Mammalian Brain As a Network of Networks

Acknowledgements AZ, SG and AL acknowledge support from the Russian Science Foundation (16-12-00077). Authors thank T. Kuznetsova for Fig. 6.Peer reviewedPublisher PD

Is the Cell Really a Machine?

It has become customary to conceptualize the living cell as an intricate piece of machinery, different to a man-made machine only in terms of its superior complexity. This familiar understanding grounds the conviction that a cell's organization can be explained reductionistically, as well as the idea that its molecular pathways can be construed as deterministic circuits. The machine conception of the cell owes a great deal of its success to the methods traditionally used in molecular biology. However, the recent introduction of novel experimental techniques capable of tracking individual molecules within cells in real time is leading to the rapid accumulation of data that are inconsistent with an engineering view of the cell. This paper examines four major domains of current research in which the challenges to the machine conception of the cell are particularly pronounced: cellular architecture, protein complexes, intracellular transport, and cellular behaviour. It argues that a new theoretical understanding of the cell is emerging from the study of these phenomena which emphasizes the dynamic, self-organizing nature of its constitution, the fluidity and plasticity of its components, and the stochasticity and non-linearity of its underlying processes

Analysis and synthesis techniques of nonlinear dynamical systems with applications to diagnostic of controlled thermonuclear fusion reactors

Nonlinear dynamical systems are of wide interest to engineers, physicists and mathematicians, and this is due to the fact that most of physical systems in nature are inherently non-linear. The nonlinearity of these systems has consequences on their time-evolution, which in some cases can be completely unpredictable, apparently random, although fundamentally deterministic. Chaotic systems are striking examples of this. In most cases, there are no hard and fast rules to analyse these systems. Often, their solutions cannot be obtained in closed form, and it is necessary to resort to numerical integration techniques, which, in case of high sensitivity to initial conditions, lead to ill-conditioning problems and high computational costs. The dynamical system theory, the branch of mathematics used to describe the behaviour of these systems, focuses not on finding exact solutions to the equations describing the dynamical system, but rather on knowing if the system stabilises to a steady state in the long term, and what are the possible attractors, e.g. a quasi-periodic or chaotic attractors. Regarding the synthesis, from both a practical and a theoretical standpoint, it is very desirable to develop methods of synthesizing these systems. Although extensive theory has been developed for linear systems, no complete formulation for nonlinear systems synthesis is present today. The main topic of this thesis is the solution of engineering problems related to the analysis and synthesis of nonlinear and chaotic systems. In particular, a new algorithm which optimizes Lyapunov exponents estimation in piecewise linear systems has been applied to PWL and polynomial chaotic systems. In the field of complex systems synthesis, a systematic method to project systems of order 2n characterized by two positive Lyapunov exponents, has been proposed. This procedure couples nth-order chaotic systems with a suitable nonlinear coupling function. Furthermore, a method for the fault detection has been developed. In the field of time series analysis, a new denoising method, based on the wavelet transform of the noisy signal, has been described. The method implements a variable thresholding, whose optimal value is determined by analysing the cross-correlation between the denoised signal and the residuals and by applying different criteria depending on the particular decomposition level. Finally, a study of dynamical behaviour of Type I ELMs has been performed for a future modelization of the phenomenon. In this context, a statistical analysis of time intervals between successive Type I ELMs has been proposed.---------------------------------- Il tema principale di questa tesi è la soluzione di problemi ingegneristici legati all’analisi e alla sintesi di sistemi dinamici non lineari. I sistemi dinamici non lineari sono di largo interesse per ingegneri, fisici e matematici, e questo è dovuto al fatto che la maggior parte dei sistemi fisici in natura è intrinsecamente non lineare. La non linearità di questi sistemi ha conseguenze sulla loro evoluzione temporale, che in certi casi può rivelarsi del tutto imprevedibile, apparentemente casuale, seppure fondamentalmente deterministica. I sistemi caotici sono un esempio lampante di questo comportamento. Nella maggior parte dei casi non esistono delle regole standard per l’analisi di questi sistemi. Spesso, le soluzioni non possono essere ottenute in forma chiusa, ed è necessario ricorrere a tecniche di integrazione numerica, che, in caso di elevata sensibilità alle condizioni iniziali, portano a problemi di mal condizionamento e di elevato costo computazionale. La teoria dei sistemi dinamici, la branca della matematica usata per descrivere il comportamento di questi sistemi, non si concentra sulla ricerca di soluzioni esatte per le equazioni che descrivono il sistema dinamico, ma piuttosto sull’analisi del comportamento a lungo termine del sistema, per sapere se questo si stabilizzi in uno stato stabile e per sapere quali siano i possibili attrattori, ad esempio, attrattori quasi-periodici o caotici. Per quanto riguarda la sintesi, sia da un punto di vista pratico che teorico, è molto importante lo sviluppo di metodi in grado di sintetizzare questi sistemi. Sebbene per i sistemi lineari sia stata sviluppata una teoria ampia e esaustiva, al momento non esiste alcuna formulazione completa per la sintesi di sistemi non lineari. In questa tesi saranno affrontati problemi di caratterizzazione, analisi e sintesi, legati allo studio di sistemi non lineari e caotici. La caratterizzazione dinamica di un sistema non lineare permette di individuarne il comportamento qualitativo a lungo termine. Gli esponenti di Lyapunov sono degli strumenti che permettono di determinare il comportamento asintotico di un sistema dinamico. Essi danno informazioni circa il tasso di divergenza di traiettorie vicine, caratteristica chiave delle dinamiche caotiche. Le tecniche esistenti per il calcolo degli esponenti di Lyapunov sono computazionalmente costose, e questo fatto ha in qualche modo precluso l’uso estensivo di questi strumenti in problemi di grandi dimensioni. Inoltre, durante il calcolo degli esponenti sorgono dei problemi di tipo numerico, per ciò il calcolo deve essere affrontato con cautela. L’implementazione di algoritmi veloci e accurati per il calcolo degli esponenti di Lyapunov è un problema di interesse attuale. In molti casi pratici il vettore di stato del sistema non è disponibile, e una serie temporale rappresenta l’unica informazione a disposizione. L’analisi di serie storiche è un metodo di analisi dei dati provenienti da serie temporali che ha lo scopo di estrarre delle statistiche significative e altre caratteristiche dei dati, e di ottenere una comprensione della struttura e dei fattori fondamentali che hanno prodotto i dati osservati. Per esempio, un problema dei reattori a fusione termonucleare controllata è l’analisi di serie storiche della radiazione Dα, caratteristica del fenomeno chiamato Edge Localized Modes (ELMs). La comprensione e il 16 controllo degli ELMs sono problemi cruciali per il funzionamento di ITER, in cui il type-I ELMy H-mode è stato scelto come scenario di funzionamento standard. Determinare se la dinamica degli ELM sia caotica o casuale è cruciale per la corretta descrizione dell’ELM cycle. La caratterizzazione dinamica effettuata sulle serie temporali ricorrendo al cosiddetto spazio di embedding, può essere utilizzata per distinguere serie random da serie caotiche. Uno dei problemi più frequenti che si incontra nell’analisi di serie storiche sperimentali è la presenza di rumore, che in alcuni casi può raggiungere anche il 10% o il 20% del segnale. È quindi essenziale , prima di ogni analisi, sviluppare una tecnica appropriata e robusta per il denosing. Quando il modello del sistema è noto, l’analisi di serie storiche può essere applicata al rilevamento di guasti. Questo problema può essere formalizzato come un problema di identificazione dei parametri. In questi casi, la teorie dell’algebra differenziale fornisce utili informazioni circa la natura dei rapporti fra l’osservabile scalare, le variabili di stato e gli altri parametri del sistema. La sintesi di sistemi caotici è un problema fondamentale e interessante. Questi sistemi non implicano soltanto un metodo di realizzazione di modelli matematici esistenti ma anche di importanti sistemi fisici reali. La maggior parte dei metodi presentati in letteratura dimostra numericamente la presenza di dinamiche caotiche, per mezzo del calcolo degli esponenti di Lyapunov. In particolare, le dinamiche ipercaotiche sono identificate dalla presenza di due esponenti di Lyapunov positivi

Computational Design of Synthetic Microbial Communities

In naturally occurring microbial systems, species rarely exist in isolation. There is strong ecological evidence for a positive relationship between species diversity and the functional output of communities. The pervasiveness of these communities in nature highlights that there may be advantages for engineered strains to exist in cocultures as well. Building synthetic microbial communities allows us to create distributed systems that mitigate issues often found in engineering a monoculture, especially when functional complexity is increasing. The establishment of synthetic microbial communities is a major challenge we must overcome in order to implement coordinated multicellular systems. Here I present computational tools that help us design engineering strategies for establishing synthetic microbial communities. Using these tools I identify promising candidates for several design scenarios. This work highlights the importance of parameter inference and model selection to build robust communities. The findings highlight important interaction motifs that provide stability, and identify requirements for selecting genetic parts and tuning the community composition. Additionally, I show that fundamental interactions in small synthetic communities can produce chaotic behaviour that is unforecastable. Together these findings have important ramifications for how we build synthetic communities in the lab, and the considerations of interactions in microbiomes we manipulate

Is the astronomical forcing a reliable and unique pacemaker for climate? A conceptual model study

There is evidence that ice age cycles are paced by astronomical forcing, suggesting some kind of synchronisation phenomenon. Here, we identify the type of such synchronisation and explore systematically its uniqueness and robustness using a simple paleoclimate model akin to the van der Pol relaxation oscillator and dynamical system theory. As the insolation is quite a complex quasiperiodic signal involving different frequencies, the traditional concepts used to define synchronisation to periodic forcing are no longer applicable. Instead, we explore a different concept of generalised synchronisation in terms of (coexisting) synchronised solutions for the forced system, their basins of attraction and instabilities. We propose a clustering technique to compute the number of synchronised solutions, each of which corresponds to a different paleoclimate history. In this way, we uncover multistable synchronisation (reminiscent of phase- or frequency-locking to individual periodic components of astronomical forcing) at low forcing strength, and monostable or unique synchronisation at stronger forcing. In the multistable regime, different initial conditions may lead to different paleoclimate histories. To study their robustness, we analyse Lyapunov exponents that quantify the rate of convergence towards each synchronised solution (local stability), and basins of attraction that indicate critical levels of external perturbations (global stability). We find that even though synchronised solutions are stable on a long term, there exist short episodes of desynchronisation where nearby climate trajectories diverge temporarily (for about 50 kyr). (...)Comment: 22 pages, 18 figure

Surface nanopatterning by ion beam irradiation: compositional effects

Surface nanopatterning induced by ion beam irradiation (IBI) has emerged as an effective nanostructuring technique since it induces patterns on large areas of a wide variety of materials, in short time, and at low cost. Nowadays, two main subfields can be distinguished within IBI nanopatterning depending on the irrelevant or relevant role played by the surface composition. In this review, we give an up-dated account of the progress reached when surface composition plays a relevant role, with a main focus on IBI surface patterning with simultaneous co-deposition of foreign atoms. In addition, we also review the advances in IBI of compound surfaces as well as IBI systems where the ion employed is not a noble gas species. In particular, for the IBI with concurrent metal co-deposition, we detail the chronological evolution of these studies because it helps us to clarify some contradictory early reports. We describe the main patterns obtained with this technique as a function of the foreign atom deposition pathway, also focusing in those systematic studies that have contributed to identify the main mechanisms leading to the surface pattern formation and development. Likewise, we explain the main theoretical models aimed at describing these nanopattern formation processes. Finally, we address two main special features of the patterns induced by this technique, namely, the enhanced pattern ordering and the possibility to produce both morphological and chemical patterns.This work was supported by Ministerio de Economía, Industria y Competitividad (MINECO, Spain), Agencia Estatal de Investigación (AEI, Spain), and Fondo Europeo de Desarrollo Regional (FEDER, EU) through Grant No. PGC2018-094763-B-I00, and by Comunidad de Madrid (Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors, No. EPUC3M23, in the context of the V Plan Regional de Investigación Científica e Innovación Tecnológica (PRICIT), as well as under the TRANSNANOAVANSENS program (S2018-NMT-4349)

In-situ synchrotron X-ray imaging and tomography studies of the evolution of solidification microstructures under pulse electromagnetic fields

This research studies the dynamic evolution of dendritic structures and intermetallic phases of four Al based alloys during the solidification under pulse electromagnetic fields (PMFs). An advanced PMF solidification device was upgraded, built, commissioned for the research. The alloys used were Al-15Cu, Al-35Cu, Al-15Ni and Al-5Cu-1.5Fe-1Si. Systematic in-situ and real-time observation and studies were carried out at the TOMCAT beamline of Swiss Light Source, I13-2 beamline of Diamond Light Source and ID19 beamline of European Synchrotron Radiation Facility in the duration of this project. Synchrotron X-ray radiography and tomography were used primarily to observe and study the influence of PMFs on the nucleation and growth of primary dendritic structures and intermetallic phases under different magnetic flux and solidification conditions for the four alloys. More than 20 TB images and tomography datasets have been obtained throughout this research. Much effort and time was spent on segmenting, visualising and analysing these huge datasets using the Hull University supercomputer cluster, Viper, and the software, Avizo, ImageJ (Fiji), etc to explore and extract new insights and new science from those datasets. In particular, the skeletonisation function available from Avizo was customised and used to quantify the complex 3D microstructures and interconnected networks of different phases for the alloys. The important new findings of the research are:(1) Fragmentation of primary Al dendrites in the Al-15%Cu alloy was found when the magnetic flux of PMF applied is above 0.75 T; similarly, the fragmentation of Al3Ni intermetallic phases in the Al-15%Ni alloy was also observed when the magnetic flux of PMF applied is above 0.8 T. The clear and real-time observation of the fragmentation events in both dendritic and intermetallic phases provide unambiguous evidence to demonstrate that PMFs play a dominant role in structure fragmentation and multiplication, which is one important mechanism for structure (grain) refinement.(2) PMFs also produces pinch pressure gradient inside the semi-solid melt. Due to the different magnetic anisotropic properties between the liquid and solid phases, shear stresses due to the pinch pressure gradient may be produced. In the case of Al-15%Ni alloy, shear stresses of up to 30 MPa is created, which is sufficient to fracture Al3Ni phases. For the first time, such fragmentation mechanism for the Al3Ni phases in the Al-15%Ni alloy was revealed in this research.(3) The transition (or change of growth modes) of Al columnar dendrites to seaweed type dendrites in Al-15Cu alloy; and the facet growth to dendritic growth of the Al3Ni phases in the Al-15%Ni alloy were also observed in real-time when the magnetic flux is in the range of 0.75~0.8 T. Again, such dynamic changes in structure growth under PMFs are due to the enhanced melt flow caused by the applied fields.(4) In-situ tomography observation of PMF processing of the Al-5Cu-1.5Fe-1Si alloy also shows the effect of PMF on the refinement of the Chinese script type Fe intermetallic phases. In addition, the true 3D morphologies of three different types of Fe intermetallic phases in this alloy were clarified, again for the first time, in this research

4D quantifications of intermetallics in solidifying aluminium alloys

High-speed synchrotron X-ray tomography was used to investigate the growth dynamics and mechanisms of faceted intermetallic compounds (IMCs) in aluminium alloys under different solidification conditions (temperature gradients, cooling rates and external magnetic field). Different IMCs in four aluminium alloys are studied including Al13Fe4 in Al-5wt%Fe alloys, Al2Cu in Al-45wt%Cu alloys, Al3Ni in Al-10wt%Ni alloy and β-IMCs in W319 (Al-Si-Cu) based alloys. 4D quantifications (3D plus time) were achieved in determining the nucleation rates, nucleation densities, volume fractions and growth velocities of Al$_{13}$Fe$_4$ IMCs with various faceted morphologies. In both Al-45wt%Cu and Al-10wt%Ni, two stages of the formation processes were identified including the growth of the basic unit and the growth of the faceted dendrite. The transition of various morphologies of the basic unit was observed and the relationship between these morphologies was determined. The growth mechanism of the faceted dendrite was proposed to be self-repeated layer-by-layer stacking of the basic units (such as L-shaped in Al$_2$Cu or V-shaped in Al$_3$Ni). In addition, the work studied the effect of magnetic fields on solidification in Al-45wt%Cu and W319 alloys. A transverse magnetic field of 0.5T was used to control the solidification processes while the sample was rotating. Highly refined Al$_2$Cu intermetallic compounds were obtained including the in Al-45wt%Cu alloys which were much finer than those without the imposition of the magnetic field. Under the magnetic field, fine α-Al dendrite with smaller primary dendrite arm spacing in W319 alloys was obtained. The macro segregation zone was almost eliminated, while the solid/liquid interface was altered from tilted to flat. Gradient volume distribution of the secondary β-IMCs was observed. This work first reveals the growth mechanisms of different faceted IMCs with various morphologies. It also demonstrates that rotating the sample under a transversal magnetic field is a simple yet effective method of controlling the morphologies and volume distribution of crystals via altering the temperature and composition profiles in the melt