Microscopic theory of cooperative spin crossover: Interaction of molecular modes with phonons

In this article, we present a new microscopic theoretical approach to the description of spin crossover in molecular crystals. The spin crossover crystals under consideration are composed of molecular fragments formed by the spin-crossover metal ion and its nearest ligand surrounding and exhibiting well defined localized (molecular) vibrations. As distinguished from the previous models of this phenomenon, the developed approach takes into account the interaction of spin-crossover ions not only with the phonons but also a strong coupling of the electronic shells with molecular modes. This leads to an effective coupling of the local modes with phonons which is shown to be responsible for the cooperative spin transition accompanied by the structural reorganization. The transition is characterized by the two order parameters representing the mean values of the products of electronic diagonal matrices and the coordinates of the local modes for the high- and low-spin states of the spin crossover complex. Finally, we demonstrate that the approach provides a reasonable explanation of the observed spin transition in the [Fe(ptz)6](BF4)2 crystal. The theory well reproduces the observed abrupt low-spin → high-spin transition and the temperature dependence of the high-spin fraction in a wide temperature range as well as the pronounced hysteresis loop. At the same time within the limiting approximations adopted in the developed model, the evaluated high-spin fraction vs. T shows that the cooperative spin-lattice transition proves to be incomplete in the sense that the high-spin fraction does not reach its maximum value at high temperature.

An approach to automatic learning assessment based on the computational theory of perceptions

E-learning systems output a huge quantity of data on a learning process. However, it takes a lot of specialist human resources to manually process these data and generate an assessment report. Additionally, for formative assessment, the report should state the attainment level of the learning goals defined by the instructor. This paper describes the use of the granular linguistic model of a phenomenon (GLMP) to model the assessment of the learning process and implement the automated generation of an assessment report. GLMP is based on fuzzy logic and the computational theory of perceptions. This technique is useful for implementing complex assessment criteria using inference systems based on linguistic rules. Apart from the grade, the model also generates a detailed natural language progress report on the achieved proficiency level, based exclusively on the objective data gathered from correct and incorrect responses. This is illustrated by applying the model to the assessment of Dijkstra’s algorithm learning using a visual simulation-based graph algorithm learning environment, called GRAPHs

Feature selection in the reconstruction of complex network representations of spectral data

Complex networks have been extensively used in the last decade to characterize and analyze complex systems, and they have been recently proposed as a novel instrument for the analysis of spectra extracted from biological samples. Yet, the high number of measurements composing spectra, and the consequent high computational cost, make a direct network analysis unfeasible. We here present a comparative analysis of three customary feature selection algorithms, including the binning of spectral data and the use of information theory metrics. Such algorithms are compared by assessing the score obtained in a classification task, where healthy subjects and people suffering from different types of cancers should be discriminated. Results indicate that a feature selection strategy based on Mutual Information outperforms the more classical data binning, while allowing a reduction of the dimensionality of the data set in two orders of magnitude

Correlation Dimension of Complex Networks

We propose a new measure to characterize the dimension of complex networks based on the ergodic theory of dynamical systems. This measure is derived from the correlation sum of a trajectory generated by a random walker navigating the network, and extends the classical Grassberger-Procaccia algorithm to the context of complex networks. The method is validated with reliable results for both synthetic networks and real-world networks such as the world air-transportation network or urban networks, and provides a computationally fast way for estimating the dimensionality of networks which only relies on the local information provided by the walkers.

Recruitment and replacement of hippocampal neurons in young and adult chickadees: an addition to the theory of hippocampal learning.

We used [3H]thymidine to document the birth of neurons and their recruitment into the hippocampal complex (HC) of juvenile (4.5 months old) and adult blackcapped chickadees (Parus atricapillus) living in their natural surroundings. Birds received a single dose of [3H]thymidine in August and were recaptured and killed 6 weeks later, in early October. All brains were stained with Cresyl violet, a Nissl stain. The boundaries of the HC were defined by reference to the ventricular wall, the brain surface, or differences in neuronal packing density. The HC of juveniles was as large as or larger than that of adults and packing density of HC neurons was 31% higher in juveniles than in adults. Almost all of the 3H-labeled HC neurons were found in a 350-m-wide layer of tissue adjacent to the lateral ventricle. Within this layer the fraction of 3H-labeled neurons was 50% higher in juveniles than in adults. We conclude that the HC of juvenile chickadees recruits more neurons and has more neurons than that of adults. We speculate that juveniles encounter greater environmental novelty than adults and that the greater number of HC neurons found in juveniles allows them to learn more than adults. At a more general level, we suggest that (i) long-term learning alters HC neurons irreversibly; (ii) sustained hippocampal learning requires the periodic replacement of HC neurons; (iii) memories coded by hippocampal neurons are transferred elsewhere before the neurons are replaced.

Monetary Effervescence: A Sociological Theory of Religion Applied to Money

This project attempts to answer the question "What holds the construction of money together?" by asserting that it is money's religious nature which provides the moral compulsion for people to use, and continue to uphold, money as a socially constructed concept. This project is primarily descriptive and focuses on the religious nature of money by employing a sociological theory of religion in viewing money as a technical concept. This is an interdisciplinary work between religious studies, economics, and sociology and draws heavily from Emile Durkheim's 'The Elementary Forms of Religious Life' as well as work related to heterodox theories of money developed by Geoffrey Ingham, A. Mitchell Innes, and David Graeber. Two new concepts are developed: the idea of monetary sacrality and monetary effervescence, both of which serve to recharge the religious saliency of money. By developing the concept of monetary sacrality, this project shows how money acts to interpret our economic relations while also obfuscating complex power dynamics in society, making them seem naturally occurring and unchangeable. The project also shows how our contemporary fractional reserve banking system contributes to money's collective effervescence and serves to animate economic acting within a monetary network. The project concludes by outlining multiple implications for religious studies, economics, sociology, and central banking.

Syntactic and Semantic Relationships in Models of Complex Systems: An Ecological Case

In this paper, the authors extend and generalize the methodology based on the dynamics of systems with the use of differential equations as equations of state, allowing that first order transformed functions not only apply to the primitive or original variables, but also doing so to more complex expressions derived from them, and extending the rules that determine the generation of transformed superior to zero order (variable or primitive). Also, it is demonstrated that for all models of complex reality, there exists a complex model from the syntactic and semantic point of view. The theory is exemplified with a concrete model: MARIOLA model.

Theory of mind and relational complexity

Cognitive complexity and control theory and relational complexity theory attribute developmental changes in theory of mind (TOM) to complexity. In 3 studies, 3-, 4-, and 5-year-olds performed TOM tasks (false belief, appearance-reality), less complex connections (Level 1 perspective-taking) tasks, and transformations tasks (understanding the effects of location changes and colored filters) with content similar to TOM. There were also predictor tasks at binary-relational and ternary-relational complexity levels, with different content. Consistent with complexity theories: (a) connections and transformations were easier and mastered earlier than TOM; (b) predictor tasks accounted for more than 80% of age-related variance in TOM; and (c) ternary-relational items accounted for TOM variance, before and after controlling for age and binary-relational items. Prediction did not require hierarchically structured predictor tasks.

Self-consistent theory of atomic Fermi gases with a Feshbach resonance at the superfluid transition

A self-consistent theory is derived to describe the BCS-Bose-Einstein-condensate crossover for a strongly interacting Fermi gas with a Feshbach resonance. In the theory the fluctuation of the dressed molecules, consisting of both preformed Cooper pairs and bare Feshbach molecules, has been included within a self-consistent T-matrix approximation, beyond the Nozieres and Schmitt-Rink strategy considered by Ohashi and Griffin. The resulting self-consistent equations are solved numerically to investigate the normal-state properties of the crossover at various resonance widths. It is found that the superfluid transition temperature T-c increases monotonically at all widths as the effective interaction between atoms becomes more attractive. Furthermore, a residue factor Z(m) of the molecule's Green function and a complex effective mass have been determined to characterize the fraction and lifetime of Feshbach molecules at T-c. Our many-body calculations of Z(m) agree qualitatively well with recent measurments of the gas of Li-6 atoms near the broad resonance at 834 G. The crossover from narrow to broad resonances has also been studied.

Telling the story of theory of mind: Deaf and hearing children's narratives and mental state understanding

Theory of mind (ToM) was examined in late-signing deaf children in two studies by using standard tests and measures of spontaneous talk about inner states of perception, affect and cognition during storytelling. In Study 1, there were 21 deaf children aged 6 to 11 years and 13 typical-hearing children matched with the deaf by chronological age. In Study 2, there were 17 deaf children aged 6 to 12 years and 17 typical-hearing preschoolers aged 4 to 5 years who were matched with the deaf by ToM test performance. In addition to replicating the consistently reported finding of poor performance on standard false belief tests by late-signing deaf children, significant correlations emerged in both studies between deaf children's ToM test scores and their spontaneous narrative talk about imaginative cognition (e.g. 'pretend'). In Study 2, with a new set of purpose-built pictures that evoked richer and more complex mentalistic narration than the published picture book of Study 1, results of multiple regression analyses showed that children's narrative talk about imaginative cognition was uniquely important, over and above hearing status and talking of other kinds of mental states, in predicting ToM scores. The same was true of children's elaborated narrative talk using utterances that either spelt out thoughts, explained inner states or introduced contrastives. In addition, results of a Guttman scalograrn analysis in Study 2 suggested a consistent sequence in narrative and standard test performance by deaf and hearing children that went from (1) narrative mention of visible (affective or perceptual) mental states only, along with FB failure, to (2) narrative mention of cognitive states along with (1), to (3) elaborated narrative talk about inner states along with (2), and finally to (4) simple and elaborated narrative talk about affective/perceptual and cognitive states along with FIB test success. Possible explanations for this performance ordering, as well as for the observed correlations in both studies between ToM test scores and narrative variables, were considered.

Asymptotic theory of time varying networks with memory and heterogeneous activation pattern

In this thesis work we develop a new generative model of social networks belonging to the family of Time Varying Networks. The importance of correctly modelling the mechanisms shaping the growth of a network and the dynamics of the edges activation and inactivation are of central importance in network science. Indeed, by means of generative models that mimic the real-world dynamics of contacts in social networks it is possible to forecast the outcome of an epidemic process, optimize the immunization campaign or optimally spread an information among individuals. This task can now be tackled taking advantage of the recent availability of large-scale, high-quality and time-resolved datasets. This wealth of digital data has allowed to deepen our understanding of the structure and properties of many real-world networks. Moreover, the empirical evidence of a temporal dimension in networks prompted the switch of paradigm from a static representation of graphs to a time varying one. In this work we exploit the Activity-Driven paradigm (a modeling tool belonging to the family of Time-Varying-Networks) to develop a general dynamical model that encodes fundamental mechanism shaping the social networks' topology and its temporal structure: social capital allocation and burstiness. The former accounts for the fact that individuals does not randomly invest their time and social interactions but they rather allocate it toward already known nodes of the network. The latter accounts for the heavy-tailed distributions of the inter-event time in social networks. We then empirically measure the properties of these two mechanisms from seven real-world datasets and develop a data-driven model, analytically solving it. We then check the results against numerical simulations and test our predictions with real-world datasets, finding a good agreement between the two. Moreover, we find and characterize a non-trivial interplay between burstiness and social capital allocation in the parameters phase space. Finally, we present a novel approach to the development of a complete generative model of Time-Varying-Networks. This model is inspired by the Kaufman's adjacent possible theory and is based on a generalized version of the Polya's urn. Remarkably, most of the complex and heterogeneous feature of real-world social networks are naturally reproduced by this dynamical model, together with many high-order topological properties (clustering coefficient, community structure etc.).

Towards an integrative theory of religion and politics

In the social sciences, debate on the relationship between religion and politics is mainly the subject of analysis in the sociology of religion and the theory of international relations. While each of these fields promotes different approaches to study their interdependency. The individual's perception of religion and politics is neglected by current research. The faithful, who participates in religious ceremonies, listening and behaving according to specific religious teachings, actively engaging in the liturgical life of the institutional form of his religion, has a specific way of understanding the relationship between religion and politics. I argue that this aspect is under-researched and misrepresented in the literature of sociology and international relations. However, a more complex analysis is offered by the study of nationalism, and especially by its ethnosymbolic approach, which includes at the micro and macro societal level the presence of myths and symbols as part of the individual's and the nation's life. An integrative theory analysing the connection between religion and politics takes into account the role of myths and symbols from the perspectives of both individuals and ethnic communities.

From detection of complex motion to descriptions of moving surfaces in human vision

A preliminary study by Freeman et al (1996b) has suggested that when complex patterns of motion elicit impressions of 2-dimensionality, odd-item-out detection improves given targets can be differentiated on the basis of surface properties. Their results can be accounted for, it if is supposed that observers are permitted efficient access to 3-D surface descriptions but access to 2-D motion descriptions is restricted. To test the hypothesis, a standard search technique was employed, in which targets could be discussed on the basis of slant sign. In one experiment, slant impressions were induced through the summing of deformation and translation components. In a second theory were induced through the summing of shear and translation components. Neither showed any evidence of efficient access. A third experiment explored the possibility that access to these representations may have been hindered by a lack of grouping between the stimuli. Attempts to improve grouping failed to produce convincing evidence in support of life. An alternative explanation is that complex patterns of motion are simply not processed simultaneously. Psychophysical and physiological studies have, however, suggested that multiple mechanisms selective for complex motion do exist. Using a subthreshold summation technique I found evidence supporting the notion that complex motions are processed in parallel. Furthermore, in a spatial summation experiment, coherence thresholds were measured for displays containing different numbers of complex motion patches. Consistent with the idea that complex motion processing proceeds in parallel, increases in the number of motion patches were seen to decrease thresholds, both for expansion and rotation. Moreover, the rates of decrease were higher than those typically expected from probability summation, thus implying mechanisms are available, which can pool signals from spatially distinct complex motion flows.