The investigation of vertebral injury sustained during aircrew ejection. Phase 2a - Basic science experimental design and investigation of dynamic characteristics of vertebral columns considered as an engineering structure Annual report, 1 Nov. 1966 - 31 Oct. 1967

Dynamic strength studies on human vertebrae for correlation with data on effects of forcible ejection from disabled aircraf

Unique transcriptomic landscapes identified in idiopathic spontaneous and infection related preterm births compared to normal term births.

Preterm birth (PTB) is leading contributor to infant death in the United States and globally, yet the underlying mechanistic causes are not well understood. Histopathological studies of preterm birth suggest advanced villous maturity may have a role in idiopathic spontaneous preterm birth (isPTB). To better understand pathological and molecular basis of isPTB, we compared placental villous transcriptomes from carefully phenotyped cohorts of PTB due to infection or isPTB between 28-36 weeks gestation and healthy term placentas. Transcriptomic analyses revealed a unique expression signature for isPTB distinct from the age-matched controls that were delivered prematurely due to infection. This signature included the upregulation of three IGF binding proteins (IGFBP1, IGFBP2, and IGFBP6), supporting a role for aberrant IGF signaling in isPTB. However, within the isPTB expression signature, we detected secondary signature of inflammatory markers including TNC, C3, CFH, and C1R, which have been associated with placental maturity. In contrast, the expression signature of the gestational age-matched infected samples included upregulation of proliferative genes along with cell cycling and mitosis pathways. Together, these data suggest an isPTB molecular signature of placental hypermaturity, likely contributing to the premature activation of inflammatory pathways associated with birth and providing a molecular basis for idiopathic spontaneous birth

Outsourcing or efficiency? Investigating the decline in final energy consumption in the UK productive sectors

Over the past two decades reductions in the final energy consumption of the productive sectors (industry, public administration, commercial services and agriculture), have made important contributions to overall reductions in UK final energy consumption. This study investigates the drivers of the reductions in final energy consumption in the UK productive sectors between 1997 and 2013 using a decomposition analysis that incorporates two novel approaches. Firstly, it uses results from a multi-regional input-output model to investigate how much of the structural change in the economy has been driven by outsourcing production overseas. Secondly, it utilises energy conversion chain analysis to determine how much increases in the conversion efficiency from final energy to useful exergy have contributed to improvements in final energy intensity. In aggregate all energy savings from structural change are attributed to outsourcing. Improvements in the conversion efficiency produced savings of a similar size. However energy savings from both factors have stalled since 2009. Improvements in useful exergy intensity, the useful exergy used per unit of monetary output, provided the biggest share of energy savings, but these savings are concentrated in a few sectors and rarely lead to absolute reductions in final energy use. All of this suggests that a return to the rates of energy reduction seen between 2001 and 2009 should not be taken for granted and that active policy interventions might be required to achieve further reductions

A Diffusion Network Event History Estimator

Research on the diffusion of political decisions across jurisdictions typically accounts for units’ influence over each other with (1) observable measures or (2) by inferring latent network ties from past decisions. The former approach assumes that interdependence is static and perfectly captured by the data. The latter mitigates these issues but requires analytical tools that are separate from the main empirical methods for studying diffusion. As a solution, we introduce network event history analysis (NEHA), which incorporates latent network inference into conventional discrete-time event history models. We demonstrate NEHA’s unique methodological and substantive benefits in applications to policy adoption in the American states. Researchers can analyze the ties and structure of inferred networks to refine model specifications, evaluate diffusion mechanisms, or test new or existing hypotheses. By capturing targeted relationships unexplained by standard covariates, NEHA can improve models, facilitate richer theoretical development, and permit novel analyses of the diffusion process

Dimming Supernovae without Cosmic Acceleration

We present a simple model where photons propagating in extra-galactic magnetic fields can oscillate into very light axions. The oscillations may convert some of the photons departing a distant supernova into axions, making the supernova appear dimmer and hence more distant than it really is. Averaging over different configurations of the magnetic field we find that the dimming saturates at about 1/3 of the light from the supernovae at very large redshifts. This results in a luminosity-distance vs. redshift curve almost indistinguishable from that produced by the accelerating Universe, if the axion mass and coupling scale are m ~ 10^-16 eV, M ~ 4 10^11 GeV. This phenomenon may be an alternative to the accelerating Universe for explaining supernova observations.Comment: 11 pages, LaTex, 2 figures included. Comments on effects of refraction within galaxies and references adde

Modelling net-zero emissions energy systems requires a change in approach

Energy modelling can assist national decision makers in determining strategies that achieve net-zero greenhouse gas (GHG) emissions. However, three key challenges for the modelling community are emerging under this radical climate target that needs to be recognized and addressed. A first challenge is the need to represent new mitigation options not currently represented in many energy models. We emphasize here the under representation of end-use sector demand-side options due to the traditional supply side focus of many energy models, along with issues surrounding robustness in deploying carbon dioxide removal (CDR) options. A second challenge concerns the types of models used. We highlight doubts about whether current models provide sufficient relevant insights on system feasibility, actor behaviour, and policy effectiveness. A third challenge concerns how models are applied for policy analyses. Priorities include the need for expanding scenario thinking to incorporate a wider range of uncertainty factors, providing insights on target setting, alignment with broader policy objectives, and improving engagement and transparency of approaches. There is a significant risk that without reconsidering energy modelling approaches, the role that the modelling community can play in providing effective decision support may be reduced. Such support is critical, as countries seek to develop new Nationally Determined Contributions and longer-term strategies over the next few years

Modelling net-zero emissions energy systems requires a change in approach

Energy modelling can assist national decision makers in determining strategies that achieve net-zero greenhouse gas (GHG) emissions. However, three key challenges for the modelling community are emerging under this radical climate target that needs to be recognized and addressed. A first challenge is the need to represent new mitigation options not currently represented in many energy models. We emphasize here the under representation of end-use sector demand-side options due to the traditional supply side focus of many energy models, along with issues surrounding robustness in deploying carbon dioxide removal (CDR) options. A second challenge concerns the types of models used. We highlight doubts about whether current models provide sufficient relevant insights on system feasibility, actor behaviour, and policy effectiveness. A third challenge concerns how models are applied for policy analyses. Priorities include the need for expanding scenario thinking to incorporate a wider range of uncertainty factors, providing insights on target setting, alignment with broader policy objectives, and improving engagement and transparency of approaches. There is a significant risk that without reconsidering energy modelling approaches, the role that the modelling community can play in providing effective decision support may be reduced. Such support is critical, as countries seek to develop new Nationally Determined Contributions and longer-term strategies over the next few years

Constraints on Variant Axion Models

A particular class of variant axion models with two higgs doublets and a singlet is studied. In these models the axion couples either to the $u$-quark or $t$-quark or both, but not to $b$, $c$, $s$, or $d$. When the axion couples to only one quark the models possess the desirable feature of having no domain wall problem, which makes them viable candidates for a cosmological axion string scenario. We calculate the axion couplings to leptons, photons and nucleons, and the astrophysical constraints on the axion decay constant $v_a$ are investigated and compared to the DFSZ axion model. We find that the most restrictive lower bound on $v_a$, that from SN1987a, is lowered by up to a factor of about 30, depending on the model and also the ratio of the vacuum expectation values of the higgs doublets. For scenarios with axionic strings, the allowed window for $v_a$ in the $u$ quark model can be more than two orders of magnitude. For inflationary scenarios, the cosmological upper bound on $v_a/N$, where $N$ is the QCD anomaly factor, is unaffected: however, the variant models have $N$ either 3 or 6 times smaller than the DFSZ model.Comment: 21pp RevTeX, 1 eps fig, uses graphics style, typo corrected, and corrected file sent this time. To appear in Physical Review