Signal and noise in global warming detection. Final report

The specific objectives of this study were the following: (1) What is the expected sampling error and bias incurred in estimation of the global average temperature from a finite number of point gauges? (2) What is the best one can do by optimally arranging N point gauges, how can one make best use of existing data at N point gauges by optimally weighting them? (3) What is a good estimation of the signal of global warming based upon simple models of the climate system? (4) How does one develop an optimal signal detection technique from the knowledge of signal and noise

Suppression of non-Poissonian shot noise by Coulomb correlations in ballistic conductors

We investigate the current injection into a ballistic conductor under the space-charge limited regime, when the distribution function of injected carriers is an arbitrary function of energy F_c(epsilon). The analysis of the coupled kinetic and Poisson equations shows that the injected current fluctuations may be essentially suppressed by Coulomb correlations, and the suppression level is determined by the shape of F_c(epsilon). This is in contrast to the time-averaged quantities: the mean current and the spatial profiles are shown to be insensitive to F_c(epsilon) in the leading-order terms at high biases. The asymptotic high-bias behavior for the energy resolved shot-noise suppression has been found for an arbitrary (non-Poissonian) injection, which may suggest a new field of investigation on the optimization of the injected energy profile to achieve the desired noise-suppression level.Comment: extended version 4 -> 8 pages, examples and figure adde

Suppression of non-Poissonian shot noise by Coulomb correlations in ballistic conductors

We investigate the current injection into a ballistic conductor under the space-charge limited regime, when the distribution function of injected carriers is an arbitrary function of energy F_c(epsilon). The analysis of the coupled kinetic and Poisson equations shows that the injected current fluctuations may be essentially suppressed by Coulomb correlations, and the suppression level is determined by the shape of F_c(epsilon). This is in contrast to the time-averaged quantities: the mean current and the spatial profiles are shown to be insensitive to F_c(epsilon) in the leading-order terms at high biases. The asymptotic high-bias behavior for the energy resolved shot-noise suppression has been found for an arbitrary (non-Poissonian) injection, which may suggest a new field of investigation on the optimization of the injected energy profile to achieve the desired noise-suppression level.Comment: extended version 4 -> 8 pages, examples and figure adde

Node-weighted measures for complex networks with spatially embedded, sampled, or differently sized nodes

When network and graph theory are used in the study of complex systems, a typically finite set of nodes of the network under consideration is frequently either explicitly or implicitly considered representative of a much larger finite or infinite region or set of objects of interest. The selection procedure, e.g., formation of a subset or some kind of discretization or aggregation, typically results in individual nodes of the studied network representing quite differently sized parts of the domain of interest. This heterogeneity may induce substantial bias and artifacts in derived network statistics. To avoid this bias, we propose an axiomatic scheme based on the idea of node splitting invariance to derive consistently weighted variants of various commonly used statistical network measures. The practical relevance and applicability of our approach is demonstrated for a number of example networks from different fields of research, and is shown to be of fundamental importance in particular in the study of spatially embedded functional networks derived from time series as studied in, e.g., neuroscience and climatology.Comment: 21 pages, 13 figure

Regional forecasting with global atmospheric models; Fourth year report

The scope of the report is to present the results of the fourth year`s work on the atmospheric modeling part of the global climate studies task. The development testing of computer models and initial results are discussed. The appendices contain studies that provide supporting information and guidance to the modeling work and further details on computer model development. Complete documentation of the models, including user information, will be prepared under separate reports and manuals

Regional forecasting with global atmospheric models; Fourth year report

The scope of the report is to present the results of the fourth year`s work on the atmospheric modeling part of the global climate studies task. The development testing of computer models and initial results are discussed. The appendices contain studies that provide supporting information and guidance to the modeling work and further details on computer model development. Complete documentation of the models, including user information, will be prepared under separate reports and manuals

Scientists’ call to action: Microbes, planetary health, and the Sustainable Development Goals

Microorganisms, including bacteria, archaea, viruses, fungi, and protists, are essential to life on Earth and the functioning of the biosphere. Here, we discuss the key roles of microorganisms in achieving the United Nations Sustainable Development Goals (SDGs), highlighting recent and emerging advances in microbial research and technology that can facilitate our transition toward a sustainable future. Given the central role of microorganisms in the biochemical processing of elements, synthesizing new materials, supporting human health, and facilitating life in managed and natural landscapes, microbial research and technologies are directly or indirectly relevant for achieving each of the SDGs. More importantly, the ubiquitous and global role of microbes means that they present new opportunities for synergistically accelerating progress toward multiple sustainability goals. By effectively managing microbial health, we can achieve solutions that address multiple sustainability targets ranging from climate and human health to food and energy production. Emerging international policy frameworks should reflect the vital importance of microorganisms in achieving a sustainable future.Funding was provided by the Bernina Foundation and DOB Ecolog

Associations of autozygosity with a broad range of human phenotypes

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44–66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding