@article{8644,
  abstract     = {Determining the phase diagram of systems consisting of smaller subsystems 'connected' via a tunable coupling is a challenging task relevant for a variety of physical settings. A general question is whether new phases, not present in the uncoupled limit, may arise. We use machine learning and a suitable quasidistance between different points of the phase diagram to study layered spin models, in which the spin variables constituting each of the uncoupled systems (to which we refer as layers) are coupled to each other via an interlayer coupling. In such systems, in general, composite order parameters involving spins of different layers may emerge as a consequence of the interlayer coupling. We focus on the layered Ising and Ashkin–Teller models as a paradigmatic case study, determining their phase diagram via the application of a machine learning algorithm to the Monte Carlo data. Remarkably our technique is able to correctly characterize all the system phases also in the case of hidden order parameters, i.e. order parameters whose expression in terms of the microscopic configurations would require additional preprocessing of the data fed to the algorithm. We correctly retrieve the three known phases of the Ashkin–Teller model with ferromagnetic couplings, including the phase described by a composite order parameter. For the bilayer and trilayer Ising models the phases we find are only the ferromagnetic and the paramagnetic ones. Within the approach we introduce, owing to the construction of convolutional neural networks, naturally suitable for layered image-like data with arbitrary number of layers, no preprocessing of the Monte Carlo data is needed, also with regard to its spatial structure. The physical meaning of our results is discussed and compared with analytical data, where available. Yet, the method can be used without any a priori knowledge of the phases one seeks to find and can be applied to other models and structures.},
  author       = {Rzadkowski, Wojciech and Defenu, N and Chiacchiera, S and Trombettoni, A and Bighin, Giacomo},
  issn         = {13672630},
  journal      = {New Journal of Physics},
  number       = {9},
  publisher    = {IOP Publishing},
  title        = {{Detecting composite orders in layered models via machine learning}},
  doi          = {10.1088/1367-2630/abae44},
  volume       = {22},
  year         = {2020},
}

@article{8645,
  abstract     = {Epistasis, the context-dependence of the contribution of an amino acid substitution to fitness, is common in evolution. To detect epistasis, fitness must be measured for at least four genotypes: the reference genotype, two different single mutants and a double mutant with both of the single mutations. For higher-order epistasis of the order n, fitness has to be measured for all 2n genotypes of an n-dimensional hypercube in genotype space forming a ‘combinatorially complete dataset’. So far, only a handful of such datasets have been produced by manual curation. Concurrently, random mutagenesis experiments have produced measurements of fitness and other phenotypes in a high-throughput manner, potentially containing a number of combinatorially complete datasets. We present an effective recursive algorithm for finding all hypercube structures in random mutagenesis experimental data. To test the algorithm, we applied it to the data from a recent HIS3 protein dataset and found all 199 847 053 unique combinatorially complete genotype combinations of dimensionality ranging from 2 to 12. The algorithm may be useful for researchers looking for higher-order epistasis in their high-throughput experimental data.},
  author       = {Esteban, Laura A and Lonishin, Lyubov R and Bobrovskiy, Daniil M and Leleytner, Gregory and Bogatyreva, Natalya S and Kondrashov, Fyodor and Ivankov, Dmitry N },
  issn         = {1460-2059},
  journal      = {Bioinformatics},
  number       = {6},
  pages        = {1960--1962},
  publisher    = {Oxford Academic},
  title        = {{HypercubeME: Two hundred million combinatorially complete datasets from a single experiment}},
  doi          = {10.1093/bioinformatics/btz841},
  volume       = {36},
  year         = {2020},
}

@article{8652,
  abstract     = {Nature creates electrons with two values of the spin projection quantum number. In certain applications, it is important to filter electrons with one spin projection from the rest. Such filtering is not trivial, since spin-dependent interactions are often weak, and cannot lead to any substantial effect. Here we propose an efficient spin filter based upon scattering from a two-dimensional crystal, which is made of aligned point magnets. The polarization of the outgoing electron flux is controlled by the crystal, and reaches maximum at specific values of the parameters. In our scheme, polarization increase is accompanied by higher reflectivity of the crystal. High transmission is feasible in scattering from a quantum cavity made of two crystals. Our findings can be used for studies of low-energy spin-dependent scattering from two-dimensional ordered structures made of magnetic atoms or aligned chiral molecules.},
  author       = {Ghazaryan, Areg and Lemeshko, Mikhail and Volosniev, Artem},
  issn         = {2399-3650},
  journal      = {Communications Physics},
  publisher    = {Springer Nature},
  title        = {{Filtering spins by scattering from a lattice of point magnets}},
  doi          = {10.1038/s42005-020-00445-8},
  volume       = {3},
  year         = {2020},
}

@phdthesis{8653,
  abstract     = {Mutations are the raw material of evolution and come in many different flavors. Point mutations change a single letter in the DNA sequence, while copy number mutations like duplications or deletions add or remove many letters of the DNA sequence simultaneously.  Each type of mutation exhibits specific properties like its rate of formation and reversal. 
Gene expression is a fundamental phenotype that can be altered by both, point and copy number mutations. The following thesis is concerned with the dynamics of gene expression evolution and how it is affected by the properties exhibited by point and copy number mutations. Specifically, we are considering i) copy number mutations during adaptation to fluctuating environments and ii) the interaction of copy number and point mutations during adaptation to constant environments.  },
  author       = {Tomanek, Isabella},
  issn         = {2663-337X},
  keywords     = {duplication, amplification, promoter, CNV, AMGET, experimental evolution, Escherichia coli},
  pages        = {117},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{The evolution of gene expression by copy number and point mutations}},
  doi          = {10.15479/AT:ISTA:8653},
  year         = {2020},
}

@phdthesis{8657,
  abstract     = {Synthesis of proteins – translation – is a fundamental process of life. Quantitative studies anchor translation into the context of bacterial physiology and reveal several mathematical relationships, called “growth laws,” which capture physiological feedbacks between protein synthesis and cell growth. Growth laws describe the dependency of the ribosome abundance as a function of growth rate, which can change depending on the growth conditions. Perturbations of translation reveal that bacteria employ a compensatory strategy in which the reduced translation capability results in increased expression of the translation machinery.
Perturbations of translation are achieved in various ways; clinically interesting is the application of translation-targeting antibiotics – translation inhibitors. The antibiotic effects on bacterial physiology are often poorly understood. Bacterial responses to two or more simultaneously applied antibiotics are even more puzzling. The combined antibiotic effect determines the type of drug interaction, which ranges from synergy (the effect is stronger than expected) to antagonism (the effect is weaker) and suppression (one of the drugs loses its potency).
In the first part of this work, we systematically measure the pairwise interaction network for translation inhibitors that interfere with different steps in translation. We find that the interactions are surprisingly diverse and tend to be more antagonistic. To explore the underlying mechanisms, we begin with a minimal biophysical model of combined antibiotic action. We base this model on the kinetics of antibiotic uptake and binding together with the physiological response described by the growth laws. The biophysical model explains some drug interactions, but not all; it specifically fails to predict suppression.
In the second part of this work, we hypothesize that elusive suppressive drug interactions result from the interplay between ribosomes halted in different stages of translation. To elucidate this putative mechanism of drug interactions between translation inhibitors, we generate translation bottlenecks genetically using in- ducible control of translation factors that regulate well-defined translation cycle steps. These perturbations accurately mimic antibiotic action and drug interactions, supporting that the interplay of different translation bottlenecks partially causes these interactions.
We extend this approach by varying two translation bottlenecks simultaneously. This approach reveals the suppression of translocation inhibition by inhibited translation. We rationalize this effect by modeling dense traffic of ribosomes that move on transcripts in a translation factor-mediated manner. This model predicts a dissolution of traffic jams caused by inhibited translocation when the density of ribosome traffic is reduced by lowered initiation. We base this model on the growth laws and quantitative relationships between different translation and growth parameters.
In the final part of this work, we describe a set of tools aimed at quantification of physiological and translation parameters. We further develop a simple model that directly connects the abundance of a translation factor with the growth rate, which allows us to extract physiological parameters describing initiation. We demonstrate the development of tools for measuring translation rate.
This thesis showcases how a combination of high-throughput growth rate mea- surements, genetics, and modeling can reveal mechanisms of drug interactions. Furthermore, by a gradual transition from combinations of antibiotics to precise genetic interventions, we demonstrated the equivalency between genetic and chemi- cal perturbations of translation. These findings tile the path for quantitative studies of antibiotic combinations and illustrate future approaches towards the quantitative description of translation.},
  author       = {Kavcic, Bor},
  isbn         = {978-3-99078-011-4},
  issn         = {2663-337X},
  pages        = {271},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Perturbations of protein synthesis: from antibiotics to genetics and physiology}},
  doi          = {10.15479/AT:ISTA:8657},
  year         = {2020},
}

@article{8669,
  abstract     = {Pancreatic islets play an essential role in regulating blood glucose level. Although the molecular pathways underlying islet cell differentiation are beginning to be resolved, the cellular basis of islet morphogenesis and fate allocation remain unclear. By combining unbiased and targeted lineage tracing, we address the events leading to islet formation in the mouse. From the statistical analysis of clones induced at multiple embryonic timepoints, here we show that, during the secondary transition, islet formation involves the aggregation of multiple equipotent endocrine progenitors that transition from a phase of stochastic amplification by cell division into a phase of sublineage restriction and limited islet fission. Together, these results explain quantitatively the heterogeneous size distribution and degree of polyclonality of maturing islets, as well as dispersion of progenitors within and between islets. Further, our results show that, during the secondary transition, α- and β-cells are generated in a contemporary manner. Together, these findings provide insight into the cellular basis of islet development.},
  author       = {Sznurkowska, Magdalena K. and Hannezo, Edouard B and Azzarelli, Roberta and Chatzeli, Lemonia and Ikeda, Tatsuro and Yoshida, Shosei and Philpott, Anna and Simons, Benjamin D},
  issn         = {20411723},
  journal      = {Nature Communications},
  publisher    = {Springer Nature},
  title        = {{Tracing the cellular basis of islet specification in mouse pancreas}},
  doi          = {10.1038/s41467-020-18837-3},
  volume       = {11},
  year         = {2020},
}

@article{8670,
  abstract     = {The α–z Rényi relative entropies are a two-parameter family of Rényi relative entropies that are quantum generalizations of the classical α-Rényi relative entropies. In the work [Adv. Math. 365, 107053 (2020)], we decided the full range of (α, z) for which the data processing inequality (DPI) is valid. In this paper, we give algebraic conditions for the equality in DPI. For the full range of parameters (α, z), we give necessary conditions and sufficient conditions. For most parameters, we give equivalent conditions. This generalizes and strengthens the results of Leditzky et al. [Lett. Math. Phys. 107, 61–80 (2017)].},
  author       = {Zhang, Haonan},
  issn         = {00222488},
  journal      = {Journal of Mathematical Physics},
  number       = {10},
  publisher    = {AIP Publishing},
  title        = {{Equality conditions of data processing inequality for α-z Rényi relative entropies}},
  doi          = {10.1063/5.0022787},
  volume       = {61},
  year         = {2020},
}

@article{8671,
  abstract     = {We study relations between evidence theory and S-approximation spaces. Both theories have their roots in the analysis of Dempsterchr('39')s multivalued mappings and lower and upper probabilities, and have close relations to rough sets. We show that an S-approximation space, satisfying a monotonicity condition, can induce a natural belief structure which is a fundamental block in evidence theory. We also demonstrate that one can induce a natural belief structure on one set, given a belief structure on another set, if the two sets are related by a partial monotone S-approximation space. },
  author       = {Shakiba, A. and Goharshady, Amir Kafshdar and Hooshmandasl, M.R. and Alambardar Meybodi, M.},
  issn         = {2008-9473},
  journal      = {Iranian Journal of Mathematical Sciences and Informatics},
  number       = {2},
  pages        = {117--128},
  publisher    = {Iranian Academic Center for Education, Culture and Research},
  title        = {{A note on belief structures and s-approximation spaces}},
  doi          = {10.29252/ijmsi.15.2.117},
  volume       = {15},
  year         = {2020},
}

@article{8672,
  abstract     = {Cell fate transitions are key to development and homeostasis. It is thus essential to understand the cellular mechanisms controlling fate transitions. Cell division has been implicated in fate decisions in many stem cell types, including neuronal and epithelial progenitors. In other stem cells, such as embryonic stem (ES) cells, the role of division remains unclear. Here, we show that exit from naive pluripotency in mouse ES cells generally occurs after a division. We further show that exit timing is strongly correlated between sister cells, which remain connected by cytoplasmic bridges long after division, and that bridge abscission progressively accelerates as cells exit naive pluripotency. Finally, interfering with abscission impairs naive pluripotency exit, and artificially inducing abscission accelerates it. Altogether, our data indicate that a switch in the division machinery leading to faster abscission regulates pluripotency exit. Our study identifies abscission as a key cellular process coupling cell division to fate transitions.},
  author       = {Chaigne, Agathe and Labouesse, Céline and White, Ian J. and Agnew, Meghan and Hannezo, Edouard B and Chalut, Kevin J. and Paluch, Ewa K.},
  issn         = {18781551},
  journal      = {Developmental Cell},
  number       = {2},
  pages        = {195--208},
  publisher    = {Elsevier},
  title        = {{Abscission couples cell division to embryonic stem cell fate}},
  doi          = {10.1016/j.devcel.2020.09.001},
  volume       = {55},
  year         = {2020},
}

@article{8674,
  abstract     = {Extrasynaptic actions of glutamate are limited by high-affinity transporters expressed by perisynaptic astroglial processes (PAPs): this helps maintain point-to-point transmission in excitatory circuits. Memory formation in the brain is associated with synaptic remodeling, but how this affects PAPs and therefore extrasynaptic glutamate actions is poorly understood. Here, we used advanced imaging methods, in situ and in vivo, to find that a classical synaptic memory mechanism, long-term potentiation (LTP), triggers withdrawal of PAPs from potentiated synapses. Optical glutamate sensors combined with patch-clamp and 3D molecular localization reveal that LTP induction thus prompts spatial retreat of astroglial glutamate transporters, boosting glutamate spillover and NMDA-receptor-mediated inter-synaptic cross-talk. The LTP-triggered PAP withdrawal involves NKCC1 transporters and the actin-controlling protein cofilin but does not depend on major Ca2+-dependent cascades in astrocytes. We have therefore uncovered a mechanism by which a memory trace at one synapse could alter signal handling by multiple neighboring connections.},
  author       = {Henneberger, Christian and Bard, Lucie and Panatier, Aude and Reynolds, James P. and Kopach, Olga and Medvedev, Nikolay I. and Minge, Daniel and Herde, Michel K. and Anders, Stefanie and Kraev, Igor and Heller, Janosch P. and Rama, Sylvain and Zheng, Kaiyu and Jensen, Thomas P. and Sanchez-Romero, Inmaculada and Jackson, Colin J. and Janovjak, Harald L and Ottersen, Ole Petter and Nagelhus, Erlend Arnulf and Oliet, Stephane H.R. and Stewart, Michael G. and Nägerl, U. VAlentin and Rusakov, Dmitri A. },
  issn         = {10974199},
  journal      = {Neuron},
  number       = {5},
  pages        = {P919--936.E11},
  publisher    = {Elsevier},
  title        = {{LTP induction boosts glutamate spillover by driving withdrawal of perisynaptic astroglia}},
  doi          = {10.1016/j.neuron.2020.08.030},
  volume       = {108},
  year         = {2020},
}

@article{8679,
  abstract     = {A central goal of artificial intelligence in high-stakes decision-making applications is to design a single algorithm that simultaneously expresses generalizability by learning coherent representations of their world and interpretable explanations of its dynamics. Here, we combine brain-inspired neural computation principles and scalable deep learning architectures to design compact neural controllers for task-specific compartments of a full-stack autonomous vehicle control system. We discover that a single algorithm with 19 control neurons, connecting 32 encapsulated input features to outputs by 253 synapses, learns to map high-dimensional inputs into steering commands. This system shows superior generalizability, interpretability and robustness compared with orders-of-magnitude larger black-box learning systems. The obtained neural agents enable high-fidelity autonomy for task-specific parts of a complex autonomous system.},
  author       = {Lechner, Mathias and Hasani, Ramin and Amini, Alexander and Henzinger, Thomas A and Rus, Daniela and Grosu, Radu},
  issn         = {2522-5839},
  journal      = {Nature Machine Intelligence},
  pages        = {642--652},
  publisher    = {Springer Nature},
  title        = {{Neural circuit policies enabling auditable autonomy}},
  doi          = {10.1038/s42256-020-00237-3},
  volume       = {2},
  year         = {2020},
}

@article{8680,
  abstract     = {Animal development entails the organization of specific cell types in space and time, and spatial patterns must form in a robust manner. In the zebrafish spinal cord, neural progenitors form stereotypic patterns despite noisy morphogen signaling and large-scale cellular rearrangements during morphogenesis and growth. By directly measuring adhesion forces and preferences for three types of endogenous neural progenitors, we provide evidence for the differential adhesion model in which differences in intercellular adhesion mediate cell sorting. Cell type–specific combinatorial expression of different classes of cadherins (N-cadherin, cadherin 11, and protocadherin 19) results in homotypic preference ex vivo and patterning robustness in vivo. Furthermore, the differential adhesion code is regulated by the sonic hedgehog morphogen gradient. We propose that robust patterning during tissue morphogenesis results from interplay between adhesion-based self-organization and morphogen-directed patterning.},
  author       = {Tsai, Tony Y.-C. and Sikora, Mateusz K and Xia, Peng and Colak-Champollion, Tugba and Knaut, Holger and Heisenberg, Carl-Philipp J and Megason, Sean G.},
  issn         = {1095-9203},
  journal      = {Science},
  keywords     = {Multidisciplinary},
  number       = {6512},
  pages        = {113--116},
  publisher    = {American Association for the Advancement of Science},
  title        = {{An adhesion code ensures robust pattern formation during tissue morphogenesis}},
  doi          = {10.1126/science.aba6637},
  volume       = {370},
  year         = {2020},
}

@article{8691,
  abstract     = {Given l>2ν>2d≥4, we prove the persistence of a Cantor--family of KAM tori of measure O(ε1/2−ν/l) for any non--degenerate nearly integrable Hamiltonian system of class Cl(D×Td), where D⊂Rd is a bounded domain, provided that the size ε of the perturbation is sufficiently small. This extends a result by D. Salamon in \cite{salamon2004kolmogorov} according to which we do have the persistence of a single KAM torus in the same framework. Moreover, it is well--known that, for the persistence of a single torus, the regularity assumption can not be improved.},
  author       = {Koudjinan, Edmond},
  issn         = {0022-0396},
  journal      = {Journal of Differential Equations},
  keywords     = {Analysis},
  number       = {6},
  pages        = {4720--4750},
  publisher    = {Elsevier},
  title        = {{A KAM theorem for finitely differentiable Hamiltonian systems}},
  doi          = {10.1016/j.jde.2020.03.044},
  volume       = {269},
  year         = {2020},
}

@article{8694,
  abstract     = {We develop algorithms and techniques to compute rigorous bounds for finite pieces of orbits of the critical points, for intervals of parameter values, in the quadratic family of one-dimensional maps fa(x)=a−x2. We illustrate the effectiveness of our approach by constructing a dynamically defined partition 𝒫 of the parameter interval Ω=[1.4,2] into almost 4×106 subintervals, for each of which we compute to high precision the orbits of the critical points up to some time N and other dynamically relevant quantities, several of which can vary greatly, possibly spanning several orders of magnitude. We also subdivide 𝒫 into a family 𝒫+ of intervals, which we call stochastic intervals, and a family 𝒫− of intervals, which we call regular intervals. We numerically prove that each interval ω∈𝒫+ has an escape time, which roughly means that some iterate of the critical point taken over all the parameters in ω has considerable width in the phase space. This suggests, in turn, that most parameters belonging to the intervals in 𝒫+ are stochastic and most parameters belonging to the intervals in 𝒫− are regular, thus the names. We prove that the intervals in 𝒫+ occupy almost 90% of the total measure of Ω. The software and the data are freely available at http://www.pawelpilarczyk.com/quadr/, and a web page is provided for carrying out the calculations. The ideas and procedures can be easily generalized to apply to other parameterized families of dynamical systems.},
  author       = {Golmakani, Ali and Koudjinan, Edmond and Luzzatto, Stefano and Pilarczyk, Pawel},
  journal      = {Chaos},
  number       = {7},
  publisher    = {AIP},
  title        = {{Rigorous numerics for critical orbits in the quadratic family}},
  doi          = {10.1063/5.0012822},
  volume       = {30},
  year         = {2020},
}

@techreport{8695,
  abstract     = {A look at international activities on Open Science reveals a broad spectrum from individual institutional policies to national action plans. The present Recommendations for a National Open Science Strategy in Austria are based on these international initiatives and present practical considerations for their coordinated implementation with regard to strategic developments in research, technology and innovation (RTI) in Austria until 2030. They are addressed to all relevant actors in the RTI system, in particular to Research Performing Organisations, Research Funding Organisations, Research Policy, memory institutions such as Libraries and Researchers. The recommendation paper was developed from 2018 to 2020 by the OANA working group "Open Science Strategy" and published for the first time in spring 2020 for a public consultation. The now available final version of the recommendation document, which contains feedback and comments from the consultation, is intended to provide an impetus for further discussion and implementation of Open Science in Austria and serves as a contribution and basis for a potential national Open Science Strategy in Austria. The document builds on the diverse expertise of the authors (academia, administration, library and archive, information technology, science policy, funding system, etc.) and reflects their personal experiences and opinions.},
  author       = {Mayer, Katja and Rieck, Katharina and Reichmann, Stefan and Danowski, Patrick and Graschopf, Anton and König, Thomas and Kraker, Peter and Lehner, Patrick and Reckling, Falk and Ross-Hellauer, Tony and Spichtinger, Daniel and Tzatzanis, Michalis and Schürz, Stefanie},
  pages        = {36},
  publisher    = {OANA},
  title        = {{Empfehlungen für eine nationale Open Science Strategie in Österreich / Recommendations for a National Open Science Strategy in Austria}},
  doi          = {10.5281/ZENODO.4109242},
  year         = {2020},
}

@article{8697,
  abstract     = {In the computation of the material properties of random alloys, the method of 'special quasirandom structures' attempts to approximate the properties of the alloy on a finite volume with higher accuracy by replicating certain statistics of the random atomic lattice in the finite volume as accurately as possible. In the present work, we provide a rigorous justification for a variant of this method in the framework of the Thomas–Fermi–von Weizsäcker (TFW) model. Our approach is based on a recent analysis of a related variance reduction method in stochastic homogenization of linear elliptic PDEs and the locality properties of the TFW model. Concerning the latter, we extend an exponential locality result by Nazar and Ortner to include point charges, a result that may be of independent interest.},
  author       = {Fischer, Julian L and Kniely, Michael},
  issn         = {13616544},
  journal      = {Nonlinearity},
  number       = {11},
  pages        = {5733--5772},
  publisher    = {IOP Publishing},
  title        = {{Variance reduction for effective energies of random lattices in the Thomas-Fermi-von Weizsäcker model}},
  doi          = {10.1088/1361-6544/ab9728},
  volume       = {33},
  year         = {2020},
}

@article{8698,
  abstract     = {The brain represents and reasons probabilistically about complex stimuli and motor actions using a noisy, spike-based neural code. A key building block for such neural computations, as well as the basis for supervised and unsupervised learning, is the ability to estimate the surprise or likelihood of incoming high-dimensional neural activity patterns. Despite progress in statistical modeling of neural responses and deep learning, current approaches either do not scale to large neural populations or cannot be implemented using biologically realistic mechanisms. Inspired by the sparse and random connectivity of real neuronal circuits, we present a model for neural codes that accurately estimates the likelihood of individual spiking patterns and has a straightforward, scalable, efficient, learnable, and realistic neural implementation. This model’s performance on simultaneously recorded spiking activity of >100 neurons in the monkey visual and prefrontal cortices is comparable with or better than that of state-of-the-art models. Importantly, the model can be learned using a small number of samples and using a local learning rule that utilizes noise intrinsic to neural circuits. Slower, structural changes in random connectivity, consistent with rewiring and pruning processes, further improve the efficiency and sparseness of the resulting neural representations. Our results merge insights from neuroanatomy, machine learning, and theoretical neuroscience to suggest random sparse connectivity as a key design principle for neuronal computation.},
  author       = {Maoz, Ori and Tkačik, Gašper and Esteki, Mohamad Saleh and Kiani, Roozbeh and Schneidman, Elad},
  issn         = {10916490},
  journal      = {Proceedings of the National Academy of Sciences of the United States of America},
  number       = {40},
  pages        = {25066--25073},
  publisher    = {National Academy of Sciences},
  title        = {{Learning probabilistic neural representations with randomly connected circuits}},
  doi          = {10.1073/pnas.1912804117},
  volume       = {117},
  year         = {2020},
}

@article{8699,
  abstract     = {In the high spin–orbit-coupled Sr2IrO4, the high sensitivity of the ground state to the details of the local lattice structure shows a large potential for the manipulation of the functional properties by inducing local lattice distortions. We use epitaxial strain to modify the Ir–O bond geometry in Sr2IrO4 and perform momentum-dependent resonant inelastic X-ray scattering (RIXS) at the metal and at the ligand sites to unveil the response of the low-energy elementary excitations. We observe that the pseudospin-wave dispersion for tensile-strained Sr2IrO4 films displays large softening along the [h,0] direction, while along the [h,h] direction it shows hardening. This evolution reveals a renormalization of the magnetic interactions caused by a strain-driven cross-over from anisotropic to isotropic interactions between the magnetic moments. Moreover, we detect dispersive electron–hole pair excitations which shift to lower (higher) energies upon compressive (tensile) strain, manifesting a reduction (increase) in the size of the charge gap. This behavior shows an intimate coupling between charge excitations and lattice distortions in Sr2IrO4, originating from the modified hopping elements between the t2g orbitals. Our work highlights the central role played by the lattice degrees of freedom in determining both the pseudospin and charge excitations of Sr2IrO4 and provides valuable information toward the control of the ground state of complex oxides in the presence of high spin–orbit coupling.},
  author       = {Paris, Eugenio and Tseng, Yi and Paerschke, Ekaterina and Zhang, Wenliang and Upton, Mary H and Efimenko, Anna and Rolfs, Katharina and McNally, Daniel E and Maurel, Laura and Naamneh, Muntaser and Caputo, Marco and Strocov, Vladimir N and Wang, Zhiming and Casa, Diego and Schneider, Christof W and Pomjakushina, Ekaterina and Wohlfeld, Krzysztof and Radovic, Milan and Schmitt, Thorsten},
  issn         = {10916490},
  journal      = {Proceedings of the National Academy of Sciences of the United States of America},
  number       = {40},
  pages        = {24764--24770},
  publisher    = {National Academy of Sciences},
  title        = {{Strain engineering of the charge and spin-orbital interactions in Sr2IrO4}},
  doi          = {10.1073/pnas.2012043117},
  volume       = {117},
  year         = {2020},
}

@article{8700,
  abstract     = {Translation termination is a finishing step of protein biosynthesis. The significant role in this process belongs not only to protein factors of translation termination but also to the nearest nucleotide environment of stop codons. There are numerous descriptions of stop codons readthrough, which is due to specific nucleotide sequences behind them. However, represented data are segmental and don’t explain the mechanism of the nucleotide context influence on translation termination. It is well known that stop codon UAA usage is preferential for A/T-rich genes, and UAG, UGA—for G/C-rich genes, which is related to an expression level of these genes. We investigated the connection between a frequency of nucleotides occurrence in 3' area of stop codons in the human genome and their influence on translation termination efficiency. We found that 3' context motif, which is cognate to the sequence of a stop codon, stimulates translation termination. At the same time, the nucleotide composition of 3' sequence that differs from stop codon, decreases translation termination efficiency.},
  author       = {Sokolova, E. E. and Vlasov, Petr and Egorova, T. V. and Shuvalov, A. V. and Alkalaeva, E. Z.},
  issn         = {16083245},
  journal      = {Molecular Biology},
  number       = {5},
  pages        = {739--748},
  publisher    = {Springer Nature},
  title        = {{The influence of A/G composition of 3' stop codon contexts on translation termination efficiency in eukaryotes}},
  doi          = {10.1134/S0026893320050088},
  volume       = {54},
  year         = {2020},
}

@article{8701,
  abstract     = {Translation termination is a finishing step of protein biosynthesis. The significant role in this process belongs not only to protein factors of translation termination but also to the nearest nucleotide environment of stop codons. There are numerous descriptions of stop codons readthrough, which is due to specific nucleotide sequences behind them. However, represented data are segmental and don’t explain the mechanism of the nucleotide context influence on translation termination. It is well known that stop codon UAA usage is preferential for A/T-rich genes, and UAG, UGA—for G/C-rich genes, which is related to an expression level of these genes. We investigated the connection between a frequency of nucleotides occurrence in 3' area of stop codons in the human genome and their influence on translation termination efficiency. We found that 3' context motif, which is cognate to the sequence of a stop codon, stimulates translation termination. At the same time, the nucleotide composition of 3' sequence that differs from stop codon, decreases translation termination efficiency.},
  author       = {Sokolova, E. E. and Vlasov, Petr and Egorova, T. V. and Shuvalov, A. V. and Alkalaeva, E. Z.},
  issn         = {00268984},
  journal      = {Molekuliarnaia biologiia},
  number       = {5},
  pages        = {837--848},
  publisher    = {Russian Academy of Sciences},
  title        = {{The influence of A/G composition of 3' stop codon contexts on translation termination efficiency in eukaryotes}},
  doi          = {10.31857/S0026898420050080},
  volume       = {54},
  year         = {2020},
}

