Breaking the habit: measuring and predicting departures from routine in individual human mobility

Researchers studying daily life mobility patterns have recently shown that humans are typically highly predictable in their movements. However, no existing work has examined the boundaries of this predictability, where human behaviour transitions temporarily from routine patterns to highly unpredictable states. To address this shortcoming, we tackle two interrelated challenges. First, we develop a novel information-theoretic metric, called instantaneous entropy, to analyse an individual’s mobility patterns and identify temporary departures from routine. Second, to predict such departures in the future, we propose the first Bayesian framework that explicitly models breaks from routine, showing that it outperforms current state-of-the-art predictor

Tribute to Judge Duffy | Introduction

How can one (or in this case many) properly honor the memory of an iconic figure as compelling, complicated, and compassionate as the Honorable Kevin Thomas Duffy (aka “KTD” or “the Judge”)? I’m confident that I speak on behalf of the Judge’s entire law clerk family (aka “Hockey Pucks” in KTD’s vernacular)—as well as his many other friends and colleagues who were kind enough to contribute a sampling of their precious memories of the Judge to this collection of tributes—in stressing at the outset the impossibility of this task. Indeed, I’m certain the futility of even trying to scratch the surface of what a gift it was for KTD’s devoted community of Hockey Pucks to have spent our first years as lawyers under his daily tutelage was immediately apparent to each of us the moment we began this endeavor. But I also know that just attempting to do so, notwithstanding how quixotic the effort, has been a complete joy for all of us. Indeed, the common refrain I’ve heard from countless clerks over the last several weeks (as we’ve collectively tilted at this windmill) is, yet again, how grateful we all are to KTD. Remarkably, even as we commemorate the two-year anniversary of his passing, the Judge continues to be the catalyst for the welcomed reunification of his colleagues, friends, and mentees, who all leapt at the opportunity to participate in this wonderfully uplifting celebration of his life. And truth be told, we all really needed this, particularly during these challenging times when we are each craving the cathartic infusion of humanity and humor into our consciousness that this process has granted us, and which KTD so generously provided every day he was with us

Tribute to Judge Duffy | A View From Below

It is only natural that different people (clerks, colleagues, court reporters, lawyers, marshals, parties, et cetera) saw KTD differently (as a humorist, a “no nonsense” judge, a loyal friend, an iconoclast, an enigma, et cetera). I am deeply honored, as one of the Judge’s sons-at-law, to offer just a glimpse into what it was like to be within his orbit with a few illustrations of his unique manner and mind

Biogas Technology on Uzi Island, Zanzibar: A Feasibility Study

With realization of the finite quantity of fossil fuels and improved study on the effects of global climate change there has been an increasing demand for energy production from renewable, sustainable sources in developed and developing nations alike. The population of Tanzania relies overwhelmingly on biomass as a source of primary energy, with such impacts as deforestation and negative health effects. Biogas generation is a renewable energy technology that utilizes organic waste sources to produce a methane-rich gas suitable for cooking and lighting with the potential to replace current unsustainable energy sources and provide several environmental and socioeconomic benefits. A biogas feasibility study was conducted in the village of Uzi, Zanzibar through local surveys, a waste generation audit, and creation of a pilot biogas system. Currently, biogas technology is not feasible in Uzi due to economic and realistic barriers. Methods of financial aid such as government subsidy, microfinance, and a carbon credit system need to be explored in order to realize the potential of biogas technology in Uzi

Recurring cluster and operon assembly for Phenylacetate degradation genes

<p>Abstract</p> <p>Background</p> <p>A large number of theories have been advanced to explain why genes involved in the same biochemical processes are often co-located in genomes. Most of these theories have been dismissed because empirical data do not match the expectations of the models. In this work we test the hypothesis that cluster formation is most likely due to a selective pressure to gradually co-localise protein products and that operon formation is not an inevitable conclusion of the process.</p> <p>Results</p> <p>We have selected an exemplar well-characterised biochemical pathway, the phenylacetate degradation pathway, and we show that its complex history is only compatible with a model where a selective advantage accrues from moving genes closer together. This selective pressure is likely to be reasonably weak and only twice in our dataset of 102 genomes do we see independent formation of a complete cluster containing all the catabolic genes in the pathway. Additionally, <it>de novo </it>clustering of genes clearly occurs repeatedly, even though recombination should result in the random dispersal of such genes in their respective genomes. Interspecies gene transfer has frequently replaced <it>in situ </it>copies of genes resulting in clusters that have similar content but very different evolutionary histories.</p> <p>Conclusion</p> <p>Our model for cluster formation in prokaryotes, therefore, consists of a two-stage selection process. The first stage is selection to move genes closer together, either because of macromolecular crowding, chromatin relaxation or transcriptional regulation pressure. This proximity opportunity sets up a separate selection for co-transcription.</p

Historical Study in the U.S.: Assessing the Impact of Tuning within a Professional Disciplinary Society

The U.S.-based American Historical Association (AHA), the largest – and most influential – professional organization for historians, was the first disciplinary society in the world to lead a Tuning project, launching its work in 2012. This essay analyzes a survey distributed to historians on campuses that have taken part in the AHA Tuning project. The purpose is to understand, after six years of work on the project, what practical difference Tuning has made for historians, students, courses, curricula, and departments. Survey data indicate that, under the disciplinary society’s guidance and encouragement, historians have created meaningful learning outcomes, implemented the objectives in courses and curricula, and begun work in the measurement of student learning. Not surprisingly, the project has faced limits and obstacles, particularly with leadership of the work, faculty buy-in, administrative support, follow-up assistance, enrollment concerns, student engagement, and outreach to stakeholders. However, after half a dozen years of activity, U.S. historians have made marked progress not only in articulating disciplinary learning outcomes (as have colleagues in other parts of the world) but also in implementing and assessing those objectives. While precise readings of “impact” remain elusive, a Tuning project under the direction of a disciplinary society has helped generate significant pedagogical, curricular, and cultural changes in the field of history.

Models for pattern formation in somitogenesis: a marriage of cellular and molecular biology

Somitogenesis, the process by which a bilaterally symmetric pattern of cell aggregations is laid down in a cranio-caudal sequence in early vertebrate development, provides an excellent model study for the coupling of interactions at the molecular and cellular level. Here, we review some of the key experimental results and theoretical models related to this process. We extend a recent chemical pre-pattern model based on the cell cycle Journal of Theoretical Biology 207 (2000) 305-316, by including cell movement and show that the resultant model exhibits the correct spatio-temporal dynamics of cell aggregation. We also postulate a model to account for the recently observed spatio-temporal dynamics at the molecular level

Estimating changes in temperature extremes from millennial scale climate simulations using generalized extreme value (GEV) distributions

Changes in extreme weather may produce some of the largest societal impacts of anthropogenic climate change. However, it is intrinsically difficult to estimate changes in extreme events from the short observational record. In this work we use millennial runs from the CCSM3 in equilibrated pre-industrial and possible future conditions to examine both how extremes change in this model and how well these changes can be estimated as a function of run length. We estimate changes to distributions of future temperature extremes (annual minima and annual maxima) in the contiguous United States by fitting generalized extreme value (GEV) distributions. Using 1000-year pre-industrial and future time series, we show that the magnitude of warm extremes largely shifts in accordance with mean shifts in summertime temperatures. In contrast, cold extremes warm more than mean shifts in wintertime temperatures, but changes in GEV location parameters are largely explainable by mean shifts combined with reduced wintertime temperature variability. In addition, changes in the spread and shape of the GEV distributions of cold extremes at inland locations can lead to discernible changes in tail behavior. We then examine uncertainties that result from using shorter model runs. In principle, the GEV distribution provides theoretical justification to predict infrequent events using time series shorter than the recurrence frequency of those events. To investigate how well this approach works in practice, we estimate 20-, 50-, and 100-year extreme events using segments of varying lengths. We find that even using GEV distributions, time series that are of comparable or shorter length than the return period of interest can lead to very poor estimates. These results suggest caution when attempting to use short observational time series or model runs to infer infrequent extremes.Comment: 33 pages, 22 figures, 1 tabl

MultiPhyl: a high-throughput phylogenomics webserver using distributed computing

With the number of fully sequenced genomes increasing steadily, there is greater interest in performing large-scale phylogenomic analyses from large numbers of individual gene families. Maximum likelihood (ML) has been shown repeatedly to be one of the most accurate methods for phylogenetic construction. Recently, there have been a number of algorithmic improvements in maximum-likelihood-based tree search methods. However, it can still take a long time to analyse the evolutionary history of many gene families using a single computer. Distributed computing refers to a method of combining the computing power of multiple computers in order to perform some larger overall calculation. In this article, we present the first high-throughput implementation of a distributed phylogenetics platform, MultiPhyl, capable of using the idle computational resources of many heterogeneous non-dedicated machines to form a phylogenetics supercomputer. MultiPhyl allows a user to upload hundreds or thousands of amino acid or nucleotide alignments simultaneously and perform computationally intensive tasks such as model selection, tree searching and bootstrapping of each of the alignments using many desktop machines. The program implements a set of 88 amino acid models and 56 nucleotide maximum likelihood models and a variety of statistical methods for choosing between alternative models. A MultiPhyl webserver is available for public use at: http://www.cs.nuim.ie/distributed/multiphyl.php