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Search Results: 1 - 10 of 6825 matches for " Jeffrey Nichols "
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Why Are You More Engaged? Predicting Social Engagement from Word Use
Jalal Mahmud,Jilin Chen,Jeffrey Nichols
Computer Science , 2014,
Abstract: We present a study to analyze how word use can predict social engagement behaviors such as replies and retweets in Twitter. We compute psycholinguistic category scores from word usage, and investigate how people with different scores exhibited different reply and retweet behaviors on Twitter. We also found psycholinguistic categories that show significant correlations with such social engagement behaviors. In addition, we have built predictive models of replies and retweets from such psycholinguistic category based features. Our experiments using a real world dataset collected from Twitter validates that such predictions can be done with reasonable accuracy.
Home Location Identification of Twitter Users
Jalal Mahmud,Jeffrey Nichols,Clemens Drews
Computer Science , 2014,
Abstract: We present a new algorithm for inferring the home location of Twitter users at different granularities, including city, state, time zone or geographic region, using the content of users tweets and their tweeting behavior. Unlike existing approaches, our algorithm uses an ensemble of statistical and heuristic classifiers to predict locations and makes use of a geographic gazetteer dictionary to identify place-name entities. We find that a hierarchical classification approach, where time zone, state or geographic region is predicted first and city is predicted next, can improve prediction accuracy. We have also analyzed movement variations of Twitter users, built a classifier to predict whether a user was travelling in a certain period of time and use that to further improve the location detection accuracy. Experimental evidence suggests that our algorithm works well in practice and outperforms the best existing algorithms for predicting the home location of Twitter users.
Post-Newtonian Approximation in Maxwell-Like Form
Jeffrey D. Kaplan,David A. Nichols,Kip S. Thorne
Physics , 2008, DOI: 10.1103/PhysRevD.80.124014
Abstract: The equations of the linearized first post-Newtonian approximation to general relativity are often written in "gravitoelectromagnetic" Maxwell-like form, since that facilitates physical intuition. Damour, Soffel and Xu (DSX) (as a side issue in their complex but elegant papers on relativistic celestial mechanics) have expressed the first post-Newtonian approximation, including all nonlinearities, in Maxwell-like form. This paper summarizes that DSX Maxwell-like formalism (which is not easily extracted from their celestial mechanics papers), and then extends it to include the post-Newtonian (Landau-Lifshitz-based) gravitational momentum density, momentum flux (i.e. gravitational stress tensor) and law of momentum conservation in Maxwell-like form. The authors and their colleagues have found these Maxwell-like momentum tools useful for developing physical intuition into numerical-relativity simulations of compact binaries with spin.
Who Will Retweet This? Automatically Identifying and Engaging Strangers on Twitter to Spread Information
Kyumin Lee,Jalal Mahmud,Jilin Chen,Michelle Zhou,Jeffrey Nichols
Computer Science , 2014,
Abstract: There has been much effort on studying how social media sites, such as Twitter, help propagate information in different situations, including spreading alerts and SOS messages in an emergency. However, existing work has not addressed how to actively identify and engage the right strangers at the right time on social media to help effectively propagate intended information within a desired time frame. To address this problem, we have developed two models: (i) a feature-based model that leverages peoples' exhibited social behavior, including the content of their tweets and social interactions, to characterize their willingness and readiness to propagate information on Twitter via the act of retweeting; and (ii) a wait-time model based on a user's previous retweeting wait times to predict her next retweeting time when asked. Based on these two models, we build a recommender system that predicts the likelihood of a stranger to retweet information when asked, within a specific time window, and recommends the top-N qualified strangers to engage with. Our experiments, including live studies in the real world, demonstrate the effectiveness of our work.
Optimizing The Selection of Strangers To Answer Questions in Social Media
Jalal Mahmud,Michelle Zhou,Nimrod Megiddo,Jeffrey Nichols,Clemens Drews
Computer Science , 2014,
Abstract: Millions of people express themselves on public social media, such as Twitter. Through their posts, these people may reveal themselves as potentially valuable sources of information. For example, real-time information about an event might be collected through asking questions of people who tweet about being at the event location. In this paper, we explore how to model and select users to target with questions so as to improve answering performance while managing the load on people who must be asked. We first present a feature-based model that leverages users exhibited social behavior, including the content of their tweets and social interactions, to characterize their willingness and readiness to respond to questions on Twitter. We then use the model to predict the likelihood for people to answer questions. To support real-world information collection applications, we present an optimization-based approach that selects a proper set of strangers to answer questions while achieving a set of application-dependent objectives, such as achieving a desired number of answers and minimizing the number of questions to be sent. Our cross-validation experiments using multiple real-world data sets demonstrate the effectiveness of our work.
Recommending Targeted Strangers from Whom to Solicit Information on Social Media
Jalal Mahmud,Michelle X. Zhou,Nimrod Megiddo,Jeffrey Nichols,Clemens Drews
Computer Science , 2014,
Abstract: We present an intelligent, crowd-powered information collection system that automatically identifies and asks target-ed strangers on Twitter for desired information (e.g., cur-rent wait time at a nightclub). Our work includes three parts. First, we identify a set of features that characterize ones willingness and readiness to respond based on their exhibited social behavior, including the content of their tweets and social interaction patterns. Second, we use the identified features to build a statistical model that predicts ones likelihood to respond to information solicitations. Third, we develop a recommendation algorithm that selects a set of targeted strangers using the probabilities computed by our statistical model with the goal to maximize the over-all response rate. Our experiments, including several in the real world, demonstrate the effectiveness of our work.
Glomalin and Soil Aggregation under Six Management Systems in the Northern Great Plains, USA  [PDF]
Kristine A. Nichols, James Millar
Open Journal of Soil Science (OJSS) , 2013, DOI: 10.4236/ojss.2013.38043

The soil environment is linked to aboveground management including plant species composition, grazing intensity, levels of soil disturbance, residue management, and the length of time of a living plant is growing. Soil samples were collected under rangeland [native grass, rotational grazing (NGRG); tame grass, heavy grazing (TGRG); and tame grass, rotational grazing (TGHG)] and cropland [conventional till (CT); CT plus manure (CTM); and long term no till (NT)] systems. The rangeland systems were hypothesized to have higher glomalin content [measured as Bradford-reactive soil protein (BRSP)] and water stable aggregation (WSA) than the cropland systems. In addition, within both rangeland and cropland systems, BRSP and WSA were expected to decline with increased disturbance due to grazing or tillage and going from native to introduced plant species. Differences were detected for BRSP with NGRG and CTM having the highest values in range and cropland systems, respectively. However, the CTM system had higher BRSP values than one or both of the tame grass systems while the CT and NT systems had similar values. Correlation analysis showed strong relationships between all of the BRSP values and WSA.

The discovery of novel neuropeptides takes flight
Ruthann Nichols
Genome Biology , 2002, DOI: 10.1186/gb-2002-3-11-reviews1032
Abstract: Peptides synthesized in the nervous system serve as messengers and as modulators of numerous biological processes. Thus, it is important to understand how neuropeptides are produced and how they act, because inaccurate neuropeptide synthesis or signal transduction may result in organismal dysfunction or death. Knowledge of the structure of naturally occurring neuropeptides is required if we are to decipher how neuropeptide precursors are processed, to delineate their binding to receptors, and to identify their function(s).The amino-acid sequence of peptide precursors can be deduced from nucleotide sequence, but this approach does not reveal precisely what peptide is ultimately expressed. Although it is possible to predict what peptides may be processed from a precursor from putative proteolytic cleavage sites, not all conventional sites are used and processing can also occur at unconventional sites. In addition, nucleotide sequence does not provide information on the developmental or tissue-specific regulation of neuropeptide-precursor processing. Several neuropeptides can be encoded by a single gene, and processing of individual peptides from a common precursor can differ during development or between tissues.Another problem with predicting peptides from nucleotide sequence is that this yields only a putative primary sequence and does not identify post-translational modifications, which are often essential for neuropeptide activity. Historically, the primary structure of a peptide was determined by Edman degradation after it was purified to homogeneity, but purification is often a time-consuming procedure. The labile nature of post-translational modifications and the low abundance of neuropeptides also make it particularly challenging to isolate enough of a peptide to determine its structure. Thus, an efficient and effective method is needed if we are to determine the structures of naturally occurring peptides.Skold et al. [1] recently described a novel approach th
Laboratory quality control based on risk management
Nichols James
Annals of Saudi Medicine , 2011,
Abstract: Risk management is the systematic application of management policies, procedures, and practices to the tasks of analyzing, evaluating, controlling and monitoring risk (the effect of uncertainty on objectives). Clinical laboratories conduct a number of activities that could be considered risk management including verification of performance of new tests, troubleshooting instrument problems and responding to physician complaints. Development of a quality control plan for a laboratory test requires a process map of the testing process with consideration for weak steps in the preanalytic, analytic and postanalytic phases of testing where there is an increased probability of errors. Control processes that either prevent or improve the detection of errors can be implemented at these weak points in the testing process to enhance the overall quality of the test result. This manuscript is based on a presentation at the 2nd International Symposium on Point of Care Testing held at King Faisal Specialist Hospital in Riyadh, Saudi Arabia on October 12-13, 2010. Risk management principles will be reviewed and progress towards adopting a new Clinical and Laboratory Standards Institute Guideline for developing laboratory quality control plans based on risk management will be discussed.
Understanding the Funding Game: The Textual Coordination of Civil Sector Work
Naomi Nichols
The Canadian Journal of Sociology , 2008,
Abstract: This paper investigates how people's work for non-profit organizations, charities, grassroots collectives, and social justice organizations is organized by official funding processes. In my analysis, I attend to the different kinds of text-based knowledge that coordinate people's work across the civil sector. Engaging in discussions with participants about their work, I discover how an individual's ordinary documentary activities are articulated to institutional relations of accountability. Attending to text-driven accountability practices - practices increasingly taken up to justify and carry out all kinds of work in the civil sector - I investigate the ideological organization of people's work via the policy documents and textual application procedures of the Revenue Canada tax act with regard to Charitable Status and the Ontario Trillium Foundation funding application process.
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