The Dynamics of Force Fluctuations in Shear Granular Flows

Tämän työn tavoitteena oli tutkia rakeisen materiaalin kinematiikkaa ja rakentaa koelaitteisto rakeisen materiaalin leikkausjännitysvirtauksien tutkimiseen. Kokeellisessa osassa on keskitytty sisäisiin voimaheilahteluihin ja niiden ymmärtämiseen. Teoriaosassa on käyty läpi rakeisen materiaalin yleisiä ominaisuuksia ja lisäksi on esitetty kaksi eri tapaa mallintaa fysikaalisien ominaisuuksien heilahteluja rakeisessa materiaalissa. Nämä kaksi esitettyä mallinnusmenetelmää ovat skalaarinen q-malli ja simulointi. Skalaarinen q-malli määrittelee jokaiseen yksittäiseen rakeeseen kohdistuvan jännityksen, rakeen ollessa osa 2- tai 3-dimensionaalista asetelmaa. Tämän mallin perusidea on kuvata jännityksien epähomogeenisuutta, joka johtuu rakeiden satunnaisasettelusta. Simulointimallinnus perustuu event-driven algoritmiin, missä systeemin dynamiikkaa kuvataan yksittäisillä partikkelien törmäyksillä. Törmäyksien vaiheet ratkaistiin käyttämällä liikemääräyhtälöitä ja restituution määritelmää. Teoriaosuudessa käytiin vielä pieniltä osin läpi syitä jännitysheilahteluihin ja rakeisen materiaalin lukkiintumiseen. Tutkimuslaitteistolla tutkittiin rakeisen materiaalin käyttäytymistä rengasmaisessa leikkausjännitysvirtauksessa. Tutkimusosuuden päätavoitteena oli mitata partikkelien kosketuksista ja törmäyksistä johtuvia hetkellisiä voimaheilahteluja rengastilavuuden pohjalta. Rakeisena materiaalina tutkimuksessa käytettiin teräskuulia. Jännityssignaali ajan funktiona osoittaa suurta heilahtelua, joka voi olla jopa kertalukua keskiarvosta suurempaa. Tällainen suuren amplitudin omaava heilahtelu on merkittävä haittapuoli yleisesti rakeisissa materiaaleissa käytettyjen jatkuvuusmallien kanssa. Tällainen heilahtelu tekee käytetyt jatkuvuusmallit epäpäteviksi. Yleisellä tasolla jännityksien todennäköisyysjakauma on yhtäpitävä skalaarisen q-mallin tuloksien kanssa. Molemmissa tapauksissa todennäköisyysjakaumalla on eksponentiaalinen muoto.

Dynamic and quasistatic trajectories in quasifission reactions and particle emission

We show that the quasifission paths predicted by the one-body dissipation dynamics, in the slowest phase of a binary reaction, follow a quasistatic path, which represents a sequence of states of thermal equilibrium at a fixed value of the deformation coordinate. This establishes the use of the statistical particle-evaporation model in the case of dynamical time-evolving systems. Pre- and post-scission multiplicities of neutrons and total multiplicities of protons and α particles in fission reactions of 63Cu+92Mo, 60Ni+100Mo, 63Cu+100Mo at 10 MeV/u and 20Ne+144,148,154Sm at 20 MeV/u are reproduced reasonably well with statistical model calculations performed along dynamic trajectories whose slow stage (from the most compact configuration up to the point where the neck starts to develop) lasts some 35×10−21 s.

A model for the evolution of reinforcement learning in fluctuating games

Many species are able to learn to associate behaviours with rewards as this gives fitness advantages in changing environments. Social interactions between population members may, however, require more cognitive abilities than simple trial-and-error learning, in particular the capacity to make accurate hypotheses about the material payoff consequences of alternative action combinations. It is unclear in this context whether natural selection necessarily favours individuals to use information about payoffs associated with nontried actions (hypothetical payoffs), as opposed to simple reinforcement of realized payoff. Here, we develop an evolutionary model in which individuals are genetically determined to use either trial-and-error learning or learning based on hypothetical reinforcements, and ask what is the evolutionarily stable learning rule under pairwise symmetric two-action stochastic repeated games played over the individual's lifetime. We analyse through stochastic approximation theory and simulations the learning dynamics on the behavioural timescale, and derive conditions where trial-and-error learning outcompetes hypothetical reinforcement learning on the evolutionary timescale. This occurs in particular under repeated cooperative interactions with the same partner. By contrast, we find that hypothetical reinforcement learners tend to be favoured under random interactions, but stable polymorphisms can also obtain where trial-and-error learners are maintained at a low frequency. We conclude that specific game structures can select for trial-and-error learning even in the absence of costs of cognition, which illustrates that cost-free increased cognition can be counterselected under social interactions.

Thomas-Fermi theory for atomic nuclei revisited

The recently developed semiclassical variational Wigner-Kirkwood (VWK) approach is applied to finite nuclei using external potentials and self-consistent mean fields derived from Skyrme inter-actions and from relativistic mean field theory. VWK consist s of the Thomas-Fermi part plus a pure, perturbative h 2 correction. In external potentials, VWK passes through the average of the quantal values of the accumulated level density and total en energy as a function of the Fermi energy. However, there is a problem of overbinding when the energy per particle is displayed as a function of the particle number. The situation is analyzed comparing spherical and deformed harmonic oscillator potentials. In the self-consistent case, we show for Skyrme forces that VWK binding energies are very close to those obtained from extended Thomas-Fermi functionals of h 4 order, pointing to the rapid convergence of the VWK theory. This satisfying result, however, does not cure the overbinding problem, i.e., the semiclassical energies show more binding than they should. This feature is more pronounced in the case of Skyrme forces than with the relativistic mean field approach. However, even in the latter case the shell correction energy for e.g.208 Pb turns out to be only ∼ −6 MeV what is about a factor two or three off the generally accepted value. As an adhoc remedy, increasing the kinetic energy by 2.5%, leads to shell correction energies well acceptable throughout the periodic table. The general importance of the present studies for other finite Fermi systems, self-bound or in external potentials, is pointed out.

Performance Analysis of Two Quantum Reaction Dynamics Codes: Time-Dependent and Time-Independent Strategies

The computer simulation of reaction dynamics has nowadays reached a remarkable degree of accuracy. Triatomic elementary reactions are rigorously studied with great detail on a straightforward basis using a considerable variety of Quantum Dynamics computational tools available to the scientific community. In our contribution we compare the performance of two quantum scattering codes in the computation of reaction cross sections of a triatomic benchmark reaction such as the gas phase reaction Ne + H2+ %12. NeH++ H. The computational codes are selected as representative of time-dependent (Real Wave Packet [ ]) and time-independent (ABC [ ]) methodologies. The main conclusion to be drawn from our study is that both strategies are, to a great extent, not competing but rather complementary. While time-dependent calculations advantages with respect to the energy range that can be covered in a single simulation, time-independent approaches offer much more detailed information from each single energy calculation. Further details such as the calculation of reactivity at very low collision energies or the computational effort related to account for the Coriolis couplings are analyzed in this paper.

Asymmetric stochastic switching driven by intrinsic molecular noise

Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

Particle shape and orientation in laser diffraction and static image analysis size distribution analysis of micrometer sized rectangular particles

Laser diffraction (LD) and static image analysis (SIA) of rectangular particles [United States Pharmacopeia, USP30-NF25, General Chapter <776>, Optical Miroscopy.] have been systematically studied. To rule out sample dispersion and particle orientation as the root cause of differences in size distribution profiles, we immobilize powder samples on a glass plate by means of a dry disperser. For a defined region of the glass plate, we measure the diffraction pattern as induced by the dispersed particles, and the 2D dimensions of the individual particles using LD and optical microscopy, respectively. We demonstrate a correlation between LD and SIA, with the scattering intensity of the individual particles as the dominant factor. In theory, the scattering intensity is related to the square of the projected area of both spherical and rectangular particles. In traditional LD the size distribution profile is dominated by the maximum projected area of the particles (A). The diffraction diameters of a rectangular particle with length L and breadth B as measured by the LD instrument approximately correspond to spheres of diameter ØL and ØB respectively. Differences in the scattering intensity between spherical and rectangular particles suggest that the contribution made to the overall LD volume probability distribution by each rectangular particle is proportional to A2/L and A2/B. Accordingly, for rectangular particles the scattering intensity weighted diffraction diameter (SIWDD) explains an overestimation of their shortest dimension and an underestimation of their longest dimension. This study analyzes various samples of particles whose length ranges from approximately 10 to 1000 μm. The correlation we demonstrate between LD and SIA can be used to improve validation of LD methods based on SIA data for a variety of pharmaceutical powders all with a different rectangular particle size and shape.

Evolutionary dynamics of collective action in spatially structured populations.

Many models proposed to study the evolution of collective action rely on a formalism that represents social interactions as n-player games between individuals adopting discrete actions such as cooperate and defect. Despite the importance of spatial structure in biological collective action, the analysis of n-player games games in spatially structured populations has so far proved elusive. We address this problem by considering mixed strategies and by integrating discrete-action n-player games into the direct fitness approach of social evolution theory. This allows to conveniently identify convergence stable strategies and to capture the effect of population structure by a single structure coefficient, namely, the pairwise (scaled) relatedness among interacting individuals. As an application, we use our mathematical framework to investigate collective action problems associated with the provision of three different kinds of collective goods, paradigmatic of a vast array of helping traits in nature: "public goods" (both providers and shirkers can use the good, e.g., alarm calls), "club goods" (only providers can use the good, e.g., participation in collective hunting), and "charity goods" (only shirkers can use the good, e.g., altruistic sacrifice). We show that relatedness promotes the evolution of collective action in different ways depending on the kind of collective good and its economies of scale. Our findings highlight the importance of explicitly accounting for relatedness, the kind of collective good, and the economies of scale in theoretical and empirical studies of the evolution of collective action.

A thematic analysis of delusion with religious content in schizophrenia: open, closed, and mixed dynamics

The aim of the present study was to elicit how patients with delusions with religious contents conceptualized or experienced their spirituality and religiousness. Sixty-two patients with present or past religious delusions went through semistructured interviews, which were analyzed using the three coding steps described in the grounded theory. Three major themes were found in religious delusions: ''spiritual identity,'' ''meaning of illness,'' and ''spiritual figures.'' One higher-order concept was found: ''structure of beliefs.'' We identified dynamics that put these personal beliefs into a constant reconstruction through interaction with the world and others (i.e., open dynamics) and conversely structural dynamics that created a complete rupture with the surrounding world and others (i.e., closed structural dynamics); those dynamics may coexist. These analyses may help to identify psychological functions of delusions with religious content and, therefore, to better conceptualize interventions when dealing with it in psychotherapy.

What can ecosystems learn? Expanding evolutionary ecology with learning theory.

BACKGROUND: The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole? RESULTS: Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, 'unsupervised learning', well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community's response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts. CONCLUSIONS: This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions. REVIEWERS: This article was reviewed by Prof. Ricard V Solé, Universitat Pompeu Fabra, Barcelona and Prof. Rob Knight, University of Colorado, Boulder.

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns.

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs-locomotor bouts-matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior.

Minimum-uncertaity states and pseudoclassical dynamics. II

The set of initial conditions for which the pseudoclassical evolution algorithm (and minimality conservation) is verified for Hamiltonians of degrees N (N>2) is explicitly determined through a class of restrictions for the corresponding classical trajectories, and it is proved to be at most denumerable. Thus these algorithms are verified if and only if the system is quadratic except for a set of measure zero. The possibility of time-dependent a-equivalence classes is studied and its physical interpretation is presented. The implied equivalence of the pseudoclassical and Ehrenfest algorithms and their relationship with minimality conservation is discussed in detail. Also, the explicit derivation of the general unitary operator which linearly transforms minimum-uncertainty states leads to the derivation, among others, of operators with a general geometrical interpretation in phase space, such as rotations (parity, Fourier).

Small and Large Scale Dynamics in the Milky Way

This thesis contains dynamical analysis on four different scales: the Solar system, the Sun itself, the Solar neighbourhood, and the central region of the Milky Way galaxy. All of these topics have been handled through methods of potential theory and statistics. The central topic of the thesis is the orbits of stars in the Milky Way. An introduction into the general structure of the Milky Way is presented, with an emphasis on the evolution of the observed value for the scale-length of the Milky Way disc and the observations of two separate bars in the Milky Way. The basics of potential theory are also presented, as well as a developed potential model for the Milky Way. An implementation of the backwards restricted integration method is shown, rounding off the basic principles used in the dynamical studies of this thesis. The thesis looks at the orbit of the Sun, and its impact on the Oort cloud comets (Paper IV), showing that there is a clear link between these two dynamical systems. The statistical atypicalness of the orbit of the Sun is questioned (Paper I), concluding that there is some statistical typicalness to the orbit of the Sun, although it is not very significant. This does depend slightly on whether one includes a bar, or not, as a bar has a clear effect on the dynamical features seen in the Solar neighbourhood (Paper III). This method can be used to find the possible properties of a bar. Finally, we look at the effect of a bar on a statistical system in the Milky Way, seeing that there are not only interesting effects depending on the mass and size of the bar, but also how bars can capture disc stars (Paper II).

Innovations of ageing and societal transition : Dynamics of change of the socio-technical regime of ageing

The purpose of this dissertation is to examine the dynamics of the socio-technical system in the field of ageing. The study stems from the notion that the ageing of the population as a powerful megatrend has wide societal effects, and is not just a matter for the social and health sector. The central topic in the study is change: not only the age structures and structures of society are changing, but also at the same time there is constant development, for instance, in technologies, infrastructures and cultural perceptions. The changing concept of innovation has widened the understanding of innovations related to ageing from medical and assistive technological innovations to service and social innovations, as well as systemic innovations at different levels, which means the intertwined and co-evolutionary change in technologies, structures, services and thinking models. By the same token, the perceptions of older people and old age are becoming more multi-faceted: old age is no longer equated to illnesses and decline, but visions of active ageing and a third age have emerged, which are framed by choices, opportunities, resources and consumption in later life. The research task in this study is to open up the processes and mechanisms of change in the field of ageing, which are studied as a complex, multi-level and interrelated socio-technical system. The question is about co-effective elements consisting of macro-level landscape changes, the existing socio-technical regime (the rule system, practices and structures) and bottom-up niche-innovations. Societal transitions do not account for the things inside the regime alone, or for the long-term changes in the landscape, nor for the radical innovations, but for the interplay between all these levels. The research problem is studied through five research articles, which offer micro-level case studies to macro-level phenomenon. Each of the articles focus on different aspects related to ageing and change, and utilise various datasets. The framework of this study leans on the studies of socio-technical systems and multi-level perspective on transitions mainly developed by Frank Geels. Essential factors in transition from one socio-technological regime to another are the co-evolutionary processes between landscape changes, regime level and experimental niches. Landscape level changes, like the ageing of the population, destabilise the regime in the forms of coming pressures. This destabilization offers windows for opportunity to niche-innovations outside or at fringe of the regime, which, through their breakthrough, accelerate the transition process. However, the change is not easy because of various kinds of lock-ins and inertia, which tend to maintain the stability of the regime. In this dissertation, a constructionist approach of society is applied leaning mainly to the ideas of Anthony Giddens’ theory of structuration, with the dual nature of structures. The change is taking place in the interplay between actors and structures: structures shape people’s practices, but at the same time these practices constitute and reproduce social systems. Technology and other material aspects, as part of socio-technical systems, and the use of them, also take part in the structuration process. The findings of the study point out that co-evolutionary and co-effective relationships between economic, cultural, technological and institutional fields, as well as relationships between landscape changes, changes in the local and regime-level practices and rule systems, are a very complex and multi-level dynamic socio-technical phenomenon. At the landscape level of ageing, which creates the pressures and triggers to the regime change, there are three remarkable megatrends: demographic change, changes in the global economy and the development of technologies. These exert pressures to the socio-technical regime, which as a rule system is experiencing changes in the form of new markets and consumer habits, new ways of perceiving ageing, new models of organising the health care and other services and as new ways of considering innovation and innovativeness. There are also inner dynamics in the relationships between these aspects within the regime. These are interrelated and coconstructed: the prevailing perceptions of ageing and innovation, for instance, reflect the ageing policies, innovation policies, societal structures, organising models, technology and scientific discussion, and vice versa. Technology is part of the inner dynamics of the sociotechnological regime. Physical properties of the artefacts set limitations and opportunities with regard to their functions and uses. The use of and discussion about technology, contributes producing and reproducing the perceptions of old age. For societal transition, micro-level changes are also needed, in form of niche-innovations, for instance new services, organisational models or new technologies, Regimes, as stabilitystriven systems, tend to generate incremental innovations, but radically new innovations are generated in experimental niches protected from ‘normal’ market selection. The windows of opportunity for radical novelties may be opened if the circumstances are favourable for instance by tensions in the socio-technical regime affected by landscape level changes. This dissertation indicates that a change is taking place, firstly, in the dynamic interactionbetween levels, as a result of purposive action and governance to some extent. Breaking the inertia and using the window of opportunity for change and innovation offered by dynamics between levels, presupposes the actors’ special capabilities and actions such as dynamic capabilities and distance management. Secondly, the change is taking place the socio-technological negotiations inside the regime: interaction between technological and social, which is embodied in the use of technology. The use of technology includes small-level contextual scripts that also participate in forming broader societal scripts (for instance defining old age at the society level), which in their turn affect the formation of policies for innovation and ageing. Thirdly, the change is taking place by the means of active formation of the multi-actor innovation networks, where the role of distance management is crucial to facilitate the communication between actors coming from different backgrounds as well as to help the niches born outside the regime to utilise the window of opportunity offered by regime destabilisation. This dissertation has both theoretical and practical contributions. This study participates in the discussion of action-oriented view on transition by opening up of the socio-technological, coevolutionary processes of the multi-faceted phenomenon of ageing, which has lacked systematic analyses. The focus of this study, however, is not on the large-scale coordination and governance, but rather on opening up the incremental elements and structuration processes, which contribute to the transition little by little, and which can be affected to. This increases the practical importance of this dissertation, by highlighting the importance of very tiny, everyday elements in the change processes in the long run.