The forms of words as they appear in text and speech are central to theories and models of lexical processing. Nonetheless, current methods for simulating their learning and representation fail to approach the scale and heterogeneity of real wordform lexicons. A connectionist architecture termed thesequence encoderis used to learn nearly 75,000 wordform representations through exposure to strings of stress‐marked phonemes or letters. First, the mechanisms and efficacy of the sequence encoder are demonstrated and shown to overcome problems with traditional slot‐based (...) codes. Then, two large‐scale simulations are reported that learned to represent lexicons of either phonological or orthographic wordforms. In doing so, the models learned the statistics of their lexicons as shown by better processing of well‐formed pseudowords as opposed to ill‐formed (scrambled) pseudowords, and by accounting for variance in well‐formedness ratings. It is discussed how the sequence encoder may be integrated into broader models of lexical processing. (shrink)

The forms of words as they appear in text and speech are central to theories and models of lexical processing. Nonetheless, current methods for simulating their learning and representation fail to approach the scale and heterogeneity of real wordform lexicons. A connectionist architecture termed thesequence encoderis used to learn nearly 75,000 wordform representations through exposure to strings of stress‐marked phonemes or letters. First, the mechanisms and efficacy of the sequence encoder are demonstrated and shown to overcome problems with traditional slot‐based (...) codes. Then, two large‐scale simulations are reported that learned to represent lexicons of either phonological or orthographic wordforms. In doing so, the models learned the statistics of their lexicons as shown by better processing of well‐formed pseudowords as opposed to ill‐formed (scrambled) pseudowords, and by accounting for variance in well‐formedness ratings. It is discussed how the sequence encoder may be integrated into broader models of lexical processing. (shrink)

Systems biologists often distance themselves from reductionist approaches and formulate their aim as understanding living systems “as a whole.” Yet, it is often unclear what kind of reductionism they have in mind, and in what sense their methodologies would offer a superior approach. To address these questions, we distinguish between two types of reductionism which we call “modular reductionism” and “bottom-up reductionism.” Much knowledge in molecular biology has been gained by decomposing living systems into functional modules or through detailed studies (...) of molecular processes. We ask whether systems biology provides novel ways to recompose these findings in the context of the system as a whole via computational simulations. As an example of computational integration of modules, we analyze the first whole-cell model of the bacterium M. genitalium. Secondly, we examine the attempt to recompose processes across different spatial scales via multi-scale cardiac models. Although these models rely on a number of idealizations and simplifying assumptions as well, we argue that they provide insight into the limitations of reductionist approaches. Whole-cell models can be used to discover properties arising at the interfaces of dynamically coupled processes within a biological system, thereby making more apparent what is lost through decomposition. Similarly, multi-scale modeling highlights the relevance of macroscale parameters and models and challenges the view that living systems can be understood “bottom-up.” Specifically, we point out that system-level properties constrain lower-scale processes. Thus, large-scale modeling reveals how living systems at the same time are more and less than the sum of the parts. (shrink)

Analogy and similarity are central phenomena in human cognition, involved in processes ranging from visual perception to conceptual change. To capture this centrality requires that a model of comparison must be able to integrate with other processes and handle the size and complexity of the representations required by the tasks being modeled. This paper describes extensions to Structure-Mapping Engine since its inception in 1986 that have increased its scope of operation. We first review the basic SME algorithm, describe psychological evidence (...) for SME as a process model, and summarize its role in simulating similarity-based retrieval and generalization. Then we describe five techniques now incorporated into the SME that have enabled it to tackle large-scale modeling tasks: Greedy merging rapidly constructs one or more best interpretations of a match in polynomial time: O); Incremental operation enables mappings to be extended as new information is retrieved or derived about the base or target, to model situations where information in a task is updated over time; Ubiquitous predicates model the varying degrees to which items may suggest alignment; Structural evaluation of analogical inferences models aspects of plausibility judgments; Match filters enable large-scale task models to communicate constraints to SME to influence the mapping process. We illustrate via examples from published studies how these enable it to capture a broader range of psychological phenomena than before. (shrink)

Sibley, Kello, Plaut, and Elman (2008) proposed the sequence encoder as a model that learns fixed‐width distributed representations of variable‐length sequences. In doing so, the sequence encoder overcomes problems that have restricted models of word reading and recognition to processing only monosyllabic words. Bowers and Davis (2009) recently claimed that the sequence encoder does not actually overcome the relevant problems, and hence it is not a useful component of large‐scale word‐reading models. In this reply, it is noted that the (...) sequence encoder has facilitated the creation of large‐scale word‐reading models. The reasons for this success are explained and stand as counterarguments to claims made by Bowers and Davis. (shrink)

For large-scale optimization, CMA-ES has the disadvantages of high complexity and premature stagnation. An improved CMA-ES algorithm called GI-ES was proposed in this paper. For the problem of high complexity, the method in this paper replaces the calculation of a covariance matrix with the modeling of expected fitting degrees for a given covariance matrix. At the same time, to solve the problem of premature stagnation, this paper replaces the historical information of elite individuals with the historical information of all (...) individuals. The information can be seen as approximate gradients. The parameters of the next generation of individuals are generated based on the approximate gradients. The experimental results were tested using CEC 2010 and CEC2013 LSGO benchmark test suite, and the experimental results verified the effectiveness of the algorithm on a number of different tasks. (shrink)

The collection of very large text sources has revolutionized the study of natural language, leading to the development of several models of language learning and distributional semantics that extract sophisticated semantic representations of words based on the statistical redundancies contained within natural language. The models treat knowledge as an interaction of processing mechanisms and the structure of language experience. But language experience is often treated agnostically. We report a distributional semantic analysis that shows written language in fiction books varies appreciably (...) between books from the different genres, books from the same genre, and even books written by the same author. Given that current theories assume that word knowledge reflects an interaction between processing mechanisms and the language environment, the analysis shows the need for the field to engage in a more deliberate consideration and curation of the corpora used in computational studies of natural language processing. (shrink)

Court judgments contain valuable information on how statutory laws and past court precedents are interpreted and how the interdependence structure among them evolves in the courtroom. Data-mining the evolving structure of such customs and norms that reflect myriad social values from a large-scale court judgment corpus is an essential task from both the academic and industrial perspectives. In this paper, using data from approximately 110,000 court judgments from Japan spanning the period 1998–2018 from the district to the supreme court level, (...) we propose two tasks that grasp such a structure from court judgments and highlight the strengths and weaknesses of major machine learning models. One is a prediction task based on masked language modeling that connects textual information to legal codes and past court precedents. Another is a dynamic link prediction task where we predict the hidden interdependence structure in the law. We make quantitative and qualitative comparisons among major machine learning models to obtain insights for future developments. (shrink)

A person's cognitive map, or knowledge of large‐scale space, is built up from observations gathered as he travels through the environment. It acts as a problem solver to find routes and relative positions, as well as describing the current location. The TOUR model captures the multiple representations that make up the cognitive map, the problem‐solving strategies it uses, and the mechanisms for assimilating new information. The representations have rich collections of states of partial knowledge, which support many of the (...) performance characteristics of common‐sense knowledge. (shrink)

Large scale experiments at CERN’s Large Hadron Collider rely heavily on computer simulations, a fact that has recently caught philosophers’ attention. CSs obviously require appropriate modeling, and it is a common assumption among philosophers that the relevant models can be ordered into hierarchical structures. Focusing on LHC’s ATLAS experiment, we will establish three central results here: with some distinct modifications, individual components of ATLAS’ overall simulation infrastructure can be ordered into hierarchical structures. Hence, to a good degree of approximation, (...) hierarchical accounts remain valid at least as descriptive accounts of initial modeling steps. In order to perform the epistemic function Winsberg Model-based reasoning in scientific discovery. Kluwer Academic/plenum Publishers, New York, pp 255–269, 1999) assigns to models in simulation—generate knowledge through a sequence of skillful but non-deductive transformations—ATLAS’ simulation models have to be considered part of a network rather than a hierarchy, in turn making the associated simulation modeling messy rather than motley. Deriving knowledge-claims from this ‘mess’ requires two sources of justification: holistic validation :253–262, 2010; in Carrier M, Nordmann A Science in the context of application. Springer, Berlin, pp 115–130, 2011), and model coherence. As it turns out, the degree of model coherence sets HEP apart from other messy, simulation-intensive disciplines such as climate science, and the reasons for this are to be sought in the historical, empirical and theoretical foundations of the respective discipline. (shrink)

This paper examines a fundamental problem in applied mathematics. How can one model the behavior of materials that display radically different, dominant behaviors at different length scales. Although we have good models for material behaviors at small and large scales, it is often hard to relate these scale-based models to one another. Macroscale models represent the integrated effects of very subtle factors that are practically invisible at the smallest, atomic, scales. For this reason it has been notoriously difficult to model (...) realistic materials with a simple bottom-up-from-the-atoms strategy. The widespread failure of that strategy forced physicists interested in overall macro-behavior of materials toward completely top-down modeling strategies familiar from traditional continuum mechanics. The problem of the ``tyranny of scales'' asks whether we can exploit our rather rich knowledge of intermediate micro- scale behaviors in a manner that would allow us to bridge between these two dominant methodologies. Macroscopic scale behaviors often fall into large common classes of behaviors such as the class of isotropic elastic solids, characterized by two phenomenological parameters---so-called elastic coefficients. Can we employ knowledge of lower scale behaviors to understand this universality---to determine the coefficients and to group the systems into classes exhibiting similar behavior? (shrink)

This study explored calibrating a large item bank for use in multidimensional health measurement with computerized adaptive testing, using both item responses and response time (RT) information. The Activity Measure for Post-Acute Care is a patient-reported outcomes measure comprised of three correlated scales (Applied Cognition, Daily Activities, and Mobility). All items from each scale are Likert type, so that a respondent chooses a response from an ordered set of four response options. The most appropriate item response theory model for analyzing (...) and scoring these items is the multidimensional graded response model (MGRM). During the field testing of the items, an interviewer read each item to a patient and recorded, on a tablet computer, the patient’s responses and the software recorded RTs. Due to the large item bank with over 300 items, data collection was conducted in four batches with a common set of anchor items to link the scale. Van der Linden’s (2007) hierarchical modeling framework was adopted. Several models, with or without interviewer as a covariate and with or without interaction between interviewer and items, were compared for each batch of data. It was found that the model with the interaction between interviewer and item, when the interaction effect was constrained to be proportional, fit the data best. Therefore, the final hierarchical model with lognormal model for RT and the MGRM for response data was fitted to all batches of data via a concurrent calibration. Evaluation of parameter estimates revealed that (1) adding response time information did not affect the item parameter estimates and their standard errors significantly; (2) adding response time information helped reduce the standard error of patients’ multidimensional latent trait estimates, but adding interviewer as a covariate did not result in further improvement. Implications of the findings for follow up adaptive test delivery design are discussed. (shrink)

Ample research documents the health benefits of community gardens, but our understanding of the factors shaping gardener participation is limited. Neighborhood demographics and garden frames have each been theorized to play a role in shaping who participates in community gardens. Yet, our understanding of the interplay between these factors is underdeveloped and this body of work lacks consideration of the racial and class makeup of gardeners on a large scale. With a nation-wide survey that includes measures of gardener demographics (N (...) = 162), the present study considers the extent to which community garden frames and locations simultaneously shape participant demographics. I combine these factors into a conceptual model explaining community garden participation as an iterative process of framing, accessibility, and representation, all situated within a garden’s surrounding community. Results show some base correlations between gardens focusing on healthy food access or symbolic food labels and gardener demographics, but ordered logistic and negative binomial regressions show stronger evidence of community demographics shaping gardener demographics. At the same time, _t_-tests comparing mean neighborhood and gardener demographics shows a consistent under-representation of Latinx community members among gardeners. As theorized in the model presented, community garden locations are important for shaping what demographics are represented among gardeners, but how community garden benefits are framed can limit garden accessibility, and subsequently neighborhood representation, especially for Latinx residents. This model helps illustrate the mechanisms through which garden organizers and advocates can develop more inclusive community gardens through fostering representation from people of color and the working-class. (shrink)

Embryonic development and adult tissue homeostasis are controlled through activation of intracellular signal transduction pathways by extracellular growth factors. In the past, signal transduction has largely been regarded as a linear process. However, more recent data from large‐scale and high‐throughput experiments indicate that there is extensive cross‐talk between individual signaling cascades leading to the notion of a signaling network. The behavior of such complex networks cannot be predicted by simple intuitive approaches but requires sophisticated models and computational simulations. The (...) purpose of such models is to generate experimentally testable hypotheses and to find explanations for unexpected experimental results. Here, we discuss the need for, and the future impact of, mathematical models for exploring signal transduction in different biological contexts such as for example development. BioEssays 30:1110–1125, 2008. © 2008 Wiley Periodicals, Inc. (shrink)

What is philosophy of science? Numerous manuals, anthologies or essays provide carefully reconstructed vantage points on the discipline that have been gained through expert and piecemeal historical analyses. In this paper, we address the question from a complementary perspective: we target the content of one major journal of the field—Philosophy of Science—and apply unsupervised text-mining methods to its complete corpus, from its start in 1934 until 2015. By running topic-modeling algorithms over the full-text corpus, we identified 126 key research (...) topics that span across 82 years. We also tracked their evolution and fluctuating significance over time in the journal articles. Our results concur with and document known and lesser-known episodes of the philosophy of science, including the rise and fall of logic and language-related topics, the relative stability of a metaphysical and ontological questioning (space and time, causation, natural kinds, realism), the significance of epistemological issues about the nature of scientific knowledge as well as the rise of a recent philosophy of biology and other trends. These analyses exemplify how computational text-mining methods can be used to provide an empirical large-scale and data-driven perspective on the history of philosophy of science that is complementary to other current historical approaches. (shrink)

This article introduces some soft computing methods generally used for data analysis and flow pattern detection in fluid dynamics. These techniques decompose the original flow field as an expansion of modes, which can be either orthogonal in time, or in space or in time and space, or they can simply be selected using some sophisticated statistical techniques. The performance of these methods is tested in the turbulent wake of a wall-mounted square cylinder. This highly complex flow is suitable to show (...) the ability of the aforementioned methods to reduce the degrees of freedom of the original data by only retaining the large scales in the flow. The main result is a reduced-order model of the original flow case, based on a low number of modes. A deep discussion is carried out about how to choose the most computationally efficient method to obtain suitable reduced-order models of the flow. The techniques introduced in this article are data-driven methods that could be applied to model any type of non-linear dynamical system, including numerical and experimental databases. (shrink)

Much of cognitive psychology focuses on effects measured in tens of milliseconds while significant educational outcomes take tens of hours to achieve. The task of bridging this gap is analyzed in terms of Newell's (1990) bands of cognition—the Biological, Cognitive, Rational, and Social Bands. The 10 millisecond effects reside in his Biological Band while the significant learning outcomes reside in his Social Band. The paper assesses three theses: The Decomposition Thesis claims that learning occurring at the Social Band can be (...) reduced to learning occurring at lower bands. The Relevance Thesis claims that instructional outcomes at the Social Band can be improved by paying attention to cognition at the lower bands. The Modeling Thesis claims that cognitive modeling provides a basis for bridging between events on the small scale and desired outcomes on the large scale. The unit-task level, at the boundary of the Cognitive and Rational Bands, is useful for assessing these theses. There is good evidence for all three theses in efforts that bridge from the unit-task level to educational applications. While there is evidence for the Decomposition Thesis all the way down to the 10 millisecond level, more work needs to be done to establish the Relevance Thesis and particularly the Modeling Thesis at the lower levels. (shrink)

Musical rhythm abilities—the perception of and coordinated action to the rhythmic structure of music—undergo remarkable change over human development. In the current paper, we introduce a theoretical framework for modeling the development of musical rhythm. The framework, based on Neural Resonance Theory, explains rhythm development in terms of resonance and attunement, which are formalized using a general theory that includes non-linear resonance and Hebbian plasticity. First, we review the developmental literature on musical rhythm, highlighting several developmental processes related to (...) rhythm perception and action. Next, we offer an exposition of Neural Resonance Theory and argue that elements of the theory are consistent with dynamical, radically embodied and ecological approaches to cognition and development. We then discuss how dynamical models, implemented as self-organizing networks of neural oscillations with Hebbian plasticity, predict key features of music development. We conclude by illustrating how the notions of dynamical embodiment, resonance, and attunement provide a conceptual language for characterizing musical rhythm development, and, when formalized in physiologically informed dynamical models, provide a theoretical framework for generating testable empirical predictions about musical rhythm development, such as the kinds of native and non-native rhythmic structures infants and children can learn, steady-state evoked potentials to native and non-native musical rhythms, and the effects of short-term, long-term, and very-long term learning on music perception-action. (shrink)

Pantographs are important devices on high-speed trains. When a train runs at a high speed, concave and convex parts of the train cause serious airflow disturbances and result in flow separation, eddy shedding, and breakdown. A strong fluctuation pressure field will be caused and transformed into aerodynamic noises. When high-speed trains reach 300 km/h, aerodynamic noises become the main noise source. Aerodynamic noises of pantographs occupy a large proportion in far-field aerodynamic noises of the whole train. Therefore, the problem of (...) aerodynamic noises for pantographs is outstanding among many aerodynamics problems. This paper applies Detached Eddy Simulation to conducting numerical simulations of flow fields around pantographs of high-speed trains which run in the open air. Time-domain characteristics, frequency-domain characteristics, and unsteady flow fields of aerodynamic noises for pantographs are obtained. The acoustic boundary element method is used to study noise radiation characteristics of pantographs. Results indicate that eddies with different rotation directions and different scales are in regions such as pantograph heads, hinge joints, bottom frames, and insulators, while larger eddies are on pantograph heads and bottom frames. These eddies affect fluctuation pressures of pantographs to form aerodynamic noise sources. Slide plates, pantograph heads, balance rods, insulators, bottom frames, and push rods are the main aerodynamic noise source of pantographs. Radiated energies of pantographs are mainly in mid-frequency and high-frequency bands. In high-frequency bands, the far-field aerodynamic noise of pantographs is mainly contributed by the pantograph head. Single-frequency noises are in the far-field aerodynamic noise of pantographs, where main frequencies are 293 Hz, 586 Hz, 880 Hz, and 1173 Hz. The farther the observed point is from the noise source, the faster the sound pressure attenuation will be. When the distance of two adjacent observed points is increased by double, the attenuation amplitude of sound pressure levels for pantographs is around 6.6 dB. (shrink)

We introduce a new version of the perceptual retouch model. This model was used for explaining properties of temporal interaction of successive objects in reaching conscious representation. The new model incorporates two interactive binding operations – binding features for objects and binding the bound feature-objects with a large scale oscillatory system that corresponds to perceptual consciousness. Here, the typical result of masking experiments – second object advantage in conscious perception – is achieved by applying the effects of a common synchronizing (...) oscillator with a delay. This delayed modulation of each of the feature-binding first-order oscillators that represent emerging and decaying neural activities of each of the objects guarantees that the oscillating synchrony of the feature-neurons of the following object is higher than the synchrony of the feature-neurons of the first presented object. Thus we model the fact that the following object dominates the preceding object in conscious perception. We also show the capacity of the model to simulate illusory misbinding of features from different objects. The third qualitative effect, the relative release of the first object from backward masking is achieved by priming the non-specific oscillatory modulation ahead in time. (shrink)

Enzymatic misrepair of ionizing‐radiation‐induced DNA damage can produce large‐scale rearrangements of the genome, such as translocations and dicentrics. These and other chromosome exchange aberrations can cause major phenotypic alterations, including cell death, mutation and neoplasia. Exchange formation requires that two (or more) genomic loci come together spatially. Consequently, the surprisingly rich aberration spectra uncovered by recently developed techniques, when combined with biophysically based computer modeling, help characterize large‐scale chromatin architecture in the interphase nucleus. Most results are consistent (...) with a picture whereby chromosomes are mainly confined to territories, chromatin motion is limited, and interchromosomal interactions involve mainly territory surfaces. Aberration spectra and modeling also help characterize DNA repair/misrepair mechanisms. Quantitative results for mammalian cells are best described by a breakage‐and‐reunion model, suggesting that the dominant recombinational mechanism during the G0/G1 phase of the cell cycle is non‐homologous end‐joining of radiogenic DNA double strand breaks. In turn, better mechanistic and quantitative understanding of aberration formation gives new insights into health‐related applications. BioEssays 24:714–723, 2002. © 2002 Wiley Periodicals, Inc. (shrink)

Adopting deep approaches to learning can have a profound impact on learning outcomes. The extent of change in the learning approach could be attributed to the effect of contextual factors. After a substantive review, it was found that research interested in investigating the longitudinal effect of deep approaches to learning on learning outcomes were rarely directly concerned with the longitudinal state and trend of the approach itself. Moreover, the limitations of past analytical methods, has not been appropriately acknowledged. This study (...) examined deep approaches to learning in students from kindergarten to third grade using a multilevel structural equation modeling indicator-specific growth model. This was used to highlight the methodological issues to investigate the effect of context and the states, stability, and changes in deep approaches to learning over this developmental period. The current study comprised of a large-scale sample of 21,490 kindergarteners in kindergarten. Results showed: there was a contextual effect on the longitudinal changes of deep approaches to learning; deep approaches to learning was high but showed considerable individual differences; most indicators relating to deep approaches to learning declined, whereas the trend were relatively stable over time. Corresponding suggestions were proposed at the end of this article. (shrink)

Prediction and control sufficient for reliable medical and other interventions are prominent aims of modeling in systems biology. The short-term attainment of these goals has played a strong role in projecting the importance and value of the field. In this paper I identify the standard models must meet to achieve these objectives as predictive robustness—predictive reliability over large domains. Drawing on the results of an ethnographic investigation and various studies in the systems biology literature, I explore four current obstacles (...) to achieving predictive robustness; data constraints, parameter uncertainty, collaborative constraints and system-scale requirements. I use a case study and the commentary of systems biologists themselves to show that current practices in the field, rather than pursuing these goals, frequently use models heuristically to investigate and build understanding of biological systems that do not meet standards of predictive robustness but are nonetheless effective uses of computation. A more heuristic conception of modeling allows us to interpret current practices as ways that manage these obstacles more effectively, particularly collaborative constraints, such that modelers can in the long-run at least work towards prediction and control. (shrink)

AimResting state functional magnetic resonance imaging was used to analyze changes in functional connectivity within various brain networks and functional network connectivity among various brain regions in patients with high myopia.Methodsrs-fMRI was used to scan 82 patients with HM and 59 healthy control volunteers matched for age, sex, and education level. Fourteen resting state networks were extracted, of which 11 were positive. Then, the FCs and FNCs of RSNs in HM patients were examined by independent component analysis.ResultsCompared with the HC (...) group, FC in visual network 1, dorsal attention network, auditory network 2, visual network 3, and sensorimotor network significantly increased in the HM group. FC in default mode network 1 significantly decreased. Furthermore, some brain regions in default mode network 2, default mode network 3, auditory network 1, executive control network, and significance network increased while others decreased. FNC analysis also showed that the network connection between the default mode network and cerebellar network was enhanced in the HM group.ConclusionCompared with HCs, HM patients showed neural activity dysfunction within and between specific brain networks, particularly in the DMN and CER. Thus, HM patients may have deficits in visual, cognitive, and motor balance functions. (shrink)

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These (...) regularities have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (shrink)

In the nation of Belize, and in particular the south side of Belize City, the main metropolitan area of the nation, significant economic disparities have led to child and adolescent exposure to high rates of violent crime, gang activity, unsafe neighborhoods, sexual, and physical violence. Problems associated with poor Social-Emotional Character Development are especially prevalent among boys. Consequently, valid culture-relevant measures are required that identify problematic behavior for policy-based intervention and evaluation of educational programs designed to ameliorate this problem. The (...) present study demonstrates the application of Exploratory Structural Equation Modeling to existing measures through the investigation of structural validity and generalizability of the Social-Emotional and Character Development Scale with a large sample of children from schools in Belize. Exploratory structural equation modeling results demonstrate the original factor correlations were reduced, providing less biased estimates than confirmatory factor analysis. Moreover, a multi-group Exploratory Structural Equation Modeling analysis illuminates significant differences between latent factor scores of males and females for most factors. Using this newer factor analytic procedure, original factors are reconceptualized to better situate the Social Emotional Character Development Scales into the larger body of Social-Emotional Learning competencies literature. (shrink)

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These (...) regularities have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (shrink)

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These (...) regularities have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (shrink)

This book originated at a small and informal workshop held in December of 1992 in Idyllwild, a relatively secluded resort village situated amid forests in the ...

Solar radiation management (SRM) may help to reduce the negative outcomes of climate change by minimising or reversing global warming. However, many express the worry that SRM may pose a moral hazard, i.e., that information about SRM may lead to a reduction in climate change mitigation efforts. In this paper, we report a large-scale preregistered, money-incentivised, online experiment with a representative US sample (N = 2284). We compare actual behaviour (donations to climate change charities and clicks on climate change petition (...) links) as well as stated preferences (support for a carbon tax and self-reported intentions to reduce emissions) between participants who receive information about SRM with two control groups (a salience control that includes information about climate change generally and a content control that includes information about a different topic). Behavioural choices are made with an earned real-money endowment, and stated preference responses are incentivised via the Bayesian Truth Serum. We fail to find a significant impact of receiving information about SRM and, based on equivalence tests, we provide evidence in favour of the absence of a meaningfully large effect. Our results thus provide evidence for the claim that there is no detectable moral hazard with respect to SRM. [Open access]. (shrink)

Modelling and simulations have gained a leading position in contemporary attempts to describe, explain, and quantitatively predict the human brain's operations. Computer models are highly sophisticated tools developed to achieve an integrated knowledge of the brain with the aim of overcoming the actual fragmentation resulting from different neuroscientific approaches. In this paper we investigate plausibility of simulation technologies for emulation of consciousness and the potential clinical impact of large-scale brain simulation on the assessment and care of disorders of consciousness, e.g. (...) Coma, Vegetative State/Unresponsive Wakefulness Syndrome, Minimally Conscious State.Notwithstanding their technical limitations, we suggest that simulation technologies may offer new solutions to old practical problems, particularly in clinical contexts. We take DOCs as an illustrative case, arguing that the simulation of neural correlates of consciousness is potentially useful for improving treatments of patients with DOCs. (shrink)

A prominent historiographic theme in the past decade has been a movement away from causal explanation of large-scale processes and outcomes and toward narrative interpretation of singular historical processes. This article argues for the continued vitality of large-scale historical inquiry and surveys the historiographic issues that arise in large-scale historical explanation. The article proceeds through an examination of several important recent examples of large-scale history: comparative history of Europe and China, the history of alternative forms of industrial organization, and the (...) history of technology. These three cases provide the basis for a conception of what may be called "conjunctural contingent meso-level" explanations: explanations that identify intermediate-level structures and processes and highlight both the structural factors that govern change and the multiple pathways that change can take. (shrink)

Timetabling problems are specific types of scheduling problems that deal with assigning certain events to the timeslots. This assigning is subject to certain hard constraints that should be achieved to get a feasible timetable and soft constraints that must meet as many as possible during forming a feasible schedule. This paper introduces an adaptive tabu search. Eleven benchmark datasets of the year 2002 are applied to show the effectiveness of the introduced algorithm. These datasets consist of 5-small, 5-medium, and 1-large (...) dataset. As compared to other methods from previous works, the proposed algorithm produces excellent timetables, in comparison with the algorithms as well as the current results, the mathematical results showed the high effectiveness of the suggested algorithm. It has a minor deficit on the medium or the small problem adaptive Tabu, and the tabu search relies on the tabu list and penalty cost when the change in the penalty cost is checked; if it is still unchanged for the period of iterations (1,000 iterations), the tabu list reduces automatically by (−2); furthermore, the tabu list remains constant. (shrink)

In this paper we analyse the degree to which a distinction between social science and public health research and other non-research activities can account for differences between a number of large scale social surveys performed at the national and European level. The differences we will focus on are differences in how participation is elicited and how data are used for government, research and other purposes. We will argue that the research / non-research distinction does not account for the identified differences (...) in recruitment or use and that there are no other convincing justifications. We argue that this entails that eliciting participation by coercion or manipulation becomes very difficult to justify. (shrink)

At the global as well as local scales, some of the geometry of types of neuron arbors—both dendrites and axons—appears to be self-organizing: Their morphogenesis behaves like flowing water, that is, fluid dynamically; waterflow in branching networks in turn acts like a tree composed of cords under tension, that is, vector mechanically. Branch diameters and angles and junction sites conform significantly to this model. The result is that such neuron tree samples globally minimize their total volume—rather than, for example, surface (...) area or branch length. In addition, the arbors perform well at generating the cheapest topology interconnecting their terminals: their large-scale layouts are among the best of all such possible connecting patterns, approaching 5% of optimum. This model also applies comparably to arterial and river networks. S1063-651X 99 16205-6.. (shrink)

In recent years, a number of research projects have been proposed whose goal is to build large-scale simulations of brain mechanisms at unprecedented levels of biological accuracy. Here it is argued that the roles these simulations are expected to play in neuroscientific research go beyond the “synthetic method” extensively adopted in Artificial Intelligence and biorobotics. In addition we show that, over and above the common goal of simulating brain mechanisms, these projects pursue various modelling ambitions that can be sharply distinguished (...) from one another, and that correspond to conceptually different interpretations of the notion of “biological accuracy”. They include the ambition to reach extremely deep levels in the mechanistic decomposition hierarchy, to simulate networks composed of extremely large numbers of neural units, to build systems able to generate rich behavioural repertoires, to simulate “complex” neuron models, to implement the “best” theories available on brain structure and function. Some questions will be raised concerning the significance of each of these modelling ambitions with respect to the various roles played by simulations in the study of the brain. (shrink)

A number of research projects have recently taken up the challenge of formulating large-scale models of brain mechanisms at unprecedented levels of detail. These research enterprises have raised lively debates in the press and in the scientific and philosophical literature, some of them revolving around the question whether the incorporation of so many details in a theoretical model and in a computer simulations of it is really needed for the model to be explanatory. Is there a “right” level of detail? (...) In this article I analyse the claim, made by two leading neuroscientists, according to which the content of the why-question addressed and the amount of computational resources available constrains the choice of the most appropriate level of detail in brain modelling. Based on the recent philosophical literature on scientific explanation, I distinguish between two kinds of details, called here mechanistic decomposition and property details, and argue that the nature of the why-question provides only partial constraints to the choice of the most appropriate level of detail under the two interpretations of the term considered here. (shrink)

In this article, I argue that experimental ethics – like experimental economics – should also concern itself with field experiments. In particular, I defend two claims: a) that philosophers in normative ethics could considerably narrow down their disputes if they could agree on a wider range of socio-economic facts; and that b) the socio-economic facts that would be needed for this could only be generated by deliberate large-scale social experimentation. This essay normatively grounds my interest in special administration zones.

In the Modern Synthesis, the ontology of species is context-dependent: species are seen as "individuals" at any instant in geological time; through time, species-lineages are class-like entities regularly transforming themselves into other, descendant species. Moreover, at any one instant in time, species are predominantly construed as reproductive communities; through time, they are seen as economic entities, bound together by the joint possession of anatomical similarities among constituent organisms. It is argued that a more complete picture sees species as spatiotemporally bounded (...) historical "individuals", hence as reproductive communities in time as well as space; that species are not economic units; and that a complete evolutionary theory must address large-scale economic units as well as large-scale informational units, visualizing particular instances of such hierarchically arranged classes as spatiotemporally bounded historical entities -- i.e., as "individuals". (shrink)

Large-scale land acquisition (LaSLA) in developing countries is discussed controversially in both the media as well as academia: Opponents point to negative social and environmental consequences. By contrast, proponents conceive of LaSLA as much needed investment into the formerly neglected agricultural sector. This contribution aims at analyzing LaSLA’s environmental dimension against the background of strong sustainability. To this end, I will first introduce sustainable development as a normative concept based on claims for intra- and intergenerational justice. Subsequently, I will argue (...) in favor of a conception of strong sustainability and employ this conception in developing guidelines for the sustainable handling of natural capital. By outlining the main drivers and consequences of LaSLA, the contribution hopes to demonstrate that proponents conceive of LaSLA as a potential solution to several sustainability problems, notably answering growing worldwide demand for agricultural commodities by increasing agricultural yields, substituting agrofuels for fossil fuels and providing acreage for offsetting carbon emissions. Against this background I argue that if LaSLA causes environmental externalities, it actually increases the problems it is supposed to resolve. Thereby, I develop sustainability criteria in regard to LaSLA’s environmental consequences. (shrink)