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The safe and effective use of optimistic period predictions
Get PDFParameters characterizing safety critical systems are generally assigned very conservative values for reasons of safety assurance. Provisioning computing resources on the basis of such conservatively assigned parameter values can lead to system implementations that make inefficient use of platform resources during run time. We address the problem of achieving more efficient implementations of sporadic task systems where, in addition to a conservatively assigned value for the period parameter of each task, we also have a more optimistic (i.e., larger), but perhaps incorrect, prediction of this value. We devise an algorithm that executes the system more efficiently during runtime if the prediction is correct, without compromising safety if it turns out to be incorrect
Exploring indirect relations between topics in augmented reality to inform the design of a neuroscience experiment
Get PDFNeuroscientists analyse publications to inform experiment design. Exploring direct relations between topics, such as brain diseases and regions, aids this process. Brain diseases may also connect indirectly to regions through topics such as mental processes. We aim to establish whether exploring indirect relations helps design experiments.
Using a user-centred design approach, we interview neuroscientists to establish the usefulness of exploring indirect relations, specify functionality, and design a corresponding visualisation. Nine neuroscientists indicated the visualisation is suitable to present the functionality, the functionality is useful to explore indirect relations, and exploring indirect relations is useful to design experiments
Global variational quantum circuits for arbitrary symmetric state preparation
Get PDFQuantum states that are symmetric under particle exchange play a crucial role in fields such as quantum metrology and quantum error correction. We use a variational circuit composed of global one-axis twisting and global rotations to efficiently prepare arbitrary symmetric states, i.e., any superposition of Dicke states. The circuit does not require local addressability or ancilla qubits and thus can be readily implemented in a variety of experimental platforms including trapped-ion quantum simulators and cavity QED systems. We provide analytic and numerical evidence that any N-qubit symmetric state can be prepared in 2N/3 steps. We demonstrate the utility of our protocol by preparing (i) metrologically useful N-qubit Dicke states of up to N=300 qubits in O(1) gate steps with theoretical infidelities 1-F<10-3, (ii) the N=9 Ruskai codewords in P=4 gate steps with 1-F<10-4, and (iii) the N=13 Gross codewords in P=7 gate steps with 1-F<10-4. Focusing on trapped-ion platforms, for the N=9 Ruskai and N=13 Gross codewords we estimate that the protocol achieves fidelities ≳95% in the presence of typical experimental noise levels, thus providing a pathway to the preparation of a wide range of useful highly entangled quantum states
A search to distinguish reduction for the isomorphism problem on direct sum lattices
Get PDFAt Eurocrypt 2003, Szydlo presented a search to distinguish
reduction for the Lattice Isomorphism Problem (LIP) on the integer lat-
tice Zn. Here the search problem asks to find an isometry between Zn and
an isomorphic lattice, while the distinguish variant asks to distinguish
between a list of auxiliary lattices related to Zn.
In this work we generalize Szydlo’s search to distinguish reduction in
two ways. Firstly, we generalize the reduction to any lattice isomorphic
to Γ n, where Γ is a fixed base lattice. Secondly, we allow Γ to be a
module lattice over any number field. Assuming the base lattice Γ and
the number field K are fixed, our reduction is polynomial in n.
As a special case we consider the module lattice O2 used in the module-
LIP based signature scheme HAWK, and we show that one can solve
the search problem, leading to a full key recovery, with less than 2d2
distinguishing calls on two lattices each, where d is the degree of the
power-of-two cyclotomic number field and O its ring of integers
X-ray computed tomography case study: Triangle and pentagon datasets with various sizes, scales, and noise levels
No full textThe dataset consists of two laser-cut objects made from a 6-mm-thick transparent plastic material called acrylate. The objects have triangular and pentagonal shapes, each containing 12 samples with varying sizes. The right-angle edges of the triangular samples range from 2.8 cm to 4.0 cm, while the edges of the pentagonal samples range from 2.5 cm to 3.0 cm. Each scanning session involved different placements of the objects, resulting in variations in rotation and translation
The evolution and implications of the inosine tRNA modification
Get PDFEver since the legendary publication by Francis Crick in JMB introducing the wobble hypothesis in 1966, inosine has been a permanent part of molecular biology. This review aims to integrate the rich array of novel insights emerging from subsequent research on the adenine-to-inosine modification of tRNA, with an emphasis on the results obtained during the last 5 years. Both the grand panorama of 4 billion years of evolution of life and the medical implications of defects in inosine modification will be reviewed. The most salient insights are that: (1) inosine at position 34 (the first position in the anticodon) is not universally present in the tree of life; (2) in many bacteria just a single homodimeric enzyme (TadA) is responsible for both tRNA inosine modification and mRNA inosine modification; (3) rapid progress is currently being made both in the molecular understanding of the heterodimeric ADAT2/ADAT3 enzyme responsible for inosine modifications in eukaryotes and in experimental capabilities for monitoring both the cytoplasmic tRNA pool and their modifications; (4) for selected tRNAs, inosine modification at position 37 has been demonstrated but this modification remains under-studied; (5) modification of tRNAs known to contain inosine can be incomplete; (6) the GC content of the T-stem is of great importance for wobble behavior, including wobbling behavior of inosine; and (7) the tRNA inosine modification is of direct relevance to human disease. In summary, research on inosine continues to yield important novel insights
‘Toxic’ memes: A survey of computational perspectives on the detection and explanation of meme toxicities
Get PDFInternet memes are multimodal, highly shareable cultural units that condense complex messages into compact forms of communication, making them a powerful vehicle for information spread. Increasingly, they are used to propagate hateful, extremist, or otherwise ‘toxic’ narratives, symbols, and messages. Research on computational methods for meme toxicity analysis has expanded significantly over the past five years. However, existing surveys cover only studies published until 2022, resulting in inconsistent terminology and overlooked trends. This survey bridges that gap by systematically reviewing content-based computational approaches to toxic meme analysis, incorporating key developments up to early 2024. Using the PRISMA methodology, we extend the scope of prior analyses, resulting in a threefold increase in the number of reviewed works. This study makes four key contributions. First, we expand the coverage of computational research on toxic memes, reviewing 158 content-based studies, including 119 newly analyzed papers, and identifying over 30 datasets while examining their labeling methodologies. Second, we address the lack of clear definitions of meme toxicity in computational research by introducing a new taxonomy that categorizes different toxicity types, providing a more structured foundation for future studies. Third, we observe that existing content-based studies implicitly focus on three key dimensions of meme toxicity—target, intent, and conveyance tactics. We formalize this perspective by introducing a structured framework that models how these dimensions are computationally analyzed across studies. Finally, we examine emerging trends and challenges, including advancements in cross-modal reasoning, the integration of expert and cultural knowledge, the increasing demand for automatic toxicity explanations, the challenges of handling meme toxicity in low-resource languages, and the rising role of generative AI in both analyzing and generating ‘toxic’ memes
Fault-tolerant structures for measurement-based quantum computation on a network
Get PDFIn this work, we introduce a method to construct fault-tolerant measurement-based quantum computation (MBQC) architectures and numerically estimate their performance over various types of networks. A possible application of such a paradigm is distributed quantum computation, where separate computing nodes work together on a fault-tolerant computation through entanglement. We gauge error thresholds of the architectures with an efficient stabilizer simulator to investigate the resilience against both circuit-level and network noise. We show that, for both monolithic (i.e., non-distributed) and distributed implementations, an architecture based on the diamond lattice may outperform the conventional cubic lattice. Moreover, the high erasure thresholds of non-cubic lattices may be exploited further in a distributed context, as their performance may be boosted through entanglement distillation by trading in entanglement success rates against erasure errors during the error-decoding process. These results highlight the significance of lattice geometry in the design of fault-tolerant measurement-based quantum computing on a network, emphasizing the potential for constructing robust and scalable distributed quantum computers
Towards a better understanding of misfit through explainable AI techniques
No full textThis chapter introduces explainable artificial intelligence (XAI) as a novel methodological approach for studying person–environment misfit. The authors argue that traditional methods often oversimplify misfit by assuming linear and symmetrical relationships, neglecting its complex and multifaceted nature. XAI techniques, by contrast, can model nonlinear, asymmetrical, and context-dependent effects, offering a richer understanding of how and why misfit occurs. The chapter demonstrates how XAI methods such as logistic regression, decision trees, gradient boosting, SHAP values, and counterfactual explanations can be used to detect patterns of calculated and perceived misfit. Using survey data on personal and organisational values, the authors show how XAI can identify which attributes most strongly predict misfit, when contextual variables such as tenure matter, and what small changes could transform a misfit into a fit. The chapter concludes that XAI offers an exploratory yet theoretically generative means of advancing misfit research by uncovering hidden interactions, boundary conditions, and unique individual experiences. By combining human reasoning with algorithmic insight, XAI enables a more precise and theory-informed understanding of misfit, providing new pathways for scholars to model complexity and for organisations to design interventions that reduce harmful misalignments