Signal Propagation in Multi‐Layer DNAzyme Cascades Using Structured Chimeric Substrates

Signal propagation through enzyme cascades is a critical component of information processing in cellular systems. Although such systems have potential as biomolecular computing tools, rational design of synthetic protein networks remains infeasible. DNA strands with catalytic activity (DNAzymes) are an attractive alternative, enabling rational cascade design through predictable base‐pair hybridization principles. Multi‐layered DNAzyme signaling and logic cascades are now reported. Signaling between DNAzymes was achieved using a structured chimeric substrate (SCS) that releases a downstream activator after cleavage by an upstream DNAzyme. The SCS can be activated by various upstream DNAzymes, can be coupled to DNA strand‐displacement devices, and is highly resistant to interference from background DNA. This work enables the rational design of synthetic DNAzyme regulatory networks, with potential applications in biomolecular computing, biodetection, and autonomous theranostics.     

On the restricted homomorphism problem

The restricted homomorphism problem asks: given an input digraph G and a homomorphism g:G→Y, does there exist a homomorphism f:G→H? We prove that if H is hereditarily hard and YH, then is NP-complete. Since non-bipartite graphs are hereditarily hard, this settles in the affirmative a conjecture of Hell and Nešetřil.     

Dense cluster formation during aggregation and gelation of attractive slippery nanoemulsion droplets

Using time-resolved small angle neutron scattering, we have measured the wave-number-dependent structure factor S(q) of monodisperse nanoemulsions that aggregate and gel after we suddenly turn on a strong, short-range, slippery attraction between the droplets. At high q, peaks in S(q) appear as dense clusters of droplets form, and S(q) increases strongly toward low q, as these dense clusters become locked into a rigid gel network, despite the fluidity of the films between the droplets. The long-time high-q structure of nanoemulsion gels formed by slippery diffusion-limited cluster aggregation is universal in shape and remarkably independent of the droplet volume fraction, phi.     

Magnetic reconnection triggering magnetohydrodynamic instabilities during a sawtooth crash in a Tokamak plasma

Thomson scattering measurements with subcentimeter spatial resolution have been made during a sawtooth crash in a Mega Ampere Spherical Tokamak fusion plasma. The unparalleled resolution of the temperature profile has shed new light on the mechanisms that underlie the sawtooth. As magnetic reconnection occurs, the temperature gradient at the island boundary increases. The increased local temperature gradient is sufficient to make the helical core unstable to ideal magnetohydrodynamic instabilities, thought to be responsible for the rapidity of the collapse.     

Kernel-based fuzzy clustering and fuzzy clustering: A comparative experimental study

In this study, we present a comprehensive comparative analysis of kernel-based fuzzy clustering and fuzzy clustering. Kernel based clustering has emerged as an interesting and quite visible alternative in fuzzy clustering, however, the effectiveness of this extension vis-à-vis some generic methods of fuzzy clustering has neither been discussed in a complete manner nor the performance of clustering quantified through a convincing comparative analysis. Our focal objective is to understand the performance gains and the importance of parameter selection for kernelized fuzzy clustering. Generic Fuzzy C-Means (FCM) and Gustafson–Kessel (GK) FCM are compared with two typical generalizations of kernel-based fuzzy clustering: one with prototypes located in the feature space (KFCM-F) and the other where the prototypes are distributed in the kernel space (KFCM-K). Both generalizations are studied when dealing with the Gaussian kernel while KFCM-K is also studied with the polynomial kernel. Two criteria are used in evaluating the performance of the clustering method and the resulting clusters, namely classification rate and reconstruction error. Through carefully selected experiments involving synthetic and Machine Learning repository (http://archive.ics.uci.edu/beta/) data sets, we demonstrate that the kernel-based FCM algorithms produce a marginal improvement over standard FCM and GK for most of the analyzed data sets. It has been observed that the kernel-based FCM algorithms are in a number of cases highly sensitive to the selection of specific values of the kernel parameters.     

Cohomology of incidence coalgebras

The cohomology groups Hⁿ(M, C) are studied, where C is the incidence coalgebra of a locally finite partially ordered set P and where M is a C-C comodule depending on a convex coarsening of the given partial order on P. The case where P is a geometric lattice and the convex coarsening is just the equality relation is emphasized.     

Charge asymmetry in inelastic π−p interactions at 205 GeV/c for particles with transverse momentum > 1.0 GeVc

In 205 GeV/cπ^?p inelastic interactions, negative particles with transverse momentum greater than 1.0 GeV/c moving forward in the center of mass outnumber similar positive particles by a factor of 3.7 to 1, greatly in excess of the corresponding ratio for small transverse momentum. The asymmetry is reversed in the backward direction. The forward asymmetry is most prominent in 2-, 4-, and 6-prong interactions, but both forward and backward asymmetries are also substantial for higher multiplicity interactions.