scholarly journals Implementing and testing Bayesian and maximum-likelihood supertree methods in phylogenetics

2015 ◽  
Vol 2 (8) ◽  
pp. 140436 ◽  
Author(s):  
Wasiu A. Akanni ◽  
Mark Wilkinson ◽  
Christopher J. Creevey ◽  
Peter G. Foster ◽  
Davide Pisani
Keyword(s):  
Maximum Likelihood ◽  
Large Scale ◽  
Empirical Studies ◽  
Input Tree ◽  
Unbiased Test ◽  
Tree Topologies ◽  
Phylogenetic Framework ◽  
Alternative Approaches ◽  
Supertree Methods ◽  
Non Parametric

Since their advent, supertrees have been increasingly used in large-scale evolutionary studies requiring a phylogenetic framework and substantial efforts have been devoted to developing a wide variety of supertree methods (SMs). Recent advances in supertree theory have allowed the implementation of maximum likelihood (ML) and Bayesian SMs, based on using an exponential distribution to model incongruence between input trees and the supertree. Such approaches are expected to have advantages over commonly used non-parametric SMs, e.g. matrix representation with parsimony (MRP). We investigated new implementations of ML and Bayesian SMs and compared these with some currently available alternative approaches. Comparisons include hypothetical examples previously used to investigate biases of SMs with respect to input tree shape and size, and empirical studies based either on trees harvested from the literature or on trees inferred from phylogenomic scale data. Our results provide no evidence of size or shape biases and demonstrate that the Bayesian method is a viable alternative to MRP and other non-parametric methods. Computation of input tree likelihoods allows the adoption of standard tests of tree topologies (e.g. the approximately unbiased test). The Bayesian approach is particularly useful in providing support values for supertree clades in the form of posterior probabilities.

scholarly journals Tackling the phylogenetic conundrum of Hydroidolina (Cnidaria: Medusozoa: Hydrozoa) by assessing competing tree topologies with targeted high-throughput sequencing

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12104
Author(s):  
Bastian Bentlage ◽  
Allen G. Collins
Keyword(s):  
Maximum Likelihood ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Phylogenetic Analyses ◽  
Sister Group ◽  
Life Cycles ◽  
Tree Topologies ◽  
Phylogenetic Framework ◽  
Phylogenetic Hypotheses ◽  
Inference Methods

Higher-level relationships of the Hydrozoan subclass Hydroidolina, which encompasses the vast majority of medusozoan cnidarian species diversity, have been elusive to confidently infer. The most widely adopted phylogenetic framework for Hydroidolina based on ribosomal RNA data received low support for several higher level relationships. To address this issue, we developed a set of RNA baits to target more than a hundred loci from the genomes of a broad taxonomic sample of Hydroidolina for high-throughput sequencing. Using these data, we inferred the relationships of Hydroidolina using maximum likelihood and Bayesian approaches. Both inference methods yielded well-supported phylogenetic hypotheses that largely agree with each other. Using maximum likelihood and Baysian hypothesis testing frameworks, we found that several alternate topological hypotheses proposed previously may be rejected in light of the genomic data generated for this study. Both the maximum likelihood and Bayesian topologies inferred herein consistently score well across testing frameworks, suggesting that their consensus represents the most likely phylogenetic hypothesis of Hydroidolina. This phylogenetic framework places Aplanulata as sister lineage to the remainder of Hydroidolina. This is a strong deviation from previous phylogenetic analyses that placed Capitata or Siphonophorae as sister group to the remainder of Hydroidolina. Considering that Aplanulata represents a lineage comprised of species that for the most part possess a life cycle involving a solitary polyp and free-swimming medusa stage, the phylogenetic hypotheses presented herein have potentially large implications for clarifying the evolution of life cycles, coloniality, and the division of labor in Hydrozoa as taxon sampling for phylogenetic analyses becomes more complete.

Bullying, School Violence, and Climate in Evolving Contexts

2018 ◽  
Author(s):  
Ron Avi Astor ◽  
Rami Benbenisthty
Keyword(s):  
School Violence ◽  
School Safety ◽  
Media Coverage ◽  
Large Scale ◽  
Ecological Model ◽  
Empirical Studies ◽  
Practical Applications ◽  
Teacher Student ◽  
Area Of Interest ◽  
New Research

Since 2005, the bullying, school violence, and school safety literatures have expanded dramatically in content, disciplines, and empirical studies. However, with this massive expansion of research, there is also a surprising lack of theoretical and empirical direction to guide efforts on how to advance our basic science and practical applications of this growing scientific area of interest. Parallel to this surge in interest, cultural norms, media coverage, and policies to address school safety and bullying have evolved at a remarkably quick pace over the past 13 years. For example, behaviors and populations that just a decade ago were not included in the school violence, bullying, and school safety discourse are now accepted areas of inquiry. These include, for instance, cyberbullying, sexting, social media shaming, teacher–student and student–teacher bullying, sexual harassment and assault, homicide, and suicide. Populations in schools not previously explored, such as lesbian, gay, bisexual, transgender, and queer students and educators and military- and veteran-connected students, become the foci of new research, policies, and programs. As a result, all US states and most industrialized countries now have a complex quilt of new school safety and bullying legislation and policies. Large-scale research and intervention funding programs are often linked to these policies. This book suggests an empirically driven unifying model that brings together these previously distinct literatures. This book presents an ecological model of school violence, bullying, and safety in evolving contexts that integrates all we have learned in the 13 years, and suggests ways to move forward.

scholarly journals Penalized Averaging of Parametric and Non-Parametric Quantile Forecasts

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Jan G. De Gooijer ◽  
Dawit Zerom
Keyword(s):  
Risk Premium ◽  
Empirical Studies ◽  
Forecast Accuracy ◽  
Equity Premium ◽  
Adaptive Lasso ◽  
Large Set ◽  
Usual Practice ◽  
Conditional Quantile ◽  
Equity Risk ◽  
Non Parametric

Abstract We propose a hybrid penalized averaging for combining parametric and non-parametric quantile forecasts when faced with a large number of predictors. This approach goes beyond the usual practice of combining conditional mean forecasts from parametric time series models with only a few predictors. The hybrid methodology adopts the adaptive LASSO regularization to simultaneously reduce predictor dimension and obtain quantile forecasts. Several recent empirical studies have considered a large set of macroeconomic predictors and technical indicators with the goal of forecasting the S&P 500 equity risk premium. To illustrate the merit of the proposed approach, we extend the mean-based equity premium forecasting into the conditional quantile context. The application offers three main findings. First, combining parametric and non-parametric approaches adds quantile forecast accuracy over and above the constituent methods. Second, a handful of macroeconomic predictors are found to have systematic forecasting power. Third, different predictors are identified as important when considering lower, central and upper quantiles of the equity premium distribution.

scholarly journals A simple and efficient automated microvolume radiosynthesis of [18F]Florbetaben

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Ksenia Lisova ◽  
Jia Wang ◽  
Philip H. Chao ◽  
R. Michael van Dam
Keyword(s):  
Large Scale ◽  
Solid Phase ◽  
Acetonitrile Solution ◽  
Synthesis Methods ◽  
Pet Tracers ◽  
Molar Activity ◽  
Alternative Approaches ◽  
High Yields ◽  
Sufficient Concentration

Abstract Background Current automated radiosynthesizers are generally optimized for producing large batches of PET tracers. Preclinical imaging studies, however, often require only a small portion of a regular batch, which cannot be economically produced on a conventional synthesizer. Alternative approaches are desired to produce small to moderate batches to reduce cost and the amount of reagents and radioisotope needed to produce PET tracers with high molar activity. In this work we describe the first reported microvolume method for production of [18F]Florbetaben for use in imaging of Alzheimer’s disease. Procedures The microscale synthesis of [18F]Florbetaben was adapted from conventional-scale synthesis methods. Aqueous [18F]fluoride was azeotropically dried with K2CO3/K222 (275/383 nmol) complex prior to radiofluorination of the Boc-protected precursor (80 nmol) in 10 μL DMSO at 130 °C for 5 min. The resulting intermediate was deprotected with HCl at 90 °C for 3 min and recovered from the chip in aqueous acetonitrile solution. The crude product was purified via analytical scale HPLC and the collected fraction reformulated via solid-phase extraction using a miniature C18 cartridge. Results Starting with 270 ± 100 MBq (n = 3) of [18F]Fluoride, the method affords formulated product with 49 ± 3% (decay-corrected) yield,> 98% radiochemical purity and a molar activity of 338 ± 55 GBq/μmol. The miniature C18 cartridge enables efficient elution with only 150 μL of ethanol which is diluted to a final volume of 1.0 mL, thus providing a sufficient concentration for in vivo imaging. The whole procedure can be completed in 55 min. Conclusions This work describes an efficient and reliable procedure to produce [18F]Florbetaben in quantities sufficient for large-scale preclinical applications. This method provides very high yields and molar activities compared to reported literature methods. This method can be applied to higher starting activities with special consideration given to automation and radiolysis prevention.

scholarly journals A Phylogenomic Supertree of Birds

Diversity ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 109 ◽  
Author(s):  
Rebecca T. Kimball ◽  
Carl H. Oliveros ◽  
Ning Wang ◽  
Noor D. White ◽  
F. Keith Barker ◽  
...  
Keyword(s):  
Large Scale ◽  
Sequence Data ◽  
Bird Species ◽  
Divide And Conquer ◽  
Clear Understanding ◽  
Whole Genome ◽  
Efficient Manner ◽  
Sequence Capture ◽  
Branch Lengths ◽  
Supertree Methods

It has long been appreciated that analyses of genomic data (e.g., whole genome sequencing or sequence capture) have the potential to reveal the tree of life, but it remains challenging to move from sequence data to a clear understanding of evolutionary history, in part due to the computational challenges of phylogenetic estimation using genome-scale data. Supertree methods solve that challenge because they facilitate a divide-and-conquer approach for large-scale phylogeny inference by integrating smaller subtrees in a computationally efficient manner. Here, we combined information from sequence capture and whole-genome phylogenies using supertree methods. However, the available phylogenomic trees had limited overlap so we used taxon-rich (but not phylogenomic) megaphylogenies to weave them together. This allowed us to construct a phylogenomic supertree, with support values, that included 707 bird species (~7% of avian species diversity). We estimated branch lengths using mitochondrial sequence data and we used these branch lengths to estimate divergence times. Our time-calibrated supertree supports radiation of all three major avian clades (Palaeognathae, Galloanseres, and Neoaves) near the Cretaceous-Paleogene (K-Pg) boundary. The approach we used will permit the continued addition of taxa to this supertree as new phylogenomic data are published, and it could be applied to other taxa as well.

scholarly journals Induced sterility in fish and its potential and challenges for aquaculture and germ cell transplantation technology: a review

Biologia ◽  
2016 ◽  
Vol 71 (8) ◽  
Author(s):  
Amin Golpour ◽  
Mohammad Abdul Momin Siddique ◽  
Diógenes Henrique Siqueira-Silva ◽  
Martin Pšenička
Keyword(s):  
Germ Cell ◽  
Cell Transplantation ◽  
Large Scale ◽  
Hormonal Treatment ◽  
Important Species ◽  
Genetic Ablation ◽  
Germ Cell Transplantation ◽  
Commercially Important ◽  
Alternative Approaches ◽  
Hormone Signalling

AbstractInterest in reproductively sterile fish in aquaculture has prompted research into their production. Several methods are available for inducing sterility and optimizing its application in the global fishery industry. Sterilization can potentially be accomplished through irradiation, surgery, or chemical and hormonal treatment. Alternative approaches include triploidization, hybridization, and generation of new lines via advanced biotechnological techniques. Triploids of many commercially important species have been studied extensively and have been produced on a large scale for many years. Novel approaches, including disruption of gonadotropin releasing hormone signalling and genetic ablation of germ cells, have been developed that are effective in producing infertile fish but have the disadvantage of not being 100% reliable or are impractical for large-scale aquaculture. We review currently used technologies and recent advances in induction of sterility in fish, especially those intended for use in germ cell transplantation. Knowledge of the implications of these approaches remains incomplete, imposing considerable limitations.

scholarly journals Supply chain resilience in a developing country context: a case study on the interconnectedness of threats, strategies and outcomes

2017 ◽  
Vol 22 (6) ◽  
pp. 486-505 ◽  
Author(s):  
Benjamin Tukamuhabwa ◽  
Mark Stevenson ◽  
Jerry Busby
Keyword(s):  
Supply Chain ◽  
Developing Country ◽  
Large Scale ◽  
Empirical Studies ◽  
Small Scale ◽  
Supply Network ◽  
Catastrophic Events ◽  
Content Type ◽  
Supply Chain Resilience

Purpose In few prior empirical studies on supply chain resilience (SCRES), the focus has been on the developed world. Yet, organisations in developing countries constitute a significant part of global supply chains and have also experienced the disastrous effects of supply chain failures. The purpose of this paper is therefore to empirically investigate SCRES in a developing country context and to show that this also provides theoretical insights into the nature of what is meant by resilience. Design/methodology/approach Using a case study approach, a supply network of 20 manufacturing firms in Uganda is analysed based on a total of 45 interviews. Findings The perceived threats to SCRES in this context are mainly small-scale, chronic disruptive events rather than discrete, large-scale catastrophic events typically emphasised in the literature. The data reveal how threats of disruption, resilience strategies and outcomes are inter-related in complex, coupled and non-linear ways. These interrelationships are explained by the political, cultural and territorial embeddedness of the supply network in a developing country. Further, this embeddedness contributes to the phenomenon of supply chain risk migration, whereby an attempt to mitigate one threat produces another threat and/or shifts the threat to another point in the supply network. Practical implications Managers should be aware, for example, of potential risk migration from one threat to another when crafting strategies to build SCRES. Equally, the potential for risk migration across the supply network means managers should look at the supply chain holistically because actors along the chain are so interconnected. Originality/value The paper goes beyond the extant literature by highlighting how SCRES is not only about responding to specific, isolated threats but about the continuous management of risk migration. It demonstrates that resilience requires both an understanding of the interconnectedness of threats, strategies and outcomes and an understanding of the embeddedness of the supply network. Finally, this study’s focus on the context of a developing country reveals that resilience should be equally concerned both with smaller in scale, chronic disruptions and with occasional, large-scale catastrophic events.

“I Will Never Know the Person Who I Could Have Become”: Perceived Changes in Self-Identity Among Adult Survivors of Clergy-Perpetrated Sexual Abuse

2016 ◽  
Vol 34 (6) ◽  
pp. 1139-1162 ◽  
Author(s):  
Scott D. Easton ◽  
Danielle M. Leone-Sheehan ◽  
Patrick J. O’Leary
Keyword(s):  
Sexual Abuse ◽  
Media Coverage ◽  
Large Scale ◽  
Clinical Sample ◽  
Empirical Studies ◽  
Adult Survivors ◽  
Well Being ◽  
Future Research ◽  
Relational Self ◽  
Self Identity

Clergy-perpetrated sexual abuse (CPSA) during childhood represents a tragic betrayal of trust that inflicts damage on the survivor, the family, and the parish community. Survivors often report CPSA has a disturbing impact on their self-identity. Despite intense media coverage of clergy abuse globally in the Catholic Church (and other faith communities) over several decades, relatively few empirical studies have been conducted with survivors. Beyond clinical observations and advocacy group reports, very little is known about survivors’ perceptions of how the abuse impacted their long-term self-identity. Using data collected during the 2010 Health and Well-Being Survey, this qualitative analysis represents one of the first large-scale studies with a non-clinical sample of adult male survivors of CPSA from childhood ( N = 205). The negative effects of the sexual abuse on participants were expressed across six domains of self-identity: (a) total self, (b) psychological self, (c) relational self, (d) gendered self, (e) aspirational self, and (f) spiritual self. These findings highlight the range and depth of self-suffering inflicted by this pernicious form of sexual violence. The findings are useful for developing clinical services for survivors, shaping public and institutional policies to address clergy-perpetrated sexual abuse, and guiding future research with this population.

scholarly journals Small-variance asymptotics for non-parametric online robot learning

2018 ◽  
Vol 38 (1) ◽  
pp. 3-22 ◽  
Author(s):  
Ajay Kumar Tanwani ◽  
Sylvain Calinon
Keyword(s):  
Mixture Models ◽  
Dirichlet Process ◽  
Large Scale ◽  
Principal Component ◽  
Small Variance ◽  
Remote Manipulation ◽  
State Duration ◽  
Duration Information ◽  
Low Dimensional ◽  
Non Parametric

Small-variance asymptotics is emerging as a useful technique for inference in large-scale Bayesian non-parametric mixture models. This paper analyzes the online learning of robot manipulation tasks with Bayesian non-parametric mixture models under small-variance asymptotics. The analysis yields a scalable online sequence clustering (SOSC) algorithm that is non-parametric in the number of clusters and the subspace dimension of each cluster. SOSC groups the new datapoint in low-dimensional subspaces by online inference in a non-parametric mixture of probabilistic principal component analyzers (MPPCA) based on a Dirichlet process, and captures the state transition and state duration information online in a hidden semi-Markov model (HSMM) based on a hierarchical Dirichlet process. A task-parameterized formulation of our approach autonomously adapts the model to changing environmental situations during manipulation. We apply the algorithm in a teleoperation setting to recognize the intention of the operator and remotely adjust the movement of the robot using the learned model. The generative model is used to synthesize both time-independent and time-dependent behaviors by relying on the principles of shared and autonomous control. Experiments with the Baxter robot yield parsimonious clusters that adapt online with new demonstrations and assist the operator in performing remote manipulation tasks.

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