Thermodynamic metrics and optimal paths

A fundamental problem in modern thermodynamics is how a molecular-scale machine performs useful work, while operating away from thermal equilibrium without excessive dissipation. To this end, we derive a friction tensor that induces a Riemannian manifold on the space of thermodynamic states. Within the linear-response regime, this metric structure controls the dissipation of finite-time transformations, and bestows optimal protocols with many useful properties. We discuss the connection to the existing thermodynamic length formalism, and demonstrate the utility of this metric by solving for optimal control parameter protocols in a simple nonequilibrium model.Comment: 5 page

Convergent losses of decay mechanisms and rapid turnover of symbiosis genes in mycorrhizal mutualists.

To elucidate the genetic bases of mycorrhizal lifestyle evolution, we sequenced new fungal genomes, including 13 ectomycorrhizal (ECM), orchid (ORM) and ericoid (ERM) species, and five saprotrophs, which we analyzed along with other fungal genomes. Ectomycorrhizal fungi have a reduced complement of genes encoding plant cell wall-degrading enzymes (PCWDEs), as compared to their ancestral wood decayers. Nevertheless, they have retained a unique array of PCWDEs, thus suggesting that they possess diverse abilities to decompose lignocellulose. Similar functional categories of nonorthologous genes are induced in symbiosis. Of induced genes, 7-38% are orphan genes, including genes that encode secreted effector-like proteins. Convergent evolution of the mycorrhizal habit in fungi occurred via the repeated evolution of a 'symbiosis toolkit', with reduced numbers of PCWDEs and lineage-specific suites of mycorrhiza-induced genes

A universal optical all-fiber omnipolarizer

Wherever the polarization properties of a light beam are of concern, polarizers and polarizing beamsplitters (PBS) are indispensable devices in linear-, nonlinear-and quantum-optical schemes. By the very nature of their operation principle, transformation of incoming unpolarized or partially polarized beams through these devices introduces large intensity variations in the fully polarized outcoming beam(s). Such intensity fluctuations are often detrimental, particularly when light is post-processed by nonlinear crystals or other polarization-sensitive optic elements. Here we demonstrate the unexpected capability of light to self-organize its own state-of-polarization, upon propagation in optical fibers, into universal and environmentally robust states, namely right and left circular polarizations. We experimentally validate a novel polarizing device-the Omnipolarizer, which is understood as a nonlinear dual-mode polarizing optical element capable of operating in two modes-as a digital PBS and as an ideal polarizer. Switching between the two modes of operation requires changing beam's intensity

Monitoring alkylphenols in water using the polar organic chemical integrative sampler (POCIS): determining sampling rates via the extraction of PES membranes and Oasis beads

Polar organic chemical integrative samplers (POCIS) have previously been used to monitor alkylphenol (AP) contamination in water and produced water. However, only the sorbent receiving phase of the POCIS (Oasis beads) is traditionally analyzed, thus limiting the use of POCIS for monitoring a range of APs with varying hydrophobicity. Here a “pharmaceutical” POCIS was calibrated in the laboratory using a static renewal setup for APs (from 2-ethylphenol to 4-n-nonylphenol) with varying hydrophobicity (log Kow between 2.47 and 5.76). The POCIS sampler was calibrated over its 28 day integrative regime and sampling rates (Rs) were determined. Uptake was shown to be a function of AP hydrophobicity where compounds with log Kow < 4 were preferentially accumulated in Oasis beads, and compounds with log Kow > 5 were preferentially accumulated in the PES membranes. A lag phase (over a 24 h period) before uptake in to the PES membranes occurred was evident. This work demonstrates that the analysis of both POCIS phases is vital in order to correctly determine environmentally relevant concentrations owing to the fact that for APs with log Kow ≤ 4 uptake, to the PES membranes and the Oasis beads, involves different processes compared to APs with log Kow ≥ 4. The extraction of both the POCIS matrices is thus recommended in order to assess the concentration of hydrophobic APs (log Kow ≥ 4), as well as hydrophilic APs, most effectively. © 2017 Elsevier Lt

Determination of the Antiferroquadrupolar Order Parameters in UPd3

By combining accurate heat capacity and X-ray resonant scattering results we have resolved the long standing question regarding the nature of the quadrupolar ordered phases in UPd_3. The order parameter of the highest temperature quadrupolar phase has been uniquely determined to be antiphase Q_{zx} in contrast to the previous conjecture of Q_{x^2-y^2} . The azimuthal dependence of the X-ray scattering intensity from the quadrupolar superlattice reflections indicates that the lower temperature phases are described by a superposition of order parameters. The heat capacity features associated with each of the phase transitions characterize their order, which imposes restrictions on the matrix elements of the quadrupolar operators.Comment: 4 pages, 5 figure

Layout of Graphs with Bounded Tree-Width

A \emph{queue layout} of a graph consists of a total order of the vertices, and a partition of the edges into \emph{queues}, such that no two edges in the same queue are nested. The minimum number of queues in a queue layout of a graph is its \emph{queue-number}. A \emph{three-dimensional (straight-line grid) drawing} of a graph represents the vertices by points in $\mathbb{Z}^3$ and the edges by non-crossing line-segments. This paper contributes three main results: (1) It is proved that the minimum volume of a certain type of three-dimensional drawing of a graph $G$ is closely related to the queue-number of $G$. In particular, if $G$ is an $n$-vertex member of a proper minor-closed family of graphs (such as a planar graph), then $G$ has a $O(1)\times O(1)\times O(n)$ drawing if and only if $G$ has O(1) queue-number. (2) It is proved that queue-number is bounded by tree-width, thus resolving an open problem due to Ganley and Heath (2001), and disproving a conjecture of Pemmaraju (1992). This result provides renewed hope for the positive resolution of a number of open problems in the theory of queue layouts. (3) It is proved that graphs of bounded tree-width have three-dimensional drawings with O(n) volume. This is the most general family of graphs known to admit three-dimensional drawings with O(n) volume. The proofs depend upon our results regarding \emph{track layouts} and \emph{tree-partitions} of graphs, which may be of independent interest.Comment: This is a revised version of a journal paper submitted in October 2002. This paper incorporates the following conference papers: (1) Dujmovic', Morin & Wood. Path-width and three-dimensional straight-line grid drawings of graphs (GD'02), LNCS 2528:42-53, Springer, 2002. (2) Wood. Queue layouts, tree-width, and three-dimensional graph drawing (FSTTCS'02), LNCS 2556:348--359, Springer, 2002. (3) Dujmovic' & Wood. Tree-partitions of $k$-trees with applications in graph layout (WG '03), LNCS 2880:205-217, 200

DeepWalk: Online Learning of Social Representations

We present DeepWalk, a novel approach for learning latent representations of vertices in a network. These latent representations encode social relations in a continuous vector space, which is easily exploited by statistical models. DeepWalk generalizes recent advancements in language modeling and unsupervised feature learning (or deep learning) from sequences of words to graphs. DeepWalk uses local information obtained from truncated random walks to learn latent representations by treating walks as the equivalent of sentences. We demonstrate DeepWalk's latent representations on several multi-label network classification tasks for social networks such as BlogCatalog, Flickr, and YouTube. Our results show that DeepWalk outperforms challenging baselines which are allowed a global view of the network, especially in the presence of missing information. DeepWalk's representations can provide $F_1$ scores up to 10% higher than competing methods when labeled data is sparse. In some experiments, DeepWalk's representations are able to outperform all baseline methods while using 60% less training data. DeepWalk is also scalable. It is an online learning algorithm which builds useful incremental results, and is trivially parallelizable. These qualities make it suitable for a broad class of real world applications such as network classification, and anomaly detection.Comment: 10 pages, 5 figures, 4 table