Mesh-Based Entry Vehicle and Explosive Debris Re-Contact Probability Modeling

The risk to a crewed vehicle arising from potential re-contact with fragments from an explosive breakup of any jettisoned spacecraft segments during entry has long sought to be quantified. However, great difficulty lies in efficiently capturing the potential locations of each fragment and their collective threat to the vehicle. The method presented in this paper addresses this problem by using a stochastic approach that discretizes simulated debris pieces into volumetric cells, and then assesses strike probabilities accordingly. Combining spatial debris density and relative velocity between the debris and the entry vehicle, the strike probability can be calculated from the integral of the debris flux inside each cell over time. Using this technique it is possible to assess the risk to an entry vehicle along an entire trajectory as it separates from the jettisoned segment. By decoupling the fragment trajectories from that of the entry vehicle, multiple potential separation maneuvers can then be evaluated rapidly to provide an assessment of the best strategy to mitigate the re-contact risk

Reconciling long-term cultural diversity and short-term collective social behavior

An outstanding open problem is whether collective social phenomena occurring over short timescales can systematically reduce cultural heterogeneity in the long run, and whether offline and online human interactions contribute differently to the process. Theoretical models suggest that short-term collective behavior and long-term cultural diversity are mutually excluding, since they require very different levels of social influence. The latter jointly depends on two factors: the topology of the underlying social network and the overlap between individuals in multidimensional cultural space. However, while the empirical properties of social networks are well understood, little is known about the large-scale organization of real societies in cultural space, so that random input specifications are necessarily used in models. Here we use a large dataset to perform a high-dimensional analysis of the scientific beliefs of thousands of Europeans. We find that inter-opinion correlations determine a nontrivial ultrametric hierarchy of individuals in cultural space, a result unaccessible to one-dimensional analyses and in striking contrast with random assumptions. When empirical data are used as inputs in models, we find that ultrametricity has strong and counterintuitive effects, especially in the extreme case of long-range online-like interactions bypassing social ties. On short time-scales, it strongly facilitates a symmetry-breaking phase transition triggering coordinated social behavior. On long time-scales, it severely suppresses cultural convergence by restricting it within disjoint groups. We therefore find that, remarkably, the empirical distribution of individuals in cultural space appears to optimize the coexistence of short-term collective behavior and long-term cultural diversity, which can be realized simultaneously for the same moderate level of mutual influence

NIME Identity from the Performer’s Perspective

The term ‘NIME’ - New Interfaces for Musical Expression - has come to signify both technical and cultural characteristics. Not all new musical instruments are NIMEs, and not all NIMEs are defined as such for the sole ephemeral condition of being new. So, what are the typical characteristics of NIMEs and what are their roles in performers’ practice? Is there a typical NIME repertoire? This paper aims to address these questions with a bottom up approach. We reflect on the answers of 78 NIME performers to an online questionnaire discussing their performance experience with NIMEs. The results of our investigation explore the role of NIMEs in the performers’ practice and identify the values that are common among performers. We find that most NIMEs are viewed as exploratory tools created by and for performers, and that they are constantly in development and almost in no occasions in a finite state. The findings of our survey also reflect upon virtuosity with NIMEs, whose peculiar performance practice results in learning trajectories that often do not lead to the development of virtuosity as it is commonly understood in traditional performanc

Computing ecosystems: neural networks and embedded hardware platforms

Presented at the CHI2023 Workshop [WS2] - Beyond Prototyping Boards: Future Paradigms for Electronics ToolkitsPresented at the CHI2023 Workshop [WS2] - Beyond Prototyping Boards: Future Paradigms for Electronics ToolkitsPresented at the CHI2023 Workshop [WS2] - Beyond Prototyping Boards: Future Paradigms for Electronics ToolkitsPresented at the CHI2023 Workshop [WS2] - Beyond Prototyping Boards: Future Paradigms for Electronics ToolkitsEmbedded hardware platforms such as single-board computers (e.g., Raspberry Pi, Bela) or microcontrollers (e.g., Teensy, Arduino Uno) offer an entry point for beginners into physical computing. However, deploying neural networks into these platforms is challenging for various reasons: It requires lower-level software development skills, as machine learning toolkits are typically not incorporated into these platforms. Besides, the long compilation times burden debugging and quick prototyping and experimentation. Due to the low-resource nature of embedded hardware platforms, neural networks are usually trained on a host machine, which involves a back-and-forth of data, platforms and programming languages. We inquire how these computing ecosystems might be designed to facilitate prototyping and experimentation and integrate into existing programming workflows

Differentiable Modelling of Percussive Audio with Transient and Spectral Synthesis

Differentiable digital signal processing (DDSP) techniques, including methods for audio synthesis, have gained attention in recent years and lend themselves to interpretability in the parameter space. However, current differentiable synthesis methods have not explicitly sought to model the transient portion of signals, which is important for percussive sounds. In this work, we present a unified synthesis framework aiming to address transient generation and percussive synthesis within a DDSP framework. To this end, we propose a model for percussive synthesis that builds on sinusoidal modeling synthesis and incorporates a modulated temporal convolutional network for transient generation. We use a modified sinusoidal peak picking algorithm to generate time-varying non-harmonic sinusoids and pair it with differentiable noise and transient encoders that are jointly trained to reconstruct drumset sounds. We compute a set of reconstruction metrics using a large dataset of acoustic and electronic percussion samples that show that our method leads to improved onset signal reconstruction for membranophone percussion instruments

"The finer the musician, the smaller the details": NIMEcraft under the microscope

Many digital musical instrument design frameworks have been proposed that are well suited for analysis and comparison. However, not all provide applicable design suggestions, especially where subtle, important details are concerned. Using traditional lutherie as a model, we conducted a series of interviews to explore how violin makers “go beyond the obvious”, and how players perceive and describe subtle details of instrumental quality. We find that lutherie frameworks provide clear design methods, but are not enough to make a fine violin. Success comes after acquiring sufficient tacit knowledge, which enables detailed craft through subjective, empirical methods. Testing instruments for subtle qualities was suggested to be a different skill to playing. Whilst players are able to identify some specific details about instrumental quality by comparison, these are often not actionable, and important aspects of “sound and feeling” are much more difficult to describe. In the DMI domain, we introduce the term NIMEcraft to describe subtle differences between otherwise identical instruments and their underlying design processes, and consider how to improve the dissemination of NIMEcraft

Musical Instruments for Novices: Comparing NIME, HCI and Crowdfunding Approaches

Designing musical instruments to make performance accessible to novice musicians is a goal which long predates digital technology. However, just in the space of the past 6 years, dozens of instrument designs have been introduced in various academic venues and in commercial crowdfunding campaigns. In this paper, we draw comparisons in design, evaluation and marketing across four domains: crowdfunding campaigns on Kickstarter and Indiegogo; the New Interfaces for Musical Expression (NIME) conference; conferences in human-computer interaction (HCI); and researchers creating accessible instruments for children and adults with disabilities. We observe striking differences in approach between commercial and academic projects, with less pronounced differences between each of the academic communities. The paper concludes with general reflections on the identity and purpose of instruments for novice musicians, with suggestions for future exploration

Glasgow, Edinburgh, Mainz (GEM) Tagging System

The GEM tagging spectrometer was designed to make best use of the 100% DC MAMI-A beam for doing photoreaction experiments. As the location available for the spectrometer was in the Magnet Hall a non standard design was necessary so that the tagging magnet system could also act as electron beam handling system when the beam when the beam was required in Hall 2. This location also offered the possibility of parasitic operation in conjunction with experiments in Hall 2

Mesh inlay, mesh kit or native tissue repair for women having repeat anterior or posterior prolapse surgery: randomised controlled trial (PROSPECT)

Funding The project was funded by the National Institute for Health Research Health Technology Assessment Programme (Project Number 07/60/18). The Health Services Research Unit and the Health Economics Research Unit are funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. Acknowledgements The authors wish to thank the women who participated in the PROSPECT study. We also thank Margaret MacNeil for her secretarial support and data management; Dawn McRae and Lynda Constable for their trial management support; the programming team in CHaRT, led by Gladys McPherson; members of the Project Management Group for their ongoing advice and support of the study; and the staff at the recruitment sites who facilitated the recruitment, treatment and follow up of study participants.Peer reviewedPublisher PD