scholarly journals Phylogenomic Analysis of Ants, Bees and Stinging Wasps: Improved Taxon Sampling Enhances Understanding of Hymenopteran Evolution

2016 ◽  
Author(s):  
Michael G. Branstetter ◽  
Bryan N. Danforth ◽  
James P. Pitts ◽  
Brant C. Faircloth ◽  
Philip S. Ward ◽  
...  
Keyword(s):  
Taxon Sampling ◽  
Phylogenomic Analysis ◽  
Data Set ◽  
Eusocial Insects ◽  
Divergence Dating ◽  
Active Debate ◽  
Exclusion Experiments ◽  
Analytical Approaches ◽  
Complete Matrix

AbstractThe importance of taxon sampling in phylogenetic accuracy is a topic of active debate. We investigated the role of taxon sampling in causing incongruent results between two recent phylogenomic studies of stinging wasps (Hymenoptera: Aculeata), a diverse lineage that includes ants, bees and the majority of eusocial insects. Using target enrichment of ultraconserved element (UCE) loci, we assembled the largest aculeate phylogenomic data set to date, sampling 854 loci from 187 taxa, including 30 out of 31 aculeate families, and a diversity of parasitoid outgroups. We analyzed the complete matrix using multiple analytical approaches, and also performed a series of taxon inclusion/exclusion experiments, in which we analyzed taxon sets identical to and slightly modified from the previous phylogenomic studies. Our results provide a highly supported phylogeny for virtually all aculeate lineages sampled, supporting ants as sister to Apoidea (bees+apoid wasps), bees as sister to Philanthinae+Pemphredoninae (lineages within a paraphyletic Crabronidae), Melittidae as sister to remaining bees, and paraphyly of cuckoo wasps (Chrysidoidea). Our divergence dating analyses estimate ages for aculeate lineages in close concordance with the fossil record. Our analyses also demonstrate that outgroup choice and taxon evenness can fundamentally impact topology and clade support in phylogenomic inference.

scholarly journals Phylogenomic analysis of the Chilean clade ofLiolaemuslizards (Squamata: Liolaemidae) based on sequence capture data

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3941 ◽  
Author(s):  
Alejandra Panzera ◽  
Adam D. Leaché ◽  
Guillermo D’Elía ◽  
Pedro F. Victoriano
Keyword(s):  
Incomplete Lineage Sorting ◽  
Phylogenetic Analyses ◽  
Strong Support ◽  
Taxon Sampling ◽  
Phylogenomic Analysis ◽  
Molecular Systematic ◽  
Data Set ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Phylogenomic Analyses

The genusLiolaemusis one of the most ecologically diverse and species-rich genera of lizards worldwide. It currently includes more than 250 recognized species, which have been subject to many ecological and evolutionary studies. Nevertheless,Liolaemuslizards have a complex taxonomic history, mainly due to the incongruence between morphological and genetic data, incomplete taxon sampling, incomplete lineage sorting and hybridization. In addition, as many species have restricted and remote distributions, this has hampered their examination and inclusion in molecular systematic studies. The aims of this study are to infer a robust phylogeny for a subsample of lizards representing the Chilean clade (subgenusLiolaemus sensu stricto), and to test the monophyly of several of the major species groups. We use a phylogenomic approach, targeting 541 ultra-conserved elements (UCEs) and 44 protein-coding genes for 16 taxa. We conduct a comparison of phylogenetic analyses using maximum-likelihood and several species tree inference methods. The UCEs provide stronger support for phylogenetic relationships compared to the protein-coding genes; however, the UCEs outnumber the protein-coding genes by 10-fold. On average, the protein-coding genes contain over twice the number of informative sites. Based on our phylogenomic analyses, all the groups sampled are polyphyletic.Liolaemus tenuis tenuisis difficult to place in the phylogeny, because only a few loci (nine) were recovered for this species. Topologies or support values did not change dramatically upon exclusion ofL. t. tenuisfrom analyses, suggesting that missing data did not had a significant impact on phylogenetic inference in this data set. The phylogenomic analyses provide strong support for sister group relationships betweenL. fuscus,L. monticola,L. nigroviridisandL. nitidus, andL. plateiandL. velosoi. Despite our limited taxon sampling, we have provided a reliable starting hypothesis for the relationships among many major groups of the Chilean clade ofLiolaemusthat will help future work aimed at resolving theLiolaemusphylogeny.

Exchange Spin Coupling from Gaussian Process Regression

2020 ◽  
Author(s):  
Marc Philipp Bahlke ◽  
Natnael Mogos ◽  
Jonny Proppe ◽  
Carmen Herrmann
Keyword(s):  
Machine Learning ◽  
Gaussian Process ◽  
Gaussian Process Regression ◽  
Molecular Magnets ◽  
Molecular Structures ◽  
Spin Coupling ◽  
Structure Property ◽  
Data Set ◽  
Uncertainty Estimates

Heisenberg exchange spin coupling between metal centers is essential for describing and understanding the electronic structure of many molecular catalysts, metalloenzymes, and molecular magnets for potential application in information technology. We explore the machine-learnability of exchange spin coupling, which has not been studied yet. We employ Gaussian process regression since it can potentially deal with small training sets (as likely associated with the rather complex molecular structures required for exploring spin coupling) and since it provides uncertainty estimates (“error bars”) along with predicted values. We compare a range of descriptors and kernels for 257 small dicopper complexes and find that a simple descriptor based on chemical intuition, consisting only of copper-bridge angles and copper-copper distances, clearly outperforms several more sophisticated descriptors when it comes to extrapolating towards larger experimentally relevant complexes. Exchange spin coupling is similarly easy to learn as the polarizability, while learning dipole moments is much harder. The strength of the sophisticated descriptors lies in their ability to linearize structure-property relationships, to the point that a simple linear ridge regression performs just as well as the kernel-based machine-learning model for our small dicopper data set. The superior extrapolation performance of the simple descriptor is unique to exchange spin coupling, reinforcing the crucial role of choosing a suitable descriptor, and highlighting the interesting question of the role of chemical intuition vs. systematic or automated selection of features for machine learning in chemistry and material science.

Vocational Development in Emerging Adulthood

2018 ◽  
Author(s):  
Michael W. Pratt ◽  
M. Kyle Matsuba
Keyword(s):  
Turning Point ◽  
Life Stories ◽  
Life Story ◽  
Emerging Adult ◽  
Vocational Development ◽  
Data Set ◽  
The World ◽  
Key Concepts

Chapter 6 reviews research on the topic of vocational/occupational development in relation to the McAdams and Pals tripartite personality framework of traits, goals, and life stories. Distinctions between types of motivations for the work role (as a job, career, or calling) are particularly highlighted. The authors then turn to research from the Futures Study on work motivations and their links to personality traits, identity, generativity, and the life story, drawing on analyses and quotes from the data set. To illustrate the key concepts from this vocation chapter, the authors end with a case study on Charles Darwin’s pivotal turning point, his round-the-world voyage as naturalist for the HMS Beagle. Darwin was an emerging adult in his 20s at the time, and we highlight the role of this journey as a turning point in his adult vocational development.

scholarly journals Actors, Partisan Inclination, and Emotions: An Analysis of Government Shutdown News Stories Shared on Twitter

2021 ◽  
Vol 7 (2) ◽  
pp. 205630512110088
Author(s):  
Colin Agur ◽  
Lanhuizi Gan
Keyword(s):  
Emotional Responses ◽  
The United States ◽  
Online Information ◽  
News Frames ◽  
Data Set ◽  
Political Issues ◽  
News Stories ◽  
News Sharing ◽  
Government Shutdown

Scholars have recognized emotion as an increasingly important element in the reception and retransmission of online information. In the United States, because of existing differences in ideology, among both audiences and producers of news stories, political issues are prone to spark considerable emotional responses online. While much research has explored emotional responses during election campaigns, this study focuses on the role of online emotion in social media posts related to day-to-day governance in between election periods. Specifically, this study takes the 2018–2019 government shutdown as its subject of investigation. The data set shows the prominence of journalistic and political figures in leading the discussion of news stories, the nuance of emotions employed in the news frames, and the choice of pro-attitudinal news sharing.

Do the Heterogeneous Determinants of Repayment Affect Differently across Borrowers of Diverse Credit Sources in Rural Assam? A Double Hurdle Approach

2021 ◽  
pp. 245513332110316
Author(s):  
Tiken Das ◽  
Pradyut Guha ◽  
Diganta Das
Keyword(s):  
Rural Areas ◽  
Probit Model ◽  
Original Data ◽  
Community Based ◽  
Data Set ◽  
Brahmaputra Valley ◽  
Double Hurdle ◽  
Instrumental Variable Probit ◽  
Instrumental Variable Probit Model

This study made an attempt to answer the question: Do the heterogeneous determinants of repayment affect the borrowers of diverse credit sources differently? The study is based on data collected from 240 households from three districts in the lower Brahmaputra valley of Assam through a carefully designed primary survey. Besides, the study uses the double hurdle approach and the instrumental variable probit model to reduce possible selection bias. It observes better repayment performance among formal borrowers, followed by semiformal borrowers, while occupation wise it is prominent among organised employees. It has been found that in general, the household characteristics, loan characteristics and location-specific characteristics significantly affect repayment performance of borrowers. However, the nature of impact of the factors influencing repayment performance is remarkably different across credit sources. It ignores the role of traditional community-based organisations in rural Assam while analysing the determinants of repayment performance. The study also recommends for ensuring productive opportunities and efficient market linkages in rural areas of Assam. The study is based on an original data set that has specially been collected to examine question that—do the heterogeneous determinants of repayment affect the borrowers of diverse credit sources differently in the lower Brahmaputra valley of Assam—which has not been studied before.

scholarly journals Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications

2020 ◽  
Vol 17 (10) ◽  
pp. 3730 ◽  
Author(s):  
Sina Shaffiee Haghshenas ◽  
Behrouz Pirouz ◽  
Sami Shaffiee Haghshenas ◽  
Behzad Pirouz ◽  
Patrizia Piro ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Infectious Disease ◽  
Relative Humidity ◽  
Cost Function ◽  
Selection Process ◽  
Environmental Parameters ◽  
Pso Algorithm ◽  
Data Set ◽  
De Algorithm

Nowadays, an infectious disease outbreak is considered one of the most destructive effects in the sustainable development process. The outbreak of new coronavirus (COVID-19) as an infectious disease showed that it has undesirable social, environmental, and economic impacts, and leads to serious challenges and threats. Additionally, investigating the prioritization parameters is of vital importance to reducing the negative impacts of this global crisis. Hence, the main aim of this study is to prioritize and analyze the role of certain environmental parameters. For this purpose, four cities in Italy were selected as a case study and some notable climate parameters—such as daily average temperature, relative humidity, wind speed—and an urban parameter, population density, were considered as input data set, with confirmed cases of COVID-19 being the output dataset. In this paper, two artificial intelligence techniques, including an artificial neural network (ANN) based on particle swarm optimization (PSO) algorithm and differential evolution (DE) algorithm, were used for prioritizing climate and urban parameters. The analysis is based on the feature selection process and then the obtained results from the proposed models compared to select the best one. Finally, the difference in cost function was about 0.0001 between the performances of the two models, hence, the two methods were not different in cost function, however, ANN-PSO was found to be better, because it reached to the desired precision level in lesser iterations than ANN-DE. In addition, the priority of two variables, urban parameter, and relative humidity, were the highest to predict the confirmed cases of COVID-19.

Market responsiveness: antecedents and the moderating role of external supply chain integration

2017 ◽  
Vol 32 (1) ◽  
pp. 30-45 ◽  
Author(s):  
Tuan Luu
Keyword(s):  
Supply Chain ◽  
Supply Chain Integration ◽  
Manufacturing Companies ◽  
Data Set ◽  
Content Type ◽  
Business Context ◽  
Market Responsiveness ◽  
Positive Effect ◽  
Ambidextrous Leadership

Purpose The interaction between opening and closing behaviors of ambidextrous leadership produces “change” force throughout the organization in proactive response to market forces. This research aims to assess the role of ambidextrous leadership in fostering entrepreneurial orientation (EO) and market responsiveness. The research also seeks an insight into how external supply chain integration moderates the positive effect of EO on market responsiveness. Design/methodology/approach Research data were collected from 327 meso-level managers and 517 subordinates from chemical manufacturing companies in the Vietnam business context. Findings Research findings shed light on the positive effect of ambidextrous leadership on EO, which in turn contributes to market responsiveness. The moderation role that external supply chain integration plays on the EO–market responsiveness linkage was also grounded on the data set. Originality/value Through the identification of the predictive roles of ambidextrous leadership and EO for market responsiveness, the current research indicates the convergence between leadership, EO and market responsiveness research streams.

Association of Medication-Assisted Treatment and Age With Treatment Completion Among Veterans Seeking Non-VA Treatment for Opioid use Disorder at Non-Veterans Health Administration Facilities

2021 ◽  
Author(s):  
Joseph G Pickard ◽  
Carissa van den Berk-Clark ◽  
Monica M Matthieu
Keyword(s):  
Positive Impact ◽  
Treatment Completion ◽  
Armed Forces ◽  
Opioid Use Disorder ◽  
Prescription Opioid ◽  
Health Administration ◽  
Opioid Use ◽  
Data Set ◽  
Medication Assisted Treatment

ABSTRACT Background Medication-assisted treatment has been shown to be effective in treating opioid use disorder among both older adults and veterans of U.S. Armed Forces. However, limited evidence exists on MAT’s differential effect on treatment completion across age groups. This study aims to ascertain the role of MAT and age in treatment completion among veterans seeking treatment in non–Department of Veterans Affairs healthcare facilities for opioid use disorder. Methods We used the Treatment Episode Data Set—Discharges (TEDS-D; 2006-2017) to examine trends in treatment and MAT usage over time and TEDS-2017 to determine the role of age and MAT in treatment completion. We examined a subset of those who self-identified as veterans and who sought treatment for an opioid use disorder. Results Veterans presented in treatment more often as heroin users than prescription opioid users, and older veterans were more likely to get MAT than younger veterans. We found that before propensity score matching, MAT initially appeared to be associated with a lower likelihood of treatment completion in inpatient ($\beta $ = −1.47, 95% CI −1.56 to −1.39) and outpatient ($\beta $ = −1.40, 95% CI −2.21 to −0.58) settings, and age (50+ years) appeared to mediate the effect of MAT on treatment completion ($\beta $ = −0.54, 95% CI −0.87 to −0.21). After matching, older veterans were more likely to complete substance use disorder treatment ($\beta $ = 0.21, 95% CI 0.01-0.42), while age no longer mediated the effect of MAT, and MAT had a significant positive impact on treatment completion in detox settings ($\beta $ = 1.36, 95% CI 1.15-1.50) and inpatient settings ($\beta $ = 1.54, 95% CI 1.37 -1.71). Conclusion The results show that age plays an important role in outpatient treatment completion, while MAT plays an important role in inpatient treatment completion. Implications for veterans are discussed.

Le seconde generazioni: nodi critici e nuove forme di integrazione

2009 ◽  
pp. 25-46
Author(s):  
Elena Caneva ◽  
Maurizio Ambrosini
Keyword(s):  
Immigrant Families ◽  
Cultural Transformation ◽  
Religious Organizations ◽  
Ethnic Communities ◽  
Ethnic Networks ◽  
The Social ◽  
Italian Context ◽  
Human And Social Capital ◽  
Analytical Approaches

- The number of immigrant children in Italy has been increasing more and more. They are impacting both on immigration as a phenomenon and on receiving societies. Thus, it becomes important and useful to understand which factors matter in second generation's paths and potential trajectories. Through a presentation of different analytical approaches on the phenomenon of migration, the paper explores the role of the family, the ethnic community and friends, as well as of religion and religious organizations in the promotion or prevention of positive forms of inclusion. With a specific focus on the Italian context, it explains the social and cultural transformation that characterises immigrant families, stressing the role that can be played by the human and social capital embedded in ethnic networks. The main aim of this paper is to go beyond the assimilation approaches and to highlight how immigrant families, ethnic networks and religious organizations could promote integration and the upward mobility of future generations. Keywords: Immigration, Second Generation, Ethnic Communities, Integration, Social Cohesion.

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