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Spectral neighbor joining for reconstruction of latent tree models

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arXiv 2020年

作者： Jaffe, Ariel Amsel, Noah Nadler, Boaz Chang, Joseph T. Kluger, Yuval Program in Applied Mathematics Yale University New HavenCT06511 United States Department of Computer Science Weizmann Institute of Science Rehovot76100 Israel Department of Statistics Yale University New HavenCT06520 United States Interdepartmental Program in Computational Biology and Bioinformatics New HavenCT06511 Singapore Department of Pathology New HavenCT06511 United States

A key assumption in multiple scientific applications is that the distribution of observed data can be modeled by a latent tree graphical model. An important example is phylogenetics, where the tree models the evolutionary lineages of various organisms. Given a set of independent realizations of the random variables at the leaves of the tree, a common task is to infer the underlying tree topology. In this work we develop Spectral Neighbor Joining (SNJ), a novel method to recover latent tree graphical models. In contrast to distance based methods, SNJ is based on a spectral measure of similarity between all pairs of observed variables. We prove that SNJ is consistent, and derive a sufficient condition for correct tree recovery from an estimated similarity matrix. Combining this condition with a concentration of measure result on the similarity matrix, we bound the number of samples required to recover the tree with high probability. We illustrate via extensive simulations that SNJ requires fewer samples to accurately recover trees in regimes where the tree contains a large number of leaves or long edges. We provide theoretical support for this observation by analyzing the model of a perfect binary tree. Copyright © 2020, The Authors. All rights reserved.

关键词： Recovery

Mentalizing imagery therapy for depressed family dementia caregivers: Feasibility, clinical outcomes and brain connectivity changes

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Journal of Affective Disorders Reports 2021年 5卷 100155-100155页

作者： Jain, Felipe A. Chernyak, Sergey Nickerson, Lisa Abrams, Michelle Iacoboni, Marco Christov-Moore, Leonardo Connolly, Colm G. Fisher, Lauren B. Sakurai, Hitoshi Bentley, Kate Tan, Emily Pittman, Michael Lavretsky, Helen Leuchter, Andrew F. Depression Clinical and Research Program Department of Psychiatry Massachusetts General Hospital Harvard Medical School Boston MA United States Applied Neuroimaging Statistics Laboratory McLean Hospital Harvard Medical School Belmont MA United States Semel Institute for Neuroscience and Human Behavior University of California Los Angeles CA United States Department of Biomedical Sciences College of Medicine Florida State University Tallahassee FL United States

Background: Family dementia caregivers experience high rates of depression and anxiety that often go untreated due to time demands. We aimed to determine the feasibility of a brief, 4-week Mentalizing Imagery Therapy intervention, which couples mindfulness with guided imagery practices aimed at bolstering mentalizing capacity, to reduce caregiver psychological symptoms and to explore potential impact on dorsolateral prefrontal cortex connectivity. Methods: Twenty-four family dementia caregivers with moderate depression symptoms (a score of 10 in Patient Health Questionnaire-9) were assigned to either group Mentalizing Imagery Therapy (MIT, n = 12) or a waitlist augmented by optional relaxation exercises (n = 12). Participants completed questionnaires to measure depression and anxiety at baseline and followup, and those eligible also underwent resting state functional magnetic resonance (fMRI) brain imaging at these time points. Results: Eleven of 12 caregivers assigned to MIT completed the intervention and attended weekly groups 98% of the time. MIT home practice logs indicated average practice of 5 ± 2 sessions per week for 23±8 min per session. All participants in waitlist completed the post-assessment. MIT participants exhibited significantly greater improvement than waitlist on self-reported depression and anxiety symptoms (p<.05) after 4 weeks. Neuroimaging results revealed increased dorsolateral prefrontal cortex connectivity with a putative emotion regulation network in the MIT group (p=.05) but not in waitlist (p = 1.0). Limitations: Sample size limitations necessitate validation of findings in larger, randomized controlled trials. Conclusions: A 4-week group MIT program was feasible for caregivers, with high levels of participation in weekly group meetings and home practice exercises. © 2021

关键词： Dementia Depression Family caregivers Mindfulness Neuroimaging

Integrability of Goldilocks quantum cellular automata

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arXiv 2024年

作者： Hillberry, Logan E. Piroli, Lorenzo Vernier, Eric Halpern, Nicole Yunger Prosen, Tomaž Carr, Lincoln D. Department of Physics The University of Texas at Austin AustinTX78712 United States Dipartimento di Fisica e Astronomia Università di Bologna INFN Sezione di Bologna via Irnerio 46 BolognaI-40126 Italy Laboratoire de Probabilités Statistique et Modélisation CNRS Université Paris Cité Sorbonne Université Paris France Joint Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States Faculty of Mathematics and Physics University of Ljubljana Jadranska 19 LjubljanaSI-1000 Slovenia Institute of Mathematics Physics and Mechanics Jadranska 19 LjubljanaSI-1000 Slovenia Quantum Engineering Program Colorado School of Mines GoldenCO80401 United States Department of Physics Colorado School of Mines GoldenCO80401 United States Department of Applied Mathematics and Statistics Colorado School of Mines GoldenCO80401 United States

Goldilocks quantum cellular automata (QCA) have been simulated on quantum hardware and produce emergent small-world correlation networks. In Goldilocks QCA, a single-qubit unitary is applied to each qubit in a one-dimensional chain subject to a balance constraint: a qubit is updated if its neighbors are in opposite basis states. Here, we prove that a subclass of Goldilocks QCA—including the one implemented experimentally—map onto free fermions and therefore can be classically simulated efficiently. We support this claim with two independent proofs, one involving a Jordan–Wigner transformation and one mapping the integrable six-vertex model to QCA. We compute local conserved quantities of these QCA and predict experimentally measurable expectation values. These calculations can be applied to test large digital quantum computers against known solutions. In contrast, typical Goldilocks QCA have equilibration properties and quasienergy-level statistics that suggest nonintegrability. Still, the latter QCA conserve one quantity useful for error mitigation. Our work provides a parametric quantum circuit with tunable integrability properties with which to test quantum hardware. © 2024, CC BY.

关键词： Qubits

On the cross-validation bias due to unsupervised preprocessing

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arXiv 2019年

作者： Moscovich, Amit Rosset, Saharon Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Department of Statistics and Operations Research Tel-Aviv University Tel-Aviv Israel

Cross-validation is the de facto standard for predictive model evaluation and selection. In proper use, it provides an unbiased estimate of a model's predictive performance. However, data sets often undergo various forms of data-dependent preprocessing, such as mean-centering, rescaling, dimensionality reduction, and outlier removal. It is often believed that such preprocessing stages, if done in an unsupervised manner (that does not incorporate the class labels or response values) are generally safe to do prior to cross-validation. In this paper, we study three commonly-practiced preprocessing procedures prior to a regression analysis: (i) variance-based feature selection;(ii) grouping of rare categorical features;and (iii) feature rescaling. We demonstrate that unsupervised preprocessing can, in fact, introduce a substantial bias into cross-validation estimates and potentially hurt model selection. This bias may be either positive or negative and its exact magnitude depends on all the parameters of the problem in an intricate manner. Further research is needed to understand the real-world impact of this bias across different application domains, particularly when dealing with small sample sizes and high-dimensional *** Codes 62-07 Copyright © 2019, The Authors. All rights reserved.

关键词： Regression analysis

Levels and trends in the sex ratio at birth in seven provinces of Nepal between 1980 and 2016 with probabilistic projections to 2050: A Bayesian modeling approach

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arXiv 2020年

作者： Chao, Fengqing Samir, K.C. Ombao, Hernando Statistics Program Computer Electrical And Mathematical Sciences And Engineering Division King Abdullah University Of Science And Technology 4700 KAUST Thuwal23955-6900 Saudi Arabia Asian Demographic Research Institute Shanghai University Shangda Road Shanghai200444 China International Institute For Applied Systems Analysis Schlossplatz 1 Laxenburg2361 Austria

Background: The sex ratio at birth (SRB;ratio of male to female births) in Nepal has been reported without imbalance on the national level. However, the national SRB could mask the disparity within the country. Given the demographic and cultural heterogeneities in Nepal, it is crucial to model Nepal SRB on the subnational level. Prior studies on subnational SRB in Nepal are mostly based on reporting observed values from surveys and census, and no study has provided probabilistic projections. We aim to estimate and project SRB for the seven provinces of Nepal from 1980 to 2050 using a Bayesian modeling approach. Methods: We compiled an extensive database on provincial SRB of Nepal, consisting 2001, 2006, 2011, and 2016 Nepal Demographic and Health Surveys and 2011 Census. We adopted a Bayesian hierarchical time series model to estimate and project the provincial SRB, with a focus on modelling the potential SRB imbalance. Results: In 2016, the highest SRB is estimated in Province 5 at 1.102 with a 95% credible interval (1.044, 1.127) and the lowest SRB is in Province 2 at 1.053 (1.035, 1.109). During 1980-2016, the provincial SRB was around the same level as the national SRB baseline of 1.049. The SRB imbalance probabilities in all provinces are generally low and vary from 16% in Province 2 to 81% in Province 5. SRB imbalances are estimated to have begun at the earliest in 2001 in Province 5 with a 95% credible interval (1992, 2022) and the latest in 2017 (1998, 2040) in Province 2. We project SRB in all provinces to begin converging back to the national baseline in the mid-2030s. By 2050, the SRBs in all provinces are projected to be around the SRB baseline level. Conclusion: Our findings imply that the majority of provinces in Nepal have low risks of SRB imbalance for the period 1980-2016. However, we identify a few provinces with higher probabilities of having SRB inflation. The projected SRB is an important illustration of potential future prenatal sex discriminat

关键词： Bayesian networks

Assessing alternatives for meeting water demand: A case study of water resource management in the Brazilian Semiarid region

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Assessing alternatives for meeting water demand: A case stud...

作者： de Andrade Santana, Rosinele Marques Bezerra, Saulo de Tarso Melo dos Santos, Sylvana Paiva Coutinho, Artur Lopes Coelho, Isabela Carolina Silva Pessoa, Ruben Vivaldi Postgraduation Program in Civil and Environmental Engineering Universidade Federal de Pernambuco CaruaruPE Brazil Department of Technology Universidade Federal de Pernambuco Avenida Campina Grande S/N CaruaruPE55014-900 Brazil Department of Civil and Environmental Engineering Universidade Federal de Pernambuco RecifePE Brazil Postgraduation Program in Biometry and Applied Statistics Universidade Federal Rural de Pernambuco RecifePE Brazil

Population growth, climate change, and the occurrence of droughts have intensified the water supply crises in the Brazilian Semiarid region. The objective of this study was to identify the most relevant measures for the improvement of the water supply of Caruaru, Brazil. The research involved five steps: the selection of experts, comprehension of variables, application of Delphi research, statistical analyses, and consolidation of results. Projects to expand the system and reduce real losses are the most recommended measures. It is also important to implement an integrated water resources management approach that embraces alternative technological and governance strategies. © 2019 Elsevier Ltd

关键词： Water supply

Cholesterol incorporation into curimba sperm membrane improve cryosurvival

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Cryobiology 2022年 109卷 68-68页

作者： Karine V. Antunes Illa Carla S. Carvalho Elizabeth Maria S. Moreira Jairo José S. Santos Elenice A. Moraes Guilherme R. Moreira Rozzano Antonio C.R. Figueiredo Research Center for Pigs Native and Wild Species Federal University of Sao Francisco Valley Petrolina Brazil Department of Animal Science Federal University of Sao Francisco Valley Petrolina Brazil Biometrics and Applied Statistics Program Rural Federal University of Pernambuco Recife Brazil Regional Superintendence of the Sao Francisco and Parnaiba Valley Development Company Petrolina Brazil

Exploring Modified Gravity: Constraints on the μ and Σ Parametrization with WMAP, ACT, and SPT

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arXiv 2023年

作者： Andrade, Uendert Capistrano, Abraão J.S. Di Valentino, Eleonora Nunes, Rafael C. Leinweber Center for Theoretical Physics University of Michigan 450 Church Street Ann ArborMI48109-1040 United States Department of Physics College of Literature Science and the Arts University of Michigan 450 Church Street Ann ArborMI48109-1040 United States Observatório Nacional RJ Rio de Janeiro20921-400 Brazil Universidade Federal do Paraná PR Palotina85950-000 Brazil Applied physics graduation program UNILA PR Foz do Iguaçu85867-670 Brazil School of Mathematics and Statistics University of Sheffield United Kingdom Instituto de Física Universidade Federal do Rio Grande do Sul Porto Alegre RS 91501-970 Brazil Divisão de Astrofísica Instituto Nacional de Pesquisas Espaciais Avenida dos Astronautas 1758 SP São José dos Campos12227-010 Brazil

The cosmic acceleration problem remains one of the most significant challenges in cosmology. One of the proposed solutions to this problem is the modification of gravity on large scales. In this paper, we explore the well-known μ-Σ parametrization scenarios and confront them with observational data, including the cosmic microwave background (CMB) radiation from the Wilkinson Microwave Anisotropy Probe (WMAP), Atacama Cosmology Telescope (ACT), and South Pole Telescope (SPT), as well as large-scale structure data from the Sloan Digital Sky Survey (SDSS: BAO+RSD) and Pantheon Supernovae (SN) catalog. We employ a Bayesian framework to constrain the model parameters and discuss the implications of our results on the viability of modified gravity theories. Our analysis reveals the strengths and limitations of the μ-Σ parametrization and provides valuable insights into the nature of gravity on cosmological scales. From the joint analysis of the ACT + WMAP + SDSS + SN, we find μ0 − 1 = 0.02 ± 0.19 and Σ0 − 1 = 0.021 ± 0.068 at 68% CL. In light of the SPT + WMAP + SDSS + SN, we find μ0 − 1 = 0.07 ± 0.18 and Σ0 − 1 = −0.009+−0007811 at 68% CL. In all the analyses carried out, we do not find any deviations from the theory of general relativity. Our results represent an observational update on the well-known μ-Σ parameterization in view of current CMB data, independent and competitive with the constraints obtained with the Planck data. Copyright © 2023, The Authors. All rights reserved.

关键词： Telescopes

Nonrigid registration using Gaussian processes and local likelihood estimation

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arXiv 2020年

作者： Wiens, Ashton Kleiber, William Nychka, Douglas Barnhart, Katherine R. Department of Applied Mathematics University of Colorado BoulderCO United States Department of Applied Mathematics and Statistics Colorado School of Mines GoldenCO United States Cooperative Institute for Research in Environmental Sciences University of Colorado BoulderCO United States Department of Geological Sciences University of Colorado BoulderCO United States US Geological Survey Landslide Hazards Program 1711 Illinois St. GoldenCO80401 United States

Surface registration, the task of aligning several multidimensional point sets, is a necessary task in many scientific fields. In this work, a novel statistical approach is developed to solve the problem of nonrigid registration. While the application of an affine transformation results in rigid registration, using a general nonlinear function to achieve nonrigid registration is necessary when the point sets require deformations that change over space. The use of a local likelihood-based approach using windowed Gaussian processes provides a flexible way to accurately estimate the nonrigid deformation. This strategy also makes registration of massive data sets feasible by splitting the data into many subsets. The estimation results yield spatially-varying local rigid registration parameters. Gaussian process surface models are then fit to the parameter fields, allowing prediction of the transformation parameters at unestimated locations, specifically at observation locations in the unregistered data set. Applying these transformations results in a global, nonrigid registration. A penalty on the transformation parameters is included in the likelihood objective function. Combined with smoothing of the local estimates from the surface models, the nonrigid registration model can prevent the problem of overfitting. The efficacy of the nonrigid registration method is tested in two simulation studies, varying the number of windows and number of points, as well as the type of deformation. The nonrigid method is applied to a pair of massive remote sensing elevation data sets exhibiting complex geological terrain, with improved accuracy and uncertainty quantification in a cross validation study versus two rigid registration methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Uncertainty analysis