Asymptotic prime divisors of torsion-free symmetric powers of modules

AbstractLet R be a Noetherian ring, F:=Rr and M⊆F a submodule of rank r. Let A∗¯(M) denote the stable value of Ass(Fn/Mn¯), for n large, where Fn is the nth symmetric power of Fn and Mn is the image of the nth symmetric power of M in Fn. We provide a number of characterizations for a prime ideal to belong to A∗¯(M). We also show that A∗¯(M)⊆A∗(M), where A∗(M) denotes the stable value of Ass(Fn/Mn)

Multidimensional spectroscopy with a single broadband phase-shaped laser pulse

We calculate the frequency-dispersed nonlinear transmission signal of a phase-shaped visible pulse to fourth order in the field. Two phase profiles, a phase-step and phase-pulse, are considered. Two dimensional signals obtained by varying the detected frequency and phase parameters are presented for a three electronic band model system. We demonstrate how two-photon and stimulated Raman resonances can be manipulated by the phase profile and sign, and selected quantum pathways can be suppressed.Comment: 26 pages, 15 figure

Aligning Our Books to Our Patrons

Rice Majors is the Associate University Librarian for Collections & Scholarly Communication at Santa Clara University. In that role, he does research on the collection performance and especially the performance of print monographs, looking at the comparative performance of print monographs in different academic disciplines and with different collection development strategies at different academic institutions. He has also published on the comparative user experiences of catalog discovery layers. Glenn Johnson-Grau is Head of Acquisitions & Collection Development at Loyola Marymount University where he manages library acquisitions for books, periodicals, media, and electronic resources. His interests include consortial collaboration on print and electronic collection development and shared print retention projects, as well as the impact of campus politics on academic library activities

Aligning Our Books to Our Patrons

Three universities (Santa Clara University, University of San Francisco, Loyola Marymount University) have engaged in a multi-year project to leverage patron-initiated inter-library borrowing data to inform collection development. We now have three years of analyzing data for inter-library borrowing, spending, and circulation of local collections. In addition to establishing what a “normal” level of borrowing looks like, we have used this data to identify and fix gaps in our local collections; we also now have data on subsequent circulations of titles purchased as a result of this project. One original goal of the project was to strengthen the meta-collection of our consortium (LINK+) through the intentional and coordinated diversification of approval plan profiles, however, massive change in our consortium membership is also requiring us to evaluate the impact on our libraries of issues like increased inter-library lending, demonstrating the risks as well as the rewards of shared collection decision making. We will discuss methodology and findings to date: how data is being gathered, analyzed, and then used on our campuses to inform collection development decisions

Assessing the Books We Didn’t Buy (the Sequel)

Three universities (Santa Clara University, the University of San Francisco, and Loyola Marymount University) are leveraging patron-initiated borrowing data to inform our collection development. Expanding on a pilot project that began in 2014, we have been looking at five years of recent borrowing data, along with five years of acquisition data and five years of circulation data of local collections, to help us define what a “normal” level of borrowing looks like as well as identify gaps in local collections. We are also using the data to strengthen the meta-collection of our consortium (LINK+) through the intentional and coordinated diversification of approval plan profiles. We will discuss both methodology and findings to date: how this data is being gathered, analyzed, and then used on our campuses to inform collection development decisions

Concurrent Session, Project Compass: A Model for Transforming Campuses for Underserved Student Success

Funded by the Nellie Mae Education Foundation, Project Compass is a multi-campus, multi-year initiative. It supports four public, four-year colleges engaged in institution-level change essential to expanding, sustaining, and integrating rigorous, evidence-based efforts to retain underserved students. Presenters will discuss the development of campus-based communities of practice; the development of dynamic logic models assuring measurable outcomes; the formation of a cross-campus learning community; and the uniquely engaged, collaborative role established between the Foundation’s intermediary and funded campuses. They will also share formative findings. Participants will engage in a collaborative learning activity that applies the structure and underlying principles of the initiative to their home campuses. Discussion will include resources, questions, and promising practices for institutionalizing sustainable approaches to underserved student success

Disease transmission models for public health decision making: analysis of epidemic and endemic conditions caused by waterborne pathogens.

Developing effective policy for environmental health issues requires integrating large collections of information that are diverse, highly variable, and uncertain. Despite these uncertainties in the science, decisions must be made. These decisions often have been based on risk assessment. We argue that two important features of risk assessment are to identify research needs and to provide information for decision making. One type of information that a model can provide is the sensitivity of making one decision over another on factors that drive public health risk. To achieve this goal, a risk assessment framework must be based on a description of the exposure and disease processes. Regarding exposure to waterborne pathogens, the appropriate framework is one that explicitly models the disease transmission pathways of pathogens. This approach provides a crucial link between science and policy. Two studies--a Giardia risk assessment case study and an analysis of the 1993 Milwaukee, Wisconsin, Cryptosporidium outbreak--illustrate the role that models can play in policy making

An In Silico Approach for Evaluating a Fraction-Based, Risk Assessment Method for Total Petroleum Hydrocarbon Mixtures

Both the Massachusetts Department of Environmental Protection (MADEP) and the Total Petroleum Hydrocarbon Criteria Working Group (TPHCWG) developed fraction-based approaches for assessing human health risks posed by total petroleum hydrocarbon (TPH) mixtures in the environment. Both organizations defined TPH fractions based on their expected environmental fate and by analytical chemical methods. They derived toxicity values for selected compounds within each fraction and used these as surrogates to assess hazard or risk of exposure to the whole fractions. Membership in a TPH fraction is generally defined by the number of carbon atoms in a compound and by a compound's equivalent carbon (EC) number index, which can predict its environmental fate. Here, we systematically and objectively re-evaluate the assignment of TPH to specific fractions using comparative molecular field analysis and hierarchical clustering. The approach is transparent and reproducible, reducing inherent reliance on judgment when toxicity information is limited. Our evaluation of membership in these fractions is highly consistent (˜80% on average across various fractions) with the empirical approach of MADEP and TPHCWG. Furthermore, the results support the general methodology of mixture risk assessment to assess both cancer and noncancer risk values after the application of fractionation