TY - CONF
AB - We settle the complexity of the $(\Delta+1)$-coloring and $(\Delta+1)$-list coloring problems in the CONGESTED CLIQUE model by presenting a simple deterministic algorithm for both problems running in a constant number of rounds. This matches the complexity of the recent breakthrough randomized constant-round $(\Delta+1)$-list coloring algorithm due to Chang et al. (PODC'19), and significantly improves upon the state-of-the-art deterministic bounds of $O(\log \Delta)$ rounds for $(\Delta+1)$-coloring and $O(\log^3 \Delta)$ rounds for $(\Delta+1)$-list coloring.
A remarkable property of our algorithm is its simplicity. Whereas the state-of-the-art randomized algorithms for this problem are based on the quite involved local coloring algorithm of Chang et al. (STOC'18), our algorithm can be described in just few lines. At a high level, it applies a careful derandomization of a recursive procedure which partitions the nodes and their respective palettes into separate bins. We show that after $O(1)$ recursion steps, the remaining uncolored subgraph within each bin has linear size, and thus can be solved locally by collecting it to a single node. This algorithm can also be implemented in the Massively Parallel Computation (MPC) model provided that each machine has linear (in $n$, the number of nodes in the input graph) space.
We also show an extension of our algorithm to the MPC regime in which machines have sublinear space: we present the first deterministic $(\Delta+1)$-list coloring algorithm designed for sublinear-space MPC, which runs in $O(\log \Delta + \log\log n)$ rounds.
AU - Czumaj, Artur
AU - Davies, Peter
AU - Parter, Merav
ID - 7803
T2 - Proceedings of the 2020 ACM Symposium on Principles of Distributed Computing (PODC 2020)
TI - Simple, deterministic, constant-round coloring in the congested clique
ER -
TY - JOUR
AB - Besides pro-inflammatory roles, the ancient cytokine interleukin-17 (IL-17) modulates neural circuit function. We investigate IL-17 signaling in neurons, and the extent it can alter organismal phenotypes. We combine immunoprecipitation and mass spectrometry to biochemically characterize endogenous signaling complexes that function downstream of IL-17 receptors in C. elegans neurons. We identify the paracaspase MALT-1 as a critical output of the pathway. MALT1 mediates signaling from many immune receptors in mammals, but was not previously implicated in IL-17 signaling or nervous system function. C. elegans MALT-1 forms a complex with homologs of Act1 and IRAK and appears to function both as a scaffold and a protease. MALT-1 is expressed broadly in the C. elegans nervous system, and neuronal IL-17–MALT-1 signaling regulates multiple phenotypes, including escape behavior, associative learning, immunity and longevity. Our data suggest MALT1 has an ancient role modulating neural circuit function downstream of IL-17 to remodel physiology and behavior.
AU - Flynn, Sean M.
AU - Chen, Changchun
AU - Artan, Murat
AU - Barratt, Stephen
AU - Crisp, Alastair
AU - Nelson, Geoffrey M.
AU - Peak-Chew, Sew Yeu
AU - Begum, Farida
AU - Skehel, Mark
AU - De Bono, Mario
ID - 7804
JF - Nature Communications
TI - MALT-1 mediates IL-17 neural signaling to regulate C. elegans behavior, immunity and longevity
VL - 11
ER -
TY - JOUR
AB - Plants as non-mobile organisms constantly integrate varying environmental signals to flexibly adapt their growth and development. Local fluctuations in water and nutrient availability, sudden changes in temperature or other abiotic and biotic stresses can trigger changes in the growth of plant organs. Multiple mutually interconnected hormonal signaling cascades act as essential endogenous translators of these exogenous signals in the adaptive responses of plants. Although the molecular backbones of hormone transduction pathways have been identified, the mechanisms underlying their interactions are largely unknown. Here, using genome wide transcriptome profiling we identify an auxin and cytokinin cross-talk component; SYNERGISTIC ON AUXIN AND CYTOKININ 1 (SYAC1), whose expression in roots is strictly dependent on both of these hormonal pathways. We show that SYAC1 is a regulator of secretory pathway, whose enhanced activity interferes with deposition of cell wall components and can fine-tune organ growth and sensitivity to soil pathogens.
AU - Hurny, Andrej
AU - Cuesta, Candela
AU - Cavallari, Nicola
AU - Ötvös, Krisztina
AU - Duclercq, Jerome
AU - Dokládal, Ladislav
AU - Montesinos López, Juan C
AU - Gallemi, Marçal
AU - Semeradova, Hana
AU - Rauter, Thomas
AU - Stenzel, Irene
AU - Persiau, Geert
AU - Benade, Freia
AU - Bhalearo, Rishikesh
AU - Sýkorová, Eva
AU - Gorzsás, András
AU - Sechet, Julien
AU - Mouille, Gregory
AU - Heilmann, Ingo
AU - De Jaeger, Geert
AU - Ludwig-Müller, Jutta
AU - Benková, Eva
ID - 7805
JF - Nature Communications
TI - Synergistic on Auxin and Cytokinin 1 positively regulates growth and attenuates soil pathogen resistance
VL - 11
ER -
TY - CONF
AB - We consider the following decision problem EMBEDk→d in computational topology (where k ≤ d are fixed positive integers): Given a finite simplicial complex K of dimension k, does there exist a (piecewise-linear) embedding of K into ℝd?
The special case EMBED1→2 is graph planarity, which is decidable in linear time, as shown by Hopcroft and Tarjan. In higher dimensions, EMBED2→3 and EMBED3→3 are known to be decidable (as well as NP-hard), and recent results of Čadek et al. in computational homotopy theory, in combination with the classical Haefliger–Weber theorem in geometric topology, imply that EMBEDk→d can be solved in polynomial time for any fixed pair (k, d) of dimensions in the so-called metastable range .
Here, by contrast, we prove that EMBEDk→d is algorithmically undecidable for almost all pairs of dimensions outside the metastable range, namely for . This almost completely resolves the decidability vs. undecidability of EMBEDk→d in higher dimensions and establishes a sharp dichotomy between polynomial-time solvability and undecidability.
Our result complements (and in a wide range of dimensions strengthens) earlier results of Matoušek, Tancer, and the second author, who showed that EMBEDk→d is undecidable for 4 ≤ k ϵ {d – 1, d}, and NP-hard for all remaining pairs (k, d) outside the metastable range and satisfying d ≥ 4.
AU - Filakovský, Marek
AU - Wagner, Uli
AU - Zhechev, Stephan Y
ID - 7806
SN - 9781611975994
T2 - Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
TI - Embeddability of simplicial complexes is undecidable
VL - 2020-January
ER -
TY - CONF
AB - In a straight-line embedded triangulation of a point set P in the plane, removing an inner edge and—provided the resulting quadrilateral is convex—adding the other diagonal is called an edge flip. The (edge) flip graph has all triangulations as vertices, and a pair of triangulations is adjacent if they can be obtained from each other by an edge flip. The goal of this paper is to contribute to a better understanding of the flip graph, with an emphasis on its connectivity.
For sets in general position, it is known that every triangulation allows at least edge flips (a tight bound) which gives the minimum degree of any flip graph for n points. We show that for every point set P in general position, the flip graph is at least -vertex connected. Somewhat more strongly, we show that the vertex connectivity equals the minimum degree occurring in the flip graph, i.e. the minimum number of flippable edges in any triangulation of P, provided P is large enough. Finally, we exhibit some of the geometry of the flip graph by showing that the flip graph can be covered by 1-skeletons of polytopes of dimension (products of associahedra).
A corresponding result ((n – 3)-vertex connectedness) can be shown for the bistellar flip graph of partial triangulations, i.e. the set of all triangulations of subsets of P which contain all extreme points of P. This will be treated separately in a second part.
AU - Wagner, Uli
AU - Welzl, Emo
ID - 7807
SN - 9781611975994
T2 - Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
TI - Connectivity of triangulation flip graphs in the plane (Part I: Edge flips)
VL - 2020-January
ER -
TY - CONF
AB - Quantization converts neural networks into low-bit fixed-point computations which can be carried out by efficient integer-only hardware, and is standard practice for the deployment of neural networks on real-time embedded devices. However, like their real-numbered counterpart, quantized networks are not immune to malicious misclassification caused by adversarial attacks. We investigate how quantization affects a network’s robustness to adversarial attacks, which is a formal verification question. We show that neither robustness nor non-robustness are monotonic with changing the number of bits for the representation and, also, neither are preserved by quantization from a real-numbered network. For this reason, we introduce a verification method for quantized neural networks which, using SMT solving over bit-vectors, accounts for their exact, bit-precise semantics. We built a tool and analyzed the effect of quantization on a classifier for the MNIST dataset. We demonstrate that, compared to our method, existing methods for the analysis of real-numbered networks often derive false conclusions about their quantizations, both when determining robustness and when detecting attacks, and that existing methods for quantized networks often miss attacks. Furthermore, we applied our method beyond robustness, showing how the number of bits in quantization enlarges the gender bias of a predictor for students’ grades.
AU - Giacobbe, Mirco
AU - Henzinger, Thomas A
AU - Lechner, Mathias
ID - 7808
SN - 03029743
T2 - International Conference on Tools and Algorithms for the Construction and Analysis of Systems
TI - How many bits does it take to quantize your neural network?
VL - 12079
ER -
TY - CONF
AB - Interprocedural data-flow analyses form an expressive and useful paradigm of numerous static analysis applications, such as live variables analysis, alias analysis and null pointers analysis. The most widely-used framework for interprocedural data-flow analysis is IFDS, which encompasses distributive data-flow functions over a finite domain. On-demand data-flow analyses restrict the focus of the analysis on specific program locations and data facts. This setting provides a natural split between (i) an offline (or preprocessing) phase, where the program is partially analyzed and analysis summaries are created, and (ii) an online (or query) phase, where analysis queries arrive on demand and the summaries are used to speed up answering queries.
In this work, we consider on-demand IFDS analyses where the queries concern program locations of the same procedure (aka same-context queries). We exploit the fact that flow graphs of programs have low treewidth to develop faster algorithms that are space and time optimal for many common data-flow analyses, in both the preprocessing and the query phase. We also use treewidth to develop query solutions that are embarrassingly parallelizable, i.e. the total work for answering each query is split to a number of threads such that each thread performs only a constant amount of work. Finally, we implement a static analyzer based on our algorithms, and perform a series of on-demand analysis experiments on standard benchmarks. Our experimental results show a drastic speed-up of the queries after only a lightweight preprocessing phase, which significantly outperforms existing techniques.
AU - Chatterjee, Krishnendu
AU - Goharshady, Amir Kafshdar
AU - Ibsen-Jensen, Rasmus
AU - Pavlogiannis, Andreas
ID - 7810
SN - 03029743
T2 - European Symposium on Programming
TI - Optimal and perfectly parallel algorithms for on-demand data-flow analysis
VL - 12075
ER -
TY - JOUR
AB - Scientific research is to date largely restricted to wealthy laboratories in developed nations due to the necessity of complex and expensive equipment. This inequality limits the capacity of science to be used as a diplomatic channel. Maker movements use open-source technologies including additive manufacturing (3D printing) and laser cutting, together with low-cost computers for developing novel products. This movement is setting the groundwork for a revolution, allowing scientific equipment to be sourced at a fraction of the cost and has the potential to increase the availability of equipment for scientists around the world. Science education is increasingly recognized as another channel for science diplomacy. In this perspective, we introduce the idea that the Maker movement and open-source technologies have the potential to revolutionize science, technology, engineering and mathematics (STEM) education worldwide. We present an open-source STEM didactic tool called SCOPES (Sparking Curiosity through Open-source Platforms in Education and Science). SCOPES is self-contained, independent of local resources, and cost-effective. SCOPES can be adapted to communicate complex subjects from genetics to neurobiology, perform real-world biological experiments and explore digitized scientific samples. We envision such platforms will enhance science diplomacy by providing a means for scientists to share their findings with classrooms and for educators to incorporate didactic concepts into STEM lessons. By providing students the opportunity to design, perform, and share scientific experiments, students also experience firsthand the benefits of a multinational scientific community. We provide instructions on how to build and use SCOPES on our webpage: http://scopeseducation.org.
AU - Beattie, Robert J
AU - Hippenmeyer, Simon
AU - Pauler, Florian
ID - 7814
JF - Frontiers in Education
SN - 2504-284X
TI - SCOPES: Sparking curiosity through Open-Source platforms in education and science
VL - 5
ER -
TY - JOUR
AB - Beginning from a limited pool of progenitors, the mammalian cerebral cortex forms highly organized functional neural circuits. However, the underlying cellular and molecular mechanisms regulating lineage transitions of neural stem cells (NSCs) and eventual production of neurons and glia in the developing neuroepithelium remains unclear. Methods to trace NSC division patterns and map the lineage of clonally related cells have advanced dramatically. However, many contemporary lineage tracing techniques suffer from the lack of cellular resolution of progeny cell fate, which is essential for deciphering progenitor cell division patterns. Presented is a protocol using mosaic analysis with double markers (MADM) to perform in vivo clonal analysis. MADM concomitantly manipulates individual progenitor cells and visualizes precise division patterns and lineage progression at unprecedented single cell resolution. MADM-based interchromosomal recombination events during the G2-X phase of mitosis, together with temporally inducible CreERT2, provide exact information on the birth dates of clones and their division patterns. Thus, MADM lineage tracing provides unprecedented qualitative and quantitative optical readouts of the proliferation mode of stem cell progenitors at the single cell level. MADM also allows for examination of the mechanisms and functional requirements of candidate genes in NSC lineage progression. This method is unique in that comparative analysis of control and mutant subclones can be performed in the same tissue environment in vivo. Here, the protocol is described in detail, and experimental paradigms to employ MADM for clonal analysis and lineage tracing in the developing cerebral cortex are demonstrated. Importantly, this protocol can be adapted to perform MADM clonal analysis in any murine stem cell niche, as long as the CreERT2 driver is present.
AU - Beattie, Robert J
AU - Streicher, Carmen
AU - Amberg, Nicole
AU - Cheung, Giselle T
AU - Contreras, Ximena
AU - Hansen, Andi H
AU - Hippenmeyer, Simon
ID - 7815
IS - 159
JF - Journal of Visual Experiments (JoVE)
SN - 1940-087X
TI - Lineage tracing and clonal analysis in developing cerebral cortex using mosaic analysis with double markers (MADM)
ER -
TY - JOUR
AB - Purpose of review: Cancer is one of the leading causes of death and the incidence rates are constantly rising. The heterogeneity of tumors poses a big challenge for the treatment of the disease and natural antibodies additionally affect disease progression. The introduction of engineered mAbs for anticancer immunotherapies has substantially improved progression-free and overall survival of cancer patients, but little efforts have been made to exploit other antibody isotypes than IgG.
Recent findings: In order to improve these therapies, ‘next-generation antibodies’ were engineered to enhance a specific feature of classical antibodies and form a group of highly effective and precise therapy compounds. Advanced antibody approaches include among others antibody-drug conjugates, glyco-engineered and Fc-engineered antibodies, antibody fragments, radioimmunotherapy compounds, bispecific antibodies and alternative (non-IgG) immunoglobulin classes, especially IgE.
Summary: The current review describes solutions for the needs of next-generation antibody therapies through different approaches. Careful selection of the best-suited engineering methodology is a key factor in developing personalized, more specific and more efficient mAbs against cancer to improve the outcomes of cancer patients. We highlight here the large evidence of IgE exploiting a highly cytotoxic effector arm as potential next-generation anticancer immunotherapy.
AU - Singer, Judit
AU - Singer, Josef
AU - Jensen-Jarolim, Erika
ID - 7864
IS - 3
JF - Current opinion in allergy and clinical immunology
TI - Precision medicine in clinical oncology: the journey from IgG antibody to IgE
VL - 20
ER -