Water Quality Trends across Select 319 Monitoring Sites in Northwest Arkansas

Northwest Arkansas contains two 319 priority watersheds that the Arkansas Natural Resources Commission has identified as being impacted by point source and nonpoint source pollution (i.e., phosphorus, nitrogen, and sediment). This project specifically focused on determining water quality trends at select sites within the Illinois River (HUC# 11110103) and Beaver Reservoir (HUC# 11010001) priority watersheds, including Ballard Creek, Osage Creek, Illinois River, White River, West Fork White River and the Kings River where sufficient constituent data were available. Water quality trends were analyzed using flow‐adjusted constituent concentrations of phosphorus, nitrogen, sediment, sulfate and chloride, and parametric and non‐parametric statistical techniques to determine if constituent concentrations were increasing, decreasing or not significantly changing over time. Overall, flow‐adjusted concentrations of phosphorus and sediment have been decreasing across these watersheds based upon both statistical approaches. The decrease in phosphorus was likely the most important observation, because most water quality concerns in this region have focused on elevated phosphorus concentrations in these transboundary watersheds. These trends can be used along with other watershed information to improve the knowledge of how past, current, and future management decisions have influenced the watershed

The structure and function of complex networks

Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.Comment: Review article, 58 pages, 16 figures, 3 tables, 429 references, published in SIAM Review (2003

Treatments used for obsessive-compulsive disorder-An international perspective

© 2019 John Wiley & Sons, Ltd.OBJECTIVE: The objective of this study was to characterise international trends in the use of psychotropic medication, psychological therapies, and novel therapies used to treat obsessive-compulsive disorder (OCD). METHODS: Researchers in the field of OCD were invited to contribute summary statistics on the characteristics of their samples. Consistency of summary statistics across countries was evaluated. RESULTS: The study surveyed 19 expert centres from 15 countries (Argentina, Australia, Brazil, China, Germany, Greece, India, Italy, Japan, Mexico, Portugal, South Africa, Spain, the United Kingdom, and the United States) providing a total sample of 7,340 participants. Fluoxetine (n = 972; 13.2%) and fluvoxamine (n = 913; 12.4%) were the most commonly used selective serotonin reuptake inhibitor medications. Risperidone (n = 428; 7.3%) and aripiprazole (n = 415; 7.1%) were the most commonly used antipsychotic agents. Neurostimulation techniques such as transcranial magnetic stimulation, deep brain stimulation, gamma knife surgery, and psychosurgery were used in less than 1% of the sample. There was significant variation in the use and accessibility of exposure and response prevention for OCD. CONCLUSIONS: The variation between countries in treatments used for OCD needs further evaluation. Exposure and response prevention is not used as frequently as guidelines suggest and appears difficult to access in most countries. Updated treatment guidelines are recommended.Peer reviewe

Performance of random forests and logic regression methods using mini-exome sequence data

Machine learning approaches are an attractive option for analyzing large-scale data to detect genetic variants that contribute to variation of a quantitative trait, without requiring specific distributional assumptions. We evaluate two machine learning methods, random forests and logic regression, and compare them to standard simple univariate linear regression, using the Genetic Analysis Workshop 17 mini-exome data. We also apply these methods after collapsing multiple rare variants within genes and within gene pathways. Linear regression and the random forest method performed better when rare variants were collapsed based on genes or gene pathways than when each variant was analyzed separately. Logic regression performed better when rare variants were collapsed based on genes rather than on pathways

Wireless aquatic navigator for detection and analysis (WANDA)

The cost of monitoring and detecting pollutants in natural waters is of major concern. Current and forthcoming bodies of legislation will continue to drive demand for spatial and selective monitoring of our environment, as the focus increasingly moves towards effective enforcement of legislation through detection of events, and unambiguous identification of perpetrators. However, these monitoring demands are not being met due to the infrastructure and maintenance costs of conventional sensing models. Advanced autonomous platforms capable of performing complex analytical measurements at remote locations still require individual power, wireless communication, processor and electronic transducer units, along with regular maintenance visits. Hence the cost base for these systems is prohibitively high, and the spatial density and frequency of measurements are insufficient to meet requirements. In this paper we present a more cost effective approach for water quality monitoring using a low cost mobile sensing/communications platform together with very low cost stand-alone ‘satellite’ indicator stations that have an integrated colorimetric sensing material. The mobile platform is equipped with a wireless video camera that is used to interrogate each station to harvest information about the water quality. In simulation experiments, the first cycle of measurements is carried out to identify a ‘normal’ condition followed by a second cycle during which the platform successfully detected and communicated the presence of a chemical contaminant that had been localised at one of the satellite stations