@article{8634, abstract = {In laboratory studies and numerical simulations, we observe clear signatures of unstable time-periodic solutions in a moderately turbulent quasi-two-dimensional flow. We validate the dynamical relevance of such solutions by demonstrating that turbulent flows in both experiment and numerics transiently display time-periodic dynamics when they shadow unstable periodic orbits (UPOs). We show that UPOs we computed are also statistically significant, with turbulent flows spending a sizable fraction of the total time near these solutions. As a result, the average rates of energy input and dissipation for the turbulent flow and frequently visited UPOs differ only by a few percent.}, author = {Suri, Balachandra and Kageorge, Logan and Grigoriev, Roman O. and Schatz, Michael F.}, issn = {1079-7114}, journal = {Physical Review Letters}, keywords = {General Physics and Astronomy}, number = {6}, publisher = {American Physical Society}, title = {{Capturing turbulent dynamics and statistics in experiments with unstable periodic orbits}}, doi = {10.1103/physrevlett.125.064501}, volume = {125}, 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 University Press}, 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}, } @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 = {0022-2488}, 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 = {1878-1551}, 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{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{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 = {1091-6490}, 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 = {1091-6490}, 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 = {1608-3245}, 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 = {0026-8984}, 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}, } @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 = {1050-4729}, 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{8721, abstract = {Spontaneously arising channels that transport the phytohormone auxin provide positional cues for self-organizing aspects of plant development such as flexible vasculature regeneration or its patterning during leaf venation. The auxin canalization hypothesis proposes a feedback between auxin signaling and transport as the underlying mechanism, but molecular players await discovery. We identified part of the machinery that routes auxin transport. The auxin-regulated receptor CAMEL (Canalization-related Auxin-regulated Malectin-type RLK) together with CANAR (Canalization-related Receptor-like kinase) interact with and phosphorylate PIN auxin transporters. camel and canar mutants are impaired in PIN1 subcellular trafficking and auxin-mediated PIN polarization, which macroscopically manifests as defects in leaf venation and vasculature regeneration after wounding. The CAMEL-CANAR receptor complex is part of the auxin feedback that coordinates polarization of individual cells during auxin canalization.}, author = {Hajny, Jakub and Prat, Tomas and Rydza, N and Rodriguez Solovey, Lesia and Tan, Shutang and Verstraeten, Inge and Domjan, David and Mazur, E and Smakowska-Luzan, E and Smet, W and Mor, E and Nolf, J and Yang, B and Grunewald, W and Molnar, Gergely and Belkhadir, Y and De Rybel, B and Friml, Jiří}, issn = {1095-9203}, journal = {Science}, number = {6516}, pages = {550--557}, publisher = {American Association for the Advancement of Science}, title = {{Receptor kinase module targets PIN-dependent auxin transport during canalization}}, doi = {10.1126/science.aba3178}, 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}, } @inproceedings{8725, abstract = {The design and implementation of efficient concurrent data structures have seen significant attention. However, most of this work has focused on concurrent data structures providing good \emph{worst-case} guarantees. In real workloads, objects are often accessed at different rates, since access distributions may be non-uniform. Efficient distribution-adaptive data structures are known in the sequential case, e.g. the splay-trees; however, they often are hard to translate efficiently in the concurrent case. In this paper, we investigate distribution-adaptive concurrent data structures and propose a new design called the splay-list. At a high level, the splay-list is similar to a standard skip-list, with the key distinction that the height of each element adapts dynamically to its access rate: popular elements ``move up,'' whereas rarely-accessed elements decrease in height. We show that the splay-list provides order-optimal amortized complexity bounds for a subset of operations while being amenable to efficient concurrent implementation. Experimental results show that the splay-list can leverage distribution-adaptivity to improve on the performance of classic concurrent designs, and can outperform the only previously-known distribution-adaptive design in certain settings.}, author = {Aksenov, Vitaly and Alistarh, Dan-Adrian and Drozdova, Alexandra and Mohtashami, Amirkeivan}, booktitle = {34th International Symposium on Distributed Computing}, isbn = {9783959771689}, issn = {1868-8969}, location = {Freiburg, Germany}, pages = {3:1--3:18}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik}, title = {{The splay-list: A distribution-adaptive concurrent skip-list}}, doi = {10.4230/LIPIcs.DISC.2020.3}, volume = {179}, year = {2020}, } @article{8726, abstract = {Several realistic spin-orbital models for transition metal oxides go beyond the classical expectations and could be understood only by employing the quantum entanglement. Experiments on these materials confirm that spin-orbital entanglement has measurable consequences. Here, we capture the essential features of spin-orbital entanglement in complex quantum matter utilizing 1D spin-orbital model which accommodates SU(2)⊗SU(2) symmetric Kugel-Khomskii superexchange as well as the Ising on-site spin-orbit coupling. Building on the results obtained for full and effective models in the regime of strong spin-orbit coupling, we address the question whether the entanglement found on superexchange bonds always increases when the Ising spin-orbit coupling is added. We show that (i) quantum entanglement is amplified by strong spin-orbit coupling and, surprisingly, (ii) almost classical disentangled states are possible. We complete the latter case by analyzing how the entanglement existing for intermediate values of spin-orbit coupling can disappear for higher values of this coupling.}, author = {Gotfryd, Dorota and Paerschke, Ekaterina and Wohlfeld, Krzysztof and Oleś, Andrzej M.}, issn = {2410-3896}, journal = {Condensed Matter}, number = {3}, publisher = {MDPI}, title = {{Evolution of spin-orbital entanglement with increasing ising spin-orbit coupling}}, doi = {10.3390/condmat5030053}, volume = {5}, year = {2020}, } @article{8746, abstract = {Research in the field of colloidal semiconductor nanocrystals (NCs) has progressed tremendously, mostly because of their exceptional optoelectronic properties. Core@shell NCs, in which one or more inorganic layers overcoat individual NCs, recently received significant attention due to their remarkable optical characteristics. Reduced Auger recombination, suppressed blinking, and enhanced carrier multiplication are among the merits of core@shell NCs. Despite their importance in device development, the influence of the shell and the surface modification of the core@shell NC assemblies on the charge carrier transport remains a pertinent research objective. Type-II PbTe@PbS core@shell NCs, in which exclusive electron transport was demonstrated, still exhibit instability of their electron ransport. Here, we demonstrate the enhancement of electron transport and stability in PbTe@PbS core@shell NC assemblies using iodide as a surface passivating ligand. The combination of the PbS shelling and the use of the iodide ligand contributes to the addition of one mobile electron for each core@shell NC. Furthermore, both electron mobility and on/off current modulation ratio values of the core@shell NC field-effect transistor are steady with the usage of iodide. Excellent stability in these exclusively electron-transporting core@shell NCs paves the way for their utilization in electronic devices. }, author = {Miranti, Retno and Septianto, Ricky Dwi and Ibáñez, Maria and Kovalenko, Maksym V. and Matsushita, Nobuhiro and Iwasa, Yoshihiro and Bisri, Satria Zulkarnaen}, issn = {1077-3118}, journal = {Applied Physics Letters}, number = {17}, publisher = {AIP Publishing}, title = {{Electron transport in iodide-capped core@shell PbTe@PbS colloidal nanocrystal solids}}, doi = {10.1063/5.0025965}, volume = {117}, year = {2020}, } @article{8747, abstract = {Appropriately designed nanocomposites allow improving the thermoelectric performance by several mechanisms, including phonon scattering, modulation doping and energy filtering, while additionally promoting better mechanical properties than those of crystalline materials. Here, a strategy for producing Bi2Te3–Cu2xTe nanocomposites based on the consolidation of heterostructured nanoparticles is described and the thermoelectric properties of the obtained materials are investigated. We first detail a two-step solution-based process to produce Bi2Te3–Cu2xTe heteronanostructures, based on the growth of Cu2xTe nanocrystals on the surface of Bi2Te3 nanowires. We characterize the structural and chemical properties of the synthesized nanostructures and of the nanocomposites produced by hot-pressing the particles at moderate temperatures. Besides, the transport properties of the nanocomposites are investigated as a function of the amount of Cu introduced. Overall, the presence of Cu decreases the material thermal conductivity through promotion of phonon scattering, modulates the charge carrier concentration through electron spillover, and increases the Seebeck coefficient through filtering of charge carriers at energy barriers. These effects result in an improvement of over 50% of the thermoelectric figure of merit of Bi2Te3.}, author = {Zhang, Yu and Liu, Yu and Calcabrini, Mariano and Xing, Congcong and Han, Xu and Arbiol, Jordi and Cadavid, Doris and Ibáñez, Maria and Cabot, Andreu}, journal = {Journal of Materials Chemistry C}, number = {40}, pages = {14092--14099}, publisher = {Royal Society of Chemistry}, title = {{Bismuth telluride-copper telluride nanocomposites from heterostructured building blocks}}, doi = {10.1039/D0TC02182B}, volume = {8}, year = {2020}, } @inproceedings{8750, abstract = {Efficiently handling time-triggered and possibly nondeterministic switches for hybrid systems reachability is a challenging task. In this paper we present an approach based on conservative set-based enclosure of the dynamics that can handle systems with uncertain parameters and inputs, where the uncertainties are bound to given intervals. The method is evaluated on the plant model of an experimental electro-mechanical braking system with periodic controller. In this model, the fast-switching controller dynamics requires simulation time scales of the order of nanoseconds. Accurate set-based computations for relatively large time horizons are known to be expensive. However, by appropriately decoupling the time variable with respect to the spatial variables, and enclosing the uncertain parameters using interval matrix maps acting on zonotopes, we show that the computation time can be lowered to 5000 times faster with respect to previous works. This is a step forward in formal verification of hybrid systems because reduced run-times allow engineers to introduce more expressiveness in their models with a relatively inexpensive computational cost.}, author = {Forets, Marcelo and Freire, Daniel and Schilling, Christian}, booktitle = {18th ACM-IEEE International Conference on Formal Methods and Models for System Design}, isbn = {9781728191485}, location = {Virtual Conference}, publisher = {IEEE}, title = {{Efficient reachability analysis of parametric linear hybrid systems with time-triggered transitions}}, doi = {10.1109/MEMOCODE51338.2020.9314994}, year = {2020}, }