@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{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}, } @inproceedings{8704, abstract = {Traditional robotic control suits require profound task-specific knowledge for designing, building and testing control software. The rise of Deep Learning has enabled end-to-end solutions to be learned entirely from data, requiring minimal knowledge about the application area. We design a learning scheme to train end-to-end linear dynamical systems (LDS)s by gradient descent in imitation learning robotic domains. We introduce a new regularization loss component together with a learning algorithm that improves the stability of the learned autonomous system, by forcing the eigenvalues of the internal state updates of an LDS to be negative reals. We evaluate our approach on a series of real-life and simulated robotic experiments, in comparison to linear and nonlinear Recurrent Neural Network (RNN) architectures. Our results show that our stabilizing method significantly improves test performance of LDS, enabling such linear models to match the performance of contemporary nonlinear RNN architectures. A video of the obstacle avoidance performance of our method on a mobile robot, in unseen environments, compared to other methods can be viewed at https://youtu.be/mhEsCoNao5E.}, author = {Lechner, Mathias and Hasani, Ramin and Rus, Daniela and Grosu, Radu}, booktitle = {Proceedings - IEEE International Conference on Robotics and Automation}, isbn = {9781728173955}, issn = {10504729}, location = {Paris, France}, pages = {5446--5452}, publisher = {IEEE}, title = {{Gershgorin loss stabilizes the recurrent neural network compartment of an end-to-end robot learning scheme}}, doi = {10.1109/ICRA40945.2020.9196608}, 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}, } @unpublished{14096, abstract = {A binary neutron star merger has been observed in a multi-messenger detection of gravitational wave (GW) and electromagnetic (EM) radiation. Binary neutron stars that merge within a Hubble time, as well as many other compact binaries, are expected to form via common envelope evolution. Yet five decades of research on common envelope evolution have not yet resulted in a satisfactory understanding of the multi-spatial multi-timescale evolution for the systems that lead to compact binaries. In this paper, we report on the first successful simulations of common envelope ejection leading to binary neutron star formation in 3D hydrodynamics. We simulate the dynamical inspiral phase of the interaction between a 12M⊙ red supergiant and a 1.4M⊙ neutron star for different initial separations and initial conditions. For all of our simulations, we find complete envelope ejection and final orbital separations of af≈1.3-5.1R⊙ depending on the simulation and criterion, leading to binary neutron stars that can merge within a Hubble time. We find αCE-equivalent efficiencies of ≈0.1-2.7 depending on the simulation and criterion, but this may be specific for these extended progenitors. We fully resolve the core of the star to ≲0.005R⊙ and our 3D hydrodynamics simulations are informed by an adjusted 1D analytic energy formalism and a 2D kinematics study in order to overcome the prohibitive computational cost of simulating these systems. The framework we develop in this paper can be used to simulate a wide variety of interactions between stars, from stellar mergers to common envelope episodes leading to GW sources.}, author = {Jamie A. P. Law-Smith, Jamie A. P. Law-Smith and Everson, Rosa Wallace and Enrico Ramirez-Ruiz, Enrico Ramirez-Ruiz and Mink, Selma E. de and Son, Lieke A. C. van and Götberg, Ylva Louise Linsdotter and Zellmann, Stefan and Alejandro Vigna-Gómez, Alejandro Vigna-Gómez and Renzo, Mathieu and Wu, Samantha and Schrøder, Sophie L. and Foley, Ryan J. and Tenley Hutchinson-Smith, Tenley Hutchinson-Smith}, booktitle = {arXiv}, title = {{Successful common envelope ejection and binary neutron star formation in 3D hydrodynamics}}, doi = {10.48550/arXiv.2011.06630}, 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{8737, abstract = {Mitochondrial complex I couples NADH:ubiquinone oxidoreduction to proton pumping by an unknown mechanism. Here, we present cryo-electron microscopy structures of ovine complex I in five different conditions, including turnover, at resolutions up to 2.3 to 2.5 angstroms. Resolved water molecules allowed us to experimentally define the proton translocation pathways. Quinone binds at three positions along the quinone cavity, as does the inhibitor rotenone that also binds within subunit ND4. Dramatic conformational changes around the quinone cavity couple the redox reaction to proton translocation during open-to-closed state transitions of the enzyme. In the induced deactive state, the open conformation is arrested by the ND6 subunit. We propose a detailed molecular coupling mechanism of complex I, which is an unexpected combination of conformational changes and electrostatic interactions.}, author = {Kampjut, Domen and Sazanov, Leonid A}, issn = {10959203}, journal = {Science}, number = {6516}, publisher = {American Association for the Advancement of Science}, title = {{The coupling mechanism of mammalian respiratory complex I}}, doi = {10.1126/science.abc4209}, volume = {370}, year = {2020}, } @inproceedings{8722, abstract = {Load imbalance pervasively exists in distributed deep learning training systems, either caused by the inherent imbalance in learned tasks or by the system itself. Traditional synchronous Stochastic Gradient Descent (SGD) achieves good accuracy for a wide variety of tasks, but relies on global synchronization to accumulate the gradients at every training step. In this paper, we propose eager-SGD, which relaxes the global synchronization for decentralized accumulation. To implement eager-SGD, we propose to use two partial collectives: solo and majority. With solo allreduce, the faster processes contribute their gradients eagerly without waiting for the slower processes, whereas with majority allreduce, at least half of the participants must contribute gradients before continuing, all without using a central parameter server. We theoretically prove the convergence of the algorithms and describe the partial collectives in detail. Experimental results on load-imbalanced environments (CIFAR-10, ImageNet, and UCF101 datasets) show that eager-SGD achieves 1.27x speedup over the state-of-the-art synchronous SGD, without losing accuracy.}, author = {Li, Shigang and Tal Ben-Nun, Tal Ben-Nun and Girolamo, Salvatore Di and Alistarh, Dan-Adrian and Hoefler, Torsten}, booktitle = {Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming}, location = {San Diego, CA, United States}, pages = {45--61}, publisher = {Association for Computing Machinery}, title = {{Taming unbalanced training workloads in deep learning with partial collective operations}}, doi = {10.1145/3332466.3374528}, year = {2020}, } @article{8744, abstract = {Understanding the conformational sampling of translation-arrested ribosome nascent chain complexes is key to understand co-translational folding. Up to now, coupling of cysteine oxidation, disulfide bond formation and structure formation in nascent chains has remained elusive. Here, we investigate the eye-lens protein γB-crystallin in the ribosomal exit tunnel. Using mass spectrometry, theoretical simulations, dynamic nuclear polarization-enhanced solid-state nuclear magnetic resonance and cryo-electron microscopy, we show that thiol groups of cysteine residues undergo S-glutathionylation and S-nitrosylation and form non-native disulfide bonds. Thus, covalent modification chemistry occurs already prior to nascent chain release as the ribosome exit tunnel provides sufficient space even for disulfide bond formation which can guide protein folding.}, author = {Schulte, Linda and Mao, Jiafei and Reitz, Julian and Sreeramulu, Sridhar and Kudlinzki, Denis and Hodirnau, Victor-Valentin and Meier-Credo, Jakob and Saxena, Krishna and Buhr, Florian and Langer, Julian D. and Blackledge, Martin and Frangakis, Achilleas S. and Glaubitz, Clemens and Schwalbe, Harald}, issn = {2041-1723}, journal = {Nature Communications}, keywords = {General Biochemistry, Genetics and Molecular Biology, General Physics and Astronomy, General Chemistry}, publisher = {Springer Nature}, title = {{Cysteine oxidation and disulfide formation in the ribosomal exit tunnel}}, doi = {10.1038/s41467-020-19372-x}, volume = {11}, year = {2020}, }