Allostery can convert binding free energies into concerted domain motions in enzymes by Nicole Stéphanie Galenkamp, Sarah Zernia, Yulan B. Van Oppen, Marco van den Noort, Andreas Milias-Argeitis, Giovanni Maglia

“…Kinetic analysis validated by hidden Markov models unravels the details of domain motions during catalysis. …”
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Inferential Statistics from Black Hispanic Breast Cancer Survival Data by Hafiz M. R. Khan, Anshul Saxena, Elizabeth Ross, Venkataraghavan Ramamoorthy, Diana Sheehan

“…We specifically focused on Black Hispanic race. Markov Chain Monte Carlo (MCMC) method was used for obtaining the summary results of posterior parameters. …”
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Care home resident identification: A comparison of address matching methods with Natural Language Processing. by Víctor Suárez-Paniagua, Arlene Casey, Charis A Marwick, Jennifer K Burton, Helen Callaby, Isobel Guthrie, Bruce Guthrie, Beatrice Alex

“…The performance of the system exceeds previously reported results such as Postcode matching, Markov score or Phonics score.…”
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Integrated land use land cover-energy modeling framework for solar energy planning in the future expansion areas; the case of Luxor city Region, Egypt by Mohammed Hussien Yadem Lamien, Hooman Farzaneh

“…The model integrates Cellular Automata and Markov chain methods to predict future simulated land use land cover and expansion areas, considering the impact of both physical and neighborhood driving factors. …”
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Influence of Uncertainty of Soil Hydraulic Parameters on Stability of Unsaturated Slopes Based on Bayesian Updating by Hsin-Fu Yeh, Tsien-Ting Huang, Ya-Sin Yang, Chien-Chung Ke

“…Bayesian updating was initially used to update the posterior distribution of the SWRC parameters of the model and in situ soil. Subsequently, a Markov Chain Monte Carlo (MCMC) method was used to generate random samples, and the uncertainty of the parameters was analyzed. …”
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Identifying Copy Number Variants under Selection in Geographically Structured Populations Based on -statistics by Hae-Hiang Song, Hae-Jin Hu, In-Hae Seok, Yeun-Jun Chung

“…A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific FST and can identify outlying CNVs loci with large values of FST. …”
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A hybrid critical channels and optimal feature subset selection framework for EEG fatigue recognition by Hanying Guo, Siying Chen, Yongjiang Zhou, Ting Xu, Yuhao Zhang, Hongliang Ding

“…To minimize redundant information, we propose an improved Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm for selecting the optimal feature subset, ensuring both the efficiency and accuracy of fatigue recognition. …”
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Levels and associated factors for early cessation of EBF among under six month children in Ethiopia by Fassikaw Kebede Bizuneh, Tsehay Kebede Bizuneh

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Contrast-Based 3D/2D Registration of the Left Atrium: Fast versus Consistent by Matthias Hoffmann, Christopher Kowalewski, Andreas Maier, Klaus Kurzidim, Norbert Strobel, Joachim Hornegger

“…Moreover, temporal filtering on the obtained registration results of a sequence is applied using a Markov chain framework. Evaluation was performed on 11 well-contrasted clinical angiographic sequences and 10 additional sequences with less CA. …”
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Continuous Reinforcement Algorithm and Robust Economic Dispatching-Based Spot Electricity Market Modeling considering Strategic Behaviors of Wind Power Producers and Other Particip... by Zhenyu Zhao, Shuguang Yuan, Qingyun Nie, Weishang Guo

“…Because the gradient descent continuous actor-critic algorithm is demonstrated as an effective method in dealing with Markov’s decision-making problems with continuous state and action spaces and the robust economic dispatch model can optimize the permitted real-time wind power deviation intervals based on wind power producers’ bidding power output, in this paper, considering bidding interactions among wind power producers and other participants, we propose a gradient descent continuous actor-critic algorithm-based hour-ahead electricity market modeling approach with the robust economic dispatch model embedded. …”
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A comparison of Bayesian and frequentist confidence intervals in the presence of a late Universe degeneracy by Eoin Ó. Colgáin, Saeed Pourojaghi, M. M. Sheikh-Jabbari, Darragh Sherwin

“…We explain mathematically why this non-Gaussianity arises and show, using observational Hubble data (OHD), that Markov chain Monte Carlo (MCMC) marginalisation leads to 1D posteriors that fail to track the $$\chi ^2$$ χ 2 minimum at $$68\%$$ 68 % confidence level in high redshift bins. …”
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Measurement of population agglomeration, dynamic change characteristics, and motivations in metropolitan agglomerations-A case study of the Xi'an metropolitan area. by Ke Liu, Xu Bo, Wang Zhaoping, Ran Du, Chen Heng

“…The kernel density estimation method and Markov chain model were used to conduct the study. …”
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Energy Management in Microgrids Using Model-Free Deep Reinforcement Learning Approach by Odia A. Talab, Isa Avci

“…The problem is formulated as a Markov Decision Process (MDP) with well-defined objectives. …”
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Finding a New Balance Point: Intelligent Optimization of Multi-Target Cognitive Electronic Reconnaissance Strategy for Unmanned Aerial Vehicles by Yun Zhang, Shixun You, Yunbin Yan, Qiaofeng Ou, Xiang Zhu

“…Finally, a deep reinforcement learning framework based on partially observable Markov processes is built, while a modular scenario pre-training method is used to improve the convergence of the policy network in the case of sparsely distributed high-quality samples. …”
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Reinforcement Learning Based Stochastic Shortest Path Finding in Wireless Sensor Networks by Wenwen Xia, Chong Di, Haonan Guo, Shenghong Li

“…We model the path-finding procedure as a Markov decision process and propose two online path-finding algorithms: Q<italic>_SSP</italic> algorithm and SARSA<italic>_SSP</italic> algorithm, both combined with specifically-devised average reward mechanism. …”
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Real-time monitoring and prediction of remote operator fatigue in plateau deep mining based on dynamic Bayesian networks by Shoukun Chen, Liya Pan, Kaili Xu, Xijian Li, Yujun Zuo, Zheng Zhou, Bin Li, Zhangyin Dai, Zhengrong Li

“…The characteristic data from the physiological signals (ECG, EMG and EM) of 15 driverless electric locomotive operators were tracked and tested continuously in the field for 2 h, and a dynamic fatigue state evaluation model based on a first-order hidden Markov (HMM) dynamic Bayesian network was established. …”
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Performance characteristics of the fork-join queuing system by V. I. Klimenok

“…The functioning of the system is described in terms of a multidimensional Markov chain. A constructive condition for the existence of a stationary distribution is found, and algorithms for calculating the stationary distribution and stationary performance characteristics of the system are proposed. …”
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Intelligent adjustment for power system operation mode based on deep reinforcement learning by Wei Hu, Ning Mi, Shuang Wu, Huiling Zhang, Zhewen Hu, Lei Zhang

“…Considering the characteristics of power flow adjustment, a Markov decision process model suitable for power flow adjustment is constructed. …”
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Dissemination of climate-smart agriculture practices in the Upper West Region of Ghana: insights from local stakeholders and institutions by Stephen Uwumbordo Nachibi, Abdul Wahid Arimiyaw, Eugene Muobom Ganee, Anthony Kwame Morgan

“…Qualitative interviews with farmers and local institutions supporting agriculture in Nandom, Ghana, were conducted. We found that local-level institutions employed (1) farmer-field schools (FFS) for capacity building to provide relevant knowledge for managing CSA practices; and (2) credit extension packages to reduce financial barriers to accessing inputs and technologies for CSA. …”
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A Health Economic Analysis Exploring the Cost Consequence of Using a Surgical Site Infection Prevention Bundle for Hip and Knee Arthroplasty in Germany by Rhodri Saunders, Rafael Torrejon Torres, Henning Reuter, Scott Gibson

“…The perioperative process was modeled using a decision tree, and postoperative recovery and potential SSI evaluated using a Markov model. The model reflects the hospital payers’ perspective in Germany. …”
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