Advances in understanding of air-sea exchange and cycling of greenhouse gases in the upper ocean

\ua9 2024 University of California Press. All rights reserved. The air–sea exchange and oceanic cycling of greenhouse gases (GHG), including carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), carbon monoxide (CO), and nitrogen oxides (NOx \ubc NO \ufe NO2), are fundamental in controlling the evolution of the Earth’s atmospheric chemistry and climate. Significant advances have been made over the last 10 years in understanding, instrumentation and methods, as well as deciphering the production and consumption pathways of GHG in the upper ocean (including the surface and subsurface ocean down to approximately 1000 m). The global ocean under current conditions is now well established as a major sink for CO2, a major source for N2O and a minor source for both CH4 and CO. The importance of the ocean as a sink or source of NOx is largely unknown so far. There are still considerable uncertainties about the processes and their major drivers controlling the distributions of N2O, CH4, CO, and NOx in the upper ocean. Without having a fundamental understanding of oceanic GHG production and consumption pathways, our knowledge about the effects of ongoing major oceanic changes—warming, acidification, deoxygenation, and eutrophication—on the oceanic cycling and air–sea exchange of GHG remains rudimentary at best. We suggest that only through a comprehensive, coordinated, and interdisciplinary approach that includes data collection by global observation networks as well as joint process studies can the necessary data be generated to (1) identify the relevant microbial and phytoplankton communities, (2) quantify the rates of ocean GHG production and consumption pathways, (3) comprehend their major drivers, and (4) decipher economic and cultural implications of mitigation solutions

Predicting participation in group parenting education in an Australian sample: The role of attitudes, norms, and control factors

We examined the theory of planned behavior (TPB) in predicting intentions to participate in group parenting education. One hundred and seventy-six parents (138 mothers and 38 fathers) with a child under 12 years completed TPB items assessing attitude, subjective norms, perceived behavioral control (PBC), and two additional social influence variables (self-identity and group norm). Regression analyses supported the TPB predictors of participation intentions with self-identity and group norm also significantly predicting intentions. These findings offer preliminary support for the TPB, along with additional sources of social influence, as a useful predictive model of participation in parenting education

A Realistic Radiative Fermion Mass Hierarchy in Non-supersymmetric SO(10)

A non-supersymmetric grand unified theory can exhibit a "radiative fermion mass hierarchy", in which the heavier quarks and leptons get mass at tree level and the lighter ones get mass from loop diagrams. Recently the first predictive model of this type was proposed. Here it is analyzed numerically and it is shown to give an excellent fit to the quark and lepton masses and mixings, including the CP phase violating phase $\delta_{CKM}$. A relation between the neutrino angle $\theta_{13}$ and the atmospheric neutrino angle is obtainedComment: 13 pages, 4 figures, RevTeX

Advances in understanding of air–sea exchange and cycling of greenhouse gases in the upper ocean

This is the final version. Available on open access from University of California Press via the DOI in this recordThe air–sea exchange and oceanic cycling of greenhouse gases (GHG), including carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), carbon monoxide (CO), and nitrogen oxides (NOx = NO + NO2), are fundamental in controlling the evolution of the Earth’s atmospheric chemistry and climate. Significant advances have been made over the last 10 years in understanding, instrumentation and methods, as well as deciphering the production and consumption pathways of GHG in the upper ocean (including the surface and subsurface ocean down to approximately 1000 m). The global ocean under current conditions is now well established as a major sink for CO2, a major source for N2O and a minor source for both CH4 and CO. The importance of the ocean as a sink or source of NOx is largely unknown so far. There are still considerable uncertainties about the processes and their major drivers controlling the distributions of N2O, CH4, CO, and NOx in the upper ocean. Without having a fundamental understanding of oceanic GHG production and consumption pathways, our knowledge about the effects of ongoing major oceanic changes—warming, acidification, deoxygenation, and eutrophication—on the oceanic cycling and air–sea exchange of GHG remains rudimentary at best. We suggest that only through a comprehensive, coordinated, and interdisciplinary approach that includes data collection by global observation networks as well as joint process studies can the necessary data be generated to (1) identify the relevant microbial and phytoplankton communities, (2) quantify the rates of ocean GHG production and consumption pathways, (3) comprehend their major drivers, and (4) decipher economic and cultural implications of mitigation solutions.European Space AgencyConvex Seascape SurveyEuropean Union Horizon 2020U.S. National Science Foundatio

Dissecting Genetic Networks Underlying Complex Phenotypes: The Theoretical Framework

Great progress has been made in genetic dissection of quantitative trait variation during the past two decades, but many studies still reveal only a small fraction of quantitative trait loci (QTLs), and epistasis remains elusive. We integrate contemporary knowledge of signal transduction pathways with principles of quantitative and population genetics to characterize genetic networks underlying complex traits, using a model founded upon one-way functional dependency of downstream genes on upstream regulators (the principle of hierarchy) and mutual functional dependency among related genes (functional genetic units, FGU). Both simulated and real data suggest that complementary epistasis contributes greatly to quantitative trait variation, and obscures the phenotypic effects of many ‘downstream’ loci in pathways. The mathematical relationships between the main effects and epistatic effects of genes acting at different levels of signaling pathways were established using the quantitative and population genetic parameters. Both loss of function and “co-adapted” gene complexes formed by multiple alleles with differentiated functions (effects) are predicted to be frequent types of allelic diversity at loci that contribute to the genetic variation of complex traits in populations. Downstream FGUs appear to be more vulnerable to loss of function than their upstream regulators, but this vulnerability is apparently compensated by different FGUs of similar functions. Other predictions from the model may account for puzzling results regarding responses to selection, genotype by environment interaction, and the genetic basis of heterosis

Perspectives and Integration in SOLAS Science

Why a chapter on Perspectives and Integration in SOLAS Science in this book? SOLAS science by its nature deals with interactions that occur: across a wide spectrum of time and space scales, involve gases and particles, between the ocean and the atmosphere, across many disciplines including chemistry, biology, optics, physics, mathematics, computing, socio-economics and consequently interactions between many different scientists and across scientific generations. This chapter provides a guide through the remarkable diversity of cross-cutting approaches and tools in the gigantic puzzle of the SOLAS realm. Here we overview the existing prime components of atmospheric and oceanic observing systems, with the acquisition of ocean–atmosphere observables either from in situ or from satellites, the rich hierarchy of models to test our knowledge of Earth System functioning, and the tremendous efforts accomplished over the last decade within the COST Action 735 and SOLAS Integration project frameworks to understand, as best we can, the current physical and biogeochemical state of the atmosphere and ocean commons. A few SOLAS integrative studies illustrate the full meaning of interactions, paving the way for even tighter connections between thematic fields. Ultimately, SOLAS research will also develop with an enhanced consideration of societal demand while preserving fundamental research coherency. The exchange of energy, gases and particles across the air-sea interface is controlled by a variety of biological, chemical and physical processes that operate across broad spatial and temporal scales. These processes influence the composition, biogeochemical and chemical properties of both the oceanic and atmospheric boundary layers and ultimately shape the Earth system response to climate and environmental change, as detailed in the previous four chapters. In this cross-cutting chapter we present some of the SOLAS achievements over the last decade in terms of integration, upscaling observational information from process-oriented studies and expeditionary research with key tools such as remote sensing and modelling. Here we do not pretend to encompass the entire legacy of SOLAS efforts but rather offer a selective view of some of the major integrative SOLAS studies that combined available pieces of the immense jigsaw puzzle. These include, for instance, COST efforts to build up global climatologies of SOLAS relevant parameters such as dimethyl sulphide, interconnection between volcanic ash and ecosystem response in the eastern subarctic North Pacific, optimal strategy to derive basin-scale CO2 uptake with good precision, or significant reduction of the uncertainties in sea-salt aerosol source functions. Predicting the future trajectory of Earth’s climate and habitability is the main task ahead. Some possible routes for the SOLAS scientific community to reach this overarching goal conclude the chapter

Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics

Spatial context in images induces perceptual phenomena associated with salience and modulates the responses of neurons in primary visual cortex (V1). However, the computational and ecological principles underlying contextual effects are incompletely understood. We introduce a model of natural images that includes grouping and segmentation of neighboring features based on their joint statistics, and we interpret the firing rates of V1 neurons as performing optimal recognition in this model. We show that this leads to a substantial generalization of divisive normalization, a computation that is ubiquitous in many neural areas and systems. A main novelty in our model is that the influence of the context on a target stimulus is determined by their degree of statistical dependence. We optimized the parameters of the model on natural image patches, and then simulated neural and perceptual responses on stimuli used in classical experiments. The model reproduces some rich and complex response patterns observed in V1, such as the contrast dependence, orientation tuning and spatial asymmetry of surround suppression, while also allowing for surround facilitation under conditions of weak stimulation. It also mimics the perceptual salience produced by simple displays, and leads to readily testable predictions. Our results provide a principled account of orientation-based contextual modulation in early vision and its sensitivity to the homogeneity and spatial arrangement of inputs, and lends statistical support to the theory that V1 computes visual salience

Public education institutions as providers of private training programs: Degree apprenticeships in the United Kingdom

The Humboldt model of higher education describes two main missions of universities, i.e. teaching and research; however, this has increasingly been complemented with the third mission of connecting with business and communities through knowledge transfer, valorisation, engagement and training. One important dimension of this third mission is the provision of training programmes which bring numerous benefits to universities and their constituent communities. Yet, closer inspection of this training reveals a complex array of provision and it is argued that the term ‘knowledge transfer’ provides a more accurate picture from a learning perspective. In recent decades, the UK has maintained a laissez-faire approach allowing industry to respond to the market; however, recently there has been a significant change with a new interventionist industrial strategy. The Industrial Strategy document described the University of Sheffield’s Advanced Manufacturing Research Centre (AMRC) as a role model for innovation and economic growth. The AMRC Training Centre will be discussed to provide a practical context with regard to degree apprenticeships and other training which is delivered to employees of approximately 300 companies, including Boeing, McLaren and Rolls Royce which have established manufacturing facilities at the AMRC

Jet energy measurement and its systematic uncertainty in proton–proton collisions at √s=7 TeV with the ATLAS detector

The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector using proton–proton collision data with a centre-of-mass energy of √s=7 TeV corresponding to an integrated luminosity of 4.7 fb −1. Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells using the anti-kt algorithm with distance parameters R=0.4 or R=0.6, and are calibrated using MC simulations. A residual JES correction is applied to account for differences between data and MC simulations. This correction and its systematic uncertainty are estimated using a combination of in situ techniques exploiting the transverse momentum balance between a jet and a reference object such as a photon or a Z boson, for 20≤pTjet1 TeV. The calibration of forward jets is derived from dijet pT balance measurements. The resulting uncertainty reaches its largest value of 6 % for low-pT jets at |η|=4.5. Additional JES uncertainties due to specific event topologies, such as close-by jets or selections of event samples with an enhanced content of jets originating from light quarks or gluons, are also discussed. The magnitude of these uncertainties depends on the event sample used in a given physics analysis, but typically amounts to 0.5–3 %