Relativistic transition wavelenghts and probabilities for spectral lines of Ne II

Transition wavelengths and probabilities for several 2p4 3p - 2p4 3s and 2p4 3d - 2p4 3p lines in fuorine-like neon ion (NeII) have been calculated within the multiconfiguration Dirac-Fock (MCDF) method with quantum electrodynamics (QED) corrections. The results are compared with all existing experimental and theoretical data

Computational Nuclear Physics and Post Hartree-Fock Methods

We present a computational approach to infinite nuclear matter employing Hartree-Fock theory, many-body perturbation theory and coupled cluster theory. These lectures are closely linked with those of chapters 9, 10 and 11 and serve as input for the correlation functions employed in Monte Carlo calculations in chapter 9, the in-medium similarity renormalization group theory of dense fermionic systems of chapter 10 and the Green's function approach in chapter 11. We provide extensive code examples and benchmark calculations, allowing thereby an eventual reader to start writing her/his own codes. We start with an object-oriented serial code and end with discussions on strategies for porting the code to present and planned high-performance computing facilities.Comment: 82 pages, to appear in Lecture Notes in Physics (Springer), "An advanced course in computational nuclear physics: Bridging the scales from quarks to neutron stars", M. Hjorth-Jensen, M. P. Lombardo, U. van Kolck, Editor

Clam feeding plasticity reduces herbivore vulnerability to ocean warming and acidification

Ocean warming and acidification affect species populations, but how interactions within communities are affected and how this translates into ecosystem functioning and resilience remain poorly understood. Here we demonstrate that experimental ocean warming and acidification significantly alters the interaction network among porewater nutrients, primary producers, herbivores and burrowing invertebrates in a seafloor sediment community, and is linked to behavioural plasticity in the clam Scrobicularia plana. Warming and acidification induced a shift in the clam's feeding mode from predominantly suspension feeding under ambient conditions to deposit feeding with cascading effects on nutrient supply to primary producers. Surface-dwelling invertebrates were more tolerant to warming and acidification in the presence of S. plana, most probably due to the stimulatory effect of the clam on their microalgal food resources. This study demonstrates that predictions of population resilience to climate change require consideration of non-lethal effects such as behavioural changes of key species. Changes in ocean temperature and pH will impact on species, as well as impacting on community interactions. Here warming and acidification cause a clam species to change their feeding mode, with cascading effects for the marine sedimentary food web

Testate amoeba response to acid deposition in a Scottish peatland

Peatlands around the world are exposed to anthropogenic or volcanogenic sulphur pollution. Impacts on peatland microbial communities have been inferred from changes in gas flux but have rarely been directly studied. In this study, the impacts of sulphuric acid deposition on peatland testate amoebae were investigated by analysis of experimental plots on a Scottish peatland almost 7 years after acid treatment. Results showed reduced concentration of live amoebae and changes in community structure which remained significant even when differences in pH were accounted for. Several possible explanations for the impacts can be proposed including taphonomic processes and changes in plant communities. Previous studies have inferred a shift from methanogenic archaea to sulphate-reducing bacteria in sulphate-treated peats; it is possible that the impacts detected here might relate to this change, perhaps through testate amoeba predation on methanotrophs

Ensuring efficient and robust offshore storage – The role of marine system modelling

This paper describes the utility of developing marine system models to aid the efficient and regulatory compliant development of offshore carbon storage, maximising containment assurance by well-planned monitoring strategies. Using examples from several model systems, we show that marine models allow us to characterize the chemical perturbations arising from hypothetical release scenarios whilst concurrently quantifying the natural variability of the system with respect to the same chemical signatures. Consequently models can identify a range of potential leakage anomaly detection criteria, identifying the most sensitive discriminators applicable to a given site or season. Further, using models as in-silico testbeds we can devise the most cost-efficient deployment of sensors to maximise detection of CO2 leakage. Modelling studies can also contribute to the required risk assessments, by quantifying potential impact from hypothetical release scenarios. Finally, given this demonstrable potential we discuss the challenges to ensuring model systems are available, fit for purpose and transferable to CCS operations across the globe

Generating and repairing genetically programmed DNA breaks during immunoglobulin class switch recombination

Adaptive immune responses require the generation of a diverse repertoire of immunoglobulins (Igs) that can recognize and neutralize a seemingly infinite number of antigens. V(D)J recombination creates the primary Ig repertoire, which subsequently is modified by somatic hypermutation (SHM) and class switch recombination (CSR). SHM promotes Ig affinity maturation whereas CSR alters the effector function of the Ig. Both SHM and CSR require activation-induced cytidine deaminase (AID) to produce dU:dG mismatches in the Ig locus that are transformed into untemplated mutations in variable coding segments during SHM or DNA double-strand breaks (DSBs) in switch regions during CSR. Within the Ig locus, DNA repair pathways are diverted from their canonical role in maintaining genomic integrity to permit AID-directed mutation and deletion of gene coding segments. Recently identified proteins, genes, and regulatory networks have provided new insights into the temporally and spatially coordinated molecular interactions that control the formation and repair of DSBs within the Ig locus. Unravelling the genetic program that allows B cells to selectively alter the Ig coding regions while protecting non-Ig genes from DNA damage advances our understanding of the molecular processes that maintain genomic integrity as well as humoral immunity

Re-imagining the future:repetition decreases hippocampal involvement in future simulation

Imagining or simulating future events has been shown to activate the anterior right hippocampus (RHC) more than remembering past events does. One fundamental difference between simulation and memory is that imagining future scenarios requires a more extensive constructive process than remembering past experiences does. Indeed, studies in which this constructive element is reduced or eliminated by “pre-imagining” events in a prior session do not report differential RHC activity during simulation. In this fMRI study, we examined the effects of repeatedly simulating an event on neural activity. During scanning, participants imagined 60 future events; each event was simulated three times. Activation in the RHC showed a significant linear decrease across repetitions, as did other neural regions typically associated with simulation. Importantly, such decreases in activation could not be explained by non-specific linear time-dependent effects, with no reductions in activity evident for the control task across similar time intervals. Moreover, the anterior RHC exhibited significant functional connectivity with the whole-brain network during the first, but not second and third simulations of future events. There was also evidence of a linear increase in activity across repetitions in right ventral precuneus, right posterior cingulate and left anterior prefrontal cortex, which may reflect source recognition and retrieval of internally generated contextual details. Overall, our findings demonstrate that repeatedly imagining future events has a decremental effect on activation of the hippocampus and many other regions engaged by the initial construction of the simulation, possibly reflecting the decreasing novelty of simulations across repetitions, and therefore is an important consideration in the design of future studies examining simulation

Juvenile king scallop, Pecten maximus, is potentially tolerant to low levels of ocean acidification when food is unrestricted.

The decline in ocean water pH and changes in carbonate saturation states through anthropogenically mediated increases in atmospheric CO2 levels may pose a hazard to marine organisms. This may be particularly acute for those species reliant on calcareous structures like shells and exoskeletons. This is of particular concern in the case of valuable commercially exploited species such as the king scallop, Pecten maximus. In this study we investigated the effects on oxygen consumption, clearance rates and cellular turnover in juvenile P. maximus following 3 months laboratory exposure to four pCO2 treatments (290, 380, 750 and 1140 µatm). None of the exposure levels were found to have significant effect on the clearance rates, respiration rates, condition index or cellular turnover (RNA: DNA) of individuals. While it is clear that some life stages of marine bivalves appear susceptible to future levels of ocean acidification, particularly under food limiting conditions, the results from this study suggest that where food is in abundance, bivalves like juvenile P. maximus may display a tolerance to limited changes in seawater chemistry

Neuroimaging-Based Classification of PTSD Using Data-Driven Computational Approaches:A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.</p