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23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020

作者： Noble, Stephanie Scheinost, Dustin Department of Radiology and Biomedical Imaging Yale University New HavenCT United States Department of Biomedical Engineering Yale University New HavenCT United States Department of Statistics and Data Science Yale University New HavenCT United States Interdepartmental Neuroscience Program Yale University New HavenCT United States Child Study Center Yale University New HavenCT United States

ISBN: (纸本)9783030597276

Neuroimaging research aimed at dissecting the network organization of the brain is poised to flourish under major initiatives, but converging evidence suggests more accurate inferential procedures are needed to promote discovery. Inference is typically performed at the cluster level with a network-based statistic (NBS) that boosts power by leveraging known dependence within the local neighborhood. However, existing NBS methods overlook another important form of dependence—shared membership in large-scale brain networks. Here, we propose a new level of inference that pools information within predefined large-scale networks: the Constrained Network-Based Statistic (cNBS). We evaluated sensitivity and specificity of cNBS against existing standard NBS and threshold-free NBS by resampling task data from the largest openly available fMRI database: the Human Connectome Project. cNBS was most sensitive to effect sizes below medium, which accounts for the majority of ground truth effects. In contrast, threshold-free NBS was most sensitive to higher effect sizes. Ground truth maps showed grouping of effects within large-scale networks, supporting the relevance of cNBS. All methods controlled FWER as intended. In summary, cNBS is a promising new level of inference for promoting more valid inference, a critical step towards more reproducible discovery in neuroscience. © 2020, Springer Nature Switzerland AG.

关键词： statistics

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Air Pollution Steady-State Advection-Diffusion Equation: The General Three-Dimensional Solution

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Journal of Environmental Protection 2012年第9期3卷 1124-1134页

作者： Daniela Buske Marco Túllio Vilhena Tiziano Tirabassi Bardo Bodmann Department of Mathematics and Statistics (IFM/DME) Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program in Mechanical Engineering Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Institute of Atmospheric Sciences and Climate (ISAC) National Research Council (CNR) Bologna Italy

Atmospheric air pollution turbulent fluxes can be assumed to be proportional to the mean concentration gradient. This assumption, along with the equation of continuity, leads to the advection-diffusion equation. Many models simulating air pollution dispersion are based upon the solution (numerical or analytical) of the advection-diffusion equation as- suming turbulence parameterization for realistic physical scenarios. We present the general steady three-dimensional solution of the advection-diffusion equation considering a vertically inhomogeneous atmospheric boundary layer for arbitrary vertical profiles of wind and eddy-diffusion coefficients. Numerical results and comparison with experimental data are shown.

关键词： Advection-Diffusion Equation Analytical Solution Laplace Transform Air Pollution Modeling Atmospheric Boundary Layer Eulerian Models

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In-silico structural and functional analysis of nonsynonymous single nucleotide polymorphisms in human FOLH1 gene

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In silico pharmacology 2025年第1期13卷 32页

作者： Abtin Tondar Muhammad Irfan Sergio Sánchez-Herrero Hafsa Athar Aleena Haqqi Asim Kumar Bepari Laura Calvet Liñán David Hervás Marin Department of Computer Science Multimedia and Telecommunication Interuniversity Doctoral Program in Bioinformatics Universitat Oberta de Catalunya Barcelona (UOC) Spain. Stanford Deep Data Research Center Stanford University Stanford USA. Atta-Ur-Rahman School of Applied Biosciences (ASAB) National University of Sciences and Technology (NUST) Islamabad Punjab Pakistan. School of Medical Laboratory Technology Minhaj University Lahore (MUL) Lahore Punjab Pakistan. Department of Pharmaceutical Sciences North South University (NSU) Dhaka Bangladesh. Telecommunications and Systems Engineering Department Universitat Autònoma de Barcelona (UAB) Sabadell Spain. Department of Applied Statistics and Operational Research and Quality Alcoy Universitat Politècnica de València (UPV) Alcoy Spain.

Non-synonymous single nucleotide polymorphisms (nsSNPs), also known as missense SNPs, can seriously affect an individual’s vulnerability to numerous diseases, including cancer. In this study, we conducted a comprehensive in-silico analysis to examine the structural and functional implications of nsSNPs within the Folate Hydrolase 1(FOLH1) gene, which encodes the Prostate-Specific Membrane Antigen (PSMA). A total of 504 SNPs were retrieved, and after filtering, 15 pathogenic nsSNPs were identified using five different in-silico tools. Three of these SNPs—R255H (rs375565491), R255C (rs201789325), and G168E (rs267602926)—were consistently predicted to be pathogenic across all in-silico tools. MutPred2 was used to predict the structural and functional consequences of the identified mutations. The analysis revealed multiple alterations in the PSMA protein, including changes in helical conformations, glycosylation patterns, transmembrane properties, and solvent accessibility. Furthermore, I-Mutant 2.0 analysis demonstrated a decrease in protein stability for most nsSNPs, except for rs267602926 (G168E), which was predicted to increase stability. Conservation analysis using ConSurf revealed varying degrees of amino acid conservation, with R255H and R255C identified as highly conserved residues, indicating their potential functional and structural significance. Additionally, post-translational modification (PTM) analysis indicated that while phosphorylation and methylation sites remained unchanged, specific glycosylation sites were lost in two pathogenic mutant variants (R255H and R255C), potentially affecting PSMA function and adversely impacting prostate cancer. Our findings highlight the importance of in silico studies to investigate the structural and functional impacts of FOLH1 nsSNPs on the PSMA protein. Such in silico studies can deepen our understanding of the roles of nsSNPs in prostate cancer onset, progression, and drug resistance.

关键词： FOLH1 In-silico structural and functional analyses PSMA PTM nsSNPs

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Forecasting electricity prices using a RBF neural network With GARCH errors

Forecasting electricity prices using a RBF neural network Wi...

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International Joint Conference on Neural Networks (IJCNN)

作者： Andre Alves Portela Santos Leandro dos Santos Coelho Carlos Eduardo Klein Department of Statistics Universidad Carlos III de Madrid Spain Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba Parana Brazil CNPq National Council for Scientific and Technological Development Brazil

In this article, we propose a nonlinear forecasting model based on radial basis function neural networks (RBF-NNs) with Gaussian activation functions and robust clustering algorithms to model the conditional mean and a parametric generalized autoregressive conditional heteroskedasticity (GARCH) specification to model the conditional volatility. Instead of calibrating the parameters of the RBF-NNs via numerical simulations, we propose a novel estimation procedure by which the number of basis functions, their corresponding widths and the parameters of the GARCH model are jointly estimated via maximum likelihood along with a genetic algorithm to maximize the likelihood function. We use this model to provide hour-ahead point and direction-of-change forecasts of the Spanish electricity pool prices.

关键词： Load modeling Artificial neural networks Predictive models

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Anticipatory monitoring and control of complex energy systems using a fuzzy based fusion of support vector regressors

Anticipatory monitoring and control of complex energy system...

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International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： Miltiadis Alamaniotis Vivek Agarwal Tatjana Jevremovic Nuclear Engineering Program The University of Utah Salt Lake City UT USA Department of Human Factors Controls and Statistics Idaho National Laboratory Idaho Falls ID USA University of Utah Salt Lake City UT US

This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are then inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.

关键词： Monitoring Support vector machines Turbines Control systems Fuzzy logic Predictive models Degradation

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Fractional Integrable Nonlinear Soliton Equations

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Physical Review Letters 2022年第18期128卷 184101-184101页

作者： Mark J. Ablowitz Joel B. Been Lincoln D. Carr Department of Applied Mathematics University of Colorado Boulder Colorado 80309 USA Department of Applied Mathematics and Statistics Colorado School of Mines Golden Colorado 80401 USA Department of Physics Colorado School of Mines Golden Colorado 80401 USA Quantum Engineering Program Colorado School of Mines Golden Colorado 80401 USA

Nonlinear integrable equations serve as a foundation for nonlinear dynamics, and fractional equations are well known in anomalous diffusion. We connect these two fields by presenting the discovery of a new class of integrable fractional nonlinear evolution equations describing dispersive transport in fractional media. These equations can be constructed from nonlinear integrable equations using a widely generalizable mathematical process utilizing completeness relations, dispersion relations, and inverse scattering transform techniques. As examples, this general method is used to characterize fractional extensions to two physically relevant, pervasive integrable nonlinear equations: the Korteweg–deVries and nonlinear Schrödinger equations. These equations are shown to predict superdispersive transport of nondissipative solitons in fractional media.

关键词： Solitons

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Environment, krill and squid in the Monterey Bay: From fisheries to life histories and back again

Environment, krill and squid in the Monterey Bay: From fishe...

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作者： Ish, Teresa Dick, E.J. Switzer, Paul V. Mangel, Marc Graduate Program in Marine Sciences University of California Santa Cruz CA United States Dept. of Ecol. and Evol. Biology University of California Santa Cruz CA United States Department of Biological Sciences Eastern Illinois University Charleston IL United States Dept. of Appl. Math. and Statistics The Jack Baskin Sch. of Engineering University of California 95064 Santa Cruz CA United States

The fishery for market squid in California is extremely valuable and only recently subject to regulations (in that sense, it is one of the last great open-access fisheries on the western coast of North America). We briefly review the history of the fishery for Loligo opalescens, on an annual time scale. Within-season analyses suggest that cohorts of squid persist offshore and move inshore for reproduction throughout the season. In order to predict the timing of inshore movement of squid, we develop a life history model using stochastic dynamic programming. This model allows us to link squid growth and reproduction with environmental factors, particularly, upwelling, temperature, and food abundance, in a consistent Darwinian framework. Using the model, we predict the timing of squid movement inshore in cold and warm environments, and the amount of biomass inshore in weekly intervals. We compare the model predictions with unpublished fishery-dependent data subsampled from landings and discuss the implications of our work for management of the squid fishery. © 2004 Elsevier Ltd. All rights reserved.

关键词： Oceanography

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Genetic variant analysis of boys with Autism: A pilot study on linking facial phenotype to genotype

Genetic variant analysis of boys with Autism: A pilot study ...

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2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

作者： Obafemi-Ajayi, Tayo Settles, Luke Su, Yuqing Germeroth, Cynthia Olbricht, Gayla R. Wunsch, Donald C. Takahashi, T. Nicole Miles, Judith Engineering Program Missouri State University Springfield MO United States Mathematics and Statistics Dept. Missouri University of Science and Technology RollaMO United States Information Technology Missouri University of Science and Technology RollaMO United States Electrical and Computer Eng. Dept. Missouri University of Science and Technology RollaMO United States Thompson Center for Autism and Neurodevelopmental Disorders ColumbiaMO United States

ISBN: (纸本)9781509030491

This work examines the validity of facial phenotypes as Autism Spectrum Disorders (ASD) biomarkers in boys with essential autism. A family-based association analysis framework is presented that uses previously identified facially-delineated (FD) clusters to examine relationship between FD clusters and known ASD genes. The hypothesis is that there are certain genetic variants, single nucleotide polymorphisms (SNP), specific to the FD clusters. Although statistical significance was not established, the results identified some candidate SNPs unique to each of the FD clusters that could indicate an underlying etiological difference. Further, recommendations are provided for larger-scale studies that could utilize the analysis framework presented. © 2017 IEEE.

关键词： Biomarkers

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The Small-World Effect for Interferometer Networks

arXiv

引用

arXiv 2023年

作者： Krawciw, Benjamin Carr, Lincoln D. Behn, Cecilia Diniz Department of Applied Mathematics and Statistics Colorado School of Mines GoldenCO United States Department of Physics Colorado School of Mines GoldenCO United States Quantum Engineering Program Colorado School of Mines GoldenCO United States

Complex network theory has focused on properties of networks with real-valued edge weights. However, in signal transfer networks, such as those representing the transfer of light across an interferometer, complex-valued edge weights are needed to represent the manipulation of the signal in both magnitude and phase. These complex-valued edge weights introduce interference into the signal transfer, but it is unknown how such interference affects network properties such as small-worldness. To address this gap, we have introduced a small-world interferometer network model with complex-valued edge weights and generalized existing network measures to define the interferometric clustering coefficient, the apparent path length, and the interferometric small-world coefficient. Using high-performance computing resources, we generated a large set of small-world interferometers over a wide range of parameters in system size, nearest-neighbor count, and edge-weight phase and computed their interferometric network measures. We found that the interferometric small-world coefficient depends significantly on the amount of phase on complex-valued edge weights: for small edge-weight phases, constructive interference led to a higher interferometric small-world coefficient;while larger edge-weight phases induced destructive interference which led to a lower interferometric small-world coefficient. Thus, for the small-world interferometer model, interferometric measures are necessary to capture the effect of interference on signal transfer. This model is an example of the type of problem that necessitates interferometric measures, and applies to any wave-based network including quantum networks. Copyright © 2023, The Authors. All rights reserved.

关键词： Interferometers

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Forgery blind inspection for detecting manipulations of gel electrophoresis images

arXiv

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arXiv 2020年

作者： Shao, Hao-Chiang Cheng, Ya-Jen Duh, Meng-Yun Lin, Chia-Wen Dept. Statistics and Information Science Fu Jen Catholic University Taiwan Office of Neuroscience Program of Academia Sinica Institute of Molecular Biology Academia Sinica Taiwan Dept. Electrical Engineering National Tsing Hua University Taiwan

Recently, falsified images have been found in papers involved in research misconducts. However, although there have been many image forgery detection methods, none of them was designed for molecular-biological experiment images. In this paper, we proposed a fast blind inquiry method, named FBIGEL, for integrity of images obtained from two common sorts of molecular experiments, i.e., western blot (WB) and polymerase chain reaction (PCR). Based on an optimized pseudo-background capable of highlighting local residues, FBIGEL can reveal traceable vestiges suggesting inappropriate local modifications on WB/PCR images. Additionally, because the optimized pseudo-background is derived according to a closed-form solution, FBIGEL is computationally efficient and thus suitable for large scale inquiry tasks for WB/PCR image integrity. We applied FBIGEL on several papers questioned by the public on PUBPEER, and our results show that figures of those papers indeed contain doubtful unnatural patterns. Copyright © 2020, The Authors. All rights reserved.

关键词： Polymerase chain reaction

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