Rate-induced tipping from periodic attractors: partial tipping and connecting orbits

This is the author accepted manuscript. The final version is available from AIP Publishing via the DOI in this recordWe consider how breakdown of the quasistatic approximation for attractors can lead to rate-dependent tipping, where a qualitative change in tracking/tipping behaviour of trajectories can be characterised in terms of a critical rate. Associated with rate-dependent tipping (where tracking of a branch of quasistatic attractors breaks down) we find a new phenomenon for attractors that are not simply equilibria: partial tipping of the pullback attractor where certain phases of the periodic attractor tip and others track the quasistatic attractor. For a specific model system with a parameter shift between two asymptotically autonomous systems with periodic attractors we characterise thresholds of rate-dependent tipping to partial and total tipping. We show these thresholds can be found in terms of certain periodic-to-periodic (PtoP) and periodic-to-equilibrium (PtoE) connections that we determine using Lin's method for an augmented system.HA’s research is funded by the Higher Committee For Education Development in Iraq (HCED Iraq) grant agreement No D13436. PA’s research is partially supported by the CRITICS Innovative Training Network, funded by the European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 643073

Autism and the transition to university from the student perspective

University provides individuals with the opportunity to develop greater independence in living skills and social networks, while also gaining valuable qualifications. Despite a high proportion of autistic individuals aspiring to attend university, many either do not seek or gain entry or drop out prematurely. Although some steps have been taken to develop effective support, a recent review highlighted the scarcity of research into programmes designed to support autistic students transitioning to university. In addition, few studies have examined the views of autistic students themselves. This study investigated the perspectives of autistic students transitioning to university. Three focus groups were conducted with 25 autistic students preparing to start university. Participants were asked about their hopes for starting university, as well as their worries and concerns. Data were analysed using thematic analysis, from which five main themes were identified: The Social World, Academic Demands, Practicalities of University Living, Leaving the Scaffolding of Home and Transition to Adulthood. The results provide an important account of the challenges autistic students face when transitioning to university, as well as their aspirations. These findings have a number of practical implications

State of the world's birds

We present an overview of the global spatiotemporal distribution of avian biodiversity, changes in our knowledge of that biodiversity, and the extent to which it is imperilled. Birds are probably the most completely inventoried large taxonomic class of organisms, permitting a uniquely detailed understanding of how the Anthropocene has shaped their distributions and conservation status in space and time. We summarize the threats driving changes in bird species richness and abundance, highlighting the increasingly synergistic interactions between threats such as habitat loss, climate change, and overexploitation. Many metrics of avian biodiversity are exhibiting globally consistent negative trends, with the International Union for Conservation of Nature's Red List Index showing a steady deterioration in the conservation status of the global avifauna over the past three decades. We identify key measures to counter this loss of avian biodiversity and associated ecosystem services, which will necessitate increased consideration of the social context of bird conservation interventions in order to deliver positive transformative change for nature

Oscillating systems with cointegrated phase processes

We present cointegration analysis as a method to infer the network structure of a linearly phase coupled oscillating system. By defining a class of oscillating systems with interacting phases, we derive a data generating process where we can specify the coupling structure of a network that resembles biological processes. In particular we study a network of Winfree oscillators, for which we present a statistical analysis of various simulated networks, where we conclude on the coupling structure: the direction of feedback in the phase processes and proportional coupling strength between individual components of the system. We show that we can correctly classify the network structure for such a system by cointegration analysis, for various types of coupling, including uni-/bi-directional and all-to-all coupling. Finally, we analyze a set of EEG recordings and discuss the current applicability of cointegration analysis in the field of neuroscience.</p

Root Canal Anatomy of Maxillary and Mandibular Teeth

It is a common knowledge that a comprehensive understanding of the complexity of the internal anatomy of teeth is imperative to ensure successful root canal treatment. The significance of canal anatomy has been emphasized by studies demonstrating that variations in canal geometry before cleaning, shaping, and obturation procedures had a greater effect on the outcome than the techniques themselves. In recent years, significant technological advances for imaging teeth, such as CBCT and micro-CT, respectively, have been introduced. Their noninvasive nature allows to perform in vivo anatomical studies using large populations to address the influence of several variables such as ethnicity, aging, gender, and others, on the root canal anatomy, as well as to evaluate, quantitatively and/or qualitatively, specific and fine anatomical features of a tooth group. The purpose of this chapter is to summarize the morphological aspects of the root canal anatomy published in the literature of all groups of teeth and illustrate with three-dimensional images acquired from micro-CT technology.info:eu-repo/semantics/publishedVersio

Analysis of a bistable climate toy model with physics-based machine learning methods

We propose a comprehensive framework able to address both the predictability of the first and of the second kind for high-dimensional chaotic models. For this purpose, we analyse the properties of a newly introduced multistable climate toy model constructed by coupling the Lorenz ’96 model with a zero-dimensional energy balance model. First, the attractors of the system are identified with Monte Carlo Basin Bifurcation Analysis. Additionally, we are able to detect the Melancholia state separating the two attractors. Then, Neural Ordinary Differential Equations are applied to predict the future state of the system in both of the identified attractors