@inproceedings{140, abstract = {Reachability analysis is difficult for hybrid automata with affine differential equations, because the reach set needs to be approximated. Promising abstraction techniques usually employ interval methods or template polyhedra. Interval methods account for dense time and guarantee soundness, and there are interval-based tools that overapproximate affine flowpipes. But interval methods impose bounded and rigid shapes, which make refinement expensive and fixpoint detection difficult. Template polyhedra, on the other hand, can be adapted flexibly and can be unbounded, but sound template refinement for unbounded reachability analysis has been implemented only for systems with piecewise constant dynamics. We capitalize on the advantages of both techniques, combining interval arithmetic and template polyhedra, using the former to abstract time and the latter to abstract space. During a CEGAR loop, whenever a spurious error trajectory is found, we compute additional space constraints and split time intervals, and use these space-time interpolants to eliminate the counterexample. Space-time interpolation offers a lazy, flexible framework for increasing precision while guaranteeing soundness, both for error avoidance and fixpoint detection. To the best of out knowledge, this is the first abstraction refinement scheme for the reachability analysis over unbounded and dense time of affine hybrid systems, which is both sound and automatic. We demonstrate the effectiveness of our algorithm with several benchmark examples, which cannot be handled by other tools.}, author = {Frehse, Goran and Giacobbe, Mirco and Henzinger, Thomas A}, issn = {03029743}, location = {Oxford, United Kingdom}, pages = {468 -- 486}, publisher = {Springer}, title = {{Space-time interpolants}}, doi = {10.1007/978-3-319-96145-3_25}, volume = {10981}, year = {2018}, } @article{14003, abstract = {Molecular chirality plays an essential role in most biochemical processes. The observation and quantification of chirality-sensitive signals, however, remains extremely challenging, especially on ultrafast timescales and in dilute media. Here, we describe the experimental realization of an all-optical and ultrafast scheme for detecting chiral dynamics in molecules. This technique is based on high-harmonic generation by a combination of two-color counterrotating femtosecond laser pulses with polarization states tunable from linear to circular. We demonstrate two different implementations of chiral-sensitive high-harmonic spectroscopy on an ensemble of randomly oriented methyloxirane molecules in the gas phase. Using two elliptically polarized fields, we observe that the ellipticities maximizing the harmonic signal reach up to 4.4 ± 0.2 % (at 17.6 eV). Using two circularly polarized fields, we observe circular dichroisms ranging up to 13 ± 6 % (28.3–33.1 eV). Our theoretical analysis confirms that the observed chiral response originates from subfemtosecond electron dynamics driven by the magnetic component of the driving laser field. This assignment is supported by the experimental observation of a strong intensity dependence of the chiral effects and its agreement with theory. We moreover report and explain a pronounced variation of the signal strength and dichroism with the driving-field ellipticities and harmonic orders. Finally, we demonstrate the sensitivity of the experimental observables to the shape of the electron hole. This technique for chiral discrimination will yield femtosecond temporal resolution when integrated in a pump-probe scheme and subfemtosecond resolution on chiral charge migration in a self-probing scheme.}, author = {Baykusheva, Denitsa Rangelova and Wörner, Hans Jakob}, issn = {2160-3308}, journal = {Physical Review X}, keywords = {General Physics and Astronomy}, number = {3}, publisher = {American Physical Society}, title = {{Chiral discrimination through bielliptical high-harmonic spectroscopy}}, doi = {10.1103/physrevx.8.031060}, volume = {8}, year = {2018}, } @inproceedings{141, abstract = {Given a model and a specification, the fundamental model-checking problem asks for algorithmic verification of whether the model satisfies the specification. We consider graphs and Markov decision processes (MDPs), which are fundamental models for reactive systems. One of the very basic specifications that arise in verification of reactive systems is the strong fairness (aka Streett) objective. Given different types of requests and corresponding grants, the objective requires that for each type, if the request event happens infinitely often, then the corresponding grant event must also happen infinitely often. All ω -regular objectives can be expressed as Streett objectives and hence they are canonical in verification. To handle the state-space explosion, symbolic algorithms are required that operate on a succinct implicit representation of the system rather than explicitly accessing the system. While explicit algorithms for graphs and MDPs with Streett objectives have been widely studied, there has been no improvement of the basic symbolic algorithms. The worst-case numbers of symbolic steps required for the basic symbolic algorithms are as follows: quadratic for graphs and cubic for MDPs. In this work we present the first sub-quadratic symbolic algorithm for graphs with Streett objectives, and our algorithm is sub-quadratic even for MDPs. Based on our algorithmic insights we present an implementation of the new symbolic approach and show that it improves the existing approach on several academic benchmark examples.}, author = {Chatterjee, Krishnendu and Henzinger, Monika H and Loitzenbauer, Veronika and Oraee, Simin and Toman, Viktor}, location = {Oxford, United Kingdom}, pages = {178--197}, publisher = {Springer}, title = {{Symbolic algorithms for graphs and Markov decision processes with fairness objectives}}, doi = {10.1007/978-3-319-96142-2_13}, volume = {10982}, year = {2018}, } @inproceedings{14198, abstract = {High-dimensional time series are common in many domains. Since human cognition is not optimized to work well in high-dimensional spaces, these areas could benefit from interpretable low-dimensional representations. However, most representation learning algorithms for time series data are difficult to interpret. This is due to non-intuitive mappings from data features to salient properties of the representation and non-smoothness over time. To address this problem, we propose a new representation learning framework building on ideas from interpretable discrete dimensionality reduction and deep generative modeling. This framework allows us to learn discrete representations of time series, which give rise to smooth and interpretable embeddings with superior clustering performance. We introduce a new way to overcome the non-differentiability in discrete representation learning and present a gradient-based version of the traditional self-organizing map algorithm that is more performant than the original. Furthermore, to allow for a probabilistic interpretation of our method, we integrate a Markov model in the representation space. This model uncovers the temporal transition structure, improves clustering performance even further and provides additional explanatory insights as well as a natural representation of uncertainty. We evaluate our model in terms of clustering performance and interpretability on static (Fashion-)MNIST data, a time series of linearly interpolated (Fashion-)MNIST images, a chaotic Lorenz attractor system with two macro states, as well as on a challenging real world medical time series application on the eICU data set. Our learned representations compare favorably with competitor methods and facilitate downstream tasks on the real world data.}, author = {Fortuin, Vincent and Hüser, Matthias and Locatello, Francesco and Strathmann, Heiko and Rätsch, Gunnar}, booktitle = {International Conference on Learning Representations}, location = {New Orleans, LA, United States}, title = {{SOM-VAE: Interpretable discrete representation learning on time series}}, year = {2018}, } @inproceedings{142, abstract = {We address the problem of analyzing the reachable set of a polynomial nonlinear continuous system by over-approximating the flowpipe of its dynamics. The common approach to tackle this problem is to perform a numerical integration over a given time horizon based on Taylor expansion and interval arithmetic. However, this method results to be very conservative when there is a large difference in speed between trajectories as time progresses. In this paper, we propose to use combinations of barrier functions, which we call piecewise barrier tube (PBT), to over-approximate flowpipe. The basic idea of PBT is that for each segment of a flowpipe, a coarse box which is big enough to contain the segment is constructed using sampled simulation and then in the box we compute by linear programming a set of barrier functions (called barrier tube or BT for short) which work together to form a tube surrounding the flowpipe. The benefit of using PBT is that (1) BT is independent of time and hence can avoid being stretched and deformed by time; and (2) a small number of BTs can form a tight over-approximation for the flowpipe, which means that the computation required to decide whether the BTs intersect the unsafe set can be reduced significantly. We implemented a prototype called PBTS in C++. Experiments on some benchmark systems show that our approach is effective.}, author = {Kong, Hui and Bartocci, Ezio and Henzinger, Thomas A}, location = {Oxford, United Kingdom}, pages = {449 -- 467}, publisher = {Springer}, title = {{Reachable set over-approximation for nonlinear systems using piecewise barrier tubes}}, doi = {10.1007/978-3-319-96145-3_24}, volume = {10981}, year = {2018}, } @inproceedings{14201, abstract = {Variational inference is a popular technique to approximate a possibly intractable Bayesian posterior with a more tractable one. Recently, boosting variational inference has been proposed as a new paradigm to approximate the posterior by a mixture of densities by greedily adding components to the mixture. However, as is the case with many other variational inference algorithms, its theoretical properties have not been studied. In the present work, we study the convergence properties of this approach from a modern optimization viewpoint by establishing connections to the classic Frank-Wolfe algorithm. Our analyses yields novel theoretical insights regarding the sufficient conditions for convergence, explicit rates, and algorithmic simplifications. Since a lot of focus in previous works for variational inference has been on tractability, our work is especially important as a much needed attempt to bridge the gap between probabilistic models and their corresponding theoretical properties.}, author = {Locatello, Francesco and Khanna, Rajiv and Ghosh, Joydeep and Rätsch, Gunnar}, booktitle = {Proceedings of the 21st International Conference on Artificial Intelligence and Statistics}, location = {Playa Blanca, Lanzarote}, pages = {464--472}, publisher = {ML Research Press}, title = {{Boosting variational inference: An optimization perspective}}, volume = {84}, year = {2018}, } @inproceedings{14202, abstract = {Approximating a probability density in a tractable manner is a central task in Bayesian statistics. Variational Inference (VI) is a popular technique that achieves tractability by choosing a relatively simple variational family. Borrowing ideas from the classic boosting framework, recent approaches attempt to \emph{boost} VI by replacing the selection of a single density with a greedily constructed mixture of densities. In order to guarantee convergence, previous works impose stringent assumptions that require significant effort for practitioners. Specifically, they require a custom implementation of the greedy step (called the LMO) for every probabilistic model with respect to an unnatural variational family of truncated distributions. Our work fixes these issues with novel theoretical and algorithmic insights. On the theoretical side, we show that boosting VI satisfies a relaxed smoothness assumption which is sufficient for the convergence of the functional Frank-Wolfe (FW) algorithm. Furthermore, we rephrase the LMO problem and propose to maximize the Residual ELBO (RELBO) which replaces the standard ELBO optimization in VI. These theoretical enhancements allow for black box implementation of the boosting subroutine. Finally, we present a stopping criterion drawn from the duality gap in the classic FW analyses and exhaustive experiments to illustrate the usefulness of our theoretical and algorithmic contributions.}, author = {Locatello, Francesco and Dresdner, Gideon and Khanna, Rajiv and Valera, Isabel and Rätsch, Gunnar}, booktitle = {Advances in Neural Information Processing Systems}, isbn = {9781510884472}, issn = {1049-5258}, location = {Montreal, Canada}, publisher = {Neural Information Processing Systems Foundation}, title = {{Boosting black box variational inference}}, volume = {31}, year = {2018}, } @inproceedings{14203, abstract = {We propose a conditional gradient framework for a composite convex minimization template with broad applications. Our approach combines smoothing and homotopy techniques under the CGM framework, and provably achieves the optimal O(1/k−−√) convergence rate. We demonstrate that the same rate holds if the linear subproblems are solved approximately with additive or multiplicative error. In contrast with the relevant work, we are able to characterize the convergence when the non-smooth term is an indicator function. Specific applications of our framework include the non-smooth minimization, semidefinite programming, and minimization with linear inclusion constraints over a compact domain. Numerical evidence demonstrates the benefits of our framework.}, author = {Yurtsever, Alp and Fercoq, Olivier and Locatello, Francesco and Cevher, Volkan}, booktitle = {Proceedings of the 35th International Conference on Machine Learning}, location = {Stockholm, Sweden}, pages = {5727--5736}, publisher = {ML Research Press}, title = {{A conditional gradient framework for composite convex minimization with applications to semidefinite programming}}, volume = {80}, year = {2018}, } @inproceedings{14204, abstract = {Two popular examples of first-order optimization methods over linear spaces are coordinate descent and matching pursuit algorithms, with their randomized variants. While the former targets the optimization by moving along coordinates, the latter considers a generalized notion of directions. Exploiting the connection between the two algorithms, we present a unified analysis of both, providing affine invariant sublinear O(1/t) rates on smooth objectives and linear convergence on strongly convex objectives. As a byproduct of our affine invariant analysis of matching pursuit, our rates for steepest coordinate descent are the tightest known. Furthermore, we show the first accelerated convergence rate O(1/t2) for matching pursuit and steepest coordinate descent on convex objectives.}, author = {Locatello, Francesco and Raj, Anant and Karimireddy, Sai Praneeth and Rätsch, Gunnar and Schölkopf, Bernhard and Stich, Sebastian U. and Jaggi, Martin}, booktitle = {Proceedings of the 35th International Conference on Machine Learning}, pages = {3198--3207}, publisher = {ML Research Press}, title = {{On matching pursuit and coordinate descent}}, volume = {80}, year = {2018}, } @inproceedings{14224, abstract = {Clustering is a cornerstone of unsupervised learning which can be thought as disentangling multiple generative mechanisms underlying the data. In this paper we introduce an algorithmic framework to train mixtures of implicit generative models which we particularize for variational autoencoders. Relying on an additional set of discriminators, we propose a competitive procedure in which the models only need to approximate the portion of the data distribution from which they can produce realistic samples. As a byproduct, each model is simpler to train, and a clustering interpretation arises naturally from the partitioning of the training points among the models. We empirically show that our approach splits the training distribution in a reasonable way and increases the quality of the generated samples.}, author = {Locatello, Francesco and Vincent, Damien and Tolstikhin, Ilya and Ratsch, Gunnar and Gelly, Sylvain and Scholkopf, Bernhard}, booktitle = {6th International Conference on Learning Representations}, location = {Vancouver, Canada}, title = {{Clustering meets implicit generative models}}, year = {2018}, } @article{14284, abstract = {Pore-forming toxins (PFT) are virulence factors that transform from soluble to membrane-bound states. The Yersinia YaxAB system represents a family of binary α-PFTs with orthologues in human, insect, and plant pathogens, with unknown structures. YaxAB was shown to be cytotoxic and likely involved in pathogenesis, though the molecular basis for its two-component lytic mechanism remains elusive. Here, we present crystal structures of YaxA and YaxB, together with a cryo-electron microscopy map of the YaxAB complex. Our structures reveal a pore predominantly composed of decamers of YaxA–YaxB heterodimers. Both subunits bear membrane-active moieties, but only YaxA is capable of binding to membranes by itself. YaxB can subsequently be recruited to membrane-associated YaxA and induced to present its lytic transmembrane helices. Pore formation can progress by further oligomerization of YaxA–YaxB dimers. Our results allow for a comparison between pore assemblies belonging to the wider ClyA-like family of α-PFTs, highlighting diverse pore architectures.}, author = {Bräuning, Bastian and Bertosin, Eva and Praetorius, Florian M and Ihling, Christian and Schatt, Alexandra and Adler, Agnes and Richter, Klaus and Sinz, Andrea and Dietz, Hendrik and Groll, Michael}, issn = {2041-1723}, journal = {Nature Communications}, keywords = {General Physics and Astronomy, General Biochemistry, Genetics and Molecular Biology, General Chemistry, Multidisciplinary}, publisher = {Springer Nature}, title = {{Structure and mechanism of the two-component α-helical pore-forming toxin YaxAB}}, doi = {10.1038/s41467-018-04139-2}, volume = {9}, year = {2018}, } @inproceedings{143, abstract = {Vector Addition Systems with States (VASS) provide a well-known and fundamental model for the analysis of concurrent processes, parameterized systems, and are also used as abstract models of programs in resource bound analysis. In this paper we study the problem of obtaining asymptotic bounds on the termination time of a given VASS. In particular, we focus on the practically important case of obtaining polynomial bounds on termination time. Our main contributions are as follows: First, we present a polynomial-time algorithm for deciding whether a given VASS has a linear asymptotic complexity. We also show that if the complexity of a VASS is not linear, it is at least quadratic. Second, we classify VASS according to quantitative properties of their cycles. We show that certain singularities in these properties are the key reason for non-polynomial asymptotic complexity of VASS. In absence of singularities, we show that the asymptotic complexity is always polynomial and of the form Θ(nk), for some integer k d, where d is the dimension of the VASS. We present a polynomial-time algorithm computing the optimal k. For general VASS, the same algorithm, which is based on a complete technique for the construction of ranking functions in VASS, produces a valid lower bound, i.e., a k such that the termination complexity is (nk). Our results are based on new insights into the geometry of VASS dynamics, which hold the potential for further applicability to VASS analysis.}, author = {Brázdil, Tomáš and Chatterjee, Krishnendu and Kučera, Antonín and Novotny, Petr and Velan, Dominik and Zuleger, Florian}, isbn = {978-1-4503-5583-4}, location = {Oxford, United Kingdom}, pages = {185 -- 194}, publisher = {IEEE}, title = {{Efficient algorithms for asymptotic bounds on termination time in VASS}}, doi = {10.1145/3209108.3209191}, volume = {F138033}, year = {2018}, } @phdthesis{14306, abstract = {Function and activity of biomolecules often depend on their spatial arrangement. The method introduced here allows genetically encoding the spatial arrangement of proteins and DNA. The approach relies on staple proteins that fold double-stranded DNA into user-defined shapes. This thesis describes the development of staple proteins based on the DNA recognition of TAL effectors and presents experimentally derived rules for designing a variety of self-assembling nanoscale shapes featuring structural motifs such as curvature, vertices, corners, and multilayer helix packing. }, author = {Praetorius, Florian M}, publisher = {Technische Universität München}, title = {{Genetically encoding the spatial arrangement of DNA and proteins in self-assembling nanostructures}}, year = {2018}, } @article{9053, abstract = {The development of strategies to assemble microscopic machines from dissipative building blocks are essential on the route to novel active materials. We recently demonstrated the hierarchical self-assembly of phoretic microswimmers into self-spinning microgears and their synchronization by diffusiophoretic interactions [Aubret et al., Nat. Phys., 2018]. In this paper, we adopt a pedagogical approach and expose our strategy to control self-assembly and build machines using phoretic phenomena. We notably introduce Highly Inclined Laminated Optical sheets microscopy (HILO) to image and characterize anisotropic and dynamic diffusiophoretic interactions, which cannot be performed by conventional fluorescence microscopy. The dynamics of a (haematite) photocatalytic material immersed in (hydrogen peroxide) fuel under various illumination patterns is first described and quantitatively rationalized by a model of diffusiophoresis, the migration of a colloidal particle in a concentration gradient. It is further exploited to design phototactic microswimmers that direct towards the high intensity of light, as a result of the reorientation of the haematite in a light gradient. We finally show the assembly of self-spinning microgears from colloidal microswimmers and carefully characterize the interactions using HILO techniques. The results are compared with analytical and numerical predictions and agree quantitatively, stressing the important role played by concentration gradients induced by chemical activity to control and design interactions. Because the approach described hereby is generic, this works paves the way for the rational design of machines by controlling phoretic phenomena.}, author = {Aubret, Antoine and Palacci, Jérémie A}, issn = {1744-6848}, journal = {Soft Matter}, keywords = {General Chemistry, Condensed Matter Physics}, number = {47}, pages = {9577--9588}, publisher = {Royal Society of Chemistry }, title = {{Diffusiophoretic design of self-spinning microgears from colloidal microswimmers}}, doi = {10.1039/c8sm01760c}, volume = {14}, year = {2018}, } @article{9062, abstract = {Self-assembly is the autonomous organization of components into patterns or structures: an essential ingredient of biology and a desired route to complex organization1. At equilibrium, the structure is encoded through specific interactions2,3,4,5,6,7,8, at an unfavourable entropic cost for the system. An alternative approach, widely used by nature, uses energy input to bypass the entropy bottleneck and develop features otherwise impossible at equilibrium9. Dissipative building blocks that inject energy locally were made available by recent advances in colloidal science10,11 but have not been used to control self-assembly. Here we show the targeted formation of self-powered microgears from active particles and their autonomous synchronization into dynamical superstructures. We use a photoactive component that consumes fuel, haematite, to devise phototactic microswimmers that form self-spinning microgears following spatiotemporal light patterns. The gears are coupled via their chemical clouds by diffusiophoresis12 and constitute the elementary bricks of synchronized superstructures, which autonomously regulate their dynamics. The results are quantitatively rationalized on the basis of a stochastic description of diffusio-phoretic oscillators dynamically coupled by chemical gradients. Our findings harness non-equilibrium phoretic phenomena to program interactions and direct self-assembly with fidelity and specificity. It lays the groundwork for the autonomous construction of dynamical architectures and functional micro-machinery.}, author = {Aubret, Antoine and Youssef, Mena and Sacanna, Stefano and Palacci, Jérémie A}, issn = {1745-2481}, journal = {Nature Physics}, number = {11}, pages = {1114--1118}, publisher = {Springer Nature}, title = {{Targeted assembly and synchronization of self-spinning microgears}}, doi = {10.1038/s41567-018-0227-4}, volume = {14}, year = {2018}, } @article{9066, abstract = {The novel electronic state of the canted antiferromagnetic (AFM) insulator, strontium iridate (Sr2IrO4) has been well described by the spin-orbit-entangled isospin Jeff = 1/2, but the role of isospin in transport phenomena remains poorly understood. In this study, antiferromagnet-based spintronic functionality is demonstrated by combining unique characteristics of the isospin state in Sr2IrO4. Based on magnetic and transport measurements, large and highly anisotropic magnetoresistance (AMR) is obtained by manipulating the antiferromagnetic isospin domains. First-principles calculations suggest that electrons whose isospin directions are strongly coupled to in-plane net magnetic moment encounter the isospin mismatch when moving across antiferromagnetic domain boundaries, which generates a high resistance state. By rotating a magnetic field that aligns in-plane net moments and removes domain boundaries, the macroscopically-ordered isospins govern dynamic transport through the system, which leads to the extremely angle-sensitive AMR. As with this work that establishes a link between isospins and magnetotransport in strongly spin-orbit-coupled AFM Sr2IrO4, the peculiar AMR effect provides a beneficial foundation for fundamental and applied research on AFM spintronics.}, author = {Lee, Nara and Ko, Eunjung and Choi, Hwan Young and Hong, Yun Jeong and Nauman, Muhammad and Kang, Woun and Choi, Hyoung Joon and Choi, Young Jai and Jo, Younjung}, issn = {0935-9648}, journal = {Advanced Materials}, keywords = {Mechanical Engineering, General Materials Science, Mechanics of Materials}, number = {52}, publisher = {Wiley}, title = {{Antiferromagnet‐based spintronic functionality by controlling isospin domains in a layered perovskite iridate}}, doi = {10.1002/adma.201805564}, volume = {30}, year = {2018}, } @article{9068, abstract = {We report the temperature-dependent resistivity ρ(T) of chalcogenide NiS2-xSex (x = 0.1) using hydrostatic pressure as a control parameter in the temperature range of 4–300 K. The insulating behavior of ρ(T) survives at low temperatures in the pressure regime below 7.5 kbar, whereas a clear insulator-to-metallic transition is observed above 7.5 kbar. Two types of magnetic transitions, from the paramagnetic (PM) to the antiferromagnetic (AFM) state and from the AFM state to the weak ferromagnetic (WF) state, were evaluated and confirmed by magnetization measurement. According to the temperature–pressure phase diagram, the WF phase survives up to 7.5 kbar, and the transition temperature of the WF transition decreases as the pressure increases, whereas the metal–insulator transition temperature increases up to 9.4 kbar. We analyzed the metallic behavior and proposed Fermi-liquid behavior of NiS1.9Se0.1.}, author = {Hussain, Tayyaba and Oh, Myeong-jun and Nauman, Muhammad and Jo, Younjung and Han, Garam and Kim, Changyoung and Kang, Woun}, issn = {0921-4526}, journal = {Physica B: Condensed Matter}, pages = {235--238}, publisher = {Elsevier}, title = {{Pressure-induced metal–insulator transitions in chalcogenide NiS2-Se}}, doi = {10.1016/j.physb.2017.11.032}, volume = {536}, year = {2018}, } @article{913, abstract = {Coordinated cell polarization in developing tissues is a recurrent theme in multicellular organisms. In plants, a directional distribution of the plant hormone auxin is at the core of many developmental programs. A feedback regulation of auxin on the polarized localization of PIN auxin transporters in individual cells has been proposed as a self-organizing mechanism for coordinated tissue polarization, but the molecular mechanisms linking auxin signalling to PIN-dependent auxin transport remain unknown. We performed a microarray-based approach to find regulators of the auxin-induced PIN relocation in the Arabidopsis thaliana root. We identified a subset of a family of phosphatidylinositol transfer proteins (PITP), the PATELLINs (PATL). Here, we show that PATLs are expressed in partially overlapping cells types in different tissues going through mitosis or initiating differentiation programs. PATLs are plasma membrane-associated proteins accumulated in Arabidopsis embryos, primary roots, lateral root primordia, and developing stomata. Higher order patl mutants display reduced PIN1 repolarization in response to auxin, shorter root apical meristem, and drastic defects in embryo and seedling development. This suggests PATLs redundantly play a crucial role in polarity and patterning in Arabidopsis.}, author = {Tejos, Ricardo and Rodríguez Furlán, Cecilia and Adamowski, Maciek and Sauer, Michael and Norambuena, Lorena and Friml, Jirí}, issn = {00219533}, journal = {Journal of Cell Science}, number = {2}, publisher = {Company of Biologists}, title = {{PATELLINS are regulators of auxin mediated PIN1 relocation and plant development in Arabidopsis thaliana}}, doi = {10.1242/jcs.204198}, volume = {131}, year = {2018}, } @article{9134, abstract = {Several studies have shown the existence of a critical latitude where the dissipation of internal tides is strongly enhanced. Internal tides are internal waves generated by barotropic tidal currents impinging rough topography at the seafloor. Their dissipation and concomitant diapycnal mixing are believed to be important for water masses and the large‐scale ocean circulation. The purpose of this study is to clarify the physical processes at the origin of this strong latitudinal dependence of tidal energy dissipation. We find that different mechanisms are involved equatorward and poleward of the critical latitude. Triadic resonant instabilities are responsible for the dissipation of internal tides equatorward of the critical latitude. In particular, a dominant triad involving the primary internal tide and near‐inertial waves is key. At the critical latitude, the peak of energy dissipation is explained by both increased instability growth rates, and smaller scales of secondary waves thus more prone to break and dissipate their energy. Surprisingly, poleward of the critical latitude, the generation of evanescent waves appears to be crucial. Triadic instabilities have been widely studied, but the transfer of energy to evanescent waves has received comparatively little attention. Our work suggests that the nonlinear transfer of energy from the internal tide to evanescent waves (corresponding to the 2f‐pump mechanism described by Young et al., 2008, https://doi.org/10.1017/S0022112008001742) is an efficient mechanism to dissipate internal tide energy near and poleward of the critical latitude. The theoretical results are confirmed in idealized high‐resolution numerical simulations of a barotropic M2 tide impinging sinusoidal topography in a linearly stratified fluid.}, author = {Richet, O. and Chomaz, J.-M. and Muller, Caroline J}, issn = {2169-9275}, journal = {Journal of Geophysical Research: Oceans}, number = {9}, pages = {6136--6155}, publisher = {American Geophysical Union}, title = {{Internal tide dissipation at topography: Triadic resonant instability equatorward and evanescent waves poleward of the critical latitude}}, doi = {10.1029/2017jc013591}, volume = {123}, year = {2018}, } @article{9135, abstract = {Idealized simulations of tropical moist convection have revealed that clouds can spontaneously clump together in a process called self-aggregation. This results in a state where a moist cloudy region with intense deep convection is surrounded by extremely dry subsiding air devoid of deep convection. Because of the idealized settings of the simulations where it was discovered, the relevance of self-aggregation to the real world is still debated. Here, we show that self-aggregation feedbacks play a leading-order role in the spontaneous genesis of tropical cyclones in cloud-resolving simulations. Those feedbacks accelerate the cyclogenesis process by a factor of 2, and the feedbacks contributing to the cyclone formation show qualitative and quantitative agreement with the self-aggregation process. Once the cyclone is formed, wind-induced surface heat exchange (WISHE) effects dominate, although we find that self-aggregation feedbacks have a small but nonnegligible contribution to the maintenance of the mature cyclone. Our results suggest that self-aggregation, and the framework developed for its study, can help shed more light into the physical processes leading to cyclogenesis and cyclone intensification. In particular, our results point out the importance of the longwave radiative cooling outside the cyclone.}, author = {Muller, Caroline J and Romps, David M.}, issn = {0027-8424}, journal = {Proceedings of the National Academy of Sciences}, keywords = {Multidisciplinary}, number = {12}, pages = {2930--2935}, publisher = {Proceedings of the National Academy of Sciences}, title = {{Acceleration of tropical cyclogenesis by self-aggregation feedbacks}}, doi = {10.1073/pnas.1719967115}, volume = {115}, year = {2018}, }