Short-Term Memory in Orthogonal Neural Networks

We study the ability of linear recurrent networks obeying discrete time dynamics to store long temporal sequences that are retrievable from the instantaneous state of the network. We calculate this temporal memory capacity for both distributed shift register and random orthogonal connectivity matrices. We show that the memory capacity of these networks scales with system size.Comment: 4 pages, 4 figures, to be published in Phys. Rev. Let

Taking a PEEK into YOLOv5 for Satellite Component Recognition via Entropy-based Visual Explanations

The escalating risk of collisions and the accumulation of space debris in Low Earth Orbit (LEO) has reached critical concern due to the ever increasing number of spacecraft. Addressing this crisis, especially in dealing with non-cooperative and unidentified space debris, is of paramount importance. This paper contributes to efforts in enabling autonomous swarms of small chaser satellites for target geometry determination and safe flight trajectory planning for proximity operations in LEO. Our research explores on-orbit use of the You Only Look Once v5 (YOLOv5) object detection model trained to detect satellite components. While this model has shown promise, its inherent lack of interpretability hinders human understanding, a critical aspect of validating algorithms for use in safety-critical missions. To analyze the decision processes, we introduce Probabilistic Explanations for Entropic Knowledge extraction (PEEK), a method that utilizes information theoretic analysis of the latent representations within the hidden layers of the model. Through both synthetic in hardware-in-the-loop experiments, PEEK illuminates the decision-making processes of the model, helping identify its strengths, limitations and biases

Everything Is Science: A Free City-Wide Science Festival

A week-long, city-wide science festival called Everything is Science (EiS) was developed to educate the community in an informal manner. The festival serves as a platform for presenters from diverse professions to give engaging talks (without PowerPoint slides) to the public, free of charge, in restaurants and bars around town. Over 350 people attended the events over 5 days with 33 presenters. Surveys completed by attendees and session coordinators indicate strong support for this festival. Altogether, the EiS festival serves as a no-cost method to engage with the community and improve science literacy with potential for adoption in other cities

The Stellar Content of Obscured Galactic Giant H II Regions IV.: NGC3576

We present deep, high angular resolution near-infrared images of the obscured Galactic Giant H II region NGC3576. Our images reach objects to ~3M_sun. We collected high signal-to-noise K-band spectra of eight of the brightest objects, some of which are affected by excess emission and some which follow a normal interstellar reddening law. None of them displayed photospheric features typical of massive OB type stars. This indicates that they are still enshrouded in their natal cocoons. The K-band brightest source (NGC3576 #48) shows CO 2.3 micron bandhead emission, and three others have the same CO feature in absorption. Three sources display spatially unresolved H_2 emission, suggesting dense shocked regions close to the stars. We conclude that the remarkable object NGC3576 #48 is an early-B/late-O star surrounded by a thick circumstellar disk. A number of other relatively bright cluster members also display excess emission in the K-band, indicative of reprocessing disks around massive stars (YSOs). Such emission appears common in other Galactic Giant H II regions we have surveyed. The IMF slope of the cluster, Gamma = -1.51, is consistent with Salpeter's distribution and similar to what has been observed in the Magellanic Cloud clusters and in the periphery of our Galaxy.Comment: 14 pages, 11 figures, accepted for publication in A

Consideration of compound drivers and impacts in the disaster risk reduction cycle

Consideration of compound drivers and impacts are often missing from applications within the Disaster Risk Reduction cycle, leading to poorer understanding of risk and benefits of actions. The need to include compound considerations is known, but lack of guidance is prohibiting practitioners from including these considerations. This paper makes a step towards practitioner guidance by providing examples where consideration of compound drivers, hazards and impacts may affect different application domains within disaster risk management. We discern five DRR categories, and provide illustrative examples of studies that highlight the role of "compound thinking" in early warning, emergency response, infrastructure management, long-term planning and capacity building. We conclude with a number of common elements that may contribute to the development of practical guidelines to develop appropriate applications for risk management

Volcanic ash as a resource for future research on Earth and the Moon

When a volcano erupts, it is often associated with destruction, particularly damage to infrastructure and loss of life. But these natural events also offer unexpected research opportunities, leading to serendipitous discoveries. This was the case for the volcanic events that made the headlines during 19 September to 25 December 2021, on the Canarian Island of La Palma. Rather than viewing the voluminous ash that erupted as a waste material needing to be removed as soon as possible, we saw the many possibilities that this remarkable material could offer science and engineering. Sustainability is a word that is commonly used in connection with geology these days. Here we present some possibilities of how the La Palma ash can be re‐purposed for use on this planet but also help us to develop new ideas for the future living on the Moon

Reclassifying historical disasters : from single to multi-hazards

Multi-hazard events, characterized by the simultaneous, cascading, or cumulative occurrence of multiple natural hazards, pose a significant threat to human lives and assets. This is primarily due to the cumulative and cascading effects arising from the interplay of various natural hazards across space and time. However, their identification is challenging, which is attributable to the complex nature of natural hazard interactions and the limited availability of multi-hazard observations. This study presents an approach for identifying multi-hazard events during the past 123 years (1900–2023) using the EM-DAT global disaster database. Leveraging the ‘associated hazard’ information in EM-DAT, multi-hazard events are detected and assessed in relation to their frequency, impact on human lives and assets, and reporting trends. The interactions between various combinations of natural hazard pairs are explored, reclassifying them into four categories: preconditioned/triggering, multivariate, temporally compounding, and spatially compounding multi-hazard events. The results show, globally, approximately 19 % of the 16,535 disasters recorded in EM-DAT can be classified as multi-hazard events. However, the multi-hazard events recorded in EM-DAT are disproportionately responsible for nearly 59 % of the estimated global economic losses. Conversely, single hazard events resulted in higher fatalities compared to multi-hazard events. The largest proportion of multi-hazard events are associated with floods, storms, and earthquakes. Landslides emerge as the predominant secondary hazards within multi-hazard pairs, primarily triggered by floods, storms, and earthquakes, with the majority of multi-hazard events exhibiting preconditioned/triggering and multivariate characteristics. There is a higher prevalence of multi-hazard events in Asia and North America, whilst temporal overlaps of multiple hazards predominate in Europe. These results can be used to increase the integration of multi-hazard thinking in risk assessments, emergency management response plans and mitigation policies at both national and international levels

Tools to enable the study and translation of supramolecular amphiphiles

This tutorial review focuses on providing a summary of the key techniques used for the characterisation of supramolecular amphiphiles and their self-assembled aggregates; from the understanding of low-level molecular interactions, to materials analysis, use of data to support computer-aided molecular design and finally, the translation of this class of compounds for real world application, specifically within the clinical setting. We highlight the common methodologies used for the study of traditional amphiphiles and build to provide specific examples that enable the study of specialist supramolecular systems. This includes the use of nuclear magnetic resonance spectroscopy, mass spectrometry, x-ray scattering techniques (small- and wide-angle x-ray scattering and single crystal x-ray diffraction), critical aggregation (or micelle) concentration determination methodologies, machine learning, and various microscopy techniques. Furthermore, this review provides guidance for working with supramolecular amphiphiles in in vitro and in vivo settings, as well as the use of accessible software programs, to facilitate screening and selection of druggable molecules. Each section provides: a methodology overview – information that may be derived from the use of the methodology described; a case study – examples for the application of these methodologies; and a summary section – providing methodology specific benefits, limitations and future applications