Impacts of variations in Caspian Sea surface area on catchment-scale and large-scale climate

The Caspian Sea (CS) is the largest inland lake in the world. Large variations in sea level and surface area occurred in the past and are projected for the future. The potential impacts on regional and large-scale hydroclimate are not well understood. Here, we examine the impact of CS area on climate within its catchment and across the northern hemisphere, for the first time with a fully coupled climate model. The Community Earth System Model (CESM1.2.2) is used to simulate the climate of four scenarios: (a) larger than present CS area, (b) current area, (c) smaller than present area, and (d) no-CS scenario. The results reveal large changes in the regional atmospheric water budget. Evaporation (e) over the sea increases with increasing area, while precipitation (P) increases over the south-west CS with increasing area. P-E over the CS catchment decreases as CS surface area increases, indicating a dominant negative lake-evaporation feedback. A larger CS reduces summer surface air temperatures and increases winter temperatures. The impacts extend eastwards, where summer precipitation is enhanced over central Asia and the north-western Pacific experiences warming with reduced winter sea ice. Our results also indicate weakening of the 500-hPa troughs over the northern Pacific with larger CS area. We find a thermal response triggers a southward shift of the upper troposphere jet stream during summer. Our findings establish that changing CS area results in climate impacts of such scope that CS area variations should be incorporated into climate model simulations, including palaeo and future scenarios. © 2021. The Authors

The unusual electronic structure of the "pseudo-ladder" compound CaCu2O3

Experimental and theoretical studies of the unoccupied electronic structure of CaCu2O3 single crystals have been performed using polarization-dependent x-ray absorption spectroscopy and band structure calculations. The measured hole distribution shows an unusual large number of holes in orbitals parallel to the interlayer direction which is in agreement with the theoretical analysis. CaCu2O3 deviates significantly from the standard pd-sigma cuprate picture. The corresponding strong interlayer exchange is responsible for the missing spin gap generic for other two-leg ladder cuprates.Comment: 4 pages, 3 figures include

Detecting controlling nodes of boolean regulatory networks

Boolean models of regulatory networks are assumed to be tolerant to perturbations. That qualitatively implies that each function can only depend on a few nodes. Biologically motivated constraints further show that functions found in Boolean regulatory networks belong to certain classes of functions, for example, the unate functions. It turns out that these classes have specific properties in the Fourier domain. That motivates us to study the problem of detecting controlling nodes in classes of Boolean networks using spectral techniques. We consider networks with unbalanced functions and functions of an average sensitivity less than 23k, where k is the number of controlling variables for a function. Further, we consider the class of 1-low networks which include unate networks, linear threshold networks, and networks with nested canalyzing functions. We show that the application of spectral learning algorithms leads to both better time and sample complexity for the detection of controlling nodes compared with algorithms based on exhaustive search. For a particular algorithm, we state analytical upper bounds on the number of samples needed to find the controlling nodes of the Boolean functions. Further, improved algorithms for detecting controlling nodes in large-scale unate networks are given and numerically studied

A recipe for simulating the interannual variability of the Asian summer monsoon and its relation with ENSO

Author Posting. © The Authors, 2006. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Climate Dynamics 28 (2007): 441-460, doi: 10.1007/s00382-006-0190-0.This study investigates how accurately the interannual variability over the Indian Ocean basin and the relationship between the Indian summer monsoon and the El Nino Southern Oscillation (ENSO) can be simulated by different modelling strategies. With a hierarchy of models, from an atmospherical general circulation model (AGCM) forced by observed SST, to a coupled model with the ocean component limited to the tropical Pacific and Indian Oceans, the role of heat fluxes and of interactive coupling is analyzed. Whenever sea surface temperature anomalies in the Indian basin are created by the coupled model, the inverse relationship between the ENSO index and the Indian summer monsoon rainfall is recovered, and it is preserved if the atmospherical model is forced by the SSTs created by the coupled model. If the ocean model domain is limited to the Indian Ocean, changes in the Walker circulation over the Pacific during El Nino years induce a decrease of rainfall over the Indian subcontinent. However the observed correlation between the ENSO and the Indian Ocean Zonal Mode (IOZM) is not properly modelled and the two indices are not significantly correlated, independently on season. Whenever the ocean domain extends to the Pacific, and ENSO can impact both the atmospheric circulation and the ocean subsurface in the equatorial Eastern Indian Ocean, modelled precipitation patterns associated both to ENSO and to the IOZM closely resemble the observations.The experiments described were performed as a contribution to the ENSEMBLES project funded by the European Commission’s 6th Framework Programme, contract number GOCE-CT-2003-505539

Bright Side of Lignin Depolymerization:Toward New Platform Chemicals

Lignin, a major component of lignocellulose, is the largest source of aromatic building blocks on the planet and harbors great potential to serve as starting material for the production of biobased products. Despite the initial challenges associated with the robust and irregular structure of lignin, the valorization of this intriguing aromatic biopolymer has come a long way: recently, many creative strategies emerged that deliver defined products via catalytic or biocatalytic depolymerization in good yields. The purpose of this review is to provide insight into these novel approaches and the potential application of such emerging new structures for the synthesis of biobased polymers or pharmacologically active molecules. Existing strategies for functionalization or defunctionalization of lignin-based compounds are also summarized. Following the whole value chain from raw lignocellulose through depolymerization to application whenever possible, specific lignin-based compounds emerge that could be in the future considered as potential lignin-derived platform chemicals

Identification of regulatory variants associated with genetic susceptibility to meningococcal disease

Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes

Identification of regulatory variants associated with genetic susceptibility to meningococcal disease.

Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes