790 research outputs found
Language Design for Reactive Systems: On Modal Models, Time, and Object Orientation in Lingua Franca and SCCharts
Reactive systems play a crucial role in the embedded domain. They continuously interact with their environment, handle concurrent operations, and are commonly expected to provide deterministic behavior to enable application in safety-critical systems. In this context, language design is a key aspect, since carefully tailored language constructs can aid in addressing the challenges faced in this domain, as illustrated by the various concurrency models that prevent the known pitfalls of regular threads. Today, many languages exist in this domain and often provide unique characteristics that make them specifically fit for certain use cases. This thesis evolves around two distinctive languages: the actor-oriented polyglot coordination language Lingua Franca and the synchronous statecharts dialect SCCharts. While they take different approaches in providing reactive modeling capabilities, they share clear similarities in their semantics and complement each other in design principles. This thesis analyzes and compares key design aspects in the context of these two languages. For three particularly relevant concepts, it provides and evaluates lean and seamless language extensions that are carefully aligned with the fundamental principles of the underlying language. Specifically, Lingua Franca is extended toward coordinating modal behavior, while SCCharts receives a timed automaton notation with an efficient execution model using dynamic ticks and an extension toward the object-oriented modeling paradigm
Evaluating Architectural Safeguards for Uncertain AI Black-Box Components
Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Brain Computations and Connectivity [2nd edition]
This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read on the Oxford Academic platform and offered as a free PDF download from OUP and selected open access locations.
Brain Computations and Connectivity is about how the brain works. In order to understand this, it is essential to know what is computed by different brain systems; and how the computations are performed.
The aim of this book is to elucidate what is computed in different brain systems; and to describe current biologically plausible computational approaches and models of how each of these brain systems computes.
Understanding the brain in this way has enormous potential for understanding ourselves better in health and in disease. Potential applications of this understanding are to the treatment of the brain in disease; and to artificial intelligence which will benefit from knowledge of how the brain performs many of its extraordinarily impressive functions.
This book is pioneering in taking this approach to brain function: to consider what is computed by many of our brain systems; and how it is computed, and updates by much new evidence including the connectivity of the human brain the earlier book: Rolls (2021) Brain Computations: What and How, Oxford University Press.
Brain Computations and Connectivity will be of interest to all scientists interested in brain function and how the brain works, whether they are from neuroscience, or from medical sciences including neurology and psychiatry, or from the area of computational science including machine learning and artificial intelligence, or from areas such as theoretical physics
Evolution from the ground up with Amee – From basic concepts to explorative modeling
Evolutionary theory has been the foundation of biological research for about a century
now, yet over the past few decades, new discoveries and theoretical advances have rapidly
transformed our understanding of the evolutionary process. Foremost among them are
evolutionary developmental biology, epigenetic inheritance, and various forms of evolu-
tionarily relevant phenotypic plasticity, as well as cultural evolution, which ultimately led
to the conceptualization of an extended evolutionary synthesis. Starting from abstract
principles rooted in complexity theory, this thesis aims to provide a unified conceptual
understanding of any kind of evolution, biological or otherwise. This is used in the second
part to develop Amee, an agent-based model that unifies development, niche construction,
and phenotypic plasticity with natural selection based on a simulated ecology. Amee
is implemented in Utopia, which allows performant, integrated implementation and
simulation of arbitrary agent-based models. A phenomenological overview over Amee’s
capabilities is provided, ranging from the evolution of ecospecies down to the evolution
of metabolic networks and up to beyond-species-level biological organization, all of
which emerges autonomously from the basic dynamics. The interaction of development,
plasticity, and niche construction has been investigated, and it has been shown that while
expected natural phenomena can, in principle, arise, the accessible simulation time and
system size are too small to produce natural evo-devo phenomena and –structures. Amee thus can be used to simulate the evolution of a wide variety of processes
Jornadas Nacionales de Investigación en Ciberseguridad: actas de las VIII Jornadas Nacionales de Investigación en ciberseguridad: Vigo, 21 a 23 de junio de 2023
Jornadas Nacionales de Investigación en Ciberseguridad (8ª. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernización tecnolóxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida
Recommended from our members
Dissecting the biological content of host and parasite-derived extracellular vesicles in malaria
Plasmodium falciparum causes the deadliest form of malaria, especially in African children under five years. The parasite and its human host secrete small nanoparticles called extracellular vesicles (EVs) into their extracellular milieu. EVs contain bioactive molecules such as RNA and proteins reflecting that in the secreting cells. However, the biological contents of EVs are not well-characterized in the context of falciparum malaria. EVs are attractive sources of non-invasive biomarkers for diseases affecting inaccessible tissues such as the brain. Analysing the biological content of EVs will provide insights into their functions and could illuminate pathophysiological mechanisms of severe malaria syndromes, including cerebral malaria, respiratory distress, and severe malaria anaemia.
The first part of this thesis aimed to investigate the biological benefit of EVs to the secreting parasite. To achieve this purpose, I sequenced four-hourly RNA samples obtained from EVs secreted by six P. falciparum isolates and compared them to the RNA within the secreting whole parasites. The data suggest parasite-derived EVs might be part of a post-transcriptional gene regulatory mechanism that maintains RNA homeostasis in P. falciparum. The second part of this thesis aimed to understand the pathophysiology of severe malaria complications. To this purpose, I quantified the protein and RNA content of plasma EVs obtained from acute malaria patients. I developed temporal models of disease progression by applying manifold learning to the cross-sectionally collected EV samples. In a parallel approach, I used plasma EV transcriptomes to develop a pseudo-temporal model of cerebral malaria. I determined that cerebral malaria might feature a progressive decrease in neural gene expression and an increase in glial gene expression, which can be followed using peripheral blood EVs. I conclude that EVs are treasure troves of biomarkers that can be used to eavesdrop on biological mechanisms in P. falciparum and its human host
- …