Development of a Force Feedback Controller with a Speed Feedforward Compensator for a Cable-Driven Actuator by Juan Fang, Michael Haldimann, Bardia Amiryavari, Robert Riener

“…Inclusion of the speed feedforward compensator improved the force control accuracy, resulting in a mean error at various speeds of 5.6 N. …”
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Comprehensive analysis of glycometabolism-related genes reveals PLOD2 as a prognostic biomarker and therapeutic target in gastric cancer by Wanchun Ye, Xiaolei Zhang, Zhongjie Tang, Yufeng Hu, Yuanliang Zheng, Yuping Yuan

“…Targeting PLOD2-mediated pathways may represent a promising strategy for precision therapy and improved clinical outcomes in gastric cancer.…”
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Accuracy Evaluation of Multi-Technique Combination Nonlinear Terrestrial Reference Frame and EOP Based on Singular Spectrum Analysis by Qiuxia Li, Xiaoya Wang, Yabo Li

“…The results show that the accuracy and stability of the newly established a nonlinear TRF and EOP based on SSA have been greatly improved and better than a linear TRF and EOP. SSA is better than least squares fitting, especially for those coordinate residual time series with varying amplitude and phase. …”
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THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTS by Viacheslav Osadchyi, Maksym Pavlenko, Liliia Pavlenko, Oleksii Sysoiev, Vladyslav Kruglyk

“…Empirical data confirm the high accuracy of AI-generated forecasts, sometimes surpassing that of humans, and indicate improved professional productivity when AI is used effectively. …”
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Remote sensing reveals the role of forage quality and quantity for summer habitat use in red deer by Thomas Rempfler, Christian Rossi, Jan Schweizer, Wibke Peters, Claudio Signer, Flurin Filli, Hannes Jenny, Klaus Hackländer, Sven Buchmann, Pia Anderwald

“…Results The combination of vegetation indices and optical traits greatly improved predictive power in both the biomass (R2 = 0.60, Root mean square error (RMSE) = 88.55 g/m2) and relative nitrogen models (R2 = 0.34, RMSE = 0.28%). …”
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Prediction of Cover–Subsidence Sinkhole Volume Using Fibre Bragg Grating Strain Sensor Data by Wesley B. Richardson, Suné von Solms, Johan Meyer, Charis Harley

“…It was found that statistical techniques and machine-learning algorithms that assume normality are inappropriate when performing phase classification and volume regression tasks on the cover–subsidence sinkhole when given fibre Bragg grating sensor’s strain data. …”
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Thermal comfort and energy related occupancy behavior in Dutch residential dwellings by Anastasios Ioannou

“…National and European level policies the past decades have improved the quality of the building stock by setting stricter standards on the external envelope of newly made buildings, the efficiency of the mechanical and heating components, the renovation practices and by establishing an energy labelling system. …”
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Deteksi Dan Klasifikasi Hama Potato Beetle Pada Tanaman Kentang Menggunakan YOLOV8 by Daniel Geoffrey Manurung, Mohammad Ryan Pinasthika, Muhammad Azka Obila Vasya, Rania Aprilia Dwi Setya Putri, Agustinus Parasian Tampubolon, Rakan Fadhil Prayata, Septia Khoirin Nisa, Novanto Yudistira

“…However, there is room for improvement in mAP50-95 to measure detection accuracy at stricter levels. …”
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First trimester circulating miR-208b-3p and miR-26a-1-3p are relevant to the prediction of gestational hypertension by Andrée-Anne Clément, Cécilia LÉGARÉ, Véronique Desgagné, Kathrine Thibeault, Frédérique White, Michelle S. Scott, Pierre-Étienne Jacques, William D Fraser, Patrice Perron, Renée Guérin, Marie-France Hivert, Anne-Marie Côté, Luigi Bouchard

“…The addition of miR-208b-3p, and miR-26a-1-3p to the model significantly improves the prediction performance over that of MAP alone (p = 0.03). …”
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Spatial Information of Somatosensory Stimuli in the Brain: Multivariate Pattern Analysis of Functional Magnetic Resonance Imaging Data by In-Seon Lee, Won-mo Jung, Hi-Joon Park, Younbyoung Chae

“…Identification of distinct neural patterns of body surfaces will help in improving neural biomarkers for pain and other sensory percepts in the future.…”
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Recommendations for All-Round Newborns and Infants Hearing Screening in Russian Federation by S. S. Chibisova, G. S. Tufatulin, L. S. Namazova-Baranova, I. V. Koroleva, E. R. Tsygankova, T. G. Markova, N. N. Volodin, G. A. Tavartkiladze

“…Moreover, audiologic screening system for newborns and infants should be revised in every region to identify the reasons of mismatch with international standards and to find ways of its efficacy improvement. Objective. The aim of the study is to increase the efficacy of Russian program of all-round newborns and infants hearing screening. …”
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Sistem Kontrol Swarm untuk Flocking Wahana NR-Awak Quadrotor dengan Optimasi Algoritma Genetik by Endra Joelianto, Winarendra Satya Rajasa, Agus Samsi

“…Whereas when parameters ,  and  are searched using GA, it does not have much effect in improving the quadrotor swarm simulation results. …”
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RETRACTED: Gyrotactic Motile Microorganisms Impact on Pseudoplastic Nanofluid Flow over a Moving Riga Surface with Exponential Heat Flux by Hassan Waqas, Mowffaq Oreijah, Kamel Guedri, Sami Ullah Khan, Song Yang, Sumeira Yasmin, Muhammad Ijaz Khan, Omar T. Bafakeeh, El Sayed Mohamed Tag-ElDin, Ahmed M. Galal

“…<b><i>Background:</i></b> The improvement of the thermal conductivity of nanofluids is practical for different processes such as drug delivery, manufacturing of crystals, polymer processing, food and drink, cancer treatment, oil and gas, paper making and for many more. …”
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Analyzing the impact of area of interest (AOI) size and endmember selection on evapotranspiration (ET) estimation through a contextual model (SEBAL) by Hamza Barguache, Jamal Ezzahar, Jamal Elfarkh, Said Khabba, Salah Er-Raki, Valerie Le Dantec, Mohamed Hakim Kharrou, Ghizlane Aouade, Abdelghani Chehbouni

“…Contextual models such as the Surface Energy Balance Algorithm for Land (SEBAL) are particularly valuable for ET estimation. …”
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Intraoperative Nerve Mapping and Visualization System: Optimal Neurological Function Preservation in Schwannoma Surgery by Wenjianlong Zhou, Xiaoyi Shi, Qin Xu, Xiangxiang Liu, Junshi Li, Hui Qiao, Lirui Yang, Baowang Li, Liangpeng Chen, Yuan Zhang, Xiudong Guan, Shunchang Ma, Zhongyan Wang, Linhao Yuan, Jiang Li, Tieqiang Zhang, Deling Li, Dong Huang, Zhihong Li, Wang Jia

“…While intraoperative neuromonitoring (IONM) has improved surgical outcomes, it offers an indirect assessment of neural structures and functions. …”
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Reinforcement Learning Solutions for Microgrid Control and Management: A Survey by Pedro I. N. Barbalho, Anderson L. Moraes, Vinicius A. Lacerda, Pedro H. A. Barra, Ricardo A. S. Fernandes, Denis V. Coury

“…Having an appropriate design, MG controllers improve energy efficiency, playing a vital role in the modern distribution system. …”
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The new era of artificial intelligence in neuroradiology: current research and promising tools by Fabíola Bezerra de Carvalho Macruz, Ana Luiza Mandetta Pettengil Dias, Celi Santos Andrade, Mariana Penteado Nucci, Carolina de Medeiros Rimkus, Leandro Tavares Lucato, Antônio José da Rocha, Felipe Campos Kitamura

“…If well designed, AI algorithms have the potential to radically improve radiology, strengthening image analysis, enhancing the value of quantitative imaging techniques, and mitigating diagnostic errors.…”
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Advancements in Medical Radiology Through Multimodal Machine Learning: A Comprehensive Overview by Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman, Zuhal Y. Hamd, Zhe Liu

“…By extracting novel characteristics from diverse medical data sources, advanced identification techniques known as multimodal learning may be applied, enabling algorithms to analyze data from various sources and eliminating the need to train each modality. …”
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Identifying potential three key targets gene for septic shock in children using bioinformatics and machine learning methods by Wei Guo, Hao Chen, Feng Wang, Yingjiao Chi, Wei Zhang, Shan Wang, Kezhu Chen, Hong Chen

“…Early prediction of the risk of death in children with septic shock is helpful for clinicians to judge the severity of the disease, take active treatment measures, and improve the adverse outcomes of patients. However, the mechanism of death from sepsis in children remains unclear. …”
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Machine learning for the prediction of mortality in patients with sepsis-associated acute kidney injury: a systematic review and meta-analysis by Xiangui Lv, Daiqiang Liu, Xinwei Chen, Lvlin Chen, Xiaohui Wang, Xiaomei Xu, Lin Chen, Chao Huang

“…The results showed that the machine learning algorithms had a good performance in predicting sepsis-related acute kidney injury death prediction. …”
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