Skip to main content Skip to navigation
Showcase Abstract 2020

Case Studies on Academic Library Virtual Reference (VR) Services

Case Studies on Academic Library Virtual Reference (VR) Services

Primary author: Christy Zlatos

Primary college/unit: Libraries
Campus: Pullman

Abstract:

Although VR services are performed in nearly every academic library as part of its overall library services, very little is known about individual library variations in services. In seven interviews with experts in the field, this work presents an overview of some best practices covering 7 broad groups of issues/concerns in the field including software/technology available, user satisfaction, staffing, consortia providers, marketing of the service, and the referral of library patrons to experts. The seven VR experts selected include one software company representative, the head of a state cooperative, and five academic librarians. In looking VR services in academic libraries, I hope to learn whether large VR services are different than smaller ones, what sorts of library workers best provide the service, how many libraries participate in consortia, what VR software libraries using, how libraries market these services, how libraries might target these services to specific populations (e.g., international students), and how libraries handle referrals (i.e., getting the library users hooked up with the expert they need). The finished report should provide snapshot of the industry in 2020 and shed some insight on some perennial issues.

Transforming Library Data to Wikidata in the Linked Data Environment

Transforming Library Data to Wikidata in the Linked Data Environment

Primary author: Lihong Zhu

Primary college/unit: Libraries
Campus: Pullman

Abstract:

Wikidata is a free, collaborative, multilingual database that collects structured data to provide support for Wikipedia, Wikimedia Commons, the other wikis of the Wikimedia movement, and to anyone in the world. (https://www.wikidata.org/wiki/Wikidata:Main_Page) Wikidata is not only a free collaborative knowledge base that is evolving with its community members and their needs; it is also a central place where data created by people from different cultures and languages can coexist. This study focused on three research questions: (1) What makes the Wikidata data model special in the linked data environment? (2) Why should libraries get involved with Wikidata? (3) What are issues and trends in transforming library data to Wikidata?

When Wide and Shallow Better than Narrow and Deep: Misinformation Correction across Social Media Platforms

When Wide and Shallow Better than Narrow and Deep: Misinformation Correction across Social Media Platforms

Primary author: Wenqing Zhao
Co-author(s): Mina Park
Faculty sponsor: mina.park@wsu.edu

Primary college/unit: Edward R. Murrow College of Communication
Campus: Pullman

Abstract:

Since social media has become a major platform of spreading misinformation and reinforcing misperception, scholars and practitioners have devoted to correct misleading content on social media. In line with these efforts, this study tries to figure out how to use social media effectively to combat misinformation. In particular, this study examines the effects of using multiple social media platforms in correcting vaccine misinformation compared to using a single social media platform given the consistent number of times of corrective message exposure. To test the hypotheses, a between-subjects online experiment was conducted. The results showed that people exposed to corrective messages on multiple social media platforms have higher level of positive evaluations for corrective messages and more positive attitudes toward vaccination compared to those exposed to the same messages on a single social media platform. The findings suggested that multi-platform correction is a promising technique for misinformation correction. This study has both theoretical and practical implications of misinformation correction and social media.

Narrative Theory in Gallery Design: It’s Use (Or Misuse) and Impact on Visitor Experience

Narrative Theory in Gallery Design: Its Use (Or Misuse) and Impact on Visitor Experience

Primary author: Carrie Vielle

Primary college/unit: Voiland College of Engineering and Architecture
Campus: Pullman

Abstract:

Narrative Theory’s origins lie in the fundamental understanding that storytelling is a basic human strategy for understanding our experience, Visitors in museum galleries naturally seek out and construct narratives – it’s essential in the meaning-making, understanding, and remembering process of museum material. Capitalizing on this visitor behavior, many contemporary exhibition designers create varying degrees of controlled, immersive narratives and participatory experiences designed to influence specific visitor understanding and experience.

The value of the application of narrative in exhibition design is a widely debated, multi-dimensional topic: is immersive storytelling controlled by exhibit designers truly beneficial to comprehensive understanding, or does a more discursive, free exploration of exhibition material and its consequent visitor-constructed narrative produce a more successful outcome? While this research will not answer that question directly, it will focus on defining design strategies employed to establish an immersive vs. discursive experience. The analyses and comparisons of a variety of exhibitions that represent either narrative approach will propose that a balance of immersive and discursive narrative approaches within a single exhibition design can potentially accommodate the benefits of both types of narrative construction. The key exhibition used to support this conclusion will be the world-wide traveling exhibition “Pompeii: The Immortal City.”

The Impact on Student Motivation to Engage in Behavioral Harm Reduction Practices

The Impact on Student Motivation to Engage in Behavioral Harm Reduction Practices

Primary author: Alex Steiner
Co-author(s): Oluwafemi Sunday; Patricia Maarhuis

Primary college/unit: Cougar Health Services/Health Promotion
Campus: Pullman

Abstract:

This research project evaluated the WSU IMPACT program’s effectiveness by measuring students’ motivation to engage in behavioral harm reduction practices regarding high-risk substance use, which in turn affects academic success. Student motivation was measured via four questions using a “level of importance” Likert scale associated with self-reported engagement in protective strategies, as well as participant willingness and intention to engage in these strategies. IMPACT is a harm reduction and psycho-education service provided to students mandated by the WSU Center for Community Standards sanction process for substance use violations. The purpose of this small group intervention is to administer a substance abuse BASICS (Brief Alcohol Screening and Intervention for College Students) program (1999) based on efficacious best practices identified in the CollegeAim Matrix report (2015). Analyses: Independent T-test and ANOVA of pre/post brief intervention results were conducted across two sessions and four pre/post time points (Alcohol group N = 252, Cannabis group N = 106). Results: Overall, across all four questions, significant differences were found between timepoints one and two as well as timepoints three and four, with an upward slope or increases in reported positive harm reduction behaviors post IMPACT intervention (Alcohol: F(1, 116) = 5043.15, p = .001; Cannabis: F(1, 38) = 848.64, p = .001) Conclusion: Per these self-reported data, the IMPACT intervention was effective in increasing motivation and intention for positive behavior change regarding high-risk substance use across multiple timepoints.

Measuring community and school district readiness for prevention using publicly available secondary data: Findings from a Delphi study

Measuring community and school district readiness for prevention using publicly available secondary data: Findings from a Delphi study

Primary author: Gitanjali Shrestha
Co-author(s): Laura Hill; Clara Hill
Faculty sponsor: Laura Hill

Primary college/unit: Agricultural, Human and Natural Resource Sciences
Campus: Pullman

Abstract:
Introduction: Readiness for prevention is an important factor in prevention program success; thus, measuring readiness is a key step in disseminating prevention programs. Existing measures of readiness are time and resource intensive. Thus, the identification of publicly available proxy variables for readiness will not only be more resource efficient, it will also help prevention efforts in which readiness data has not been prospectively collected. The purpose of this study was to use the Delphi technique to identify publicly available proxy variables for community and school district readiness.

Method: We conducted a three-round Delphi study with ten prevention experts across five states to garner expert consensus on publicly available variables that could be considered proxies for readiness. Round 1 consisted of expert interviews, while rounds 2 and 3 consisted of online surveys.

Results: Findings reveal that certain dimensions of community readiness can be assessed using publicly available secondary datasets. Results indicated that 17 variables across eight domains can be considered proxies for readiness. Six of these 17 variables are specific to school district readiness, while the remaining 11 are proxies for both community and school district readiness. The study also yielded interesting insights into readiness such as the distinction between proxy variables for readiness and contextual variables for readiness, as well as the overlap between community readiness variables and school district readiness variables.

Conclusion: The list of proxy readiness variables is especially useful in large-scale evaluations or in circumstances where limited resources prohibit the collection of readiness data.

Deep Neural Network a Posteriori Probability Detector for Two-dimensional Magnetic Recording

Deep Neural Network a Posteriori Probability Detector for Two-dimensional Magnetic Recording

Primary author: Jinlu Shen
Faculty sponsor: Benjamin Belzer, Krishnamoorthy Sivakumar

Primary college/unit: Voiland College of Engineering and Architecture
Campus: Pullman

Abstract:

The magnetic recording channel in hard disk drives is a binary inter-symbol interference (ISI) channel that typically adopts a linear minimum mean square error (MMSE) equalizer with partial response (PR) signaling followed by a trellis-based detector such as Bahl-Cocke-Jelinek-Raviv (BCJR) or Viterbi. In two-dimensional magnetic recording (TDMR), an array of heads read data from multiple adjacent tracks in order to equalize inter-track interference (ITI), which is severe in high density recording. The multi-track effects combined with pattern-dependent noise inherent to HDD recording channels lead to a trellis state explosion problem, when an auto-regressive model is used for pattern dependent noise prediction (PDNP). The detector complexity grows exponentially with ISI channel length I and noise predictor order L, and becomes impractical for more than two tracks.
As a solution, we propose a novel deep neural network (DNN). The DNN detector replaces the typical Viterbi-PDNP or BCJR-PDNP, directly outputs log likelihood ratios of the coded bits and iteratively exchanges them with a channel decoder to minimize decoded BER. Three DNN architectures are investigated – fully connected DNN, convolutional neural networks (CNN), and long short-term memory (LSTM). The DNN’s complexity is limited by employing MMSE equalizer pre-processing. The best performing DNN architecture, CNN, is selected for iterative decoding with a channel decoder. Simulation results on a realistic media model shows as much as 30.47% detector BER reduction, and as much as 21.72% areal density gain compared to a conventional system.

Straightlining in a Survey Assessing Behavioral Health Treatment Services in Washington State

Straightlining in a Survey Assessing Behavioral Health Treatment Services in Washington State

Primary author: Felix I. Rodriguez
Co-author(s): Rose Krebill-Prather; Kristen R. Petersen; Kent J. Miller

Primary college/unit: Edward R. Murrow College of Communication
Campus: Pullman

Abstract:
Straightlining, or non-differentiation in ratings across items, compromises the data quality of survey responses by introducing the possibility that satisficing or response bias has occurred. Recent studies on straightlining have examined the effects of demographic characteristics and mode of administration on this type of behavior. This study examines the extent of straightlining in survey responses of a sensitive population, using data from a statewide survey designed to evaluate publicly funded behavioral health services.

The Behavioral Health Enrollee Survey was administered in 2018 using a mixed-mode telephone/web design. Responses were collected from 2,135 randomly selected adults who received publicly funded behavioral health treatment services in Washington State from May through October of the preceding year.

First, the incidence of straightlining behavior is measured on four batteries of survey questions: quality of services, experience with services, perceived outcome of services, and feelings of being stigmatized. Then incidence of straightlining on each of these batteries is compared across groups by age, gender, minority status, behavioral health diagnosis, and mode of survey administration.

Preliminary results suggest straightlining occurs on each of the four batteries of questions. However, the extent to which straightlining is significantly related to other factors of interest varies from one battery to the next. Additional analyses examine more specifically what combinations of factors are related to straightlining. The results will shed light on whether these response patterns may be due to satisficing, or a more general lack of attention or care in survey responses for this population of behavioral health enrollees.

Characterization of Galacturonic Acid Catabolic Genes in Sclerotinia sclerotiorum

Characterization of Galacturonic Acid Catabolic Genes in Sclerotinia sclerotiorum

Primary author: Nickisha Pierre-Pierre
Co-author(s): Wei Wei
Faculty sponsor: Weidong Chen

Primary college/unit: Agricultural, Human and Natural Resource Sciences
Campus: Pullman

Abstract:

Sclerotinia sclerotiorum is a necrotrophic fungal pathogen causing white mold disease on more than 600 plant species, including many economically important crops. The most prominent symptom of white mold is maceration of host tissue, suggesting the efficiency of pathogen in degrading plant cell wall. Galacturonic acid is the major building block of pectin which is a main component of plant cell wall. Thus, the resulting galacturonic acid after tissue maceration is likely the nutrient source for S. sclerotiorum. The genome of S. sclerotiorum encodes the genes responsible for galacturonic acid catabolism. However, the roles of these galacturonic acid catabolic genes in the biology and virulence of S. sclerotiorum are unknown.
The D-galacturonic acid catabolic pathway in S. sclerotiorum consists of three catalytic steps converting D-galacturonic acid to pyruvate and L-glyceraldehyde. In an effort to characterize the functions of the galacturonic acid catabolic pathway genes, gene deletion mutants of these genes in S. sclerotiorum were generated using targeted mutagenesis.
The wildtype and gene-deletion mutant strains of S. sclerotiorum were tested on media with different carbon sources. For radial growth assays, mycelium of strains were inoculated on Murashige and Skoog media supplemented with Ammonium dihydrogen phosphate and as a carbon source either glucose, D-galacturonic acid, citrus fruit pectin, apple pectin or sodium pectate. The significance of the effects of Sclerotinia sclerotiorum and the characterization of its virulence in host plants will be discussed in efforts to understand the epidemiology of the disease.

Additive Manufacturing Using Liquid Metal

Additive Manufacturing Using Liquid Metal

Primary author: Steven Peyron
Faculty sponsor: Arda Gozen

Primary college/unit: Voiland College of Engineering and Architecture
Campus: Pullman

Abstract:

Metal 3d printing has played a role in rethinking our manufacturing methods. Using the study of eGaIn and the numerical model of filamentary metal alloys developed by Dr. Gannarapu et al[1] we are going to evaluate the further nonnoble metals and alloys. We will be examining the oxide skin’s effect on the filamentary shape and strength in the subsequent metals and metal alloys. With that information further research on layer interactions of the oxide skin and the thermofluidic flow of the metal alloys and metals at the mesoscale. We have confirmed the layer interactions of eGaIn act like that of a liquid and the oxide skin does not maintain individual layers while liquid. The next step is to print with a metal that is sold at room temperature. We will start with fields alloy and move on to high-temperature metals.