73 research outputs found

    Determining causal relationships in leadership research using machine learning: the powerful synergy of experiments and data science

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    This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordMachine Learning (ML) techniques offer exciting new avenues for leadership research. In this paper we discuss how ML techniques can be used to inform predictive and causal models of leadership effects and clarify why both types of models are important for leadership research. We propose combining ML and experimental designs to draw causal inferences by introducing a recently developed technique to isolate “heterogeneous treatment effects.” We provide a step-by-step guide on how to design studies that combine field experiments with the application of ML to establish causal relationships with maximal predictive power. Drawing on examples in the leadership literature, we illustrate how the suggested approach can be applied to examine the impact of, for example, leadership behavior on follower outcomes. We also discuss how ML can be used to advance leadership research from theoretical, methodological and practical perspectives and consider limitations

    Design of dual ligands using excessive pharmacophore query alignment

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    Dual- or multi-target ligands have gained increased attention in the past years due to several advantages, including more simple pharmacokinetic and phamarcodynamic properties compared to a combined application of several drugs. Furthermore multi-target ligands often possess improved efficacy. We present a new approach for the discovery of dual-target ligands using aligned pharmacophore models combined with a shape-based scoring. Starting with two sets of known active compounds for each target, a number of different pharmacophore models is generated and subjected to pairwise graph-based alignment using the Kabsch-Algorithm. Since a compound may be able to bind to different targets in different conformations, the algorithm aligns pairs of pharmacophore models sharing the same features which are not necessarily at the exactly same spatial distance. Using the aligned models, a pharmacophore search on a multi-conformation-database is performed to find compounds matching both models. The potentially “dual” ligands are scored by a shape-based comparison with the known active molecules using ShaEP. Using this approach, we performed a prospective fragment-based virtual screening for dual 5-LO/sEH inhibitors. Both enzymes play an important role in the arachidonic acid cascade and are involved in inflammatory processes, pain, cardiovascular diseases and allergic reactions. Beside several new selective inhibitors we were able to find a compound inhibiting both enzymes in low micromolar concentrations. The results indicate that the idea of aligned pharmacophore models can be successfully employed for the discovery of dual-target ligands

    The motivation for citizens’ involvement in life sciences research is predicted by age and gender

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    Open Science is an umbrella term encompassing multiple concepts as open access to publications, open data, open education and citizen science that aim to make science more open and transparent. Citizen science, an important facet of Open Science, actively involves nonscientists in the research process, and can potentially be beneficial for multiple actors, such as scientists, citizens, policymakers and society in general. However, the reasons that motivate different segments of the public to participate in research are still understudied. Therefore, based on data gathered from a survey conducted in Czechia, Germany, Italy, Spain, Sweden, and the UK (N = 5,870), this study explores five types of incentives that can motivate individuals to become involved in life sciences research. The results demonstrate that men and younger individuals are more persuaded by extrinsic motives (external benefits or rewards), as compared with women and older people, who are driven by intrinsic motives (that originates from within an individual). This paper shows that specific strata of the population are differentially motivated to engage in research, thereby providing relevant knowledge for effectively designing public involvement activities that target various groups of the public in research projects

    Identification and Phylogenetic Analysis of Tityus pachyurus and Tityus obscurus Novel Putative Na+-Channel Scorpion Toxins

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    Background: Colombia and Brazil are affected by severe cases of scorpionism. In Colombia the most dangerous accidents are caused by Tityus pachyurus that is widely distributed around this country. In the Brazilian Amazonian region scorpion stings are a common event caused by Tityus obscurus. The main objective of this work was to perform the molecular cloning of the putative Na+-channel scorpion toxins (NaScTxs) from T. pachyurus and T. obscurus venom glands and to analyze their phylogenetic relationship with other known NaScTxs from Tityus species. Methodology/Principal Findings: cDNA libraries from venom glands of these two species were constructed and five nucleotide sequences from T. pachyurus were identified as putative modulators of Na+-channels, and were named Tpa4, Tpa5, Tpa6, Tpa7 and Tpa8; the latter being the first anti-insect excitatory b-class NaScTx in Tityus scorpion venom to be described. Fifteen sequences from T. obscurus were identified as putative NaScTxs, among which three had been previously described, and the others were named To4 to To15. The peptides Tpa4, Tpa5, Tpa6, To6, To7, To9, To10 and To14 are closely related to the a-class NaScTxs, whereas Tpa7, Tpa8, To4, To8, To12 and To15 sequences are more related to the b-class NaScTxs. To5 is possibly an arthropod specific toxin. To11 and To13 share sequence similarities with both a and b NaScTxs. By means of phylogenetic analysis using the Maximum Parsimony method and the known NaScTxs from Tityus species, these toxins were clustered into 14 distinct groups. Conclusions/Significance: This communication describes new putative NaScTxs from T. pachyurus and T. obscurus and their phylogenetic analysis. The results indicate clear geographic separation between scorpions of Tityus genus inhabiting the Amazonian and Mountain Andes regions and those distributed over the Southern of the Amazonian rainforest. Based on the consensus sequences for the different clusters, a new nomenclature for the NaScTxs is proposed

    Abstracts of presentations on selected topics at the XIVth international plant protection congress (IPPC) July 25-30, 1999

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    Conservation and Diversity of Seed Associated Endophytes in Zea across Boundaries of Evolution, Ethnography and Ecology

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    Endophytes are non-pathogenic microbes living inside plants. We asked whether endophytic species were conserved in the agriculturally important plant genus Zea as it became domesticated from its wild ancestors (teosinte) to modern maize (corn) and moved from Mexico to Canada. Kernels from populations of four different teosintes and 10 different maize varieties were screened for endophytic bacteria by culturing, cloning and DNA fingerprinting using terminal restriction fragment length polymorphism (TRFLP) of 16S rDNA. Principle component analysis of TRFLP data showed that seed endophyte community composition varied in relation to plant host phylogeny. However, there was a core microbiota of endophytes that was conserved in Zea seeds across boundaries of evolution, ethnography and ecology. The majority of seed endophytes in the wild ancestor persist today in domesticated maize, though ancient selection against the hard fruitcase surrounding seeds may have altered the abundance of endophytes. Four TRFLP signals including two predicted to represent Clostridium and Paenibacillus species were conserved across all Zea genotypes, while culturing showed that Enterobacter, Methylobacteria, Pantoea and Pseudomonas species were widespread, with γ-proteobacteria being the prevalent class. Twenty-six different genera were cultured, and these were evaluated for their ability to stimulate plant growth, grow on nitrogen-free media, solubilize phosphate, sequester iron, secrete RNAse, antagonize pathogens, catabolize the precursor of ethylene, produce auxin and acetoin/butanediol. Of these traits, phosphate solubilization and production of acetoin/butanediol were the most commonly observed. An isolate from the giant Mexican landrace Mixteco, with 100% identity to Burkholderia phytofirmans, significantly promoted shoot potato biomass. GFP tagging and maize stem injection confirmed that several seed endophytes could spread systemically through the plant. One seed isolate, Enterobacter asburiae, was able to exit the root and colonize the rhizosphere. Conservation and diversity in Zea-microbe relationships are discussed in the context of ecology, crop domestication, selection and migration

    Epoxyeicosanoids promote organ and tissue regeneration

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    Epoxyeicosatrienoic acids (EETs), lipid mediators produced by cytochrome P450 epoxygenases, regulate inflammation, angiogenesis, and vascular tone. Despite pleiotropic effects on cells, the role of these epoxyeicosanoids in normal organ and tissue regeneration remains unknown. EETs are produced predominantly in the endothelium. Normal organ and tissue regeneration require an active paracrine role of the microvascular endothelium, which in turn depends on angiogenic growth factors. Thus, we hypothesize that endothelial cells stimulate organ and tissue regeneration via production of bioactive EETs. To determine whether endothelial-derived EETs affect physiologic tissue growth in vivo, we used genetic and pharmacological tools to manipulate endogenous EET levels. We show that endothelial-derived EETs play a critical role in accelerating tissue growth in vivo, including liver regeneration, kidney compensatory growth, lung compensatory growth, wound healing, corneal neovascularization, and retinal vascularization. Administration of synthetic EETs recapitulated these results, whereas lowering EET levels, either genetically or pharmacologically, delayed tissue regeneration, demonstrating that pharmacological modulation of EETs can affect normal organ and tissue growth. We also show that soluble epoxide hydrolase inhibitors, which elevate endogenous EET levels, promote liver and lung regeneration. Thus, our observations indicate a central role for EETs in organ and tissue regeneration and their contribution to tissue homeostasis

    Effect of bayesian student modeling on academic achievement in foreign language teaching (university level english preparatory school example) [İnternet üzerinden yabanci{dotless} dil ögretiminde bayes ögrenci modellemesi yaklaşi{dotless}mi{dotless}ni{dotless}n akademik başari{dotless}ya etkisi (üniversite i·ngilizce hazi{dotless}rli{dotless}k örnegi)]

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    Considering the increasing importance of adaptive approaches in CALL systems, this study implemented a machine learning based student modeling middleware with Bayesian networks. The profiling approach of the student modeling system is based on Felder and Silverman's Learning Styles Model and Felder and Soloman's Index of Learning Styles Questionnaire. The questionnaire was adapted to Turkish for this experimental study conducted with respect to the visual/verbal and active/reflective dimensions of the model. A topic in EFL was chosen for the learning content design, which was also carried into the digital domain and remastered as separate learning scenes for different learning styles. Computer software was also implemented to carry out the experimental learning processes. A quasi-experimental pre-test, post-test design was conducted with 46 volunteers, with 23 students assigned each to a control and an experimental group to compare academic achievement between student-based learning and conventional computer-based learning. No significant difference was found in academic achievement between the control and experimental groups after the experimental treatment. The diagnostic performance of the proposed student modeling system was also compared with performances from similar studies. This student modeling system had a successful prediction rate of 41% on the visual/verbal dimension and 54% on the active/reflective dimension, respectively. © 2014 Educational Consultancy and Research Center
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