Optical Analysis of Dry Reforming of Methane in Microwave-Induced Plasma at Atmospheric Pressure by Xiuqiang Zhang, Nobusuke Kobayashi, Yoshinori Itaya

“…According to the Boltzmann plot, the relative error of the ion temperature in this study was less than 0.02 when the ion temperature was lower than 10,000 K, and the error corresponding to the highest ion temperature was also less than 0.05, indicating that the temperature of the Ar (II) ion describing a particular energy state can be determined with reasonable accuracy. …”
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Optimal prediction method for CO2 solubility in saline aquifers by DONG Lifei, DONG Wenzhuo, ZHANG Qi, ZHONG Pinzhi, WANG Miao, YU Bo, WEI Haiyu, YANG Chao

“…The average relative errors between the prediction results of the gray GM（1,1） model were 2.37%、19.29%、3.62% and 3.94%, respectively. …”
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Ranking network of a captive rhesus macaque society: a sophisticated corporative kingdom. by Hsieh Fushing, Michael P McAssey, Brianne Beisner, Brenda McCowan

“…The first step simultaneously infers the ranking potentials among all network members, which requires accommodation of heterogeneous measurement error inherent in behavioral data. Our second step estimates the social rank for all individuals by minimizing the network-wide errors in the ranking potentials. …”
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Visual navigation and crop mapping of a phenotyping robot MARS-PhenoBot in simulation by Zhengkun Li, Rui Xu, Changying Li, Longsheng Fu

“…Using this mapping workflow, the average crop localization error was measured at 6.4 cm, primarily caused by the visual odometry drift. …”
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A big data framework for short-term power load forecasting using heterogenous data by Haibo ZHAO, Zhijun XIANG, Linsong XIAO

“…The power system is in a transition towards a more intelligent, flexible and interactive system with higher penetration of renewable energy generation, load forecasting, especially short-term load forecasting for individual electric customers plays an increasingly essential role in future grid planning and operation.A big data framework for short-term power load forcasting using heterogenous was proposed, which collected the data from smart meters and weather forecast, pre-processed and loaded it into a NoSQL database that was capable to store and further processing large volumes of heterogeneous data.Then, a long short-term memory (LSTM) recurrent neural network was designed and implemented to determine the load profiles and forecast the electricity consumption for the residential community for the next 24 hours.The proposed framework was tested with a publicly available smart meter dataset of a residential community, of which LSTM’s performance was compared with two benchmark algorithms in terms of root mean square error and mean absolute percentage error, and its validity has been verified.…”
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Precision evaluation criteria for simulation algorithms in infinite systems: A network model-based approach by Yonglong Ding

“…Employing the Monte Carlo algorithm’s application to the Ising model as a case study, this paper demonstrates that, despite the simulation’s extension to an infinite lattice size, a fundamental error bound persists. This work explicitly derives this lower bound on the error, offering a quantitative understanding of the algorithm’s limitations in the limit of infinite scale. …”
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Low frequency mitochondrial DNA heteroplasmy SNPs in blood, retina, and [RPE+choroid] of age-related macular degeneration subjects. by Shari R Atilano, Nitin Udar, Timothy A Satalich, Viraat Udar, Marilyn Chwa, M Cristina Kenney

“…Finally, high levels of transition mutations suggest that accumulation of heteroplasmic SNPs may occur through replication errors rather than oxidative damage.…”
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Does foreign finance promote the production and consumption of renewable energy in developing countries? The role of globalization by Ebaidalla M. Ebaidalla

“…The study uses advanced panel data methods including Driscoll-Kraay robust standard errors, a method of moments quantile regression (MMQR), and a generalized method of moments (GMM). …”
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Russian Foreign Policy: from “New Thinking” to New Strategic Thinking by M. A. Neimark

“…While studying the changes in the conceptual foundations of Russian foreign policy from its inception to the present day, an important place is occupied by the systematization of factors, circumstances and trends that predetermined the beginning of overcoming mistakes and errors of the 90s and the transition to its doctrinal sovereignty. …”
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Quantitative assessment of lugers’ nutrition in the annual training cycle by Małgorzata Bagińska, Małgorzata Morawska-Tota, Łukasz Tota

“…The dietary errors shown in the study group may affect sports performance. …”
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A siamese neural network model for phase identification in distribution networks by Dong Liu, Juan S. Giraldo, Peter Palensky, Pedro P. Vergara

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ABOUT TWO-STAR GBAS by O. I. Zavalishin

“…The figure shows the implementation of estimation errors for the same record in using all visible and navigational satellites. …”
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Enhancing Smart and Zero-Carbon Cities Through a Hybrid CNN-LSTM Algorithm for Sustainable AI-Driven Solar Power Forecasting (SAI-SPF) by Haytham Elmousalami, Felix Kin Peng Hui, Aljawharah A. Alnaser

“…The hybrid Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model outperformed other models, achieving a Mean Absolute Percentage Error (MAPE) of 2.04%, Root Mean Square Error (RMSE) of 184, Mean Absolute Error (MAE) of 252, and R² of 0.99 for Benban, and an MAPE of 2.00%, RMSE of 190, MAE of 255, and R² of 0.98 for Sakaka. …”
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Quantum Zeno Monte Carlo for computing observables by Mancheon Han, Hyowon Park, Sangkook Choi

“…We introduce Quantum Zeno Monte Carlo (QZMC), a classical-quantum hybrid algorithm that demonstrates resilience to device noise and Trotter errors while showing polynomial computational cost for a gapped system. …”
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Classical Simulability of Quantum Circuits with Shallow Magic Depth by Yifan Zhang, Yuxuan Zhang

“…Surprisingly, with the addition of just one T-gate layer or merely replacing all T gates with T^{1/2}, the Pauli evaluation task reveals a sharp complexity transition from being in P to being GapP-complete. Nevertheless, when the precision requirement is relaxed to 1/poly(n) additive error, we are able to give a polynomial-time classical algorithm to compute amplitudes, Pauli observables, and sampling from log⁡(n)-sized marginal distributions for any magic-depth-1 circuit that is decomposable into a product of diagonal gates. …”
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Prediction of Automotive Wire Harness Aging Based on CNN-biLSTM-Attention by Kun Xia, Qi Zhu, Qingqing Yuan, Jingxia Wang

“…The results show the system achieves a mean absolute error (MAE) of 0.02806, with 32.50% and 62.06% error reduction compared to LSTM and Random Forest models, respectively, demonstrating effective prediction performance.…”
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Nonlinearity of the Fidelity in Open Qudit Systems: Gate and Noise Dependence in High-dimensional Quantum Computing by Jean-Gabriel Hartmann, Denis Janković, Rémi Pasquier, Mario Ruben, Paul-Antoine Hervieux

“…High-dimensional quantum computing has generated significant interest due to its potential to address scalability and error correction challenges faced by traditional qubit-based systems. …”
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De la secció de diari al recull d’articles. El procés de reescriptura d’El dia del senyor de Quim Monzó by Xavier Hernàndez i Garcia

“…This work compares the articles published by Quim Monzó in the early 1980s in the newspaper Avui and its versions published in the collection El dia del senyor (The Day of the Lord) of 1984. The transition from the periodical press to the volume of articles entails a rewriting process that ranges from correcting spelling errors to excision or massive adhesion of text. …”
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Structural Reforms in Agrarian Sector of Economy, Stages and Results: Problems of Modernization and Import Substitution by A. A. Shutkov

“…Conclusions and Relevance: structural reforms in the agricultural sector as a result of errors did not contribute to the sustainable growth of its efficiency, which lead to a sharp decline in production, the country has lost food independence. …”
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Research on Parameter Tuning of Electro-Hydrostatic Actuator Position Sliding Mode Controller Based on Enhanced Dynamic Sand Cat Search Optimization Algorithm by Weibo Li, Shuai Cao, Xiaoqing Deng, Junjie Chen, Hao Zhang

“…Simulation validations conducted on the combined platform of MATLAB/Simulink and AMESim demonstrate that the sliding mode PID controller optimized by the EDSCSO algorithm achieves smaller steady-state and tracking errors, exhibits greater robustness, and offers enhanced computational efficiency compared to other swarm intelligence optimization algorithms. …”
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