The genetic architecture underlying the evolution of a rare piscivorous life history form in brown trout after secondary contact and strong introgression

Identifying the genetic basis underlying phenotypic divergence and reproductive isolation is a longstanding problem in evolutionary biology. Genetic signals of adaptation and reproductive isolation are often confounded by a wide range of factors, such as variation in demographic history or genomic features. Brown trout ( ) in the Loch Maree catchment, Scotland, exhibit reproductively isolated divergent life history morphs, including a rare piscivorous (ferox) life history form displaying larger body size, greater longevity and delayed maturation compared to sympatric benthivorous brown trout. Using a dataset of 16,066 SNPs, we analyzed the evolutionary history and genetic architecture underlying this divergence. We found that ferox trout and benthivorous brown trout most likely evolved after recent secondary contact of two distinct glacial lineages, and identified 33 genomic outlier windows across the genome, of which several have most likely formed through selection. We further identified twelve candidate genes and biological pathways related to growth, development and immune response potentially underpinning the observed phenotypic differences. The identification of clear genomic signals divergent between life history phenotypes and potentially linked to reproductive isolation, through size assortative mating, as well as the identification of the underlying demographic history, highlights the power of genomic studies of young species pairs for understanding the factors shaping genetic differentiation

Exploring Pathways from Data to Knowledge to Insights in the Pharmaceutical Industry: ‘Introducing the Pharmaceutical Knowledge Ecosystem’

The ecosystem of how the pharmaceutical industry acquires data, transforms these data into tangible knowledge, and derives valuable insights throughout the process, is highly complex. Data, information, knowledge, and the resulting insights, are necessary to support decision- making, manage risk, problem solve, ensure product realisation, enable continual improvement, and enhance operational effectiveness. Building on the fundamental concepts established in the well-known Data Information Knowledge Wisdom (DIKW) hierarchy, this paper reviews the basic concepts involved in the DIKW pathway and begins to relate these concepts to both established capabilities (e.g., PAT), existing requirements (e.g., data integrity), and emerging trends in the industry (e.g., industry 4.0). This paper introduces additional research studies which the Pharmaceutical Regulatory Science Team (PRST) is considering, regarding how one might apply systems thinking concepts to develop a framework which will enable key stakeholders (Industry, Regulatory and Academia) to better relate the many elements of this ecosystem. The paper concludes by identifying preliminary foundational principles which could form the basis of such a framework, coined by the authors as ‘The pharmaceutical knowledge ecosystem’, and makes the case for further exploration of this concept

Drivers of atmospheric and oceanic surface temperature variance: A frequency domain approach

Ocean–atmosphere coupling modifies the variability of Earth’s climate over a wide range of time scales. However, attribution of the processes that generate this variability remains an outstanding problem. In this article, air–sea coupling is investigated in an eddy-resolving, medium-complexity, idealized ocean–atmosphere model. The model is run in three configurations: fully coupled, partially coupled (where the effect of the ocean geostrophic velocity on the sea surface temperature field is minimal), and atmosphere-only. A surface boundary layer temperature variance budget analysis computed in the frequency domain is shown to be a powerful tool for studying air–sea interactions, as it differentiates the relative contributions to the variability in the temperature field from each process across a range of time scales (from daily to multidecadal). This method compares terms in the ocean and atmosphere across the different model configurations to infer the underlying mechanisms driving temperature variability. Horizontal advection plays a dominant role in driving temperature variance in both the ocean and the atmosphere, particularly at time scales shorter than annual. At longer time scales, the temperature variance is dominated by strong coupling between atmosphere and ocean. Furthermore, the Ekman transport contribution to the ocean’s horizontal advection is found to underlie the low-frequency behavior in the atmosphere. The ocean geostrophic eddy field is an important driver of ocean variability across all frequencies and is reflected in the atmospheric variability in the western boundary current separation region at longer time scales.This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant DGE 1256260. PEM also acknowledges the associated Graduate Research Opportunities Worldwide fellowship to conduct research at the Australian National University. Q-GCM and analysis were run on the National Computational Infrastructure (NCI), which is supported by the Australian Government. The codes are written in Python with the Pangeo environment. Specific software used includes NumPy (Harris et al. 2020), Matplotlib (Hunter 2007), xarray (Hoyer and Hamman 2017), and Dask (Dask Development Team 2016). PEM and BKA acknowledge support from NSF Grants OCE-0960820, OCE-1351837, and OCE-1851164, and the University of Michigan African Studies Center and M-Cubed program, the latter supported by the Office of the Provost and the College of Literature, Science, and the Arts

Seesaw Extended MSSM and Anomaly Mediation without Tachyonic Sleptons

Superconformal anomalies provide an elegant and economical way to understand the soft breaking parameters in SUSY models; however, implementing them leads to the several undesirable features including: tachyonic sleptons and electroweak symmetry breaking problems in both the MSSM and the NMSSM. Since these two theories also have the additonal problem of massless neutrinos, we have reconsidered the AMSB problems in a class of models that extends the NMSSM to explain small neutrino masses via the seesaw mechanism. In a recent paper, we showed that for a class of minimal left-right extensions, a built-in mechanism exists which naturally solves the tachyonic slepton problem and provides new alternatives to the MSSM that also have automatic R-parity conservation. In this paper, we discuss how electroweak symmetry breaking arises in this model through an NMSSM-like low energy theory with a singlet VEV, induced by the structure of the left-right extension and of the right magnitude. We then study the phenomenological issues and find: the LSP is an Higgsino-wino mix, new phenomenology for chargino decays to the LSP, degenerate same generation sleptons and a potential for a mild squark-slepton degeneracy. We also discuss possible collider signatures and the feasibility of dark matter in this model.Comment: 40 pages, 10 figures, 5 tables; v3: Added addendum and three new references; v4: Added reference that was inadvertently omitte

Like Sign Dilepton Signature for R-Parity Violating SUSY Search at the Tevatron Collider

The like sign dileptons provide the most promising signature for superparticle search in a large category of $R$-parity violating SUSY models. We estimate the like sign dilepton signals at the Tevatron collider, predicted by these models, over a wide region of the MSSM parameter space. One expects an unambiguous signal upto a gluino mass of $200 - 300$ GeV ($\geq 500$ GeV) with the present (proposed) accumulated luminosity of $\sim 0.1~(1)~{\rm fb}^{-1}$.Comment: 12 page LaTeX file; 5 figures available upon request from the autho

Offspring ADHD as a risk factor for parental marital problems: Controls for genetic and environmental confounds

Background: Previous studies have found that child attention-deficit/hyperactivity disorder (ADHD) is associated with more parental marital problems. However, the reasons for this association are unclear. The association might be due to genetic or environmental confounds that contribute to both marital problems and ADHD. Method: Data were drawn from the Australian Twin Registry, including 1,296 individual twins, their spouses, and offspring. We studied adult twins who were discordant for offspring ADHD. Using a discordant twin pairs design, we examined the extent to which genetic and environmental confounds, as well as measured parental and offspring characteristics, explain the ADHD-marital problems association. Results: Offspring ADHD predicted parental divorce and marital conflict. The associations were also robust when comparing differentially exposed identical twins to control for unmeasured genetic and environmental factors, when controlling for measured maternal and paternal psychopathology, when restricting the sample based on timing of parental divorce and ADHD onset, and when controlling for other forms of offspring psychopathology. Each of these controls rules out alternative explanations for the association. Conclusion: The results of the current study converge with those of prior research in suggesting that factors directly associated with offspring ADHD increase parental marital problems

Algorithms for Game Metrics

Simulation and bisimulation metrics for stochastic systems provide a quantitative generalization of the classical simulation and bisimulation relations. These metrics capture the similarity of states with respect to quantitative specifications written in the quantitative {\mu}-calculus and related probabilistic logics. We first show that the metrics provide a bound for the difference in long-run average and discounted average behavior across states, indicating that the metrics can be used both in system verification, and in performance evaluation. For turn-based games and MDPs, we provide a polynomial-time algorithm for the computation of the one-step metric distance between states. The algorithm is based on linear programming; it improves on the previous known exponential-time algorithm based on a reduction to the theory of reals. We then present PSPACE algorithms for both the decision problem and the problem of approximating the metric distance between two states, matching the best known algorithms for Markov chains. For the bisimulation kernel of the metric our algorithm works in time O(n^4) for both turn-based games and MDPs; improving the previously best known O(n^9\cdot log(n)) time algorithm for MDPs. For a concurrent game G, we show that computing the exact distance between states is at least as hard as computing the value of concurrent reachability games and the square-root-sum problem in computational geometry. We show that checking whether the metric distance is bounded by a rational r, can be done via a reduction to the theory of real closed fields, involving a formula with three quantifier alternations, yielding O(|G|^O(|G|^5)) time complexity, improving the previously known reduction, which yielded O(|G|^O(|G|^7)) time complexity. These algorithms can be iterated to approximate the metrics using binary search.Comment: 27 pages. Full version of the paper accepted at FSTTCS 200

Near-Surface Oceanic Kinetic Energy Distributions From Drifter Observations and Numerical Models

The geographical variability, frequency content, and vertical structure of near-surface oceanic kinetic energy (KE) are important for air-sea interaction, marine ecosystems, operational oceanography, pollutant tracking, and interpreting remotely sensed velocity measurements. Here, KE in high-resolution global simulations (HYbrid Coordinate Ocean Model; HYCOM, and Massachusetts Institute of Technology general circulation model; MITgcm), at the sea surface (0 m) and at 15 m, are compared with KE from undrogued and drogued surface drifters, respectively. Global maps and zonal averages are computed for low-frequency

ALPGEN, a generator for hard multiparton processes in hadronic collisions

This paper presents a new event generator, ALPGEN, dedicated to the study of multiparton hard processes in hadronic collisions. The code performs, at the leading order in QCD and EW interactions, the calculation of the exact matrix elements for a large set of parton-level processes of interest in the study of the Tevatron and LHC data. The current version of the code describes the following final states: (W -> ffbar') QQbar+ N jets (Q being a heavy quark, and f=l,q), with N f fbar)+QQbar+Njets (f=l,nu), with N ffbar') + charm + N jets (f=l,q), N f fbar') + N jets (f=l,q) and (Z/gamma* -> f fbar)+ N jets (f=l,nu), with N<=6; nW+mZ+lH+N jets, with n+m+l+N<=8 and N<=3 including all 2-fermion decay modes of W and Z bosons, with spin correlations; Q Qbar+N jets (N b f fbar' decays and relative spin correlations included if Q=t; Q Qbar Q' Qbar'+N jets, with Q and Q' heavy quarks (possibly equal) and N b f fbar' decays and relative spin correlations included if Q=t; N jets, with N<=6. Parton-level events are generated, providing full information on their colour and flavour structure, enabling the evolution of the partons into fully hadronised final states.Comment: 1+38 pages, uses JHEP.cls. Documents code version 1.2: extended list of processes, updated documentation and bibliograph