Encapsulation of a {Cu16} cluster containing four [Cu4O4] cubanes within an isopolyoxometalate {W44} cluster

We report a {Cu16} embedded within a {W44} cluster containing four cubane-like [Cu4O4] units within an isopolyoxotungstate (isoPOT) in a {Na4Cu4[(H2W11O38) (CH3COO)(OH)3]}4·88H2O (1) and a polyanion Cu-linked {W11} chain Na6Cu2[(H2W11O38)(CH3COO)(OH)]·26H2O (2). Electronically, the redox properties show that both compounds 1 and 2 undergo irreversible reductions resulting in the demetalation of the compounds, whilst the magnetic behavior of 1 and 2 shows a weak antiferromagnetic and a stronger ferromagnetic coupling, respectively

Constraints on discrete symmetries from anomaly cancellation in compactified superstring theories

Compactified string theories give rise to discrete symmetries which are essential if they are to provide a realistic low energy theory. We find that in a class of four dimensional string theories these symmetries are constrained by similar conditions to those discrete anomaly cancellation conditions found in the case the discrete symmetry is a residue of a spontaneously broken gauge symmetry. Such conditions strongly constrain the allowed form of the low energy effective theory.Comment: 8 pages, OUTP-93-14

Skin temperature changes in wild chimpanzees upon hearing vocalizations of conspecifics

The authors are grateful to the Royal Zoological Society of Scotland for providing core funding to the Budongo Conservation Field Station. The research was supported by a Fyssen fellowship awarded to GD, funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration (grant agreement no 283871), and the Swiss National Science Foundation (PZ00P3_154741) awarded to CDD.A growing trend of research using infra-red thermography (IRT) has shown that changes in skin temperature, associated with activity of the autonomic nervous system, can be reliably detected in human and non-human animals. A contact-free method, IRT provides the opportunity to uncover emotional states in free-ranging animals during social interactions. Here, we measured nose and ear temperatures of wild chimpanzees of Budongo Forest, Uganda, when exposed to naturally occurring vocalizations of conspecifics. We found a significant temperature decrease over the nose after exposure to conspecifics’ vocalizations, whereas we found a corresponding increase for ear temperature. Our study suggests that IRT can be used in wild animals to quantify changes in emotional states in response to the diversity of vocalizations, their functional significance and acoustical characteristics. We hope that it will contribute to more research on physiological changes associated with social interactions in wild animals.Publisher PDFPeer reviewe

A machine learning approach to infant distress calls and maternal behaviour of wild chimpanzees

We are grateful to the Royal Zoological Society of Scotland for providing core funding to the Budongo Conservation Field Station. This research was supported by funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration (Grant agreement no 283871), a Fyssen Foundation post-doctoral fellowship awarded to GD, the Swiss National Science Foundation (PZ00P3_154741) and Start up-funding of the Taipei Medical University (108-6402-004-112) awarded to CDD.Distress calls are an acoustically variable group of vocalizations ubiquitous in mammals and other animals. Their presumed function is to recruit help, but there has been much debate on whether the nature of the disturbance can be inferred from the acoustics of distress calls. We used machine learning to analyse episodes of distress calls of wild infant chimpanzees. We extracted exemplars from those distress call episodes and examined them in relation to the external event triggering them and the distance to the mother. In further steps, we tested whether the acoustic variants were associated with particular maternal responses. Our results suggest that, although infant chimpanzee distress calls are highly graded, they can convey information about discrete problems experienced by the infant and about distance to the mother, which in turn may help guide maternal parenting decisions. The extent to which mothers rely on acoustic cues alone (versus integrate other contextual-visual information) to decide upon intervening should be the focus of future research.PostprintPeer reviewe

A helical-shape scintillating fiber trigger and tracker system for the DarkLight experiment and beyond

The search for new physics beyond the Standard Model has interesting possibilities at low energies. For example, the recent 6.8$\sigma$ anomaly reported in the invariant mass of $e^+e^-$ pairs from $^8\text{Be}$ nuclear transitions and the discrepancy between predicted and measured values of muon g-2 give strong motivations for a protophobic fifth-force model. At low energies, the electromagnetic interaction is well understood and produces straightforward final states, making it an excellent probe of such models. However, to achieve the required precision, an experiment must address the substantially higher rate of electromagnetic backgrounds. In this paper, we present the results of simulation studies of a trigger system, motivated by the DarkLight experiment, using helical-shape scintillating fibers in a solenoidal magnetic field to veto electron-proton elastic scattering and the associated radiative processes. We also assess the performance of a tracking detector for lepton final states using scintillating fibers in the same setup

Interpolation of Scientific Image Databases

This paper explores how recent convolutional neural network (CNN)-based techniques can be used to interpolate images inside scientific image databases. These databases are frequently used for the interactive visualization of large-scale simulations, where images correspond to samples of the parameter space (e.g., timesteps, isovalues, thresholds, etc.) and the visualization space (e.g., camera locations, clipping planes, etc.). These databases can be browsed post hoc along the sampling axis to emulate real-time interaction with large-scale datasets. However, the resulting databases are limited to their contained images, i.e., the sampling points. In this paper, we explore how efficiently and accurately CNN-based techniques can derive new images by interpolating database elements. We demonstrate on several real-world examples that the size of databases can be further reduced by dropping samples that can be interpolated post hoc with an acceptable error, which we measure qualitatively and quantitatively