On quantum effects near the liquid-vapor transition in helium

The liquid-vapor transition in He-3 and He-4 is investigated by means of path-integral molecular dynamics and the quantum virial expansion. Both methods are applied to the critical isobar and the critical isochore. While previous path-integral simulations have mainly considered the lambda transition and superfluid regime in He-4, we focus on the vicinity of the critical point and obtain good agreement with experimental results for the molar volume and the internal energy down to subcritical temperatures. We find that an effective classical potential that properly describes the two-particle radial distribution function exhibits a strong temperature dependence near the critical temperature. This contrasts with the behavior of essentially classical systems like xenon, where the effective potential is independent of temperature. It is conjectured that, owing to this difference in behavior between classical and quantum-mechanical systems, the crossover behavior observed for helium in the vicinity of the critical point differs qualitatively from that of other simple liquids

Acroneuria lycorias (Boreal Stonefly, Plecoptera: Perlidae) Emergence Behaviors Discovered in Pinus strobus Canopy

Species of Plecoptera, or stoneflies, are known to use vertical emergence supports, and researchers believe many species of Plecoptera exploit arboreal habitats during emergence. However, the exact nature of these arboreal behaviors has largely remained a mystery. While exploring the habitat potential of Pinus strobus (L.) (Eastern White Pine) canopies in northern Wisconsin we observed Acroneuria lycorias (Newman) (Boreal Stonefly, Plecoptera: Perlidae) exuviae at heights as high as 12m (observations at 6.6, 9, 9.5, and 12m). Most A. lycorias exuviae appeared to have a strong preference for emergence sites at the underside or base of branches similar to some Odonate species. We also observed A. lycorias, adults climbing upwards along the main stem, post-emergence, to heights up to 22m. To our knowledge, these heights represent the greatest heights ever documented for A. lycorias adults and exuviae, or any Plecopteran species. While other researchers have speculated that A. lycorias uses arboreal habitats during emergence, these behaviors were considered almost impossible to describe. Our observations provide us with new insights into Plecopteran emergence behaviors, especially for this species. We propose three alternative hypotheses that may explain these unique emergence behaviors

Azobenzene versus 3,3',5,5'-tetra-tert-butyl-azobenzene (TBA) at Au(111): Characterizing the role of spacer groups

We present large-scale density-functional theory (DFT) calculations and temperature programmed desorption measurements to characterize the structural, energetic and vibrational properties of the functionalized molecular switch 3,3',5,5'-tetra-tert-butyl-azobenzene (TBA) adsorbed at Au(111). Particular emphasis is placed on exploring the accuracy of the semi-empirical dispersion correction approach to semi-local DFT (DFT-D) in accounting for the substantial van der Waals component in the surface chemical bond. In line with previous findings for benzene and pure azobenzene at coinage metal surfaces, DFT-D significantly overbinds the molecule, but seems to yield an accurate adsorption geometry as far as can be judged from the experimental data. Comparing the trans adsorption geometry of TBA and azobenzene at Au(111) reveals a remarkable insensitivity of the structural and vibrational properties of the -N=N- moiety. This questions the established view of the role of the bulky tert-butyl-spacer groups for the switching of TBA in terms of a mere geometric decoupling of the photochemically active diazo-bridge from the gold substrate.Comment: 9 pages including 6 figures; related publications can be found at http://www.fhi-berlin.mpg.de/th/th.htm

Entendiendo, evaluando y solucionando los problemas de contaminación de luz en playas de anidamiento de tortugas marinas/understanding, assessing, and resolving light- pollution problems on sea turtle nesting beaches

Mantener al público informado sobre los problemas de la contaminación con luz de las playas de anidamiento de tortugas es un paso fundamental para oscurecer las playas de tortugas marinas. Muchas de aquellas personas responsables de esta iluminación no tienen conocimiento del efecto negativo que esto ocasiona y están dispuestos a corregir el problema voluntariamente una vez que son informados. Sin embargo, a menudo es necesaria legislación para un mayor control de la iluminación, y en muchas playas de anidamiento, esta es la única forma de resolver el problema de contaminación de luz. En este manual se incluyen una guía para iniciar, promocionar e implementar leyes sobre la iluminación artifical de playas, así como un modelo de una ordenanza que puede asistir con este fin

A General Framework for Sound and Complete Floyd-Hoare Logics

This paper presents an abstraction of Hoare logic to traced symmetric monoidal categories, a very general framework for the theory of systems. Our abstraction is based on a traced monoidal functor from an arbitrary traced monoidal category into the category of pre-orders and monotone relations. We give several examples of how our theory generalises usual Hoare logics (partial correctness of while programs, partial correctness of pointer programs), and provide some case studies on how it can be used to develop new Hoare logics (run-time analysis of while programs and stream circuits).Comment: 27 page

Chemical and physical influences on aerosol activation in liquid clouds: a study based on observations from the Jungfraujoch, Switzerland

A simple statistical model to predict the number of aerosols which activate to form cloud droplets in warm clouds has been established, based on regression analysis of data from four summertime Cloud and Aerosol Characterisation Experiments (CLACE) at the high-altitude site Jungfraujoch (JFJ). It is shown that 79 % of the observed variance in droplet numbers can be represented by a model accounting only for the number of potential cloud condensation nuclei (defined as number of particles larger than 80 nm in diameter), while the mean errors in the model representation may be reduced by the addition of further explanatory variables, such as the mixing ratios of O3, CO, and the height of the measurements above cloud base. The statistical model has a similar ability to represent the observed droplet numbers in each of the individual years, as well as for the two predominant local wind directions at the JFJ (northwest and southeast). Given the central European location of the JFJ, with air masses in summer being representative of the free troposphere with regular boundary layer in-mixing via convection, we expect that this statistical model is generally applicable to warm clouds under conditions where droplet formation is aerosol limited (i.e. at relatively high updraught velocities and/or relatively low aerosol number concentrations). A comparison between the statistical model and an established microphysical parametrization shows good agreement between the two and supports the conclusion that cloud droplet formation at the JFJ is predominantly controlled by the number concentration of aerosol particles

The Distance Geometry of Music

We demonstrate relationships between the classic Euclidean algorithm and many other fields of study, particularly in the context of music and distance geometry. Specifically, we show how the structure of the Euclidean algorithm defines a family of rhythms which encompass over forty timelines (\emph{ostinatos}) from traditional world music. We prove that these \emph{Euclidean rhythms} have the mathematical property that their onset patterns are distributed as evenly as possible: they maximize the sum of the Euclidean distances between all pairs of onsets, viewing onsets as points on a circle. Indeed, Euclidean rhythms are the unique rhythms that maximize this notion of \emph{evenness}. We also show that essentially all Euclidean rhythms are \emph{deep}: each distinct distance between onsets occurs with a unique multiplicity, and these multiplicies form an interval $1,2,...,k-1$. Finally, we characterize all deep rhythms, showing that they form a subclass of generated rhythms, which in turn proves a useful property called shelling. All of our results for musical rhythms apply equally well to musical scales. In addition, many of the problems we explore are interesting in their own right as distance geometry problems on the circle; some of the same problems were explored by Erd\H{o}s in the plane.Comment: This is the full version of the paper: "The distance geometry of deep rhythms and scales." 17th Canadian Conference on Computational Geometry (CCCG '05), University of Windsor, Canada, 200

Approaching the taxonomic affiliation of unidentified sequences in public databases – an example from the mycorrhizal fungi

BACKGROUND: During the last few years, DNA sequence analysis has become one of the primary means of taxonomic identification of species, particularly so for species that are minute or otherwise lack distinct, readily obtainable morphological characters. Although the number of sequences available for comparison in public databases such as GenBank increases exponentially, only a minuscule fraction of all organisms have been sequenced, leaving taxon sampling a momentous problem for sequence-based taxonomic identification. When querying GenBank with a set of unidentified sequences, a considerable proportion typically lack fully identified matches, forming an ever-mounting pile of sequences that the researcher will have to monitor manually in the hope that new, clarifying sequences have been submitted by other researchers. To alleviate these concerns, a project to automatically monitor select unidentified sequences in GenBank for taxonomic progress through repeated local BLAST searches was initiated. Mycorrhizal fungi – a field where species identification often is prohibitively complex – and the much used ITS locus were chosen as test bed. RESULTS: A Perl script package called emerencia is presented. On a regular basis, it downloads select sequences from GenBank, separates the identified sequences from those insufficiently identified, and performs BLAST searches between these two datasets, storing all results in an SQL database. On the accompanying web-service , users can monitor the taxonomic progress of insufficiently identified sequences over time, either through active searches or by signing up for e-mail notification upon disclosure of better matches. Other search categories, such as listing all insufficiently identified sequences (and their present best fully identified matches) publication-wise, are also available. DISCUSSION: The ever-increasing use of DNA sequences for identification purposes largely falls back on the assumption that public sequence databases contain a thorough sampling of taxonomically well-annotated sequences. Taxonomy, held by some to be an old-fashioned trade, has accordingly never been more important. emerencia does not automate the taxonomic process, but it does allow researchers to focus their efforts elsewhere than countless manual BLAST runs and arduous sieving of BLAST hit lists. The emerencia system is available on an open source basis for local installation with any organism and gene group as targets

Point-SLAM: Dense Neural Point Cloud-based SLAM

We propose a dense neural simultaneous localization and mapping (SLAM) approach for monocular RGBD input which anchors the features of a neural scene representation in a point cloud that is iteratively generated in an input-dependent data-driven manner. We demonstrate that both tracking and mapping can be performed with the same point-based neural scene representation by minimizing an RGBD-based re-rendering loss. In contrast to recent dense neural SLAM methods which anchor the scene features in a sparse grid, our point-based approach allows dynamically adapting the anchor point density to the information density of the input. This strategy reduces runtime and memory usage in regions with fewer details and dedicates higher point density to resolve fine details. Our approach performs either better or competitive to existing dense neural RGBD SLAM methods in tracking, mapping and rendering accuracy on the Replica, TUM-RGBD and ScanNet datasets. The source code is available at https://github.com/tfy14esa/Point-SLAM.Comment: 17 Pages, 10 Figure

UncLe-SLAM: Uncertainty Learning for Dense Neural SLAM

We present an uncertainty learning framework for dense neural simultaneous localization and mapping (SLAM). Estimating pixel-wise uncertainties for the depth input of dense SLAM methods allows re-weighing the tracking and mapping losses towards image regions that contain more suitable information that is more reliable for SLAM. To this end, we propose an online framework for sensor uncertainty estimation that can be trained in a self-supervised manner from only 2D input data. We further discuss the advantages of the uncertainty learning for the case of multi-sensor input. Extensive analysis, experimentation, and ablations show that our proposed modeling paradigm improves both mapping and tracking accuracy and often performs better than alternatives that require ground truth depth or 3D. Our experiments show that we achieve a 38\% and 27\% lower absolute trajectory tracking error (ATE) on the 7-Scenes and TUM-RGBD datasets respectively. On the popular Replica dataset using two types of depth sensors, we report an 11\% F1-score improvement on RGBD SLAM compared to the recent state-of-the-art neural implicit approaches. Source code: https://github.com/kev-in-ta/UncLe-SLAM.Comment: ICCV 2023 Workshop. 20 pages, 9 figure