Body Size Distribution and Frequency of Anthropogenic Injuries of Bluntnose Sixgill Sharks, Hexanchus griseus, at Flora Islets, British Columbia

The Bluntnose Sixgill Shark (Hexanchus griseus) is a widely distributed demersal species whose population biology is poorly understood. Although H. griseus is normally found in deep continental slope waters, individuals from a population in the Strait of Georgia, British Columbia, make unexpected diurnal movements onto a shallow reef (Flora Islets) between June and August. This shallow water activity allowed in situ length measurements to be made on 35 free-swimming Bluntnose Sixgill Sharks using stereo videography. The measured sharks were all large juveniles and sub-adults, although smaller juveniles and pregnant females are known to occur in deeper adjacent waters. The restricted size distribution at Flora Islets may arise because small juveniles avoid contact with larger conspecifics and mating takes place offshore. All measured sharks were individually identified by unique scar patterns. In 13 of 35 sharks these scars were consistent with injuries expected from hooking and entanglement by commercial fishing gear

Intrinsically-multilayer moir\'e heterostructures

We introduce trilayer and multilayer moir\'e heterostructures that cannot be viewed from the ``moir\'e-of-moir\'e" perspective of helically-twisted trilayer graphene. These ``intrinsically trilayer" moir\'e systems feature periodic modulation of a local quasicrystalline structure. They open the door to realizing moir\'e heterostructures with vastly more material constituents because they do not constrain the lattice constants of the layers. In this manuscript, we define intrinsically multilayer patterns, provide a recipe for their construction, derive their local configuration space, and connect the visual patterns to physical observables in material systems.Comment: Fixed missing figur

Importance of chirality and reduced flexibility of protein side chains: A study with square and tetrahedral lattice models

In simple models side chains are often represented implicitly (e.g., by spin-states) or simplified as one atom. We study side chain effects using square lattice and tetrahedral lattice models, with explicitly side chains of two atoms. We distinguish effects due to chirality and effects due to side chain flexibilities, since residues in proteins are L-residues, and their side chains adopt different rotameric states. Short chains are enumerated exhaustively. For long chains, we sample effectively rare events (eg, compact conformations) and obtain complete pictures of ensemble properties of these models at all compactness region. We find that both chirality and reduced side chain flexibility lower the folding entropy significantly for globally compact conformations, suggesting that they are important properties of residues to ensure fast folding and stable native structure. This corresponds well with our finding that natural amino acid residues have reduced effective flexibility, as evidenced by analysis of rotamer libraries and side chain rotatable bonds. We further develop a method calculating the exact side-chain entropy for a given back bone structure. We show that simple rotamer counting often underestimates side chain entropy significantly, and side chain entropy does not always correlate well with main chain packing. Among compact backbones with maximum side chain entropy, helical structures emerges as the dominating configurations. Our results suggest that side chain entropy may be an important factor contributing to the formation of alpha helices for compact conformations.Comment: 16 pages, 15 figures, 2 tables. Accepted by J. Chem. Phy

A Method For Appraisal Of Annual Reproductive Success In The Black Brant Population

Thesis (M.S.) University of Alaska Fairbanks, 197

PISCES: recent improvements to a PDB sequence culling server

PISCES is a database server for producing lists of sequences from the Protein Data Bank (PDB) using a number of entry- and chain-specific criteria and mutual sequence identity. Our goal in culling the PDB is to provide the longest list possible of the highest resolution structures that fulfill the sequence identity and structural quality cut-offs. The new PISCES server uses a combination of PSI-BLAST and structure-based alignments to determine sequence identities. Structure alignment produces more complete alignments and therefore more accurate sequence identities than PSI-BLAST. PISCES now allows a user to cull the PDB by-entry in addition to the standard culling by individual chains. In this scenario, a list will contain only entries that do not have a chain that has a sequence identity to any chain in any other entry in the list over the sequence identity cut-off. PISCES also provides fully annotated sequences including gene name and species. The server allows a user to cull an input list of entries or chains, so that other criteria, such as function, can be used. Results from a search on the re-engineered RCSB's site for the PDB can be entered into the PISCES server by a single click, combining the powerful searching abilities of the PDB with PISCES's utilities for sequence culling. The server's data are updated weekly. The server is available at

Evaluating system confidence of near-field antineutrino-based nuclear reactor safeguards

The International Atomic Energy Agency (IAEA) relies heavily on surveying facilities and verifying inventories to ensure that special nuclear material (SNM) pathways are correct and complete. This process, conducted through on-site inspections, draws a significant amount of the limited resources from the IAEA. Through implementing near-field antineutrino detection systems, changes in reactor core composition can be continuously monitored without the need of any expensive and invasive inspection. Our confidence in such a system, however, needs to be carefully considered for the IAEA to implement antineutrino detection systems for nuclear reactor safeguards. In this work, system confidence, or the certainty of the predicted antineutrino spectra, is evaluated to outline current antineutrino-based safeguard capabilities as well as to highlight the leading causes of uncertainty. The proposed system under evaluation is the Reactor Evaluation Through Inspection of Near-field Antineutrinos (RETINA) system, which utilizes high-fidelity modeling to predict the antineutrino spectra emitted from a simulated reactor. Certain deviations in real-time antineutrino spectra would indicate a shift in fissile inventory and a possible diversion of SNM from the reactor core. To fully analyze the role of reactor designs and diversion scenarios in the system evaluation, the antineutrino spectra was simulated for various next generation reactor designs as well as processed for possible diversion scenarios the IAEA would aim to detect. The results indicate that larger reactors with more common fissile inventories lead to lower system uncertainty. While some simulated diversion scenarios were consistently detected, the overlapping spectra led to low confidence of diversion following IAEA standards. Future work will go into modeling new reactor-detector systems as well as applying modern machine learning methods for confidence improvement.M.S

Accurate Structural Correlations from Maximum Likelihood Superpositions

The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biomolecular mechanisms and for relating structure to function. Here we report a highly accurate technique for inferring the major modes of structural correlation in macromolecules using likelihood-based statistical analysis of sets of structures. This method is generally applicable to any ensemble of related molecules, including families of nuclear magnetic resonance (NMR) models, different crystal forms of a protein, and structural alignments of homologous proteins, as well as molecular dynamics trajectories. Dominant modes of structural correlation are determined using principal components analysis (PCA) of the maximum likelihood estimate of the correlation matrix. The correlations we identify are inherently independent of the statistical uncertainty and dynamic heterogeneity associated with the structural coordinates. We additionally present an easily interpretable method (“PCA plots”) for displaying these positional correlations by color-coding them onto a macromolecular structure. Maximum likelihood PCA of structural superpositions, and the structural PCA plots that illustrate the results, will facilitate the accurate determination of dynamic structural correlations analyzed in diverse fields of structural biology

Matt: Local Flexibility Aids Protein Multiple Structure Alignment

Even when there is agreement on what measure a protein multiple structure alignment should be optimizing, finding the optimal alignment is computationally prohibitive. One approach used by many previous methods is aligned fragment pair chaining, where short structural fragments from all the proteins are aligned against each other optimally, and the final alignment chains these together in geometrically consistent ways. Ye and Godzik have recently suggested that adding geometric flexibility may help better model protein structures in a variety of contexts. We introduce the program Matt (Multiple Alignment with Translations and Twists), an aligned fragment pair chaining algorithm that, in intermediate steps, allows local flexibility between fragments: small translations and rotations are temporarily allowed to bring sets of aligned fragments closer, even if they are physically impossible under rigid body transformations. After a dynamic programming assembly guided by these “bent” alignments, geometric consistency is restored in the final step before the alignment is output. Matt is tested against other recent multiple protein structure alignment programs on the popular Homstrad and SABmark benchmark datasets. Matt's global performance is competitive with the other programs on Homstrad, but outperforms the other programs on SABmark, a benchmark of multiple structure alignments of proteins with more distant homology. On both datasets, Matt demonstrates an ability to better align the ends of α-helices and β-strands, an important characteristic of any structure alignment program intended to help construct a structural template library for threading approaches to the inverse protein-folding problem. The related question of whether Matt alignments can be used to distinguish distantly homologous structure pairs from pairs of proteins that are not homologous is also considered. For this purpose, a p-value score based on the length of the common core and average root mean squared deviation (RMSD) of Matt alignments is shown to largely separate decoys from homologous protein structures in the SABmark benchmark dataset. We postulate that Matt's strong performance comes from its ability to model proteins in different conformational states and, perhaps even more important, its ability to model backbone distortions in more distantly related proteins

Topological and stacked flat bands in bilayer graphene with a superlattice potential

We show that bilayer graphene in the presence of a 2D superlattice potential provides a highly tunable setup that can realize a variety of flat band phenomena. We focus on two regimes: (i) topological flat bands with non-zero Chern numbers, C, including bands with higher Chern numbers |C| > 1; and (ii) an unprecedented phase consisting of a stack of nearly flat bands with C = 0. For realistic values of the potential and superlattice periodicity, this stack can span nearly 100 meV, encompassing nearly all of the low-energy spectrum. Our results provide a realistic guide for future experiments to realize a new platform for flat band phenomena.Comment: 4+3 page