Artificial neural network approach for forecasting nitrogen oxides concentrations

This paper presents the application of feed-forward multilayer perceptron networks to forecast hourly nitrogen oxides levels 24 hours in advance. Input data were meteorological variables, average hourly traffic and nitrogen oxides hourly levels. The introduction of four periodic components (sine and cosine terms for the daily and weekly cycles) was analyzed in order to improve the models prediction power. The data were measured during three years at monitoring stations in Valencia (Spain) in two locations with high traffic density. The models evaluation criteria were the mean absolute error, the root mean square error, the mean absolute percentage error, and the correlation coefficient between observations and predictions. Comparisons of multilayer perceptron-based models proved that the insertion of the four additional seasonal input variables improved the ability of obtaining more accurate predictions, which emphasizes the importance of taking into account the seasonal character of nitrogen oxides. When using seasonal components as predictors, the root mean square error (RMSE) improves from 20.29 to 19.35 when predicting nitrogen dioxide, and from 45.07 to 42.37 when forecasting nitric oxides if the model includes seasonal components At one study location. At the other location the RMSE changes from 23.76 to 23.05 when predicting nitrogen dioxide and from 33.94 to 33.10 for the other pollutant s forecasts. Neural networks did not require very exhaustive information about air pollutants, reaction mechanisms, meteorological parameters or traffic characteristics, and they had the ability of allowing nonlinear and complex relationships between very different predictor variables in an urban environment.Capilla Roma, CA. (2015). Artificial neural network approach for forecasting nitrogen oxides concentrations. Environmental Engineering Science. 32(9):781-788. doi:10.1089/ees.2014.0556S78178832

Synthesis and characterization of core-shell structure silica-coated Fe29.5Ni70.5 nanoparticles

In view of potential applications of magnetic particles in biomedicine and electromagnetic devices, we made use of the classical Stober method base-catalysed hydrolysis and condensation of tetraethoxysilane (TEOS) to encapsulate FeNi nanoparticles within a silica shell. An original stirring system under high power ultrasounds made possible to disperse the otherwise agglomerated particles. Sonication guaranteed particles to remain dispersed during the Stober synthesis and also improved the efficiency of the method. The coated particles are characterized by electron microscopy (TEM) and spectroscopy (EDX) showing a core-shell structure with a uniform layer of silica. Silica-coating does not affect the core magnetic properties. Indeed, all samples are ferromagnetic at 77 K and room temperature and the Curie point remains unchanged. Only the coercive force shows an unexpected non-monotonous dependence on silica layer thickness.Comment: Regular paper submited to international peer-reveiwed journa

Partial nephrectomy should be classified as an inpatient procedure: Results from a statewide quality improvement collaborative

OBJECTIVES: To examine length of stay (LOS) and readmission rates for all minimally-invasive partial nephrectomy (MIPN) and MI radical nephrectomy (MIRN) performed for localized renal masses ≤7 cm in size (cT1RM) within 12 Michigan urology practices. Both RN and PN are commonly performed in treating cT1RM. Although technically more complex and associated with higher complication rates, Centers for Medicare & Medicaid Services considers MIPN an outpatient procedure and MIRN is inpatient. METHODS: We collected data for renal surgeries for cT1RM at MUSIC-KIDNEY practices between May 2017-February 2020. Data abstractors recorded clinical, radiographic, pathologic, surgical, and short-term follow-up data into the registry for cT1RM patients. RESULTS: Within MUSIC-KIDNEY, 807 patients underwent MI renal surgery at 12 practices. Median LOS for cT1RM patients after MIPN (n = 531, 66%) was 2 days and after MIRN (n = 276, 34%) was also 2 days. Among patients undergoing laparoscopic or robotic PN, 171 (32%), 230 (43%), and 130 (24%) stayed ≤1, 2, ≥3 days. Among patients undergoing laparoscopic or robotic RN, 81 (29%), 112 (41%), and 83 (30%) stayed ≤1, 2, ≥3 days. No significant difference was observed between MIPN and MIRN on LOS commensurate with outpatient surgery (≤1-day, OR = 0.97, P = 0.87). CONCLUSIONS: Less than one-third of patients had a LOS ≤1-day and LOS was comparable for MIPN and MIRN. Centers for Medicare & Medicaid Services should be advised that MIPN is a more complex surgery than MIRN, most patients receiving a MIPN will require a ≥2-day hospital stay and it would be more appropriate to classify MIPN an inpatient procedure with MIRN