.Results. …”
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Approaches for Localizing the Origin of PVCs in the Outflow Tract: Future Perspectives and Challenges by Baiping Sui, Yingjie Ji, Ying Wang, Ling Gao, Minghao Li

“…To mitigate these influences, combining this approach with imaging modalities such as cardiac MRI, CT, and echocardiography can help identify structural abnormalities at the foci of premature ventricular contractions (PVCs), thereby enhancing the precision of IVA localization. To decrease human error and achieve more efficient PVC localization, algorithmic analysis and anatomical modeling with computer-based methods have emerged as promising new approaches. …”
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Robustness Maximization of Parallel Multichannel Systems by Jean-Yves Baudais, Fahad Syed Muhammad, Jean-François Hélard

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End-to-end seismic signals denoising via deep residual convolution and self-attention mechanisms by ZHAO Botao, KANG Zuheng, HE Yayun, PENG Junqing, ZHANG Xulong, QU Xiaoyang, TAN Yipei, CHEN Yule, XIAO Chunguang, WANG Jianzong

“…Denoising of seismic waveform signals is crucial for seismic monitoring and seismological research. To this end, we propose an end-to-end deep learning method for denoising seismic waveforms. …”
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CNReader: a reading practice tool designed for Chinese children with developmental dyslexia by Lijuan Liu, Tuo Fang, Enmao Liu, Shang Shi, Shuo Zhai, Yang Chen, Lingyan Zhang, Yan Shi, Cheng Yao

“…Results demonstrated that CNReader significantly reduced reading error rates, enhanced reading fluency, and improved comprehension. …”
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Time Domain Similarity of Lightweight Parameters Based Soil Respiration Sensor Network Deployment by Guoying Wang, Lufeng Mo, Jizhong Zhao, Chaoqi Zhang

“…The experimental results show that TimSim method can place nodes to proper positions so as to monitor regional soil respiration carbon flux effectively with a smaller estimation error than uniform and random deployment methods.…”
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Phacoemulsification and calculation of intraocular lenses in patients given keratorefractive surgery. Part 2 by I. E. Ioshin

“…Effective rehabilitation of patients with cataracts who underwent keratorefractive surgeries requires that the optical power of the IOL be calculated correctly to avoid hyperopic error. The purpose of the 2nd part of the research (for the 1st part, see ROJ, 2021; 14 (2): 55–58) is to present the results of cataract phacoemulsification in patients subjected to keratorefractive surgery based on the author’s algorithm for calculating the optical power of the IOL. …”
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Mathematical models and ANFIS for determination of diffusivity and activation energy of button mushroom thin layer drying by Maryam Karimi Motlagh, Babak Beheshti, Ali Mohammad Borghei, Mohammad Gholami Parashkoohi

“…In this research, four temperature levels of 50, 60, 70, and 80 °C with a constant airflow rate of 1 (m/s). …”
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Retinal Vessel Segmentation Using Math-Inspired Metaheuristic Algorithms by Mehmet Bahadır Çetinkaya, Sevim Adige

“…Finally, detailed convergence analyses were also carried out in terms of the convergence speed, mean squared error (MSE), CPU time, and number of function evaluations (NFEs) metrics.…”
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Influence of Rice Husk Ash on Crystalline Phases and Mechanical Characteristics of Sustainable Bricks by F. Booth, M.B. Carranza, G. Novak, N. Okulik, A. Mocciaro, N. Rendtorff

“…Several models were analyzed to predict the elastic modulus, and the DEM model provided the best predictions, with a relative error of 1.43% for 15% RHA. The analysis of mechanical properties of porosity was conducted using various theoretical models, which allowed for a better understanding of the relationship between the porous structure of the bricks and their mechanical behavior. …”
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A Novel Method Combining Radial Projection with Simultaneous Multislice Imaging for Measuring Cerebrovascular Pulse Wave Velocity by Jeong-Min Shim, Chang-Ki Kang, Young-Don Son

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Experimental Determination of a Reflective Muffler Scattering Matrix for Single-Mode Excitation by Łukasz GORAZD

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Multilingual Prediction of Cognitive Impairment with Large Language Models and Speech Analysis by Felix Agbavor, Hualou Liang

“…Results: Our model achieved unweighted average recall of 81.83% in an MCI classification task, and root mean squared error of 1.196 in cognitive score prediction task, which placed the model at the second and the first position, respectively, in the ranking for each task. …”
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Locally differentially private continuous location sharing with randomized response by Xingxing Xiong, Shubo Liu, Dan Li, Jun Wang, Xiaoguang Niu

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Indirect Determination of the Internal Diameter of Glass Conical Volumetric Instruments by Omar Jair Purata Sifuentes

“…Findings: Comparing the direct measurement of the internal diameter of the volumetric instruments with an optical comparator, there is an average relative error below 10 %, with a maximum value below 20 % for the two different conical glass instruments studied. …”
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Logging Components Extraction Method and Anisotropy Recognition Based on 3D Holographic LWD Instrument by Shuyu Guo, Jie Wang, Xiangyu Xing, Jiaqi Xiao, Xiao Liu

“…By employing the same inversion method, the anisotropy coefficients calculated from the new signal will be more accurate than those derived from traditional signals, with the developed signal inversion average error controllable within 0.01.…”
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Survey of Deep Learning and Machine Learning Approaches for Major Depressive Disorder Detection Using EEG Data by Sumathi Balakrishnan, Raja Kumar Murugesan, Eng Lye Lim, Amna Faisal, Humaira Ashraf

“…Traditionally, MDD is diagnosed using clinical examinations and self-report questionnaires, both of which are subjective and susceptible to error. Recent advances in electroencephalogram (EEG) analysis have combined physiological markers with machine learning (ML) and deep learning (DL) techniques, offering objective, noninvasive alternatives for MDD detection. …”
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Improved Remote Photoplethysmography Using Machine Learning-Based Filter Bank by Jukyung Lee, Hyosung Joo, Jihwan Woo

“…The proposed approach was validated with an open dataset, achieving a 35.5% (i.e., resulting in a mean absolute error of 2.5 beats per minute) higher accuracy than those of conventional methods. …”
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Random Forest-Based Machine Learning Model Design for 21,700/5 Ah Lithium Cell Health Prediction Using Experimental Data by Sid-Ali Amamra

“…In this research, the use of machine learning techniques for predicting the state of health (SoH) of 5 Ah—21,700 lithium-ion cells were explored; data from an experimental aging test were used to build the prediction model. …”
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