1,721,078 research outputs found
500ns Trajectory Data for "Comparative Exploratory Analysis of Intrinsically Disordered Protein Dynamics Using Machine Learning and Network Analytic Methods," (Grazioli.et.al. 2019)
No full textThis data set currently contains two 100ns atomistic molecular dynamics trajectories of Abeta[1-40], one wild type and one E22G, following the protocol of the 500ns trajectories published in Grazioli et al. (2019). Simulation was performed at 310K in generalized Born implicit solvent; for additional details, see the associated paper. The 500ns trajectories will be added in a subsequent update to this archive
Replication Data for: Highly Scalable Maximum Likelihood and Conjugate Bayesian Inference for ERGMs on Graph Sets with Equivalent Vertices
No full textR code and data files to replicate analyses within the paper; note that use requires additional tools, including R and statnet (results were tested on ergm 4.1.2, and may vary otherwise). See the included README files for instructions
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Recommended from our members
Spectral Analysis: a New Perspective for Mining Human Activity Data
Get PDFThe pervasive usage of mobile phones provides an abundance of data associated with their users. Data generated by mobile devices includes measurements of user actions (e.g. call logs data, SMS logs data, app usage sessions data) as well as records regarding its local environment (e.g. data about other local blue tooth devices, GPS/location trajectories). These data provide information regarding the underlying behaviors of device users and their corresponding social contexts, thus giving us new opportunities for learning human spatio-temporal and social patterns.In this dissertation, new methods are developed to mine data generated by mobile devices and further improve applications in the area of social learning and inference. Particularly, three objectives are pursued here: (1) using mobile phone data to distinguish dyads embedded in social relationships from those that are not; (2) understanding how human telecommunication activities are associated with urban ecology; and (3) obtaining insights regarding users' demographic features from mobile app usage data. A key characteristic of these approaches is that they leverage activity and environmental data at the device level (in some cases, aggregated across sets of users), often allowing the data in question to be collected and stored in an efficient and privacy preserving manner. In pursuing the first objective, we introduce a new approach --\emph{activity correlation spectroscopy} -- to inferring relationships by exploiting the spectral and distributional structure of activity correlation within dyads. Unlike existing techniques, our approach can be employed with minimal, individual-level (i.e., non-relational), and non-identifying data that is easily collected using commodity hardware. We demonstrate our methodology via an application to detection of friendship and group co-membership using mobile device and survey data from the MIT Reality Mining study \citep{eagle2009}.Vis a vis the second objective, we provide a novel approach to the use of spatio-temporally aggregated cell phone data to learn features of urban ecology (i.e., spatial distributions of distinct social and economic entities and their associated activities). Specifically, our technique involves four stages: (\RN{1}) decomposing the aggregated cell phone activity within local areal units using spectral methods; (\RN{2}) learning spectral characteristics associated with ecological features using a training set; (\RN{3}) predicting local ecology composition for out-of-sample areas; and (\RN{4}) predicting activity time series for out-of-sample areas. The core of our approach is the projection of spectral features in cell phone activity series into an ecology-associated basis, allowing both identification of communication patterns arising from particular types of local activities and/or institutions and leveraging of those patterns for classification and activity prediction. We apply our methodology to aggregated communication and Internet traffic data from the cities of Milan and Trento to show the effectiveness of our method. Finally, in pursuing the third objective, we demonstrate an integrated system which can cheaply and easily collect application behavior and survey data from mobile phones; we introduce several novel features that assist the learning of individual level demographic features (e.g., gender and age group). Specifically, our approach for learning and inference for demographic features involves new techniques: (\RN{1}) decomposing the app usage from mobile phones using spectral methods; (\RN{2}) learning spectral characteristics associated with individuals using a training set; (\RN{3}) combining other temporal features with learned spectral characteristics to predict demographic features for out-of-sample individuals. The core of our methodology is the utilization of spectral features in cell phone app activity series, allowing both identification of behavior patterns arising from particular types of cell phone apps and leveraging of those patterns for demographic classification and prediction. We demonstrate the effectiveness of our approach with an application to real mobile app traffic data from the United States
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Recommended from our members
Frontier Problems in Modeling Dynamic Social Systems
Get PDFSocial dynamics – changes in the structure, existence or occurrence of social connections (e.g. sexual, friendship) or events (e.g. conversation, armed conflict) – are a core interest of social sciences (Comte, 1855; Weber, 1904; Marx and Engels, 1972). One key to understanding dynamic social systems is to understand the social networks that comprise these systems (Mayhew, 1984; Moreno, 1934). Modeling networks over time is of essential interest to understanding social systems and structure, from intimate sexual partnership ties (Lévi-Strauss, 1969; Morris and Kretzschmar, 1995; Hudson, 1993; Moody, 2002) to the interactions of large-scale organizations (Blau, 1970; Childers et al., 1971; Mayhew et al., 1972). Recently, advances in computing and statistical methodology have improved our ability to model relational dynamics. One such methodology is the exponential family models for modeling social networks (i.e. temporal exponential random graph models (TERGMs), see (Krivitsky and Handcock, 2014)). This thesis aims to improve our ability to model relational dynamics through a substantive exploration of a dynamic social system, a purely predictive imputation of edge dynamics among social media accounts, and an exploration of how a dynamic model handles temporal adjustments. I thus aim to address frontier problems in relational dynamics, to improve and extend our current models by both substantive application and methodology assessment
Recommended from our members
The Geography and Multiplexity of Personal Networks
Get PDFWhile the importance of geographic space in structuring social interactions is well established, much has remained unknown to researchers due in large part to the lack of available data on personal networks across space. Utilizing data from the American Social Fabric Study (Butts et al., 2014), a spatially stratified egocentric network study, this thesis aims to answer various methodological and substantive questions relating to networks and geography that have not been studied previously. The first paper is a methodological piece exploring what factors are related to the precision of geographic location of survey respondents (egos) as well as their social ties on six relations (alters). The second study examines an oft-studied social relation, that of the job seeking social tie, from a new perspective. In particular, we focus on the pool of potential job lead ties (rather than those that were mobilized) and study the relation in terms of multiplexity (i.e., the overlap of social relations) and locality to ego. The final paper examines another vital social relation: the ties that ego would seek to notify in the event of a disaster or emergency affecting his or her area. Given that this type of phenomenon is inherently spatial, we seek to understand the extent to which these ties are both spatially and socially embedded
Recommended from our members
Using Network Models to Relate Local Interactions with Global Topology: Applications to Protein Interactions and Emergent Multi-Body Structures
Get PDFLocal interactions within and between proteins (or interacting objects in general) inherently determine the resulting global structure, whether that be a monomeric protein structure, a dimer or multimer, or a larger aggregate consisting of tens to thousands of proteins. For proteins, structure is canonically partitioned into four levels: primary, which describes the sequence of residues that make up the protein; secondary, the α-helices and β-sheets that result from hydrogen-bonding interactions between residues; tertiary, which describes (somewhat arbitrarily defined) domains of clustered secondary structures that are typically held together with salt-bridges; and finally, quaternary structures composed of multiple proteins interacting via hydrogen-bonding or other polar interactions. Variants are proteins with point mutations, or mutations occurring to a small number (typically one) of the amino acids in the primary structure. Point mutations can alter the higher-order structure and dynamics of the protein, and thus how it responds to its environment, making it susceptible to evolutionary forces that dampen or put emphasis on a given variant. Such changes in structure and dynamics can range from subtle deformations to changes in the way the protein folds, inhibiting function. Mutations that are favored by evolution provide information about how the protein’s relationship with its environment affects its function and applies pressure to the adaptative evolution of the protein. The effects of mutations on protein structure, function, and interactions are explored in chapters two and three of this text. To contrast, the fourth chapter takes a generalized approach by delving into the range of emergent multi-body structures that can arise from slight changes in environmental or structural parameters while remaining agnostic to any specific features of a single protein sequence
- …
