Feature extraction using Hough transform for solid waste bin level detection and classification

This paper deals with the solid waste image detection and classification to detect and classify the solid waste bin level. To do so, Hough transform techniques is used for feature extraction to identify the line detection based on image’s gradient field. The feedforward neural network (FFNN) model is used to classify the level content of solid waste based on learning concept. Numbers of training have been performed using FFNN to learn and match the targets of the testing images to compute the sum squared error with the performance goal met. The images for each class are used as input samples for classification. Result from the neural network and the rules decision are used to build the receiver operating characteristic (ROC) graph. Decision graph shows the performance of the system waste system based on area under curve (AUC), WS-class reached 0.9875 for excellent result and WS-grade reached 0.8293 for good result. The system has been successfully designated with the motivation of solid waste bin monitoring system that can applied to a wide variety of local municipal authorities system.     

Soil response to a 3-year increase in temperature and nitrogen deposition measured in a mature boreal forest using ion-exchange membranes

The projected increase in atmospheric N deposition and air/soil temperature will likely affect soil nutrient dynamics in boreal ecosystems. The potential effects of these changes on soil ion fluxes were studied in a mature balsam fir stand (Abies balsamea [L.] Mill) in Quebec, Canada that was subjected to 3 years of experimentally increased soil temperature (+4 °C) and increased inorganic N concentration in artificial precipitation (three times the current N concentrations using NH₄NO₃). Soil element fluxes (NO₃, NH₄, PO₄, K, Ca, Mg, SO₄, Al, and Fe) in the organic and upper mineral horizons were monitored using buried ion-exchange membranes (PRS? probes). While N additions did not affect soil element fluxes, 3 years of soil warming increased the cumulative fluxes of K, Mg, and SO₄ in the forest floor by 43, 44, and 79 %, respectively, and Mg, SO₄, and Al in the mineral horizon by 29, 66, and 23 %, respectively. We attribute these changes to increased rates of soil organic matter decomposition. Significant interactions of the heating treatment with time were observed for most elements although no clear seasonal patterns emerged. The increase in soil K and Mg in heated plots resulted in a significant but small K increase in balsam fir foliage while no change was observed for Mg. A 6–15 % decrease in foliar Ca content with soil warming could be related to the increase in soil-available Al in heated plots, as Al can interfere with the root uptake of Ca.     

Effects of natural organic matter type and concentration on the aggregation of citrate-stabilized gold nanoparticles

The aggregation of 12 nm citrate-stabilized gold nanoparticles (cit-AuNPs) in the presence of four different natural organic matter (NOM) isolates and a monovalent electrolyte (KCl) was evaluated using time-resolved dynamic light scattering. All four NOM isolates stabilized the cit-AuNPs with respect to aggregation. However, specific effects varied among the different NOM isolates. At pH = 6 in 80 mM KCl, low concentrations (<0.25 mg C per L) of large molecular weight Suwannee River Humic Acid (SRHA) was required to stabilize cit-AuNPs, while larger concentrations (>2 mg C per L) of smaller Suwannee River Fulvic Acid (SRFA) were necessary at the same ionic strength. Suwannee River NOM (SRNOM) which contains both SRHA and SRFA behaved in a manner intermediate between the two. Pony Lake Fulvic Acid (PLFA), an autochthonous NOM isolate, provided substantial stability at low concentrations, yet aggregation was induced at NOM concentrations > 2 mg C per L, a trend that is hypothesized to be the result of favourable hydrophobic interactions between coated particles induced at increased surface coverage. For all NOM isolates, it appears that NOM adsorption or conformational changes at the AuNP surfaces result in significant increases in the hydrodynamic diameter that aren't attributable to NP-NP aggregation.     

Utilizing pyrosequencing and quantitative PCR to characterize fungal populations among house dust samples

Molecular techniques are an alternative to culturing and counting methods in quantifying indoor fungal contamination. Pyrosequencing offers the possibility of identifying unexpected indoor fungi. In this study, 50 house dust samples were collected from homes in the Yakima Valley, WA. Each sample was analyzed by quantitative PCR (QPCR) for 36 common fungi and by fungal tag-encoded flexible (FLX) amplicon pyrosequencing (fTEFAP) for these and additional fungi. Only 24 of the samples yielded amplified results using fTEFAP but QPCR successfully amplified all 50 samples. Over 450 fungal species were detected by fTEFAP but most were rare. Twenty-two fungi were found by fTEFAP to occur with at least an average of ≥0.5% relative occurrence. Many of these fungi seem to be associated with plants, soil or human skin. Combining fTEFAP and QPCR can enhance studies of fungal contamination in homes.     

Receptor model-based source apportionment of particulate pollution in Hyderabad, India

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2?±?24.6, 96.2?±?12.1, and 64.3?±?21.2 μg/m³ of PM₁₀, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m³. In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM₁₀ and PM_2.5 size fractions for three seasons. The receptor modeling results indicated that the PM₁₀ pollution is dominated by the direct vehicular exhaust and road dust (more than 60 %). PM_2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.     

Effect of power plant emission reductions on a nearby wilderness area: a case study in northwestern Colorado

This study evaluates the effect of emission reductions at two coal-fired power plants in northwestern Colorado on a nearby wilderness area. Control equipment was installed at both plants during 1999–2004 to reduce SO₂ and NOx emissions. One challenge was separating the effects of local from regional emissions, which also declined during the study period. The long-term datasets examined confirm that emission reductions had a beneficial effect on air and water quality in the wilderness. Despite a 75 % reduction in SO₂ emissions, sulfate aerosols measured in the wilderness decreased by only 20 %. Because the site is relatively close to the power plants (<75 km), the slow rate of conversion of SO₂ to sulfate, particularly under conditions of low relative humidity, might account for this less than one-to-one response. On the clearest days, emissions controls appeared to improve visibility by about 1 deciview, which is a small but perceptible improvement. On the haziest days, however, there was little improvement perhaps reflecting the dominance of regional haze and other components of visibility degradation particularly organic carbon and dust. Sulfate and acidity in atmospheric deposition decreased by 50 % near the southern end of the wilderness of which 60 % was attributed to power plant controls and the remainder to reductions in regional sources. Lake water sulfate responded rapidly to trends in deposition declining at 28 lakes monitored in and near the wilderness. Although no change in the acid–base status was observed, few of the lakes appear to be at risk from chronic or episodic acidification.     

On-line dechlorination–hydrogenation of chlorinated paraffin mixtures using GC and GC/MS

Chlorinated paraffins (CPs) are straight chain hydrocarbons that are produced as complex mixtures and are used as flame retardants and paint additives. These mixtures are extremely difficult to characterize using conventional chromatographic methods, as conventional gas chromatography results in unresolved complex chromatograms that preclude the identification and quantification of individual congeners or any reasonable assessment of the average carbon chain length. Carbon chain length is an important parameter for assessing physical properties and the toxicity of these materials. We have modified and improved a previously published gas chromatography–flame ionization detector method that uses Pd catalyst held in the gas chromatograph injector to simultaneously dechlorinate the CPs and separate the resulting alkanes. In addition, we have adapted this method to gas chromatography–mass spectrometry. Dehalogenation of other compounds was also studied with this system to investigate potential application to other complex halogenated mixtures.