International cooperation on the reduction of greenhouse gas emissions, disarmament, or free trade needs to be negotiated. The success of such negotiations depends on how they are designed. In the ...context of international climate change policy, it has been proposed e.g., M. L. Weitzman
(2014) that shifting the negotiation focus to a uniform common commitment (such as a uniform minimum carbon price) would lead to more ambitious cooperation. Yet, a proof-of-concept for this important claim is lacking. Based on game theoretical analyses, we present experimental evidence that strongly supports this conjecture. In our study, human subjects negotiate contributions to a public good. Subjects differ in their benefits and costs of cooperation. Participation in the negotiations and all commitments are voluntary. We consider treatments in which agreements are enforceable, and treatments in which they have to be self-enforcing. In both situations, negotiating a uniform common commitment is more successful in promoting cooperation than negotiating individual commitments (as in the Paris Agreement) and complex common commitments that tailor the commitment to the specific situation of each party (as attempted with the Kyoto Protocol). Furthermore, as suggested by our model, a uniform common commitment benefits most from being enforced.
Abstract
Carbon prices are the most cost-effective instrument to reduce CO$_2$ emissions, but there is strong political opposition to raising them to the efficient level. Therefore, additional ...efforts of consumers, firms and local governments are required. We study how different regulatory regimes affect moral behaviour and show that a carbon tax complements voluntary efforts to reduce emissions, while cap and trade discourages them. The opportunity to invest in offsets increases welfare, while the option to buy and delete emission rights induces more emissions and reduces welfare. Furthermore, cap and trade shifts the burden of adjustment to poor consumers and has dysfunctional incentive effects.
Cellular morphology and associated morphodynamics are widely used for qualitative and quantitative assessments of cell state. Here we implement a framework to profile cellular morphodynamics based on ...an adaptive decomposition of local cell boundary motion into instantaneous frequency spectra defined by the Hilbert-Huang transform (HHT). Our approach revealed that spontaneously migrating cells with approximately homogeneous molecular makeup show remarkably consistent instantaneous frequency distributions, though they have markedly heterogeneous mobility. Distinctions in cell edge motion between these cells are captured predominantly by differences in the magnitude of the frequencies. We found that acute photo-inhibition of Vav2 guanine exchange factor, an activator of the Rho family of signaling proteins coordinating cell motility, produces significant shifts in the frequency distribution, but does not affect frequency magnitude. We therefore concluded that the frequency spectrum encodes the wiring of the molecular circuitry that regulates cell boundary movements, whereas the magnitude captures the activation level of the circuitry. We also used HHT spectra as multi-scale spatiotemporal features in statistical region merging to identify subcellular regions of distinct motion behavior. In line with our conclusion that different HHT spectra relate to different signaling regimes, we found that subcellular regions with different morphodynamics indeed exhibit distinct Rac1 activities. This algorithm thus can serve as an accurate and sensitive classifier of cellular morphodynamics to pinpoint spatial and temporal boundaries between signaling regimes.
Structured illumination microscopy (SIM) surpasses the optical diffraction limit and offers a two-fold enhancement in resolution over diffraction limited microscopy. However, it requires both intense ...illumination and multiple acquisitions to produce a single high-resolution image. Using deep learning to augment SIM, we obtain a five-fold reduction in the number of raw images required for super-resolution SIM, and generate images under extreme low light conditions (at least 100× fewer photons). We validate the performance of deep neural networks on different cellular structures and achieve multi-color, live-cell super-resolution imaging with greatly reduced photobleaching.
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•Insert domains to allosterically control the active site with light or rapamycin.•Computational approach finds surface loops allosterically coupled to active site.•Generate split ...proteins with reduced spontaneous assembly.•Algorithm to assist finding sites to generate split proteins.•Tested on GTPases, GEFs and kinases.
Optogenetics, genetically encoded engineering of proteins to respond to light, has enabled precise control of the timing and localization of protein activity in live cells and for specific cell types in animals. Light-sensitive ion channels have become well established tools in neurobiology, and a host of new methods have recently enabled the control of other diverse protein structures as well. This review focuses on approaches to switch proteins between physiologically relevant, naturally occurring conformations using light, accomplished by incorporating light-responsive engineered domains that sterically and allosterically control the active site.
Optogenetics, the use of genetically encoded tools to control protein function with light, can generate localized changes in signaling within living cells and animals. For years it has been focused ...on channel proteins for neurobiology, but has recently expanded to cover many different types of proteins, using a broad array of different protein engineering approaches. These methods have largely been directed at proteins involved in motility, cytoskeletal regulation and gene expression. This review provides a survey of non-channel proteins that have been engineered for optogenetics. Existing molecules are used to illustrate the advantages and disadvantages of the many imaginative new approaches that the reader can use to create light-controlled proteins.
Google matrix analysis of directed networks Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.
Reviews of modern physics,
11/2015, Letnik:
87, Številka:
4
Journal Article
Recenzirano
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In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. ...Because of the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines extensively use such methods. It is highly important to develop new tools to classify and rank a massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including the World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences, and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos, and random matrix theory.
Metabolomics is the rapidly evolving field of the comprehensive measurement of ideally all endogenous metabolites in a biological fluid. However, no single analytic technique covers the entire ...spectrum of the human metabolome. Here we present results from a multiplatform study, in which we investigate what kind of results can presently be obtained in the field of diabetes research when combining metabolomics data collected on a complementary set of analytical platforms in the framework of an epidemiological study.
40 individuals with self-reported diabetes and 60 controls (male, over 54 years) were randomly selected from the participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg) study, representing an extensively phenotyped sample of the general German population. Concentrations of over 420 unique small molecules were determined in overnight-fasting blood using three different techniques, covering nuclear magnetic resonance and tandem mass spectrometry. Known biomarkers of diabetes could be replicated by this multiple metabolomic platform approach, including sugar metabolites (1,5-anhydroglucoitol), ketone bodies (3-hydroxybutyrate), and branched chain amino acids. In some cases, diabetes-related medication can be detected (pioglitazone, salicylic acid).
Our study depicts the promising potential of metabolomics in diabetes research by identification of a series of known and also novel, deregulated metabolites that associate with diabetes. Key observations include perturbations of metabolic pathways linked to kidney dysfunction (3-indoxyl sulfate), lipid metabolism (glycerophospholipids, free fatty acids), and interaction with the gut microflora (bile acids). Our study suggests that metabolic markers hold the potential to detect diabetes-related complications already under sub-clinical conditions in the general population.
We present a synergic study of protoplanetary disks to investigate links between inner-disk gas molecules and the large-scale migration of solid pebbles. The sample includes 63 disks where two types ...of measurements are available: (1) spatially resolved disk images revealing the radial distribution of disk pebbles (millimeter to centimeter dust grains), from millimeter observations with the Atacama Large Millimeter/Submillimeter Array or the Submillimeter Array, and (2) infrared molecular emission spectra as observed with Spitzer. The line flux ratios of H2O with HCN, C2H2, and CO2 all anticorrelate with the dust disk radius Rdust, expanding previous results found by Najita et al. for HCN/H2O and the dust disk mass. By normalization with the dependence on accretion luminosity common to all molecules, only the H2O luminosity maintains a detectable anticorrelation with disk radius, suggesting that the strongest underlying relation is between H2O and Rdust. If Rdust is set by large-scale pebble drift, and if molecular luminosities trace the elemental budgets of inner-disk warm gas, these results can be naturally explained with scenarios where the inner disk chemistry is fed by sublimation of oxygen-rich icy pebbles migrating inward from the outer disk. Anticorrelations are also detected between all molecular luminosities and the infrared index n13-30, which is sensitive to the presence and size of an inner-disk dust cavity. Overall, these relations suggest a physical interconnection between dust and gas evolution, both locally and across disk scales. We discuss fundamental predictions to test this interpretation and study the interplay between pebble drift, inner disk depletion, and the chemistry of planet-forming material.
The JWST Early Release Observations Pontoppidan, Klaus M.; Barrientes, Jaclyn; Blome, Claire ...
Astrophysical journal. Letters,
09/2022, Letnik:
936, Številka:
1
Journal Article
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Abstract
The James Webb Space Telescope (JWST) Early Release Observations (EROs) is a set of public outreach products created to mark the end of commissioning and the beginning of science operations ...for JWST. Colloquially known as the “Webb First Images and Spectra,” these products were intended to demonstrate to the worldwide public that JWST is ready for science, and is capable of producing spectacular results. The package was released on 2022 July 12 and included images and spectra of the galaxy cluster SMACS J0723.3-7327 and distant lensed galaxies, the interacting galaxy group Stephan’s Quintet, NGC 3324 in the Carina star-forming complex, the Southern Ring planetary nebula NGC 3132, and the transiting hot Jupiter WASP-96b. This paper describes the ERO technical design, observations, and scientific processing of data underlying the colorful outreach products.
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