Playing the Odds: Pascal’s Wager and Decision Making in the Long Scholarly Conversation

This talk explores some of the philosophical issues surrounding the nature of the scholarly record and current challenges in academic libraries. The discussion arises from a 2011 Chronicle of Higher Education feature on a widely influential 1979 article entitled “Prospect Theory: An Analysis of Decision Making Under Risk,” which proposed a new model for how people assess risk and weigh decision factors. The theory has been applied to dozens of disciplines and cited thousands of times, and it has applications in academic collection development as well as everywhere else. It addressed the limitations of Utility Theory, which grew out of Pascal’s Wager (i.e., it’s safer to bet on the existence of God), but didn’t adequately explain how people— gamblers and insurance buyers, for instance—actually weigh risks and make decisions. The pace of change and new demands facing libraries offer the opportunity to ask new questions about the nature of the scholarly record. Increasing ubiquity and transience of information, along with rapidly shifting notions of authorship and ownership, offer some interesting questions about the role of academic library collections in scholarly communication as a whole

Graduate Recital: Douglas Black

Kemp Recital HallMarch 9, 2012Friday Evening8:00 p.m

Graduate Recital: Douglas Black, Jr.

Kemp Recital HallNovember 29, 2012Thursday Evening8:00 p.m

Written corrective feedback: preferences and justifications of teachers and students in a Thai context

This study investigates the preferences and justifications of teachers and students on written corrective feedback (WCF) at a tertiary institution in Thailand and is aimed at expanding on prior similar studies conducted with smaller data sets in different contexts. Quantitative and qualitative questionnaire data were collected from 262 intermediate students and 21 teachers in order to test two hypotheses: (1) teachers’ and students’ WCF preferences would differ significantly, and (2) their justifications for their preferences would differ significantly. The hypotheses were confirmed: teachers rated indirect feedback with metalinguistic comment as being most useful while students most preferred direct feedback with metalinguistic comment. This trend extended to all types of direct feedback being preferred by students while teachers preferred all types of indirect feedback. The most common explanation for the teachers’ preferences was the development of metacognitive skills, while accuracy was the greatest concern for students. The pedagogical implications of the results regarding expectations, student agency, and self-efficacy are discussed

Estimating the Benefits of Electric Vehicle Smart Charging at Non-Residential Locations: A Data-Driven Approach

In this paper, we use data collected from over 2000 non-residential electric vehicle supply equipments (EVSEs) located in Northern California for the year of 2013 to estimate the potential benefits of smart electric vehicle (EV) charging. We develop a smart charging framework to identify the benefits of non-residential EV charging to the load aggregators and the distribution grid. Using this extensive dataset, we aim to improve upon past studies focusing on the benefits of smart EV charging by relaxing the assumptions made in these studies regarding: (i) driving patterns, driver behavior and driver types; (ii) the scalability of a limited number of simulated vehicles to represent different load aggregation points in the power system with different customer characteristics; and (iii) the charging profile of EVs. First, we study the benefits of EV aggregations behind-the-meter, where a time-of-use pricing schema is used to understand the benefits to the owner when EV aggregations shift load from high cost periods to lower cost periods. For the year of 2013, we show a reduction of up to 24.8% in the monthly bill is possible. Then, following a similar aggregation strategy, we show that EV aggregations decrease their contribution to the system peak load by approximately 40% when charging is controlled within arrival and departure times. Our results also show that it could be expected to shift approximately 0.25kWh (~2.8%) of energy per non-residential EV charging session from peak periods (12PM-6PM) to off-peak periods (after 6PM) in Northern California for the year of 2013.Comment: Pre-print, under review at Applied Energ

ISN’T THAT SPECIAL?: THE EPA’S SPECIAL-CASE DETERMINATION FOR THE LOS ANGELES RIVER EXTENDS CLEAN WATER ACT PROTECTIONS CAST IN DOUBT BY THE ARMY CORPS AND THE UNITED STATES SUPREME COURT

In an effort to examine the implications EPA’s ability to extend Clean Water Act protection through the use of its special-case determination authority, this Article provides a case study of the Los Angeles River and the regulatory interplay between the Army Corps and the EPA. To begin, Part I sets forth the factual background of the LA River, describing its fickle and often volatile physical nature. It then describes the legal framework underlying the case by providing an overview of the Clean Water Act, its shared administration by the EPA and Army Corps, and the basis for the EPA’s special-case authority. Part II then discusses the Army Corps’ initial TNW determination and the EPA’s subsequent application of its special authority to overrule the Army Corps’ determination, while highlighting the agencies’ differing treatment and characterization of evidence used in making the determination. Finally, Part III discusses the potentially far-reaching consequences of the River’s navigability determination within the context of Southern California

De novo prediction of PTBP1 binding and splicing targets reveals unexpected features of its RNA recognition and function.

The splicing regulator Polypyrimidine Tract Binding Protein (PTBP1) has four RNA binding domains that each binds a short pyrimidine element, allowing recognition of diverse pyrimidine-rich sequences. This variation makes it difficult to evaluate PTBP1 binding to particular sites based on sequence alone and thus to identify target RNAs. Conversely, transcriptome-wide binding assays such as CLIP identify many in vivo targets, but do not provide a quantitative assessment of binding and are informative only for the cells where the analysis is performed. A general method of predicting PTBP1 binding and possible targets in any cell type is needed. We developed computational models that predict the binding and splicing targets of PTBP1. A Hidden Markov Model (HMM), trained on CLIP-seq data, was used to score probable PTBP1 binding sites. Scores from this model are highly correlated (ρ = -0.9) with experimentally determined dissociation constants. Notably, we find that the protein is not strictly pyrimidine specific, as interspersed Guanosine residues are well tolerated within PTBP1 binding sites. This model identifies many previously unrecognized PTBP1 binding sites, and can score PTBP1 binding across the transcriptome in the absence of CLIP data. Using this model to examine the placement of PTBP1 binding sites in controlling splicing, we trained a multinomial logistic model on sets of PTBP1 regulated and unregulated exons. Applying this model to rank exons across the mouse transcriptome identifies known PTBP1 targets and many new exons that were confirmed as PTBP1-repressed by RT-PCR and RNA-seq after PTBP1 depletion. We find that PTBP1 dependent exons are diverse in structure and do not all fit previous descriptions of the placement of PTBP1 binding sites. Our study uncovers new features of RNA recognition and splicing regulation by PTBP1. This approach can be applied to other multi-RRM domain proteins to assess binding site degeneracy and multifactorial splicing regulation