Poisson-event-based analysis of cell proliferation.

A protocol for the assessment of cell proliferation dynamics is presented. This is based on the measurement of cell division events and their subsequent analysis using Poisson probability statistics. Detailed analysis of proliferation dynamics in heterogeneous populations requires single cell resolution within a time series analysis and so is technically demanding to implement. Here, we show that by focusing on the events during which cells undergo division rather than directly on the cells themselves a simplified image acquisition and analysis protocol can be followed, which maintains single cell resolution and reports on the key metrics of cell proliferation. The technique is demonstrated using a microscope with 1.3 μm spatial resolution to track mitotic events within A549 and BEAS-2B cell lines, over a period of up to 48 h. Automated image processing of the bright field images using standard algorithms within the ImageJ software toolkit yielded 87% accurate recording of the manually identified, temporal, and spatial positions of the mitotic event series. Analysis of the statistics of the interevent times (i.e., times between observed mitoses in a field of view) showed that cell division conformed to a nonhomogeneous Poisson process in which the rate of occurrence of mitotic events, λ exponentially increased over time and provided values of the mean inter mitotic time of 21.1 ± 1.2 hours for the A549 cells and 25.0 ± 1.1 h for the BEAS-2B cells. Comparison of the mitotic event series for the BEAS-2B cell line to that predicted by random Poisson statistics indicated that temporal synchronisation of the cell division process was occurring within 70% of the population and that this could be increased to 85% through serum starvation of the cell culture

Further Development of Event-Based Analysis of X-ray Polarization Data

An event-based maximum likelihood method for handling X-ray polarimetry data is extended to include the effects of background and nonuniform sampling of the possible position angle space. While nonuniform sampling in position angle space generally introduces cross terms in the uncertainties of polarization parameters that could create degeneracies, there are interesting cases that engender no bias or parameter covariance. When including background in Poisson-based likelihood formulation, the formula for the minimum detectable polarization (MDP) has nearly the same form as for the case of Gaussian statistics derived by Elsner et al. (2012) in the limiting case of an unpolarized signal. A polarized background is also considered, which demonstrably increases uncertainties in source polarization measurements. In addition, a Kolmogorov-style test of the event position angle distribution is proposed that can provide an unbinned test of models where the polarization angle in Stokes space depends on event characteristics such as time or energy.Comment: 8 pages, accepted for publication in the Astrophysical Journa

An Event-based Analysis Framework for Open Source Software Development Projects

The increasing popularity and success of Open Source Software (OSS) development projects has drawn significant attention of academics and open source participants over the last two decades. As one of the key areas in OSS research, assessing and predicting OSS performance is of great value to both OSS communities and organizations who are interested in investing in OSS projects. Most existing research, however, has considered OSS project performance as the outcome of static cross-sectional factors such as number of developers, project activity level, and license choice. While variance studies can identify some predictors of project outcomes, they tend to neglect the actual process of development. Without a closer examination of how events occur, an understanding of OSS projects is incomplete. This dissertation aims to combine both process and variance strategy, to investigate how OSS projects change over time through their development processes; and to explore how these changes affect project performance. I design, instantiate, and evaluate a framework and an artifact, EventMiner, to analyze OSS projects’ evolution through development activities. This framework integrates concepts from various theories such as distributed cognition (DCog) and complexity theory, applying data mining techniques such as decision trees, motif analysis, and hidden Markov modeling to automatically analyze and interpret the trace data of 103 OSS projects from an open source repository. The results support the construction of process theories on OSS development. The study contributes to literature in DCog, design routines, OSS development, and OSS performance. The resulting framework allows OSS researchers who are interested in OSS development processes to share and reuse data and data analysis processes in an open-source manner

Event-based analysis: Identifying and sequencing prehistoric activities in buried palimpsests. An example from Lake George, Australia.

This thesis presents a new methodology for sequencing behavioural events in sub-surface stone artefact assemblages. While methods have been previously presented for the identification of activities, often termed 'moments in time', these studies have focused on temporally bounded living floors, usually in cave environments. Buried assemblages in open landscapes often do not retain such coherence, and so the development of a methodology for identifying and sequencing behavioural events in mixed assemblages is needed. This study develops a method, here termed event-based analysis (EBA), for the temporal sequencing of discrete activities in undifferentiated stratigraphies with vertically distributed artefactual deposits, which then allows comparisons of prehistoric activities to be made across space and time. Event-based analysis draws on several methods previously presented in the literature, principally RMU analysis, life-history framework and refitting for the reunification of refuse from single stone-working activities and the construction of inferences regarding the reduction and flow of stone though a site. Event-based analysis relies on these methods for identifying and understanding discrete stone working activities. EBA then extends the applicability of these methods to the analysis of temporally deep buried assemblages by providing a method whereby identified knapping and discard events can be sequenced. This shifts the unit of analysis in buried palimpsests from the assemblage to the event, and allows comparisons to be built over time and space from this behaviourally meaningful unit. This thesis is concerned with how archaeologists make inferences about prehistoric cultures from the archaeological record. To this end, a new methodological framework, event-based analysis, is advanced which both guides the construction of evidence-led inferences regarding prehistoric behaviour, and promotes the comparison of those behavioural inferences for the purpose of producing generalisations concerning use of place (Schiffer 2011). Using EBA, this project examines the configuration of foraging economies and technologies in the Lake George area of south-eastern Australia. A detailed place-use history is built from the comparison of discrete knapping and discard events over time and space. This thesis thus contributes to the development of archaeological methodologies which seek to build detailed and meaningful ‘thick descriptions’ (sensu Geertz (1973)) which are firmly grounded in the evidence examined. The aim is to provide detailed descriptions of the human activities which produced the stone artefact assemblages; it is to elucidate the ‘delicacy of its distinctions, not the sweep of its abstractions’ (Geertz 1973:25)

Spatiotemporal correlations of handset-based service usages

We study spatiotemporal correlations and temporal diversities of handset-based service usages by analyzing a dataset that includes detailed information about locations and service usages of 124 users over 16 months. By constructing the spatiotemporal trajectories of the users we detect several meaningful places or contexts for each one of them and show how the context affects the service usage patterns. We find that temporal patterns of service usages are bound to the typical weekly cycles of humans, yet they show maximal activities at different times. We first discuss their temporal correlations and then investigate the time-ordering behavior of communication services like calls being followed by the non-communication services like applications. We also find that the behavioral overlap network based on the clustering of temporal patterns is comparable to the communication network of users. Our approach provides a useful framework for handset-based data analysis and helps us to understand the complexities of information and communications technology enabled human behavior.Comment: 11 pages, 15 figure

Discovering Clusters in Motion Time-Series Data

A new approach is proposed for clustering time-series data. The approach can be used to discover groupings of similar object motions that were observed in a video collection. A finite mixture of hidden Markov models (HMMs) is fitted to the motion data using the expectation-maximization (EM) framework. Previous approaches for HMM-based clustering employ a k-means formulation, where each sequence is assigned to only a single HMM. In contrast, the formulation presented in this paper allows each sequence to belong to more than a single HMM with some probability, and the hard decision about the sequence class membership can be deferred until a later time when such a decision is required. Experiments with simulated data demonstrate the benefit of using this EM-based approach when there is more "overlap" in the processes generating the data. Experiments with real data show the promising potential of HMM-based motion clustering in a number of applications.Office of Naval Research (N000140310108, N000140110444); National Science Foundation (IIS-0208876, CAREER Award 0133825

DScentTrail: A new way of viewing deception

The DScentTrail System has been created to support and demonstrate research theories in the joint disciplines of computational inference, forensic psychology and expert decision-making in the area of counter-terrorism. DScentTrail is a decision support system, incorporating artificial intelligence, and is intended to be used by investigators. The investigator is presented with a visual representation of a suspect‟s behaviour over time, allowing them to present multiple challenges from which they may prove the suspect guilty outright or receive cognitive or emotional clues of deception. There are links into a neural network, which attempts to identify deceptive behaviour of individuals; the results are fed back into DScentTrail hence giving further enrichment to the information available to the investigator

Against a Davidsonian analysis of copula sentences

Semantic research over the past three decades has provided impressive confirmation of Donald Davidsons famous claim that “there is a lot of language we can make systematic sense of if we suppose events exist” (Davidson 1980:137). Nowadays, Davidsonian event arguments are no longer reserved only for action verbs (as Davidson originally proposed) or even only for the category of verbs, but instead are widely assumed to be associated with any kind of predicate (e.g. Higginbotham 2000, Parsons 2000).1 The following quotation from Higginbotham and Ramchand (1997) illustrates the reasoning that motivates this move: "Once we assume that predicates (or their verbal, etc. heads) have a position for events, taking the many consequences that stem therefrom, as outlined in publications originating with Donald Davidson (1967), and further applied in Higginbotham (1985, 1989), and Terence Parsons (1990), we are not in a position to deny an event-position to any predicate; for the evidence for, and applications of, the assumption are the same for all predicates. (Higginbotham and Ramchand 1997:54)" In fact, since Davidson’s original proposal the burden of proof for postulating event arguments seems to have shifted completely, leading Raposo and Uriagereka (1995), for example, to the following verdict: "it is unclear what it means for a predicate not to have a Davidsonian argument (Raposo and Uriagereka 1995:182)" That is, Davidsonian eventuality arguments apparently have become something like a trademark for predicates in general. The goal of the present paper is to subject this view of the relationship between predicates and events to real scrutiny. By taking a closer look at the simplest independent predicational structure – viz. copula sentences – I will argue that current Davidsonian approaches tend to stretch the notion of events too far, thereby giving up much of its linguistic and ontological usefulness. More specifically, the paper will tackle the following three questions: 1. Do copula sentences support the current view of the inherent event-relatedness of predicates? 2. If not, what is a possible alternative to an event-based analysis of copula sentences? 3. What does this tell us about Davidsonian events? The paper is organized as follows: Section 2 first reviews current event-based analyses of copula sentences and then gives a brief summary of the Davidsonian notion of events. Section 3 examines the behavior of copula sentences with respect to some standard (as well as some new) eventuality diagnostics. Copula expressions will turn out to fail all eventuality tests. They differ sharply from state verbs like stand, sit, sleep in this respect. (The latter pass all eventuality tests and therefore qualify as true “Davidsonian state” expressions.) On the basis of these observations, section 4 provides an alternative account of copula sentences that combines Kim’s (1969, 1976) notion of property exemplifications with Ashers (1993, 2000) conception of abstract objects. Specifically, I will argue that the copula introduces a referential argument for a temporally bound property exemplification (= “Kimian state”). The proposal is implemented within a DRT framework. Finally, section 5 offers some concluding remarks and suggests that supplementing Davidsonian eventualities by Kimian states not only yields a more adequate analysis for copula expressions and the like but may also improve our treatment of events

Event Based Analysis of a Citizen Science Community: Are New and Non-sustained Users Included?

High turnover rates in online communities suggest the need for measures that move non-sustained community members towards sustained participation. Non-sustained members actively seek inclusion opportunities, but are often disappointed by the lack of access to existing members. One method of inclusion can be contact with existing members through dialogue on discussion boards. Understanding the structure of interactions between sustained and non-sustained members and can inform new strategies to address the high turnover rate and ensure community longevity. In this poster, we analyze the network structure of newcomer and existing member interaction through discussion posts. Through analysis of a citizen science community we ask: Are non-sustained and sustained participants engaged in conversations? The researcher analyzes the topological features of an affiliation network and centrality measures to determine the extent of interactions between these two groups. Finally, the researcher presents strategies to engage non-sustained participants in online.publishedye