Fields of sets, set functions, set function integrals, and finite additivity

This expository paper discusses, for set functions defined on a field of sets, some of the basic properties of set functions and set function integrals

Passing the Torch: Continuation of the South Carolina Libraries Journal

In this article, The South Carolina Libraries Editorial Board discusses the history and rebuilding of the South Carolina Libraries journal, the official publication of the South Carolina Library Association (SCLA). As the journal adjusted in response to community needs, changes in the Editorial Board, the publication cycle, and peer review process were made to expand and enhance the functionality, appearance, and content of the journal. The Editorial Board reviews strategies for library community members – including practitioners, research faculty, and LIS students – to become involved as a part of the publication through authoring, book reviewing, peer reviewing, or artwork for future issues

Environmental monitoring of antimicrobial resistant bacteria in North Carolina water and wastewater using the WHO Tricycle protocol in combination with membrane filtration and compartment bag test methods for detecting and quantifying ESBL E. coli

Antimicrobial resistance (AMR) threatens human and animal health; effective response requires monitoring AMR presence in humans, animals, and the environment. The World Health Organization Tricycle Protocol (WHO TP) standardizes and streamlines global AMR monitoring around a single indicator organism, extended-spectrum-β-lactamase-producing Escherichia coli (ESBL-Ec). The WHO TP culture-based method detects and quantifies ESBL-Ec by spread-plating or membrane filtration on either MacConkey or TBX agar (supplemented with cefotaxime). These methods require laboratories and trained personnel, limiting feasibility in low-resource and field settings. We adapted the WHO TP using a simplified method, the compartment bag test (CBT), to quantify most probable numbers (MPN) of ESBL-Ec in samples. CBT methods can be used correctly in the field by typical adults after a few hours’ training. We collected and analyzed municipal wastewater, surface water, and chicken waste samples from sites in Raleigh and Chapel Hill, NC over an 8-month period. Presumptive ESBL-Ec were quantified using MF on TBX agar supplemented with cefotaxime (MF+TBX), as well as using the CBT with chromogenic E. coli medium containing cefotaxime. Presumptive ESBL-Ec bacteria were isolated from completed tests for confirmation and characterization by Kirby Bauer disk diffusion tests (antibiotic sensitivity) and EnteroPluri biochemical tests (speciation). Both methods were easy to use, but MF+TBX required additional time and effort. The proportion of E. coli that were presumptively ESBL in surface water samples was significantly greater downstream vs upstream of wastewater treatment plant (WWTP) outfalls, suggesting that treated wastewater is a source of ESBL-Ec in some surface waters. The CBT and MF+TBX tests provided similar (but not identical) quantitative results, making the former method suitable as an alternative to the more complex MF+TBX procedure in some applications. Further AMR surveillance using MF+TBX and/or CBT methods may be useful to characterize and refine their performance for AMR monitoring in NC and elsewhere

AquaSat: A Data Set to Enable Remote Sensing of Water Quality for Inland Waters

Satellite estimates of inland water quality have the potential to vastly expand our ability to observe and monitor the dynamics of large water bodies. For almost 50 years, we have been able to remotely sense key water quality constituents like total suspended sediment, dissolved organic carbon, chlorophyll a, and Secchi disk depth. Nonetheless, remote sensing of water quality is poorly integrated into inland water sciences, in part due to a lack of publicly available training data and a perception that remote estimates are unreliable. Remote sensing models of water quality can be improved by training and validation on larger data sets of coincident field and satellite observations, here called matchups. To facilitate model development and deeper integration of remote sensing into inland water science, we have built AquaSat, the largest such matchup data set ever assembled. AquaSat contains more than 600,000 matchups, covering 1984–2019, of ground-based total suspended sediment, dissolved organic carbon, chlorophyll a, and SDDSecchi disk depth measurements paired with spectral reflectance from Landsat 5, 7, and 8 collected within ±1 day of each other. To build AquaSat, we developed open source tools in R and Python and applied them to existing public data sets covering the contiguous United States, including the Water Quality Portal, LAGOS-NE, and the Landsat archive. In addition to publishing the data set, we are also publishing our full code architecture to facilitate expanding and improving AquaSat. We anticipate that this work will help make remote sensing of inland water accessible to more hydrologists, ecologists, and limnologists while facilitating novel data-driven approaches to monitoring and understanding critical water resources at large spatiotemporal scales

Light and flow regimes regulate the metabolism of rivers

Mean annual temperature and mean annual precipitation drive much of the variation in productivity across Earth's terrestrial ecosystems but do not explain variation in gross primary productivity (GPP) or ecosystem respiration (ER) in flowing waters. We document substantial variation in the magnitude and seasonality of GPP and ER across 222 US rivers. In contrast to their terrestrial counterparts, most river ecosystems respire far more carbon than they fix and have less pronounced and consistent seasonality in their metabolic rates. We find that variation in annual solar energy inputs and stability of flows are the primary drivers of GPP and ER across rivers. A classification schema based on these drivers advances river science and informs management.We thank Ted Stets, Jordan Read, Tom Battin, Sophia Bonjour, Marina Palta, and members of the Duke River Center for their help in developing these ideas. This work was supported by grants from the NSF 1442439 (to E.S.B. and J.W.H.), 1834679 (to R.O.H.), 1442451 (to R.O.H.), 2019528 (to R.O.H. and J.R.B.), 1442140 (to M.C.), 1442451 (to A.M.H.), 1442467 (to E.H.S.), 1442522 (to N.B.G.), 1624807 (to N.B.G.), and US Geological Survey funding for the working group was supported by the John Wesley Power Center for Analysis and Synthesis. Phil Savoy contributed as a postdoc- toral associate at Duke University and as a postdoctoral associate (contractor) at the US Geological Survey

The role of epigenetics in renal ageing

An ability to separate natural ageing processes from processes specific to morbidities is required to understand the heterogeneity of age-related organ dysfunction. Mechanistic insight into how epigenetic factors regulate ageing throughout the life course, linked to a decline in renal function with ageing, is already proving to be of value in the analyses of clinical and epidemiological cohorts. Noncoding RNAs provide epigenetic regulatory circuits within the kidney, which reciprocally interact with DNA methylation processes, histone modification and chromatin. These interactions have been demonstrated to reflect the biological age and function of renal allografts. Epigenetic factors control gene expression and activity in response to environmental perturbations. They also have roles in highly conserved signalling pathways that modulate ageing, including the mTOR and insulin/insulin-like growth factor signalling pathways, and regulation of sirtuin activity. Nutrition, the gut microbiota, inflammation and environmental factors, including psychosocial and lifestyle stresses, provide potential mechanistic links between the epigenetic landscape of ageing and renal dysfunction. Approaches to modify the renal epigenome via nutritional intervention, targeting the methylome or targeting chromatin seem eminently feasible, although caution is merited owing to the potential for intergenerational and transgenerational effects