Kansas State Department of Education

Roadway surface type classification (e.g., unpaved, asphalt, concrete) is an essential data element for road safety analysis and required as part of the Model Inventory of Roadway Elements (MIRE) Fundamental Data Elements (FDEs). Supplementary guidance issued by the Federal Highway Administration (FHWA) requires detailed surface type classification for the National Highway System (NHS) and roads functionally classified as interstates; however, less detailed surface type attribute group values (i.e., unpaved surface, asphalt pavement, concrete pavement, and other paved surface) are required for all remaining road segments that are not a part of the NHS. As part of a FHWA data analysis technical assistance (DATA) team, the research team worked with the Kansas Department of Transportation (KDOT) to develop a machine learning model capable of initially categorizing roads to reduce the level of effort required to satisfy the full MIRE FDE requirements. The research team conducted a pilot image classification analysis and determined a potential workflow for a broader statewide study area. This paper outlines the pilot methodologies and results. The team developed a support vector machine (SVM) learning model combined with Bayesian statistics that classified roads as paved or unpaved from aerial imagery with an overall model accuracy of 95%.

Two common problems in the urinary system of cats are renal disease (RD) and calcium oxalate (CaOx) stones. The objective of this study was to assess urine metabolomic parameters of cats with these diseases to determine metabolic abnormalities and differences between the groups. The urine metabolic profile for each cat was determined, along with their lifetime history of stone incidence and renal disease. In order to reduce the data for analysis, factor analysis/factor loading was used allowing statistical hypothesis testing and the selection of significant metabolites from 488 identified metabolites. A total of 42 cats were used (19 healthy, 12 with CaOx stones and 11 with renal disease). Urine from the cats were tested multiple times (mean = 4.6) therefore cat ID was used as a random variable. All analytes were expressed as a ratio to creatinine in order to compensate for differences in water intake. Principal components analysis was used as the method of factor extraction resulting in six factors that differed between groups. Factors 1, 2, and 5 were elevated in healthy cats and depressed in RD and CaOx cats. These factors had several analytes that are known to be elevated in the serum of cats with CaOx stones (i.e., 7-methylguanine, erythritol, pseudouridine, N1-methylinosine). Factor 5 was elevated in healthy cats containing six phenyl moieties as well as p-cresol sulfate. There were two factors which were increased in CaOx cats. Factor 12 was increased when compared to healthy cats and contained three purine nucleic acids (inosine, xanthine and hypoxanthine) as well as 3-hydroxybutyrate while factor 23 was elevated and the only factor that contained phospholipids. These results show that urine is not simply reflecting circulating concentration changes observed in cats with CaOx stones and RD but rather also gives insight into the functional kidney changes associated with these diseases.

Nearly half of foodborne illnesses are linked to produce and nuts, and water used for produce post-harvest activities can contribute to contamination. Surface water serves as an economical source for agricultural activities; however, exposure to the environment increases microbial risks and impacts its physicochemical characteristics. In this study, peroxyacetic acid (PAA) and chlorine (Cl) were evaluated as treatments for simulated surface water to determine their efficacy at achieving ‘no detectable generic Escherichia coli’ in 100 mL. Simulated surface water was prepared to turbidities of 2 and 100 NTU, adjusted to pH 6.5 or 8.4, equilibrated to 32 or 12 °C, inoculated with 5 logs per mL of non-pathogenic (generic) E. coli, and treated with Cl 25 ± 2 ppm, PAA 75 ± 5 ppm, or sterile water control (W). Dey-Engley neutralization was followed by enumeration on E. coli/Coliform Petrifilm at times (t) 0 to 2880 min (48 h) post-treatment. When not detected, treatments were further evaluated through enrichment in 2X Brain Heart Infusion (BHI) broth. Enrichments were streaked on MacConkey agar (MAC) to confirm E. coli absence. All Cl and PAA treated samples were below the test limit of detection (<5 CFU/mL), and E. coli was not detected in 5 mL enrichments even at t = 0 (shortly after treatment). These data suggest that Cl and PAA interventions may be effective for treating surface water for post-harvest uses.

To evaluate the effectiveness of the Kansas Nurse Leader Residency (KNLR) programme in improving nurses' leadership knowledge and skills and its acceptability, feasibility and fidelity. The Future of Nursing Report (Institute of Medicine, 2011) calls for nurses to lead change and advance health. The 6-month KNLR programme was developed by the Kansas Action Coalition to support nurses' leadership development. Nurses (n=36) from four nursing specialties (acute care, long-term care, public health and school health) participated in the programme. The adapted Leader Knowledge and Skill Inventory was used to assess leadership knowledge and skills. Programme acceptability, feasibility and implementation fidelity also were evaluated. The programme completion rate was 67.7% (n=24). Programme completers had significantly improved self-assessed and mentor-assessed leadership knowledge and skills (p<.05). These post-programme gains were maintained 3months after programme completion. The KNLR programme effectively improved leadership knowledge and skills and was positively evaluated by participants. The implementation of the KNLR programme using a hybrid format of in-person sessions and online modules was feasible across four specialty areas in both rural and urban regions. The next steps include the development of an advanced programme. Residency programmes for new nurse leaders are critical for successful transition into management positions.