Article
Multidisciplinary Sciences
R. Alshenawy, Hanan Haj Ahmad, Ali Al-Alwan
Summary: This paper discusses two prediction methods for predicting the non-observed units under progressive Type-II censored samples, and provides inference on the unknown parameters of the Marshall-Olkin model. Through simulation studies and evaluation on real data examples, the best prediction method is found.
Article
Computer Science, Interdisciplinary Applications
Saubhagya S. Rathore, Grace E. Schwartz, Scott C. Brooks, Scott L. Painter
Summary: In this study, a Bayesian joint-fitting scheme is proposed to calibrate the entire biogeochemical model at once by simultaneously fitting all available datasets using the MCMC method. The joint fitting of datasets allows for complete uncertainty propagation and parameter estimates informed by all available data.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Engineering, Multidisciplinary
Jan Povala, Ieva Kazlauskaite, Eky Febrianto, Fehmi Cirak, Mark Girolami
Summary: Inverse problems involving partial differential equations (PDEs) are commonly used in science and engineering. While Markov Chain Monte Carlo (MCMC) has been the go-to method for sampling from posterior probability measures, it is computationally infeasible for large-scale problems. Variational Bayes (VB) has emerged as a more computationally tractable alternative, approximating posterior distributions with simpler trial distributions. This work presents a flexible and efficient approach to solving inverse problems using VB methods.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Mathematics, Interdisciplinary Applications
Han Gao, Jian-Xun Wang
Summary: This study introduces a novel bi-fidelity ensemble Kalman inversion method for efficient and accurate parameter calibration and field inversion in PDE-constrained inverse problems. By combining the accuracy of high-fidelity models and the efficiency of low-fidelity models, the proposed method shows excellent performance in tackling inverse problems related to fluid dynamics.
COMPUTATIONAL MECHANICS
(2021)
Article
Engineering, Mechanical
J. Ghibaudo, M. Aucejo, O. De Smet
Summary: This paper introduces a novel Bayesian filter for estimating mechanical excitation sources from vibration measurements. The proposed filter unifies most of the state-of-the-art recursive filters developed in the last decade for solving input-state estimation problems. By assuming that the predicted input vector follows a generalized Gaussian distribution, the proposed filter promotes the spatial sparsity of the estimated input vector. Numerical and experimental evaluations show that the proposed filter, called Sparse adaptive Bayesian Filter, outperforms existing filters in terms of input estimation accuracy and avoidance of the drift effect.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Astronomy & Astrophysics
Viola De Renzis, Davide Gerosa, Matthew Mould, Riccardo Buscicchio, Lorenzo Zanga
Summary: The mathematical problem of black-hole binary spin precession is related to systems with black hole spins parallel or antiparallel to the orbital angular momentum. In these systems, the up-down configuration, where the spin of the heavier (lighter) black hole is aligned (counter-aligned) with the orbital angular momentum, might be unstable to small perturbations of the spin directions. The up-down instability gives rise to gravitational wave sources with precessing spins, even if they formed with aligned spins. We propose a Bayesian procedure based on the Savage-Dickey density ratio to test the up-down origin of gravitational-wave events. This procedure is applied to simulated signals and current data from LIGO/Virgo events, indicating that strong evidence is achievable with current experiments, but the current data are not informative enough.
Article
Neurosciences
Chang Cai, Ali Hashemi, Mithun Diwakar, Stefan Haufe, Kensuke Sekihara, Srikantan S. Nagarajan
Summary: The paper proposes several robust methods to estimate the contribution of noise from outside the brain in electromagnetic brain imaging M/EEG data, improving the reconstruction of complex brain source activity. The Champagne algorithm with noise learning shows superior performance in simulations, even without the use of any baseline data.
Article
Astronomy & Astrophysics
Oliver Edy, Andrew Lundgren, Laura K. Nuttall
Summary: This study focuses on using Bayesian inference to extract unknown parameters from gravitational wave signals. The research finds that the posterior of estimated waveform parameters is no longer valid under the assumption of stationary noise, leading to under- or overestimated errors compared to the true posterior. While nonstationarity in short signals has minimal impact on parameter estimation, nonstationary data containing signals lasting tens of seconds or longer will result in significantly worse errors than stationary noise.
Article
Mathematics, Applied
Jonas Latz
Summary: Inverse problems involve blending mathematical models with observational data, and are fundamental in many scientific and engineering disciplines. These problems are typically ill-posed, but can be approached through methodologies such as the variational and Bayesian approach. In this study, the concept of well-posedness is simplified and generalized, with conditions that are significantly weaker than previous assumptions.
Article
Mathematics, Applied
Nikolaj T. Mucke, Benjamin Sanderse, Sander M. Bohte, Cornelis W. Oosterlee
Summary: In the context of solving inverse problems in physics using Bayesian inference, a new approach called Markov Chain Generative Adversarial Neural Network (MCGAN) is proposed to reduce computational costs. By training a GAN to sample from a low-dimensional latent space and incorporating it into a Markov Chain Monte Carlo method, efficient sampling from the posterior distribution is achieved, replacing the need for high-dimensional priors and expensive forward mappings. The proposed methodology converges to the true posterior in Wasserstein-1 distance and sampling from the latent space is weakly equivalent to sampling in the high-dimensional space.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2023)
Article
Astronomy & Astrophysics
Cailin Plunkett, Sophie Hourihane, Katerina Chatziioannou
Summary: This article investigates the parameter estimation for compact binary signals in gravitational waves, comparing traditional sequential estimation method and new full marginalization method. The study finds that, at current detector sensitivities, uncertainty about the noise power spectral density has a minor impact on the parameter estimation.
Article
Environmental Sciences
Hongyuan Jia, Hideki Kikumoto
Summary: This paper proposes a line source estimation method that combines Bayesian inference with the super-Gaussian function, which can effectively estimate the geometric information of pollution sources. Experimental results demonstrate the performance of this method, indicating that geometry estimation is necessary for STE.
ENVIRONMENTAL RESEARCH
(2021)
Article
Computer Science, Theory & Methods
Assyr Abdulle, Giacomo Garegnani, Grigorios A. Pavliotis, Andrew M. Stuart, Andrea Zanoni
Summary: We investigate the problem of drift estimation for two-scale continuous time series. By using filtered data and maximum likelihood estimators, we avoid the traditional subsampling method and demonstrate the asymptotic unbiasedness of the proposed estimators. Furthermore, by combining the filtered data methodology with Bayesian techniques, we provide a complete uncertainty quantification of the inference procedure.
FOUNDATIONS OF COMPUTATIONAL MATHEMATICS
(2023)
Article
Meteorology & Atmospheric Sciences
W. C. Edge, M. D. Rayson, N. L. Jones, G. N. Ivey
Summary: We present a framework for simultaneous parameter estimation in partial differential equations using sparse observations. Markov Chain Monte Carlo sampling is employed in a Bayesian framework to estimate posterior distributions for each parameter. We discuss the essential components of this approach and its wide applicability in modeling unsteady processes. The framework is applied to three case studies in cohesive sediment transport, demonstrating its ability to recover posterior distributions for all desired parameters and its agreement with independent estimates. Furthermore, we show how the framework enables comparison of different parameterizations and offers insights into parameter covariances.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2023)
Article
Thermodynamics
Bo Gao, Qiang Yang, Weizhen Pan, Yumei Ye, Fajun Yi, Songhe Meng
Summary: In this paper, dynamic Bayesian networks were used to solve inverse heat transfer problems with temperature history data. The proposed method effectively identified the parameters through sensitivity analysis and DBN structure optimization, which was validated through numerical and experimental tests.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
(2022)
Article
Electrochemistry
Venkata Sai Sriram Mosali, Linbo Li, Graeme Puxty, Michael D. Horne, Alan M. Bond, Jie Zhang
Summary: In this study, ultrathin Pd nanosheets with a (111) exposed facet were synthesized for CO evolution in a CO2 saturated KHCO3 solution. Cu was introduced into the Pd nanosheets to form CuxPdy alloy nanosheets with (111) exposed planes, which showed competitive CO evolution compared with pure Pd nanosheets. The composition of the CuxPdy alloy played a significant role in determining the nanosheet structure and the product selectivity.
Article
Chemistry, Multidisciplinary
Peng Zhou, Si-Xuan Guo, Linbo Li, Tadaharu Ueda, Yoshinori Nishiwaki, Liang Huang, Zehui Zhang, Jie Zhang
Summary: In this study, highly efficient carbon supported Ni-MoO2 heterostructured catalysts were reported for the electrochemical hydrogenation (ECH) of phenol in 0.10 M aqueous sulfuric acid (pH 0.7) at 60 degrees C. Catalysts with high and low densities of oxygen vacancy (O-v) sites achieved the highest yields of cyclohexanol and cyclohexanone, 95% and 86%, respectively, with faradaic efficiencies of approximately 50%. The enhanced phenol adsorption strength attributed to the O-v density was found to be responsible for the superior catalytic efficiency. This work provides a promising avenue for the rational design of advanced electrocatalysts for the upgrading of phenolic compounds.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2023)
Article
Chemistry, Multidisciplinary
Hoang-Long Du, Karolina Matuszek, Rebecca Y. Hodgetts, Khang Ngoc Dinh, Pavel V. Cherepanov, Jacinta M. Bakker, Douglas R. MacFarlane, Alexandr N. Simonov
Summary: Electrochemical lithium-mediated nitrogen reduction can be used to synthesize ammonia from renewables, but integrating it into electrolyzer devices is challenging due to the lack of understanding of the relationship between performance and proton transport parameters. In this study, a top-performance N-2 electroreduction system was used to investigate the correlation between reaction metrics and proton carrier properties, including alcohols, a phosphonium cation, tetrahydrofuran, a Bronsted acid, ammonium, and water. The study showed that optimized electrolyte compositions are required for productive carriers, and ammonia electrosynthesis with the phosphonium cation and iso-propanol achieved performance close to the ethanol benchmark. It was also found that ethanol undergoes irreversible degradation through reaction with oxidized solvent, unlike iso-propanol and phosphonium cation proton carriers.
ENERGY & ENVIRONMENTAL SCIENCE
(2023)
Article
Biology
Richard Creswell, Martin Robinson, David Gavaghan, Kris Parag, Chon Lok Lei, Ben Lambert
Summary: This article presents a method called EpiCluster for estimating changes in the reproduction number, Rt, of infectious diseases. The method is based on Bayesian nonparametric modeling and can automatically detect rapid changes in transmission rate and provide measures of uncertainty. It has wide applications in epidemiology.
JOURNAL OF THEORETICAL BIOLOGY
(2023)
Article
Chemistry, Physical
Anbrah E. Alzubidi, Alan M. Bond, Lisandra L. Martin
Summary: Published data suggests that sparingly soluble metal complexes of TCNQF1-n, where n=0, 1, 2, 4, can act as heterogeneous catalysts for the slow [Fe(CN)6]3- =4- -S2O2-3/S4O2-6 reaction in water. However, this study shows that the coordination polymer CuTCNQF4 can participate as a homogeneous catalyst through a small concentration of dissolved TCNQF1-4. UV-visible spectrophotometry was used to study the catalysis of the redox reaction in the presence of various catalysts. The findings suggest the need to reevaluate the mechanism of catalysis by TCNQF4 based solids.
Review
Chemistry, Multidisciplinary
Peng Zhou, Jie Zhang
Summary: Replacing conventional fossil resources with renewable raw materials is crucial for achieving carbon neutrality and alleviating the energy crisis. Biomass, due to its natural abundance and ability to fix CO2, is considered a promising candidate for this purpose. Electrochemical conversion of biomass offers advantages such as operating at ambient conditions, scalability, and green generation of equivalents. This review discusses recent progress in electrochemical transformation of biomass, including catalysts, strategies for enhancing efficiency, and mechanistic understanding.
SCIENCE CHINA-CHEMISTRY
(2023)
Article
Chemistry, Multidisciplinary
Thanh Tran-Phu, Manjunath Chatti, Joshua Leverett, Thi Kim Anh Nguyen, Darcy Simondson, Dijon A. Hoogeveen, Alexander Kiy, The Duong, Bernt Johannessen, Jaydon Meilak, Patrick Kluth, Rose Amal, Alexandr N. Simonov, Rosalie K. Hocking, Rahman Daiyan, Antonio Tricoli
Summary: To decrease the cost of hydrogen production and unlock the potential of the hydrogen economy, highly active and durable catalysts for oxygen and hydrogen evolution reactions are needed. This study reports a scalable strategy to prepare doped cobalt oxide electrocatalysts that enhance the activity of these reactions in alkaline conditions. The doping elements increase the bulk conductivity and density of redox active sites without altering the reaction mechanisms. These findings provide insights for engineering Co3O4 as a low-cost material for green hydrogen electrocatalysis at large scales.
Article
Chemistry, Physical
Madhurima Barman, Venkata Sai Sriram Mosali, Alan M. Bond, Jie Zhang, A. Sarkar
Summary: This study investigates the effects of morphology, specific surface area, and relative content of Cu/Cu-oxide in CuO-derived Cu electrocatalysts on the current density and product formation during electrochemical carbon dioxide reduction reaction (eCO(2)RR). The results show that the Cu-content of the CuO-derived Cu electrocatalysts determines the type of products and their corresponding faradic efficiencies, with higher initial Cu-content resulting in higher faradic efficiencies at lower negative potentials. Furthermore, it is found that high Cu-content, regardless of morphology, is particularly important for the formation of methane and formate. Therefore, this study reveals the relative roles of specific surface area and Cu/CuO-content of CuO-derived Cu electrocatalysts on the current densities, product formation, and associated faradic efficiencies in eCO(2)RR.
Article
Chemistry, Physical
Anbrah E. Alzubidi, Alan M. Bond, Lisandra L. Martin
Summary: Mechanistic variation in catalysis through substituent-based redox tuning is well established. Fluorination of TCNQ provides a significant variation in the redox potentials of the TCNQF(n)(0/1-) and TCNQF(n)(1/2-) processes. The catalysis of the ferrocyanide-thiosulfate redox reaction in aqueous solution occurs via different mechanisms depending on the presence of fluorinated or non-fluorinated catalysts. Thermodynamic data explain the observed differences in the catalytic mechanisms for the two systems. CuTCNQF(n) coordination polymers, previously considered as insoluble and heterogeneous catalysts, are shown to act as homogeneous catalysts in the ferricyanide-thiosulfate reaction.
Article
Biochemistry & Molecular Biology
Ruchika Ojha, Peter C. Junk, Alan M. Bond, Glen B. Deacon
Summary: Pt-IV coordination complexes were synthesized by oxidizing the antitumor agent [Pt-II(p-BrC6F4)NCH2CH2NEt2}Cl(py)]. Experimental data showed that excess H2O2 and elevated temperature favored the oxidation of the ligand, while a smaller amount of H2O2 at room temperature favored the oxidation of the metal, resulting in the formation of platinum(IV) complexes.
Article
Materials Science, Multidisciplinary
Thom R. Harris-Lee, Enrico Della Gaspera, Frank Marken, Jie Zhang, Cameron L. Bentley, Andrew L. Johnson
Summary: Aerosol-assisted chemical vapor deposition (AACVD) was used to fabricate highly nanostructured mixed anatase-rutile phase TiO2 using new and bespoke precursors. The precursor syntheses involved two steps and the suitability for AACVD was assessed using thermogravimetric analysis. The resulting TiO2 films showed exceptional OH- oxidation performance and promise for use in photoanodes for water splitting applications.
MATERIALS ADVANCES
(2023)
Article
Chemistry, Physical
Jade Nadine S. Ang, Manjunath Chatti, Khang N. Dinh, Stuart R. Batten, Alexandr N. Simonov, David R. Turner
Summary: When immobilised on an electrode surface, MOFs can effectively enhance the OER for green hydrogen synthesis. This study investigates the potential catalytic effect of a macrocyclic amine core coordinating to cobalt ions. The modified nickel foam electrode sustained a stable OER rate at low overpotential, confirming the transformation of MOF into active cobalt oxyhydroxide.
MOLECULAR SYSTEMS DESIGN & ENGINEERING
(2023)
Review
Medicine, Research & Experimental
Aditi Agrawal, Ken Wang, Liudmila Polonchuk, Jonathan Cooper, Maurice Hendrix, David J. Gavaghan, Gary R. Mirams, Michael Clerx
Summary: The L-type calcium current (ICaL) plays a critical role in cardiac electrophysiology. However, there is a large variability in the predictions of different ICaL models, and it is unclear which model is best suited for specific applications. Further experimental and modeling work is needed to reduce the competing theories and develop a consensus ICaL model.
WIRES MECHANISMS OF DISEASE
(2023)
