A technology pathway program in data technology and applications

With an exponential increase in user-generated data, there is a strong and increasing demand for employees possessing both technical skills and knowledge of human behavior. Supported by funds from the National Science Foundation Division of Undergraduate Education, we have begun to address this need by developing a technology pathway program in data technology and applications at a large, minority-serving public university. As part of this program, an interdisciplinary team of faculty created a new minor in Applied Computing for Behavioral and Social Sciences. A large number of diverse students are studying behavioral and social sciences, and the ability to model human behaviors and social interactions is a highly valuable skill set in our increasingly data-driven world. Applied Computing students complete a four-course sequence that focuses on data analytics and includes data structures and algorithms, data cleaning and management, SQL, and a culminating project. Our first full cohort of students completed the Applied Computing minor in Spring 2019. To assess the success of the minor, we conduct student surveys and interviews in each course. Here, we focus on survey data from the beginning and end of the first course, given that it served as a particularly important feedback loop to optimize the course and to inform the design and execution of subsequent courses. The data reflect a significant increase in confidence in programming abilities over time, as well as a shift in attitudes about programming that more closely matches those of experts. The data did not show a significant change in mindset over time, such that students maintained a growth mindset across the semester. Finally, with respect to goals, students placed a greater emphasis on data and tech at the end of the semester, highlighting specific career paths such as user experience and human factors. In the future, we plan to administer this same survey to social science students not involved in the minor to serve as a control group and to begin exploring the large dataset obtained from other courses in the minor. We believe that embedding computing education into the social sciences is a promising means of diversifying the technical workforce and filling the need for interdisciplinary computing professionals, as evidenced by high rates of female and underrepresented minority enrollment in our courses, as well as promising shifts in student confidence, attitudes, and career goals as a result of taking Applied Computing courses

Toward Competitive Employment for Persons with Intellectual and Developmental Disabilities: What Progress Have We Made and Where Do We Need to Go

Progress toward competitive integrated employment (CIE) for people with intellectual and developmental disabilities (IDD) over the last 40 years has been mixed. Despite evidence showing that supported employment interventions can enable adults with IDD to effectively get and keep jobs, national rates of integrated employment remain below a third of the working-age population. Progress is being made to improve these outcomes. Pathways have been identified that lead to CIE through supported employment, customized employment, internship experiences, and postsecondary education. The recent passage of the Workforce Innovation and Opportunity Act (WIOA) has created fresh momentum and increased the onus on interagency collaboration. This article examines what is known about promoting CIE through these pathways and highlights recommendations for future research and policy change. Recommendations for the future provide direction toward positive change for CIE into the 21st century

Advanced extravehicular activity systems requirements definition study. Phase 2: Extravehicular activity at a lunar base

The focus is on Extravehicular Activity (EVA) systems requirements definition for an advanced space mission: remote-from-main base EVA on the Moon. The lunar environment, biomedical considerations, appropriate hardware design criteria, hardware and interface requirements, and key technical issues for advanced lunar EVA were examined. Six remote EVA scenarios (three nominal operations and three contingency situations) were developed in considerable detail

The Rad4TopBP1 ATR-Activation domain functions in G1/S phase in a chromatin-dependent manner

DNA damage checkpoint activation can be subdivided in two steps: initial activation and signal amplification. The events distinguishing these two phases and their genetic determinants remain obscure. TopBP1, a mediator protein containing multiple BRCT domains, binds to and activates the ATR/ATRIP complex through its ATR-Activation Domain (AAD). We show that Schizosaccharomyces pombe Rad4TopBP1 AAD–defective strains are DNA damage sensitive during G1/S-phase, but not during G2. Using lacO-LacI tethering, we developed a DNA damage–independent assay for checkpoint activation that is Rad4TopBP1 AAD–dependent. In this assay, checkpoint activation requires histone H2A phosphorylation, the interaction between TopBP1 and the 9-1-1 complex, and is mediated by the phospho-binding activity of Crb253BP1. Consistent with a model where Rad4TopBP1 AAD–dependent checkpoint activation is ssDNA/RPA–independent and functions to amplify otherwise weak checkpoint signals, we demonstrate that the Rad4TopBP1 AAD is important for Chk1 phosphorylation when resection is limited in G2 by ablation of the resecting nuclease, Exo1. We also show that the Rad4TopBP1 AAD acts additively with a Rad9 AAD in G1/S phase but not G2. We propose that AAD–dependent Rad3ATR checkpoint amplification is particularly important when DNA resection is limiting. In S. pombe, this manifests in G1/S phase and relies on protein– chromatin interactions

Learning Experiences of Social Science Students in an Interdisciplinary Computing Minor

The rapid growth of the digital economy and an associated increase in user-generated data has created a strong need for interdisciplinary computing professionals possessing both technical skills and knowledge of human behavior. To help meet this need and with funds from NSF IUSE, we developed an academic minor in Applied Computing for Behavioral and Social Sciences at San Jose State University. The minor involves a four-course sequence that includes programming fundamentals, data structures and algorithms, data cleaning and management, and a culminating project. At our institution and nationwide, social science students are more diverse than engineering students, with respect to gender, race, and ethnicity. By providing social science students with computing skills that complement their domain expertise, we aim to expand their career options and address the nation\u27s need for a diverse, technology-capable workforce. We administered an exit survey on student learning experiences to two cohorts of students completing the minor. Given that the minor is new and that the first cohorts were relatively small, the number of students completing the survey was modest (n = 15). Results indicate that students were motivated to minor in Applied Computing by a desire to improve their data analysis skills and better prepare themselves for the job market/graduate school, as well as a belief that programming is a necessary skill for the future. A large majority of students indicated that their peers, instructors, and homework assignments supported their learning very well, whereas they found topics covered and course projects to be less supportive, followed by pacing of course content. With respect to career plans, a majority of students agreed that the minor provided them with their desired skills and allowed them to learn about careers in applied computing, and a large majority indicated that they planned to pursue a career utilizing applied computing. They expressed interest in fields such as human factors, data analytics, project management, teaching, clinical psychology, and various types of research. Finally, common themes that arose when providing advice to future students included not being shy in seeking help, tips for managing the level of course difficulty, encouragement to regularly practice, suggestions for how to master course content, and advice for adopting a successful mindset. These results will be instrumental in helping to optimize students\u27 experiences in the minor, ranging from how we recruit new students to how we can better support their professional development. Given the largely positive experiences of our students and their plans to pursue careers involving applied computing, we believe that our approach of adding computing education alongside a social science degree demonstrates a promising model for meeting the increasing demand for diverse interdisciplinary computing workers in this digital age

Characterization of Antibiotic Susceptibility Profiles of Extensively- and Pan-Drug Resistant Acinetobacter Baumannii Clinical Isolates

Acinetobacter baumannii is an opportunistic pathogen common in intensive care units (ICUs), particularly among immunocompromised individuals. Nosocomial A. baumannii infections have become increasingly problematic in recent years, as these bacteria rapidly acquire antibiotic resistance, leading to the emergence of multidrug, extensively drug and pan drug-resistant (MDR, XDR, and PDR, respectively) isolates. Recently, Cooper University Hospital (CUH) experienced a large increase in highly drug-resistant A. baumannii infections, which had a mortality rate of 60%. Oftentimes, physicians had to turn to combinations of drugs with no experimental verification or historically shelved antibiotics, such as the polymyxins, in a desperate attempt to save lives. This highlights the critical need for more research to identify new, effective treatment options for these difficult-to-treat infections. Here, we determined the susceptibility of 22 patient isolates from CUH against 22 standard-of-care drugs and three newly released antibiotics (eravacycline, omadacycline and plazomicin) by the standard broth microdilution technique. We found that the isolates in this collection were 70% XDR and 30% PDR, meaning there were few to no treatment options available. Overall, the collection was most susceptible to minocycline (77.3%), followed by rifampin (55%) and amikacin (40.9%). While official breakpoint data is not available from the Clinical Laboratory Standards Institute for the new tetracycline-class drugs, a number of strains had low minimum inhibitory concentrations (MICs) to eravacycline and omadacycline, suggesting that these new drugs may be effective in treatment of highly drug-resistant strains. The drug plazomicin was largely ineffective against these strains, with high MICs. We plan to explore novel combinations of eravacycline and omadacycline with the standard-of-care drugs and to search for synergistic combinatorial effects using checkerboard assays. This information can ultimately be used to design new Therapeutics against drug-resistant A. baumannii infections

Spatiotemporal Dynamics of Modality-Specific and Supramodal Word Processing

AbstractThe ability of written and spoken words to access the same semantic meaning provides a test case for the multimodal convergence of information from sensory to associative areas. Using anatomically constrained magnetoencephalography (aMEG), the present study investigated the stages of word comprehension in real time in the auditory and visual modalities, as subjects participated in a semantic judgment task. Activity spread from the primary sensory areas along the respective ventral processing streams and converged in anterior temporal and inferior prefrontal regions, primarily on the left at around 400 ms. Comparison of response patterns during repetition priming between the two modalities suggest that they are initiated by modality-specific memory systems, but that they are eventually elaborated mainly in supramodal areas

Structured purpose: Implementing Python in Purposive Sample Selection for Evaluation Interviews

We demonstrated implementation of Python-based programming to select participants for qualitative evaluation. We used a National Institutes of Health (NIH)-funded multi-site COVID-19 testing program, Rapid Diagnostics for Underserved Populations Program, as our case example. During Phase I, the NIH funded 69 projects, each with known characteristics like underserved focus population(s). Using Python coding, we selected nine sites. We established preliminary conditions for the sample based on key populations. We iteratively applied additional conditions based on site target sample, study design, and geography. For each condition, Python checked every potential sample set against the condition, removed incompatible sets, then added another condition until a single set of sites to interview emerged. The code maximized sample diversity and prioritized projects addressing multiple populations concurrently. Full implementation of code takes about thirty minutes on an ordinary laptop computer. We explain the generation of the code and make it available in Carolina Digital Repository

Strengthening Community Involvement in Grant Review: Insights from the Community–University Research Partnership (CURES) Pilot Review Process

In 2007, the Michigan Institute for Clinical and Health Research (MICHR) at the University of Michigan received a Clinical and Translational Science Award (CTSA). Within MICHR, the Community Engagement (CE) program supports partnership efforts between researchers, practitioners, and community‐based organizations in specific focal communities throughout Michigan. A key component of the CE program is the Community Engagement Coordinating Council, a group that provides input and guidance on program priorities, strategic planning, and reviews pilot funding proposals for community–academic partnerships. This paper will describe a unique MICHR pilot funding mechanism for Community–University Research Partnerships (CURES) with an emphasis on the ways that community partners are involved in the review process, as well as the benefits, challenges, and insights gained over 5 years of pilot review. There is a growing need for community involvement and expertise in review of funding proposals for community‐engaged research at both institutional and federal levels. The CURES pilot review process is one example of an institutional effort to engage community partners in university funding decisions and has demonstrated clear benefit toward accomplishing the aims of the CTSA.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106809/1/cts12141.pd