Revisiting the morphology and phylogeny of Lactifluus with three new lineages from southern China

As a recent group mainly defined by molecular data the genus Lactifluus is in need of further study to provide insight into the morphological and molecular variation within the genus, species limits and relationships. Phylogenetic analyses of nuc rDNA ITS1-5.8S-ITS2 (ITS), D1 and D2 domains of nuc 28S rDNA (28S), and part of the second largest subunit of the RNA polymerase II (rpb2) (6-7 region) sequences of 28 samples from southern China revealed three new lineages of Lactifluus. Two of them are nested in a major clade that includes the type of Lactifluus and here is treated as two new sections: L. sect. Ambicystidiati and L. sect. Tenuicystidiati. Lactifluus ambicystidiatus, described here as a new species (= sect. Ambicystidiati), has both lamprocystidia and macrocystidia in the hymenium, a unique combination of features within Russulaceae. Furthermore, only remnants of lactiferous hyphae are present in L. ambicystidiatus and our results suggest that the ability to form a lactiferous system has been lost in this lineage. Lactifluus sect. Tenuicystidiati forms a strongly supported monophyletic group as a sister lineage to L. sect. Lactifluus. We recognize it based on the thin-walled macrocystidia and smaller ellipsoid spores with an incomplete reticulum compared with L. sect. Lactifluus. The former placement of L. tenuicystidiatus in the African L. sect. Pseudogymnocarpi is not supported. Using genealogical concordance we recognize five phylogenetic species within L. sect. Tenuicystidiati and describe two of these as new, L. subpruinosus and L. tropicosinicus. The third lineage, represented by L. leoninus, forms a sister group to L. subg. Lactariopsis sensu stricto. The three lineages provide further evidence for morphological features in Lactifluus being homoplasious. Some sections and species complexes are likely to be composed of more species and merit further investigations. Subtropical-tropical Asia is likely a key region for additional sampling

Effective Electrostatic Interactions in Suspensions of Polyelectrolyte Brush-Coated Colloids

Effective electrostatic interactions between colloidal particles, coated with polyelectrolyte brushes and suspended in an electrolyte solvent, are described via linear response theory. The inner cores of the macroions are modeled as hard spheres, the outer brushes as spherical shells of continuously distributed charge, the microions (counterions and salt ions) as point charges, and the solvent as a dielectric continuum. The multi-component mixture of macroions and microions is formally mapped onto an equivalent one-component suspension by integrating out from the partition function the microion degrees of freedom. Applying second-order perturbation theory and a random phase approximation, analytical expressions are derived for the effective pair interaction and a one-body volume energy, which is a natural by-product of the one-component reduction. The combination of an inner core and an outer shell, respectively impenetrable and penetrable to microions, allows the interactions between macroions to be tuned by varying the core diameter and brush thickness. In the limiting cases of vanishing core diameter and vanishing shell thickness, the interactions reduce to those derived previously for star polyelectrolytes and charged colloids, respectively.Comment: 20 pages, 5 figures, Phys. Rev. E (in press

Low Rank Approximation of Binary Matrices: Column Subset Selection and Generalizations

Low rank matrix approximation is an important tool in machine learning. Given a data matrix, low rank approximation helps to find factors, patterns and provides concise representations for the data. Research on low rank approximation usually focus on real matrices. However, in many applications data are binary (categorical) rather than continuous. This leads to the problem of low rank approximation of binary matrix. Here we are given a $d \times n$ binary matrix $A$ and a small integer $k$. The goal is to find two binary matrices $U$ and $V$ of sizes $d \times k$ and $k \times n$ respectively, so that the Frobenius norm of $A - U V$ is minimized. There are two models of this problem, depending on the definition of the dot product of binary vectors: The $\mathrm{GF}(2)$ model and the Boolean semiring model. Unlike low rank approximation of real matrix which can be efficiently solved by Singular Value Decomposition, approximation of binary matrix is $NP$-hard even for $k=1$. In this paper, we consider the problem of Column Subset Selection (CSS), in which one low rank matrix must be formed by $k$ columns of the data matrix. We characterize the approximation ratio of CSS for binary matrices. For $GF(2)$ model, we show the approximation ratio of CSS is bounded by $\frac{k}{2}+1+\frac{k}{2(2^k-1)}$ and this bound is asymptotically tight. For Boolean model, it turns out that CSS is no longer sufficient to obtain a bound. We then develop a Generalized CSS (GCSS) procedure in which the columns of one low rank matrix are generated from Boolean formulas operating bitwise on columns of the data matrix. We show the approximation ratio of GCSS is bounded by $2^{k-1}+1$, and the exponential dependency on $k$ is inherent.Comment: 38 page

Correlated k-distribution method for radiative transfer in climate models: Application to effect of cirrus clouds on climate

A radiative transfer method appropriate for use in simple climate models and three dimensional global climate models was developed. It is fully interactive with climate changes, such as in the temperature-pressure profile, cloud distribution, and atmospheric composition, and it is accurate throughout the troposphere and stratosphere. The vertical inhomogeneity of the atmosphere is accounted for by assuming a correlation of gaseous k-distributions of different pressures and temperatures. Line-by-line calculations are made to demonstrate that The method is remarkably accurate. The method is then used in a one-dimensional radiative-convective climate model to study the effect of cirrus clouds on surface temperature. It is shown that an increase in cirrus cloud cover can cause a significant warming of the troposphere and the Earth's surface, by the mechanism of an enhanced green-house effect. The dependence of this phenomenon on cloud optical thickness, altitude, and latitude is investigated

A protein model exhibiting three folding transitions

We explain the physical basis of a model for small globular proteins with water interactions. The water is supposed to access the protein interior in an "all-or-none" manner during the unfolding of the protein chain. As a consequence of this mechanism (somewhat speculative), the model exhibits fundamental aspects of protein thermodynamics, as cold, and warm unfolding of the polypeptide chain, and hence decreasing the temperature below the cold unfolding the protein folds again, accordingly the heat capacity has three characteristic peaks. The cold and warm unfolding has a sharpness close to a two-state system, while the cold folding is a transition where the intermediate states in the folding is energetical close to the folded/unfolded states, yielding a less sharp transition. The entropy of the protein chain causes both the cold folding and the warm unfolding.Comment: 13 pages LaTeX, 4 Postscript figure

Heat Capacity of Protein Folding

We construct a Hamiltonian for a single domain protein where the contact enthalpy and the chain entropy decrease linearly with the number of native contacts. The hydration effect upon protein unfolding is included by modeling water as ideal dipoles that are ordered around the unfolded surfaces, where the influence of these surfaces, covered with an ``ice-like'' shell of water, is represented by an effective field that directs the water dipoles. An intermolecular pair interaction between water molecules is also introduced. The heat capacity of the model exhibits the common feature of small globular proteins, two peaks corresponding to cold and warm unfolding, respectively. By introducing vibrational modes, we obtain quantitatively good accordance with experiments.Comment: 14 pages, LaTex, 4 figure

The instantaneous shear modulus in the shoving model

We point out that the instantaneous shear modulus of the shoving model for the non-Arrhenius temperature dependence of viscous liquids' relaxation time is the experimentally accessible high-frequency plateau modulus, not the idealized instantaneous affine shear modulus that cannot be measured. Data for a large selection of metallic glasses are compared to three different versions of the shoving model. The original shear-modulus based version shows a slight correlation to the Poisson ratio, which is eliminated by the energy-landscape formulation of the model in which the bulk modulus plays a minor role

Generalization in Reinforcement Learning by Soft Data Augmentation

Extensive efforts have been made to improve the generalization ability of Reinforcement Learning (RL) methods via domain randomization and data augmentation. However, as more factors of variation are introduced during training, optimization becomes increasingly challenging, and empirically may result in lower sample efficiency and unstable training. Instead of learning policies directly from augmented data, we propose SOft Data Augmentation (SODA), a method that decouples augmentation from policy learning. Specifically, SODA imposes a soft constraint on the encoder that aims to maximize the mutual information between latent representations of augmented and non-augmented data, while the RL optimization process uses strictly non-augmented data. Empirical evaluations are performed on diverse tasks from DeepMind Control suite as well as a robotic manipulation task, and we find SODA to significantly advance sample efficiency, generalization, and stability in training over state-of-the-art vision-based RL methods.Comment: Website: https://nicklashansen.github.io/SODA/ Code: https://github.com/nicklashansen/dmcontrol-generalization-benchmark. Presented at International Conference on Robotics and Automation (ICRA) 202