Aligning Best Practices in Student Success and Career Preparedness: An Exploratory Study to Establish Pathways to STEM Careers for Undergraduate Minority Students

Undergraduate minority retention and graduation rates in STEM disciplines is a nationally recognized challenge for workforce growth and diversification. The Benjamin Banneker Scholars Program (BBSP) was a five-year undergraduate study developed to increase minority student retention and graduation rates at an HBCU. The program structure utilized a family model as a vehicle to orient students to the demands of college. Program activities integrated best K-12 practices and workforce skillsets to increase academic preparedness and career readiness. Findings revealed that a familial atmosphere improved academic performance, increased undergraduate research, and generated positive perceptions of faculty mentoring. Retention rates among BBSP participants averaged 88% compared to 39% among non-participant STEM peers. The BBSP graduation rate averaged 93% compared to 20% for non-participants. BBSP participants were more likely to gain employment in a STEM field or enter into a professional study. This paper furthers the body of research on STEM workforce diversity and presents a transferrable model for other institutions

Modelling the Role of Active Biomass on the Fate and Transport of a Heavy Metal in the Presence of Root Exudates

The influence of active biomass in immobilizing heavy metals in the soil rhizosphere is investigated through mechanistic models. The movement of water in the soil is modeled using Richards equation. An advection-dispersion equation, with a sink term for metal uptake by biomass, is used for modeling the fate and transport of lead. This sink term represents the nonlinear kinetics of metal adsorption to the biomass that is partitioned into mobile and stationary fractions within the soil. Transport of the mobile biomass fraction is modeled by an advection-dispersion equation, with a source term that is based on Monod growth kinetics, and a linear sink term for endogenous decay. The movement of metal in association with mobile biomass is also included as a transport mechanism for lead. Root exudates serve as carbon substrate for the biomass growth, and their transport is modeled in a similar way as that of the biomass. A hypothetical one-dimensional vertical soil column containing metal, biomass and a carbon substrate is used for analyzing lead movement. Model simulations demonstrate the influence of water content, growth rate of biomass, partitioning coefficient of biomass between soil and aqueous phase, and partitioning coefficient of metal between biomass and aqueous phase of the soil on fate and transport of lead. The extent of immobilization of lead in soil is found to be dependent on the growth of biomass, which in turn depends on the availability of root exudates in the rhizosphere. Apart from analyzing different scenarios, such a model can be used for designing future experiments

Effects of Drought on Water Quality in Streams

The objective of this research is to understand the relationship between low stream flows during droughts and their impact on water quality. The area chosen for this study is the Cedarville sub-watershed that drains into Massie Creek, a tributary to the Little Miami River, Ohio. By using stream flow and water quality data collected from the Massie Creek in Ohio, we will be able to study the impact of droughts on water quality

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.