ABJM Wilson loops in the Fermi gas approach

The matrix model of ABJM theory can be formulated in terms of a Fermi gas in an external potential. We show that, in this formalism, vevs of Wilson loops correspond to averages of operators in the statistical-mechanical problem. This makes it possible to calculate these vevs at all orders in 1/N, up to exponentially small corrections, and for arbitrary Chern-Simons coupling, by using the WKB expansion. We present explicit results for the vevs of 1/6 and the 1/2 BPS Wilson loops, at any winding number, in terms of Airy functions. Our expressions are shown to reproduce the low genus results obtained previously in the 't Hooft expansion.Comment: 48 pages, 2 figures, expansion (2.110) and typos corrected, slight improvements of the presentatio

On the discovery of non-Euclidean geometry

Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2020, Director: Carlos Dorce[en] The main goal of this work is to investigate the historical transition from Euclidean to non-Euclidean geometry, to understand what the motivation of such a transition was and to understand to the best of my abilities how it was achieved. This will be done by reviewing the relevant authors’ original work and the correspondence between some of them

Nature-inspired, multi-functional surface coatings for space applications, fabricated by additive manufacturing

Conditions in space are extreme. Nevertheless, the goal for the indoor environment on the International Space Station (ISS) remains the same as on Earth: to provide comfort and a healthy quality of life. The environmental control and life-support system (ECLSS) is, among others, responsible for the absorption of humidity from cabin air, which is treated, stored, and re-used. However, efficiency could be improved, as only 70-93% of water is recyclable, and costly resupply from Earth is needed. Additionally, astronauts on the ISS experience 0.5 Sv of ionizing radiation in one year, consisting of galactic cosmic rays (GCR) and solar particle events (SPE). Beyond Earth’s magnetic field this can increase immensely, due to potential solar flares, leading to the biggest risk to astronauts’ health, including experience of radiation syndrome and cancer, but, furthermore, threatens future bio-regenerative ECLSS. Furthermore, with humidity of more than 60%, organisms such as bacteria and fungi start to disperse and proliferate. The weakened immune system of astronauts, limited treatment, no immediate return to Earth, and increasing resistance of bacteria, reinforces the control of microbial contamination. Currently, neither of the above is feasible for future missions to Moon, Mars, and beyond and, therefore, finding new approaches for regenerative life support through passive systems is crucial. Please click Additional Files below to see the full abstract

A Role for the Longitudinal Axis of the Hippocampus in Multiscale Representations of Large and Complex Spatial Environments and Mnemonic Hierarchies

The hippocampus is involved in spatial navigation and memory in rodents and humans. Anatomically, the hippocampus extends along a longitudinal axis that shows a combination of graded and specific interconnections with neocortical and subcortical brain areas. Functionally, place cells are found all along the longitudinal axis and exhibit gradients of properties including an increasing dorsal-to-ventral place field size. We propose a view of hippocampal function in which fine-dorsal to coarse-ventral overlapping representations collaborate to form a multi-level representation of spatial and episodic memory that is dominant during navigation in large and complex environments or when encoding complex memories. This view is supported by the fact that the effects of ventral hippocampal damage are generally only found in larger laboratory-scale environments, and by the finding that human virtual navigation studies associate ventral hippocampal involvement with increased environmental complexity. Other mechanisms such as the ability of place cells to exhibit multiple fields and their ability to scale their fields with changes in environment size may be utilized when forming large-scale cognitive maps. Coarse-grained ventral representations may overlap with and provide multi-modal global contexts to finer-grained intermediate and dorsal representations, a mechanism that may support mnemonic hierarchies of autobiographical memory in humans

Forecasting a Language Shift Based on Cellular Automata

Language extinction as a consequence of language shifts is a widespread social phenomenon that affects several million people all over the world today. An important task for social sciences research should therefore be to gain an understanding of language shifts, especially as a way of forecasting the extinction or survival of threatened languages, i.e., determining whether or not the subordinate language will survive in communities with a dominant and a subordinate language. In general, modeling is usually a very difficult task in the social sciences, particularly when it comes to forecasting the values of variables. However, the cellular automata theory can help us overcome this traditional difficulty. The purpose of this article is to investigate language shifts in the speech behavior of individuals using the methodology of the cellular automata theory. The findings on the dynamics of social impacts in the field of social psychology and the empirical data from language surveys on the use of Catalan in Valencia allowed us to define a cellular automaton and carry out a set of simulations using that automaton. The simulation results highlighted the key factors in the progression or reversal of a language shift and the use of these factors allowed us to forecast the future of a threatened language in a bilingual community.Cellular Automata, Computational Simulations, Language, Social Dynamics

IMU-Based Classification of Locomotion Modes, Transitions, and Gait Phases with Convolutional Recurrent Neural Networks

This paper focuses on the classification of seven locomotion modes (sitting, standing, level ground walking, ramp ascent and descent, stair ascent and descent), the transitions among these modes, and the gait phases within each mode, by only using data in the frequency domain from one or two inertial measurement units. Different deep neural network configurations are investigated and compared by combining convolutional and recurrent layers. The results show that a system composed of a convolutional neural network followed by a long short-term memory network is able to classify with a mean [Formula: see text]-score of 0.89 and 0.91 for ten healthy subjects, and of 0.92 and 0.95 for one osseointegrated transfemoral amputee subject (excluding the gait phases because they are not labeled in the data-set), using one and two inertial measurement units, respectively, with a 5-fold cross-validation. The promising results obtained in this study pave the way for using deep learning for the control of transfemoral prostheses with a minimum number of inertial measurement units

Investigating the design space of smartwatches combining physical rotary inputs

Watches benefit from a long design history. Designers and engineers have successfully built devices using rotary physical inputs such as crowns, bezels, and wheels, separately or combined. Smart watch designers have explored the use of some of these inputs for interactions. However, a systematic exploration of their combinations has yet to be done. We investigate the design space of interactions with multiple rotary inputs through a three stages exploration. (1) We build upon observations of a collection of 113 traditional or electronic watches to propose a typology of physical rotary inputs for watches. (2) We conduct two focus groups to explore combination of physical rotary inputs. (3) We then build upon the output of these focus groups to design a low fidelity prototype, and further discuss the potential and challenges of rotary inputs combinations during a third focus group

3D printed probe for simultaneous E and H fields measurements

Additive manufacturing using conductive polylactic acid (PLA) is an emerging technology. This work presents a double-loaded loop probe made of conductive PLA and evaluates its performance compared to a previous design built on a printed circuit board (PCB). The results show that constructing near-field probes using 3D printing with conductive PLA is feasible.Peer ReviewedPostprint (published version