Copper(II) adsorption by waste tea leaves and coffee powder

The consumed coffee powder and tea leaves of local produce were found to be able to remove substantial amounts of Cu(II) ions from aqueous solution. The characteristics of Cu(II) uptake on these beverage waste were systematically investigated. It was found that the Cu(II) uptake was dependent on pH, metal concentration, physical nature of substrate and ionic strength. Competing ions/molecules such as Pb(II) and surfactant such as Triton X-lOa interfere in the uptake of Cu(II). The degree of uptake increases with pH and the pH range for maximum uptake was found to be 5 - 7 for both wastes. Metal concentration dependent assumed a Langmuir Isotherm. The results obtained were found to be consistent with the mechanisms that Cu(II) uptake was due to specific ion adsorption via ch elation and some degree of ion-exchange reaction

Differential pulse polarography and voltammetry with an automated microprocessor-based polarograph and a static mercury drop electrode

Differential pulse polarography using an automated, microprocessor- based polarographic analyzer equipped with a static mercury drop electrode has been evaluated with respect to pulse amplitude, scan rate, drop time (t), and drop area. Variation of peak current, z"p' with drop area and t - Y2, with some pulse amplitudes agree reasonably well with theory. However, dependence of and E or i scan rate and on pulse amplitude at very large and very small amplitudes was found to devide fron i theory. Similar trends were also found for anodic stripping voltammetry when differential pulse stripping was used. The precision attainable by both techniques was good. Copper peaks demonstrated good precision only when copper was plated out individually during anodic stripping voltammetry

Statistical uncertainty in quantum optical photodetection measurements

We present a complete statistical analysis of quantum optical measurement schemes based on photodetection. Statistical distributions of quantum observables determined from a finite number of experimental runs are characterized with the help of the generating function, which we derive using the exact statistical description of raw experimental outcomes. We use the developed formalism to point out that the statistical uncertainty results in substantial limitations of the determined information on the quantum state: though a family of observables characterizing the quantum state can be safely evaluated from experimental data, its further use to obtain the expectation value of some operators generates exploding statistical errors. These issues are discussed using the example of phase-insensitive measurements of a single light mode. We study reconstruction of the photon number distribution from photon counting and random phase homodyne detection. We show that utilization of the reconstructed distribution to evaluate a simple well-behaved observable, namely the parity operator, encounters difficulties due to accumulation of statistical errors. As the parity operator yields the Wigner function at the phase space origin, this example also demonstrates that transformation between various experimentally determined representations of the quantum state is a quite delicate matter.Comment: 18 pages REVTeX, 7 figures included using epsf. Few minor corrections made, clarified conclusion

Observations of HONO by laser-induced fluorescence at the South Pole during ANTCI 2003

Observations of nitrous acid (HONO) by laser-induced fluorescence (LIF) at the South Pole taken during the Antarctic Troposphere Chemistry Investigation (ANTCI), which took place over the time period of Nov. 15, 2003 to Jan. 4, 2004, are presented here. The median observed mixing ratio of HONO 10 m above the snow was 5.8 pptv (mean value 6.3 pptv) with a maximum of 18.2 pptv on Nov 30th, Dec 1st, 3rd, 15th, 17th, 21st, 22nd, 25th, 27th and 28th. The measurement uncertainty is ±35%. The LIF HONO observations are compared to concurrent HONO observations performed by mist chamber/ion chromatography (MC/IC). The HONO levels reported by MC/IC are about 7.2 ± 2.3 times higher than those reported by LIF. Citation: Liao, W., A. T. Case, J. Mastromarino, D. Tan, and J. E. Dibb (2006), Observations of HONO by laser-induced fluorescence at the South Pole during ANTCI 2003, Geophys. Res. Lett., 33, L09810, doi:10.1029/2005GL025470

A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction

A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction

A Chemical Survey of the Batang Belungkung River and the Gombak River

A chemical survey of water quality in the Batang Belungkung River and the Gombak River was conducted to assess the degree of pollution due to the continuing discharge of rubber and domestic wastes. Levels of dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), nutrients (phosphorus and nitrogen), solid and trace elements (sodium, potassium, calcium and magnesium) were monitored sequentially downriver. The Batang Belungkung River was found to be severely polluted with anaerobic conditions existing downriver. The upper region of the Gombak River was relatively unpolluted while the lower region of the Gombak River was found to be severely polluted. An increase of approximately fourteen-fold was found in the oxygen demand in the lower region of the Gombak River over the ten year period from 1968/69 to 1978/79

The Morphotropic Phase Boundary in the (1-x)PbZrO3–x[0.3Bi(Zn1/2Ti1/2)O3–0.7PbTiO3] Perovskite Solid Solution

Ceramics in the (1-x)PbZrO3–x[0.3Bi(Zn1/2Ti1/2)O3–0.7PbTiO3] solid solution system with 0.48 x 0.56 were investigated. A morphotropic phase boundary separating rhombohedral and tetragonal perovskite phases was identified at x = 0.52. This composition displays the maximum remanent polarization Pr of 40.7 μC/cm2 and the best piezoelectric coefficient d33 of 311 pC/N in the pseudo-binary system. However, the Curie temperature Tc for this MPB composition is 291 °C, much lower than initially expected

Optimal sizing and techno-economic analysis of grid-connected nanogrid for tropical climates of the savannah

Reliability and costs are mainly considered in performance analysis of renewable energy-based distributed grids. Hybrid Optimization of Multiple Energy Renewables was used in techno-economic analysis of renewable energy systems involving photovoltaics, wind, diesel and storage in tropical regions of Amazon, Central Asia and Mediterranean. In a study for a Guinea Savannah region, 70% of renewable energy fraction was achieved. However, levelized cost of energy of 0.689 $/kWh was higher than tariff rate of 0.6$/kWh. This paper considers Hybrid Optimization of Multiple Energy Renewables to achieve lower levelized cost of energy and net present costs of a nanogrid for increased reliability and low per capita energy consumption of 150 kWh in a Sudan Savannah region of Nigeria. The proposed grid connected nanogrid aims to serve daily residential demand of 355 kWh. A range of 0.0110 $/kWh to 0.0095$/kWh and $366,210 to$288,680 as negative values of levelized cost of energy and net present cost respectively were realized, implying potentials for a large grid export. The renewable energy fraction of up to 98% was also achieved in addition to low greenhouse gas emission of 2,328 tons/year. The results may further be consolidated with strategies for power dispatch and load scheduling