Second-round effects of food prices on core inflation in Turkey by Türken Fatma, Yildirim Mustafa Ozan

“…Incorporating domestic and international macroeconomic variables, the model identifies second-round effects by imposing theory-based constraints and leveraging Bayesian methods. Results reveal that core inflation reacts strongly to food price shocks, with rising food prices worsening inflation expectations and amplifying second-round effects on overall inflation. …”
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Shale Fracture Static Stability Evaluation Method Based on 3D Discrete Fracture Model: A Case Study on the Luzhou Area in Southern Sichuan Basin, SW China by Ruhua Zhang, Cheng Yin, Jianping Huang

“…In this article, seismic geometric attributes were calculated, and fracture seismic facies was established by means of the Bayesian probabilistic cluster analysis method. Then, 3D discrete fracture modeling under the constraint of fracture seismic facies was performed to establish a discrete fracture model. …”
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Enhancing catch-based stock assessment in data-limited fisheries with proxy CPUE indicators in the Yellow Sea by Kun Wang, Qi Li, Chongliang Zhang, Binduo Xu, Yiping Ren

“…These indicators were incorporated into a Bayesian state-space Schaefer surplus production model (BSM) and their performance was compared to catch-only methods (CMSY) across key evaluation criteria, including robustness of estimation, reliability in retrospective analyses, and performance when encountering catch observation errors. …”
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The rarity of mutations and the inflation of bacterial effective population sizes by Rui Borges

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Improving the Minimum Free Energy Principle to the Maximum Information Efficiency Principle by Chenguang Lu

“…Friston proposed the Minimum Free Energy Principle (FEP) based on the Variational Bayesian (VB) method. This principle emphasizes that the brain and behavior coordinate with the environment, promoting self-organization. …”
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Virtual reality-augmented differentiable simulations for digital twin applications in surgical planning by Robin Cremese, Charlotte Godard, Alexis Bénichou, Thomas Blanc, Iwan Quemada, Christian L. Vestergaard, Bassam Hajj, Alex Barbier–Chebbah, François Laurent, Jean-Baptiste Masson

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An Entropy Dynamics Approach to Inferring Fractal-Order Complexity in the Electromagnetics of Solids by Basanta R. Pahari, William Oates

“…The approach uses an information-theoretic method by combining Shannon’s entropy with fractional moment constraints in time and space. …”
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Comment on “Opinion: Can uncertainty in climate sensitivity be narrowed further?” by Sherwood and Forest (2024) by N. Lewis

“…This comment also discusses the role of priors in Bayesian ECS estimation and explains why the subjective Bayesian approach favoured by SF24 can often produce unreliable inference for uncertain parameters such as ECS. …”
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Intelligent Clustering and Adaptive Energy Management in Wireless Sensor Networks with KDE-Based Deployment by Mainak Kundu, Ria Kanjilal, Ismail Uysal

“…Simulation results demonstrate significant improvements in performance, including over 35% extension in network lifetime and higher coverage retention under energy constraints, compared to baseline methods such as LEACH and K-LEACH. …”
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Approaching maximum resolution in structured illumination microscopy via accurate noise modeling by Ayush Saurabh, Peter T. Brown, J. Shepard Bryan IV, Zachary R. Fox, Rory Kruithoff, Cristopher Thompson, Comert Kural, Douglas P. Shepherd, Steve Pressé

“…Such methods therefore suffer from high-frequency artifacts, user-dependent choices of smoothness constraints making assumptions on biological features, and unphysical negative values in the recovered fluorescence intensity map. …”
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Data-driven discovery and parameter estimation of mathematical models in biological pattern formation. by Hidekazu Hishinuma, Hisako Takigawa-Imamura, Takashi Miura

“…This method allows for parameter estimation under minimal constraints; i.e., it does not require time-series data or initial conditions and is applicable to various types of mathematical models. …”
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Stereo Online Self-Calibration Through the Combination of Hybrid Cost Functions with Shared Characteristics Considering Cost Uncertainty by Wonju Lee

“…To extend the problem to the spatiotemporal domain, Bayesian filtering is applied using the logit of zero-shot-based semantic segmentation. …”
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Deterministic and statistical calibration of constitutive models from full-field data with parametric physics-informed neural networks by David Anton, Jendrik-Alexander Tröger, Henning Wessels, Ulrich Römer, Alexander Henkes, Stefan Hartmann

“…However, monitoring is usually associated with severe time constraints, difficult to meet with standard numerical approaches. …”
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Normalizing flow-assisted nested sampling on Type-II Seesaw model by Rajneil Baruah, Subhadeep Mondal, Sunando Kumar Patra, Satyajit Roy

“…We present the results of our detailed Bayesian exploration of the model parameter space subjected to theoretical constraints and experimental data corresponding to the 125 GeV Higgs boson, $$\rho $$ ρ -parameter, and the oblique parameters. …”
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Toward reliable fluorescence imaging: Optical prior-guided probabilistic reconstruction for structured illumination microscopy by Kun Lin, Junkang Dai, Huaian Chen, Yi Jin

“…Here we present PG-SIM, a probabilistic SIM reconstruction method based on Bayesian neural networks and incorporating graph representation learning (GRL) to model optical prior knowledge. …”
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A New Evidential Reasoning Rule Considering Evidence Correlation with Maximum Information Coefficient and Application in Fault Diagnosis by Shanshan Liu, Guanyu Hu, Shaohua Du, Hongwei Gao, Liang Chang

“…Existing correlation processing methods fail to comprehensively address both linear and nonlinear correlations inherent in such heterogeneous evidence systems. …”
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Evaluation of prior probability distribution of undrained cohesion for soil in Nasiriyah by Ressol Shakir

“…Estimated PPD of Cu can be used in Bayesian approach to update the observed value in any project in this region using the posterior probability distribution, because it is considered as a measure of the initial belief about a random variable before considering any data. …”
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Multiframe Superresolution of Vehicle License Plates Based on Distribution Estimation Approach by Renchao Jin, Shengrong Zhao, Xiangyang Xu, Enmin Song

“…In order to assure the success of the SR reconstruction, the models representing smoothness constraints on images are also used to regularize the estimated HR image with the proposed feature-specific prior model. …”
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Using the Mid‐Holocene “Greening” of the Sahara to Narrow Acceptable Ranges on Climate Model Parameters by Peter O. Hopcroft, Paul J. Valdes, William Ingram

“…One possible explanation is the presence of systematic biases in the representations of atmospheric convection which might also impact future projections. We employ a Bayesian method to learn from an ensemble of present day and mid‐Holocene simulations that vary parameters in the convection, boundary layer and cloud schemes. …”
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Multi-state models: metapopulation and life history analyses by A. N. Arnason, E. Cam

“…Our call for papers for this session also invited papers illustrating multi– population meta–analysis and use of Bayesian methods. By these criteria, their paper is no outlier. …”
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