A Campus Sustainability Service Program in the General Education Curriculum

This poster describes a proposal for the addition of a sustainability-based community service requirement to the general education curriculum to encourage systemic involvement in on-campus sustainability projects. Current support for the University of Richmond’s (UR) goal to integrate sustainability across various University functions is limited and this poster outlines the Campus Sustainability Service (CSS) program as an option for addressing the issue to ensure the success of the UR Sustainability Strategic Plan. It presents a framework for the CSS program and a strategy for piloting the initiative that can support phasing in a complete version of the program over time. The poster also discusses how this proposal benefits the University and its students, staff, and faculty, emphasizing impacts on the school’s performance as an AASHE member, campus well-being, and student life outside of campus

Gold Standard for Green Spiders: Proposals for Excellence in Sustainability at the University of Richmond

The University of Richmond should commit to achieving the Gold Standard rating by the AASHE Campus Sustainability Index by 2024. Gold Standard for Green Spiders includes eight proposals that taken together, will move UR up from our current silver rating to gold. This volume also includes short summaries of the sustainability programs of eight of the top ten most sustainable liberal arts colleges in the nation. The eight student authors of these chapters completed their works as part of the Environmental Studies Senior Seminar course, the capstone course for Environmental Studies majors

Space radiation health research, 1991-1992

The present volume is a collection of 227 abstracts of radiation research sponsored by the NASA Space Radiation Health Program for the period 1991-1992. Each abstract has been categorized within one of three discipline areas: Physics, Biology and Risk Assessment. Topic areas within each discipline have been assigned as follows: Physics - Atomic Physics, Theory, Cosmic Ray and Astrophysics, Experimental, Environments and Environmental Models, Solar Activity and Prediction, Experiments, Radiation Transport and Shielding, Theory and Model Development, Experimental Studies, and Instrumentation. Biology - Biology, Molecular Biology, Cellular Radiation Biology, Transformation, Mutation, Lethality, Survival, DNA Damage and Repair, Tissue, Organs, and Organisms, In Vivo/In Vitro Systems, Carcinogenesis and Life Shortening, Cataractogenesis, Genetics/Developmental, Radioprotectants, Plants, and Other Effects. Risk Assessment - Risk Assessment, Radiation Health and Epidemiology, Space Flight Radiation Health Physics, Inter- and Intraspecies Extrapolation and Radiation Limits and Standards. Section I contains refereed journals; Section II contains reports/meetings. Keywords and author indices are provided. A collection of abstracts spanning the period 1986-1990 was previously issued as NASA Technical Memorandum 4270

MLPerf Inference Benchmark

Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organizations are building ML inference chips, and the systems that incorporate existing models span at least three orders of magnitude in power consumption and five orders of magnitude in performance; they range from embedded devices to data-center solutions. Fueling the hardware are a dozen or more software frameworks and libraries. The myriad combinations of ML hardware and ML software make assessing ML-system performance in an architecture-neutral, representative, and reproducible manner challenging. There is a clear need for industry-wide standard ML benchmarking and evaluation criteria. MLPerf Inference answers that call. In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than 30 organizations as well as more than 200 ML engineers and practitioners, MLPerf prescribes a set of rules and best practices to ensure comparability across systems with wildly differing architectures. The first call for submissions garnered more than 600 reproducible inference-performance measurements from 14 organizations, representing over 30 systems that showcase a wide range of capabilities. The submissions attest to the benchmark's flexibility and adaptability.Comment: ISCA 202

Third-party online organizational reviews: Explaining review-and-rating patterns of the United States military and large corporate organizations

Virtual spaces are a new and influential means by which present and past organizational members share reviews of their organizational experiences and socialize potential newcomers; however, online reviews can be negative and jeopardize an organization’s image. This investigation employed social identity theory and uncertainty management theory as a means of explaining patterned user ratings of organizational reviews online. In a first study, we content analyzed socialization storytelling about Basic Training on americangrit.com. Statistical analysis revealed that viewers rated stories more highly when the story portrayed the military favorably. In a second study, a content analysis of organizational reviews posted to indeed.com replicated and extended this pattern: Website visitors rewarded positive reviews of U.S. Military branches with higher ratings, while reviews of large corporate organizations (i.e., Apple, Bank of America, Michelin) varied. Implications for theory and practice conclude the paper.Financial support was provided from the Office of the Vice President for Research and Partnerships and the Office of the Provost, University of Oklahoma. Open Access fees paid for in whole or in part by the University of Oklahoma Libraries.Ye

Millennials in the Workplace: A Communication Perspective on Millennials’ Organizational Relationships and Performance

Stereotypes about Millennials, born between 1979 and 1994, depict them as self-centered, unmotivated, disrespectful, and disloyal, contributing to widespread concern about how communication with Millennials will affect organizations and how they will develop relationships with other organizational members. We review these purported characteristics, as well as Millennials’ more positive qualities—they work well in teams, are motivated to have an impact on their organizations, favor open and frequent communication with their supervisors, and are at ease with communication technologies. We discuss Millennials’ communicated values and expectations and their potential effect on coworkers, as well as how workplace interaction may change Millennials

Language and scientific communication: The case of the reprint request

This paper reports on a study of Reprint Requests (RRs). It is estimated that tens of millions of RRs are mailed each year, most being triggered by Current Contents . A sample of RRs generated by three papers, plus a questionnaire-survey of the requesters for one paper, form the basis of this study into language use patterns in the RR genre. English is ubiquitous, German and French infrequent, Russian and Spanish rare. This language data is significant because it provides unit-level language decision making (as opposed to that at other levels). Various applications of RR research are discussed, including its relevance to the issue of “Third World Science”.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43668/1/11192_2005_Article_BF02017177.pd

Automatically Harnessing Sparse Acceleration

Sparse linear algebra is central to many scientific programs, yet compilers fail to optimize it well. High-performance libraries are available, but adoption costs are significant. Moreover, libraries tie programs into vendor-specific software and hardware ecosystems, creating non-portable code. In this paper, we develop a new approach based on our specification Language for implementers of Linear Algebra Computations (LiLAC). Rather than requiring the application developer to (re)write every program for a given library, the burden is shifted to a one-off description by the library implementer. The LiLAC-enabled compiler uses this to insert appropriate library routines without source code changes. LiLAC provides automatic data marshaling, maintaining state between calls and minimizing data transfers. Appropriate places for library insertion are detected in compiler intermediate representation, independent of source languages. We evaluated on large-scale scientific applications written in FORTRAN; standard C/C++ and FORTRAN benchmarks; and C++ graph analytics kernels. Across heterogeneous platforms, applications and data sets we show speedups of 1.1$\times$ to over 10$\times$ without user intervention.Comment: Accepted to CC 202