LAS is a program that acquires augmented transition network (ATN) grammars. It requires as data sentences of the language and semantic network representatives of their meaning. In acquiring the ATN grammars, it induces the word classes of the language, the rules of formation for sentences, and the rules mapping sentences onto meaning. The induced ATN grammar can be used both for sentence generation and sentence comprehension. Critical to the performance of the program are assumptions that it makes about the (...) relation between sentence structure and surface structure (the graph deformation condition), about when word classes may be formed and when ATN networks may be merged, and about the structure of noun phrases. These assumptions seem to be good heuristics which are largely true for natural languages although they would not be true for many nonnatural languages. Provided these assumptions are satisfied LAS seems capable of learning any context‐free language. (shrink)

Urban rail transit can improve a city’s accessibility. However, high construction and operation costs restrict the development of urban rail transit. Value capture recoups the additional value that the investments of urban rail transit confer to local land and is considered to be an effective measure to alleviate this financial problem. Understanding the land value uplift effects of urban rail transit is essential for understanding value capture. This study applied a Space-P model of urban rail transit network based on complex (...) network theory and demonstrated the influence of urban rail transit network characteristics on residential and commercial land prices. The model was tested with eight metropolises in China, using the 2003 to 2022 timeframe as the context. The results showed a significant positive correlation between the number of nodes and the land prices, the average clustering coefficient was highly positively correlated with the land prices, and there was a significant negative correlation between the average path length and the land prices. This study provides theoretical support for value capture, is beneficial for urban rail transit planning, and supports improvements in the development quality of urban rail transit networks. (shrink)

Transitional justice scholars are increasingly concerned with measuring the impact of transitional justice initiatives. Scholars often assume that TJ mechanisms must be properly designed and ordered to achieve lasting effect, but the impact of TJ timing and sequencing has attracted relatively little theoretical or empirical attention. Focusing on Latin America, this article explores variation within the region as to when TJ occurs and the order in which mechanisms are implemented. We utilize qualitative comparative analysis to assess the impact of TJ (...) timing and sequencing on democratic development. We find little evidence for path dependency owing to the chronological order of mechanisms. We do find, however, that amnesties and trials approach a sufficient condition for democratic consolidation in Latin America; trials, however, come closest to being a necessary condition for successful democratic consolidation. (shrink)

Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge—an interconnected causal network, where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms—causal islands—such that events in different mechanisms are not thought to be related even when they belong to the same causal chain. To distinguish these possibilities, we tested whether people make transitive judgments about causal chains by inferring, given A causes B and B causes C, (...) that A causes C. Specifically, causal chains schematized as one chunk or mechanism in semantic memory led to transitive causal judgments. On the other hand, chains schematized as multiple chunks led to intransitive judgments despite strong intermediate links. Normative accounts of causal intransitivity could not explain these intransitive judgments. (shrink)

Autocatalytic networks have been used to model the emergence of self‐organizing structure capable of sustaining life and undergoing biological evolution. Here, we model the emergence of cognitive structure capable of undergoing cultural evolution. Mental representations (MRs) of knowledge and experiences play the role of catalytic molecules, and interactions among them (e.g., the forging of new associations) play the role of reactions and result in representational redescription. The approach tags MRs with their source, that is, whether they were acquired through (...) social learning, individual learning (of pre‐existing information), or creative thought (resulting in the generation of new information). This makes it possible to model how cognitive structure emerges and to trace lineages of cumulative culture step by step. We develop a formal representation of the cultural transition from Oldowan to Acheulean tool technology using Reflexively Autocatalytic and Food set generated (RAF) networks. Unlike more primitive Oldowan stone tools, the Acheulean hand axe required not only the capacity to envision and bring into being something that did not yet exist, but hierarchically structured thought and action, and the generation of new MRs: the concepts EDGING, THINNING, SHAPING, and a meta‐concept, HAND AXE. We show how this constituted a key transition toward the emergence of semantic networks that were self‐organizing, self‐sustaining, and autocatalytic, and we discuss how such networks replicated through social interaction. The model provides a promising approach to unraveling one of the greatest anthropological mysteries: that of why development of the Acheulean hand axe was followed by over a million years of cultural stasis. (shrink)

Cells can transit between a range of stable epithelial and mesenchymal states and this has allowed the evolution of complex body forms. Epithelial to mesenchymal transition (EMT) and its reverse, mesenchymal to epithelial transition (MET), occur sequentially in development and organogenesis. EMT often accompanies transitions between stem‐like cells and their more differentiated progeny, as occurs at gastrulation, although the relevance of this had not been clarified. New findings from the cancer and cell reprogramming fields suggest that EMT and (...) MET can act as essential portals to stem cell character. Here, we review these findings in the broader context of EMT and MET with emphasis on stem cell biology. Using the heart as an example, we also explore the potential role of EMT/MET in organ regeneration. Understanding EMT and MET at a network level will give us new tools to probe stem cell character and enhance tissue repair. (shrink)

Ideas from random graph theory are used to give an heuristic argument that associative memory structure depends discontinuously on pattern recognition ability. This argument suggests that there may be a certain minimal size for intelligent systems.

Although the rapid growth of digital data and computationally advanced methods in the social sciences has in many ways exacerbated tensions between the so-called ‘quantitative’ and ‘qualitative’ approaches, it has also been provocatively argued that the ubiquity of digital data, particularly online data, finally allows for the reconciliation of these two opposing research traditions. Indeed, a growing number of ‘qualitatively’ inclined researchers are beginning to use computational techniques in more critical, reflexive and hermeneutic ways. However, many of these claims for (...) ‘quali-quantitative’ methods hinge on a single technique: the network graph. Networks are relational, allow for the questioning of rigid categories and zooming from individual cases to patterns at the aggregate. While not refuting the use of networks in these studies, this paper argues that there must be other ways of doing quali-quantitative methods. We first consider a phenomenon which falls between quantitative and qualitative traditions but remains elusive to network graphs: the spread of information on Twitter. Through a case study of debates about nuclear power on Twitter, we develop a novel data visualisation called the modulation sequencer which depicts the spread of URLs over time and retains many of the key features of networks identified above. Finally, we reflect on the role of such tools for the project of quali-quantitative methods. (shrink)

For five individuals, a social network was constructed from a series of his or her dreams. Three important network measures were calculated for each network: transitivity, assortativity, and giant component proportion. These were monotonically related; over the five networks as transitivity increased, assortativity increased and giant component proportion decreased. The relations indicate that characters appear in dreams systematically. Systematicity likely arises from the dreamer's memory of people and their relations, which is from the dreamer's cognitive social network. But the (...) dream social network is not a copy of the cognitive social network. Waking life social networks tend to have positive assortativity; that is, people tend to be connected to others with similar connectivity. Instead, in our sample of dream social networks assortativity is more often negative or near 0, as in online social networks. We show that if characters appear via a random walk, negative assortativity can result, particularly if the random walk is biased as suggested by remote associations. (shrink)

Although many studies have provided evidence that abstract knowledge can be acquired in artificial grammar learning, it remains unclear how abstract knowledge can be attained in sequence learning. To address this issue, we proposed a dual simple recurrent network model that includes a surface SRN encoding and predicting the surface properties of stimuli and an abstract SRN encoding and predicting the abstract properties of stimuli. The results of Simulations 1 and 2 showed that the DSRN model can account for learning (...) effects in the serial reaction time task under different conditions, and the manipulation of the contribution weight of each SRN accounted for the contribution of conscious and unconscious processes in inclusion and exclusion tests in previous studies. The results of human performance in Simulation 3 provided further evidence that people can implicitly learn both chunking and abstract knowledge in sequence learning, and the results of Simulation 3 confirmed that the DSRN model can account for how people implicitly acquire the two types of knowledge in sequence learning. These findings extend the learning ability of the SRN model and help understand how different types of knowledge can be acquired implicitly in sequence learning. (shrink)

This article introduces the Culturally Meaningful Networks (CMN) approach. Following a pragmatist perspective of social mechanisms more broadly, it develops and demonstrates an approach to understanding networks that incorporates both structure and meaning and that leverages time to understand how these aspects influence each other. I apply this approach to investigate a longstanding puzzle about why some of those who leave military service for civilian life fare well, and others badly. In a mixed-methods analysis, I follow a sample (...) of individuals moving through the transition from military to civilian life in the contemporary United Kingdom. I find that the higher the proportion of alters (i.e., “contacts”) with a military background in the networks of leavers before discharge, the worse they fare after discharge. The CMN approach helps me locate a specific structural embedding that explains the presence or absence of durable cultural frames that set the context for the actual experience of the transition and cause problems during it. Attention to the temporal unfolding of network structure and social meaning is essential to bringing out this finding. By re-embedding networks within people’s experiences over time, the CMN approach helps grasp the distinctions by which leavers understand their interactions. I conclude by arguing that the CMN approach has implications for network sociology and cultural sociology that go beyond this substantive case. (shrink)

In cognitive neuroscience, dissociating the brain networks that ing—has thus become one of the best empirical situations subtend conscious and nonconscious memories constitutes a through which to study the mechanisms of implicit learning, very complex issue, both conceptually and methodologically.

In this research work, we have explored the physical and topological properties of the crystal structure of metal-insulator transition superlattice. In recent times, two-dimensional substantial have enamored comprehensive considerations owing to their novel ophthalmic and mechanical properties for anticipated employment. Recently, some researchers put their interest in modifying this material into useful forms in human life. Also, Metal-Insulator Transition Superlattice is useful in form of a thin film to utilize as two-dimensional transition metal dichalcogenides. Moreover, we have (...) defined the computed-based bond properties such as the degree constructed topological indices and their heat of formation for single crystal and monolayered structure of Ge-Sb-Te. Also, this structure is one of the most interesting composites in modern resources of science. (shrink)

The identification of network motifs has been widely considered as a significant step towards uncovering the design principles of biomolecular regulatory networks. To date, time‐invariant networks have been considered. However, such approaches cannot be used to reveal time‐specific biological traits due to the dynamic nature of biological systems, and hence may not be applicable to development, where temporal regulation of gene expression is an indispensable characteristic. We propose a concept of a “temporal sequence of network motifs”, a sequence (...) of network motifs in active sub‐networks constructed over time, and investigate significant network motifs in the active temporal sub‐networks of Drosophila melanogaster. Based on this concept, we find a temporal sequence of network motifs which changes according to developmental stages and thereby cannot be identified from the whole static network. Moreover, we show that the temporal sequence of network motifs corresponding to each developmental stage can be used to describe pivotal developmental events. (shrink)

Over the past decade, sequence learning has gradually become a central paradigm through which to study implicit learning. In this chapter, we start by briefly summarizing the results obtained with different variants of the sequence learning paradigm. We distinguish three subparadigms in terms of whether the stimulus material is generated either by following a fixed and repeating sequence (e.g., Nissen & Bullemer, 1987), by relying on a complex set of rules from which one can produce several alternative deterministic sequences (e.g., (...) Lewicki, Hill & Bizot, 1988; Stadler, 1989), or by following the output of a probabilistic set of rules such as instantiated by noisy finite-state grammars (Cleeremans & McClelland, 1991; Jiménez, Mendéz & Cleeremans, 1996). Next, we focus on the processes involved in sequence representation and acquisition. We suggest that the sensitivity to the sequential structure observed in the probabilistic subparadigm can only be a result of the acquisition of a representation of the statistical constraints of the material, and that this sensitivity emerges through the operation of mechanisms that are well instantiated by connectionist models such as the Simple Recurrent Network (Elman, 1990; Cleeremans, 1993b). We present new simulation work meant to explore to what extent the model can also account for specific data obtained in a paradigmatic instance of deterministic, rule-based sequence learning task: Lewicki et al. (1988)'s situation. Finally, we report on the results of an experiment that compares learning on otherwise similar deterministic and probabilistic structures, and we show that learning of both types of structures is equivalent only under conditions that maximally hinder explicit acquisition. Taken together, these simulation and experimental data lend support to the claim that implicit learning in all three sequence learning subparadigms can amount to a form of statistical sequence learning. They also suggest that distinguishing among several theories of sequence representation and acquisition may require us to analize the data in great detail. Hopefully, however, some truth can be found in such details.. (shrink)

We study probabilistically informative (weak) versions of transitivity by using suitable definitions of defaults and negated defaults in the setting of coherence and imprecise probabilities. We represent p-consistent sequences of defaults and/or negated defaults by g-coherent imprecise probability assessments on the respective sequences of conditional events. Moreover, we prove the coherent probability propagation rules for Weak Transitivity and the validity of selected inference patterns by proving p-entailment of the associated knowledge bases. Finally, we apply our results to study selected probabilistic (...) versions of classical categorical syllogisms and construct a new version of the square of opposition in terms of defaults and negated defaults. (shrink)

Previous research has linked the concept of number and other ordinal series to space via a spatially oriented mental number line. In addition, it has been shown that in visual scene recognition and production, speakers of a language with a left-to-right orthography respond faster to and tend to draw images in which the agent of an action is located to the left of the patient. In this study, we aim to bridge these two lines of research by employing a novel (...) method that measures the spatial bias produced by transitive sentences that use a wide variety of abstract and concrete verbs. Across four experiments, participants read sentences and then responded to probe words appearing on either the left or right sides of the screen. Probe words consisted of agents, patients, other words in the sentence, or newly encountered words. We found consistent lateral biases to responding to agents and patients, which appears to be independent of order of mention in the sentence but which does reflect a correspondence between position in the sentence and role in the causal sequence of the action. Our results also show that this spatial bias is driven by the use of the hands in two different ways: The left hand shows a greater sensitivity to the spatial effect than the right hand, and vocal responses produce no spatial effect. (shrink)

As linguistic competence so clearly illustrates, processing sequences of events is a fundamental aspect of human cognition. For this reason perhaps, sequence learning behavior currently attracts considerable attention in both cognitive psychology and computational theory. In typical sequence learning situations, participants are asked to react to each element of sequentially structured visual sequences of events. An important issue in this context is to determine whether essentially associative processes are sufficient to understand human performance, or whether more powerful learning mechanisms are (...) necessary. To address this issue, we explore how well human participants and connectionist models are capable of learning sequential material that involves complex, disjoint, longdistance contingencies. We show that the popular Simple Recurrent Network model (Elman, 1990), which has otherwise been shown to account for a variety of empirical findings (Cleeremans, 1993), fails to account for human performance in several experimental situations meant to test the model’s specific predictions. In previous research (Cleeremans, 1993) briefly described in this paper, the structure of center-embedded sequential structures was manipulated to be strictly identical or probabilistically different as a function of the elements surrounding the embedding. While the SRN could only learn in the second case, human subjects were found to be insensitive to the manipulation. In the new experiment described in this paper, we tested the idea that performance benefits from “starting small effects” (Elman, 1993) by contrasting two conditions in which the training regimen was either incremental or not. Again, while the SRN is only capable of learning in the first case, human subjects were able to learn in both. We suggest an alternative model based on Maskara & Noetzel’s (1991) Auto-Associative Recurrent Network as a way to overcome the SRN model’s failure to account for the empirical findings.. (shrink)

We develop the theory of Kim-independence in the context of NSOP $_{1}$ theories satisfying the existence axiom. We show that, in such theories, Kim-independence is transitive and that -Morley sequences witness Kim-dividing. As applications, we show that, under the assumption of existence, in a low NSOP $_{1}$ theory, Shelah strong types and Lascar strong types coincide and, additionally, we introduce a notion of rank for NSOP $_{1}$ theories.

We study probabilistically informative (weak) versions of transitivity by using suitable definitions of defaults and negated defaults in the setting of coherence and imprecise probabilities. We represent p-consistent sequences of defaults and/or negated defaults by g-coherent imprecise probability assessments on the respective sequences of conditional events. Finally, we present the coherent probability propagation rules for Weak Transitivity and the validity of selected inference patterns by proving p-entailment of the associated knowledge bases.

Industrial agriculture has extensive environmental and social costs, and efforts to create alternative farming systems are widespread if not yet widely successful. This study explored how a set of grain farmers and rotational graziers in Iowa transitioned to agroecological management practices. Our focus on the resources and strategies that farmers mobilized to develop opportunities for, and overcome barriers to, transitioning to alternative practices allows us to go beyond the existing literature focused on why farmers transition. We attend to both (...) the ecological and socioeconomic context of innovation by comparing processes of technical change in two contrasting regions of Iowa. Farmers cultivated farm-level biodiversity and enterprise diversity, developed new cognitive and psychological competencies, and overcame barriers to innovation by developing external network linkages with peers, knowledge organizations, and federal policies. Our research provides insights into how biophysical, cognitive, structural and market considerations can be integrated into research efforts that aim to make sense of innovation toward sustainable agriculture. (shrink)

For more than 20 years, sustainable development has been advocated as a way of tackling growing global environmental and social problems. The sustainable development discourse has always had a strong technological component and the literature boasts an enormous amount of debate on which technologies should be developed and employed and how this can most efficiently be done. The mainstream discourse in sustainable development argues for an eco-efficiency approach in which a technology push strategy boosts efficiency levels by a factor 10 (...) and more in industrialised and developing countries. A minority argues for a socio-cultural lifestyle switch, relying on new values, quality of life, sufficiency and redistribution strategies, with calls for appropriate and soft technologies. It is remarkable, however, that the articles, books and policy debates on sustainability seldom explicitly draw in a discussion of the nature of technology, how technology influences and is influenced by society, and what this implies for sustainable development. The mainstream interprets technology as neutral and instrumental: technology is no more than an instrument to reach a goal; it cannot be judged on its intrinsic characteristics, only on its use. The alternative view often builds on an autonomous and substantive interpretation of technology: technology is an autonomous, almost uncontrollable power that fundamentally reshapes our culture. A more balanced approach seems to be growing in the research on socio-technical sustainability transitions where the focus shifts to the co-evolution of technology and society, and to the networks, seamless webs and complex multi-actor processes that may carry a sustainability transition forward. This approach builds on insights from recent traditions in the philosophy and sociology of technology, in particular the social construction of technology (SCOT) and actor-network theory (ANT). While this provides for a better understanding of the nature and potential role of technology in sustainability policies, it remains to be seen whether it will actually influence the choice between technologies. This article investigates the different conceptualisations of technology in the sustainability debate. It first distinguishes between different approaches of sustainability and how these are related to differing views on technology. It then moves on to how the socio-technical transitions research incorporates insights from contemporary philosophy and sociology of technology. It reflects on the potential of transitions research to give guidance in technology choices, suggesting that the transition approach might be strengthened by drawing in insights from critical theory of technology and by taking a more political stance in defining sustainable development. (shrink)

Knowledge networking in the cross-cultural setting here focuses on promoting a culture of shared communication, values and knowledge, seeking cooperation through valorisation of diversity. The process is seen here in terms of creating new alliances of creators, users, mediators and facilitators of knowledge. At the global level, knowledge networking is seen as a symbiotic relationship between local and global knowledge resources. This focus is informed by the human-centred vision of the information society, which seeks a symbiotic relationship between technology and (...) society. It explores the nature of the knowledge in transition, raising issues of technology and knowledge transfer in the local–global context. The notions of human–machine symbiosis and of diversity and coherence provide a handle to explore the role of technology for sustainable development. The centrality of knowledge in stimulating knowledge networking for cross-cultural collaboration is illustrated through an exemplar of an EU–India Cross-Cultural Innovation Network project, a collaboration between European and Indian universities and institutes. (shrink)

Conventional agriculture, while nested in nature, has expanded production at the expense of water in the Midwest and through the diversion of water resources in the western United States. With the growth of population pressure and concern about water quality and quantity, demands are growing to alter the relationship of agriculture to water in both these locations. To illuminate the process of change in this relationship, the author builds on Buttel’s (Research in Rural Sociology and Development 6: 1–21, 1995) assertion (...) that agriculture is transitioning to a post “green revolution” period where farmers are paid for conservation, and employs actor network theory (Latour and Woolgar Laboratory life: The construction of scientific facts. Princeton, NJ: Princeton University Press, 1986) and the advocacy coalition framework (Sabatier and Jenkins-Smith, Policy change and learning: An advocacy coalition approach, 1–56. Boulder, CO: Westview Press, 1993) to frame discussions of water and agriculture in the upper Mississippi River watershed, particularly Iowa. The author concludes that contested views of agriculture and countryside, as well as differing views of how agriculture must change to adapt to growing water concerns, will shape coalitions that will ultimately play a significant role in shaping the future of agriculture. (shrink)

Cover Photograph: Resolving developmental genetics in the fourth dimension: an illustration (by Kwang‐Hyun Cho himself) of the principle of dynamic network motifs in Drosophila development. Hitherto largely considered in terms of time‐invariant networks, drosophila development is viewed in the article by Man‐Sun Kim, Jeong‐Rae Kim, and Kwang‐Hyun Cho as the result of networks of gene interactions that change during the course of development. Using this paradigm, pivotal developmental events can be correlated with particular changes from one constellation of (...) gene interactions to a different one, and the method allows the identification of certain network motifs that are not identifiable using static approaches. Features article: “Dynamic network rewiring determines temporal regulatory functions in the Drosophila melanogaster development processes”, see pages 505 – 513. (shrink)

According to the World Health Organisation, three to five million individuals are infected by influenza, and around 250,000 to 500,000 people die of this infectious disease worldwide. Influenza epidemics pose a serious public health threat. Moreover, graver dangers are encountered with influenza subtypes against which there is little or no preexisting human immunity. Such subtypes of influenza have the potential to cause devastating epidemics. Thus, enhancing surveillance systems for the purpose of detecting influenza epidemics in an early stage can quicken (...) response times and save millions of lives. This paper presents three adapting intelligence models: support vector machine regression, artificial neural network using particle swarm optimisation, and our intelligent time series to predict influenza epidemics. The novelty of the current study is that it proposes a new intelligent model to predict influenza outbreaks. The INTS model combines clustering with a time series model to enhance the prediction of influenza outbreaks. The innovation of our proposed model integrates the results obtained from the existing weighted exponential smoothing model with centroids obtained from clustering. We developed a surveillance system for influenza epidemics using Google search queries. The current research is based on a weighted version of the Center for Disease Control and Prevention influenza-like illness activity level obtained from the Center for Disease Control and Prevention data, as well as query data obtained from the Goggle search engine in the USA. The influenza-like illness data was collected from January 4, 2009, to December 27, 2015, stretching across a total time span of 312 weeks. Google Correlate was used to select search queries related to influenza epidemics. In total, 100 search queries were obtained from Google Correlate, 10 of which were better and more relevant search queries selected in this study. The model was evaluated using online Google search queries collected from Google Correlate. Standard measure performance MSE, RMSE, and MAE were employed to estimate the results of the proposed model. The empirical results of the INTS model showed MSE = 0.003, RMSE = 0.036, and MAE = 0.0185, indicating that the errors of the proposed model are very limited. A comparative model of predicting results between the INTS model, alternative Google Flu Trend, and autoregression with Google search data is also presented. The proposed model outperformed the existing models. (shrink)

Gödel’s first incompleteness result from 1931 states that there are true assertions about the natural numbers which do not follow from the Peano axioms. Since 1931 many researchers have been looking for natural examples of such assertions and breakthroughs were obtained in the seventies by Jeff Paris [Some independence results for Peano arithmetic. J. Symbolic Logic 43 725–731] , Handbook of Mathematical Logic, North-Holland, Amsterdam, 1977] and Laurie Kirby [L. Kirby, Jeff Paris, Accessible independence results for Peano Arithmetic, Bull. of (...) the LMS 14 285–293]) and Harvey Friedman [S.G. Simpson, Non-provability of certain combinatorial properties of finite trees, in: Harvey Friedman’s Research on the Foundations of Mathematics, North-Holland, Amsterdam, 1985, pp. 87–117; R. Smith, The consistency strength of some finite forms of the Higman and Kruskal theorems, in: Harvey Friedman’s Research on the Foundations of Mathematics, North-Holland, Amsterdam, 1985, pp. 119–136] who produced the first mathematically interesting independence results in Ramsey theory and well-order and well-quasi-order theory .In this article we investigate Friedman-style principles of combinatorial well-foundedness for the ordinals below ε0. These principles state that there is a uniform bound on the length of decreasing sequences of ordinals which satisfy an elementary recursive growth rate condition with respect to their Gödel numbers.For these independence principles we classify their phase transitions, i.e. we classify exactly the bounding conditions which lead from provability to unprovability in the induced combinatorial well-foundedness principles.As Gödel numbering for ordinals we choose the one which is induced naturally from Gödel’s coding of finite sequences from his classical 1931 paper on his incompleteness results.This choice makes the investigation highly non-trivial but rewarding and we succeed in our objectives by using an intricate and surprising interplay between analytic combinatorics and the theory of descent recursive functions. For obtaining the required bounds on count functions for ordinals we use a classical 1961 Tauberian theorem of Parameswaran which apparently is far remote from Gödel’s theorem. (shrink)

The Dynamics of Social Practice -- Introducing Theories of Practice -- Materials and Resources -- Sequence and Structure -- Making and Breaking Links -- Material, Competence and Meaning -- Car-Driving: Elements and Linkages Making Links -- Breaking Links -- Elements Between Practices -- Standardization and Diversity -- Individual and Collective Careers -- The Life of Elements -- Modes of Circulation -- Transportation and Access: Material -- Abstraction, Reversal and Migration: Competence -- Association and Classification: Meaning -- Packing and Unpacking -- (...) Emergence, Disappearance and Persistence -- Recruitment, Defection and Reproduction -- First Encounters: Networks and Communities -- Capture and Commitment: Careers and Carriers -- Collapse and Transformation: The Dynamics of Defection -- Daily Paths, Life Paths and Dominant Projects -- Connections Between Practices -- Bundles and Complexes -- Collaboration and Competition -- Selection and Integration -- Coordinating Daily Life -- Circuits of Reproduction -- Monitoring Practices-as-Performances -- Monitoring Practices-as-Entities -- Cross-Referencing Practices-as-Performances -- Cross-Referencing Practices-as-Entities -- Aggregation -- Elements of Coordination -- Intersecting Circuits -- Representing the Dynamics of Social Practice -- Representing Elements and Practices -- Characterizing Circulation -- Competition, Transformation and Convergence -- Reproducing Elements, Practices and Relations between Them -- Time and Practice -- Space and Practice -- Dominant Projects and Power -- Promoting Transitions in Practice -- Climate Change and Behaviour Change -- Basis of Action -- Processes of Change -- Positioning Policy -- Transferable Lessons -- Practice Theory and Climate Change Policy -- Configuring Elements of Practice -- Configuring Relations between Practices -- Configuring Careers: Carriers and Practices -- Configuring Connections -- Practice Oriented Policy Making. (shrink)

Natural languages vary widely in the degree to which they make use of nested compositional structure in their grammars. It has long been noted by linguists that the languages historically spoken in small communities develop much deeper levels of compositional embedding than those spoken by larger groups. Recently, this observation has been confirmed by a robust statistical analysis of the World Atlas of Language Structures. In order to examine this connection mechanistically, we propose an agent‐based model that accounts for key (...) cultural evolutionary features of language transfer and language change. We identify transitivity as a physical parameter of social networks critical for the evolution of compositional structure and the hierarchical patterning of scale‐free distributions as inhibitory. (shrink)

A biologically unavoidable sequence is an infinite gender sequence which occurs in every gendered, infinite genealogical network satisfying certain tame conditions. We show that every eventually periodic sequence is biologically unavoidable (this generalizes König's Lemma), and we exhibit some biologically avoidable sequences. Finally we give an application of unavoidable sequences to cellular automata.

A Transition to Proof: An Introduction to Advanced Mathematics describes writing proofs as a creative process. There is a lot that goes into creating a mathematical proof before writing it. Ample discussion of how to figure out the "nuts and bolts'" of the proof takes place: thought processes, scratch work and ways to attack problems. Readers will learn not just how to write mathematics but also how to do mathematics. They will then learn to communicate mathematics effectively. The text (...) emphasizes the creativity, intuition, and correct mathematical exposition as it prepares students for courses beyond the calculus sequence. The author urges readers to work to define their mathematical voices. This is done with style tips and strict "mathematical do’s and don’ts", which are presented in eye-catching "text-boxes" throughout the text. The end result enables readers to fully understand the fundamentals of proof. Features: The text is aimed at transition courses preparing students to take analysis Promotes creativity, intuition, and accuracy in exposition The language of proof is established in the first two chapters, which cover logic and set theory Includes chapters on cardinality and introductory topology. (shrink)

Recent analysis of the contribution of replication slippage to genome evolution shows that it has played a significant role in all species from eubacteria to humans. The overall level of repetition in genomes is related to genome size and to the degree of repetition that can be measured within individual ribosomai RNA genes, suggesting that the entire genome accepts simple sequences in a concerted manner when its size increases. Although coding sequences accept simple sequences much less readily than non‐coding sequences, (...) they accept some repeats, particularly (CAG)n, preferentially. This may have consequences for the evolution of the genes involved in trinucleotide expansion diseases and the transcriptional networks of which they may form a part. (shrink)