Nitrate reduction over nanoscale zero-valent iron prepared by hydrogen reduction of goethite

Nitrate reduction with nanoscale zero-valent iron (NZVI) was reported as a potential technology to remove nitrate from nitrate-contaminated water. In this paper, nitrate reduction with NZVI prepared by hydrogen reduction of natural goethite (NZVI-N, -N represents natural goethite) and hydrothermal goethite (NZVI-H, -H represents hydrothermal goethite) was conducted. Besides, the effects of reaction time, nitrate concentration, iron-to-nitrate ratio on nitrate removal rate over NZVI-H and NZVI-N were investigated. To prove their excellent nitrate reduction capacities, NZVI-N and NZVI-H were compared with ordinary zero-valent iron (OZVI-N) through the static experiments. Based on all above investigations, the mechanism of nitrate reduction with NZVI-N was proposed. The result showed that reaction time, nitrate concentration, iron-to-nitrate ratio played an important role in nitrate reduction by NZVI-N and NZVI-H. Compared with OZVI, NZVI-N and NZVI-H showed little relationship with pH. And NZVI-N for nitrate composition offers a higher stability than NZVI-H because of the existence of Al-substitution. Furthermore, NZVI-N, prepared by hydrogen reduction of goethite, has higher activity for nitrate reduction and the products contain hydrogen, nitrogen, NH 4 +, a little nitrite, but no NOx, meanwhile NZVI-N was oxidized to Fe 2+. It is a relatively easy and cost-effective method for nitrate removal, so NZVI-N reducing nitrate has a great potential application in nitrate removal of groundwater. © 2012 Elsevier B.V.

Small and medium enterprises sourcing software as a service – a dynamic perspective on IS capabilities

Software as a Service (SaaS) is a promising approach for Small and Medium Enterprises (SMEs) firms, in particular those that are focused on growing fast and leveraging new technology, due to the potential benefits arising from its inherent scalability, reduced total cost of ownership and the ease of access to global innovations. This paper proposes a dynamic perspective on IS capabilities to understand and explain SMEs sourcing and levering SaaS. The model is derived from combining the IS capabilities of Feeny and Willcocks (1998) and the dynamic capabilities of Teece (2007) and contextualizing it for SMEs and SaaS. We conclude that SMEs sourcing and leveraging SaaS require leadership, business systems thinking and informed buying for sensing and seizing SaaS opportunities and require leadership and vendor development for transforming in terms of aligning and realigning specific tangible and intangible assets.

Jackknife for bias reduction in predictive regressions

One of the fundamental econometric models in finance is predictive regression. The standard least squares method produces biased coefficient estimates when the regressor is persistent and its innovations are correlated with those of the dependent variable. This article proposes a general and convenient method based on the jackknife technique to tackle the estimation problem. The proposed method reduces the bias for both single- and multiple-regressor models and for both short- and long-horizon regressions. The effectiveness of the proposed method is demonstrated by simulations. An empirical application to equity premium prediction using the dividend yield and the short rate highlights the differences between the results by the standard approach and those by the bias-reduced estimator. The significant predictive variables under the ordinary least squares become insignificant after adjusting for the finite-sample bias. These discrepancies suggest that bias reduction in predictive regressions is important in practical applications.

Wide-field assessment of the human corneal subbasal nerve plexus in diabetic neuropathy using a novel mapping technique

To develop a rapid optimized technique of wide-field imaging of the human corneal subbasal nerve plexus. A dynamic fixation target was developed and, coupled with semiautomated tiling software, a rapid method of capturing and montaging multiple corneal confocal microscopy images was created. To illustrate the utility of this technique, wide-field maps of the subbasal nerve plexus were produced in 2 participants with diabetes, 1 with and 1 without neuropathy. The technique produced montages of the central 3 mm of the subbasal corneal nerve plexus. The maps seem to show a general reduction in the number of nerve fibers and branches in the diabetic participant with neuropathy compared with the individual without neuropathy. This novel technique will allow more routine and widespread use of subbasal nerve plexus mapping in clinical and research situations. The significant reduction in the time to image the corneal subbasal nerve plexus should expedite studies of larger groups of diabetic patients and those with other conditions affecting nerve fibers. The inferior whorl and the surrounding areas may show the greatest loss of nerve fibers in individuals with diabetic neuropathy, but this should be further investigated in a larger cohort.

Photocatalytic reduction of carbon dioxide to formic acid, formaldehyde, and methanol using dye-sensitized TiO2 film

A bifunctionalized TiO2 film containing a dye-sensitized zone and a catalysis zone is designed for visible-light photocatalytic reduction of CO2 to chemicals continuously. Charge separation can be accomplished with electron transferring to catalysis zone and positive charge transforming to anode. Highly efficient conversion of CO2 to formic acid, formaldehyde, and methanol is achieved through the transferring electrons on conduction bands (CB) of TiO2. Reduction of CO2 and O2 evolution take place in separated solutions on different catalysts. The separated solution carried out in this photo-reactor system can avoid CO2 reduction products being oxidized by anode. The yields of reduction products were enhanced remarkably by external electrical power. This study provides not only a new photocatalytic system but also a potential of renewable energy source via carbon dioxide.

The development of a virtual reality environment to model the experience of schizophrenia

Virtual Reality (VR) techniques are increasingly being used for education about and in the treatment of certain types of mental illness. Research indicates that VR is delivering on its promised potential to provide enhanced training and treatment outcomes through incorporation of this high-end technology. Schizophrenia is a mental disorder affecting 1-2% of the population, and it is estimated 12-16% of hospital beds in Australia are occupied by patients with psychosis. Tragically, there is also an increased risk of suicide associated with this diagnosis. A significant research project being undertaken across the University of Queensland faculties of Health Sciences and EPSA (Engineering, Physical Sciences and Architecture) has constructed a number of virtual environments that reproduce the phenomena experienced by patients who have psychosis. Symptoms of psychosis include delusions, hallucinations and thought disorder. The VR environment will allow behavioral, exposure therapies to be conducted with exactly controlled exposure stimuli and an expected reduction in risk of harm. This paper reports on the current work of the project, previous stages of software development and the final goal to introduce VR to medical consulting rooms.

The application of virtual reality to the understanding and treatment of schizophrenia

Virtual Reality (VR) techniques are increasingly being used in education about and in the treatment of certain types of mental illness. Research indicates VR is delivering on it's promised potential to provide enhanced training and treatment outcomes through incorporation of this high-end technology. Schizophrenia is a mental disorder affecting 1−2% of the population. A significant research project being undertaken at the University of Queensland has constructed virtual environments that reproduce the phenomena experienced by patients who have psychosis. The VR environment will allow behavioral exposure therapies to be conducted with exactly controlled exposure stimuli and an expected reduction in risk of harm. This paper reports on the work of the project, previous stages of software development and current and future educational and clinical applications of the Virtual Environments.

Supporting risk-informed decisions during business process execution

This paper proposes a technique that supports process participants in making risk-informed decisions, with the aim to reduce the process risks. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we prompt the participant with the expected risk that a given fault will occur given the particular input. These risks are predicted by traversing decision trees generated from the logs of past process executions and considering process data, involved resources, task durations and contextual information like task frequencies. The approach has been implemented in the YAWL system and its effectiveness evaluated. The results show that the process instances executed in the tests complete with substantially fewer faults and with lower fault severities, when taking into account the recommendations provided by our technique.

Empirical analysis of the effect of dimension reduction and word order on semantic vectors

The aim of this paper is to provide a comparison of various algorithms and parameters to build reduced semantic spaces. The effect of dimension reduction, the stability of the representation and the effect of word order are examined in the context of the five algorithms bearing on semantic vectors: Random projection (RP), singular value decom- position (SVD), non-negative matrix factorization (NMF), permutations and holographic reduced representations (HRR). The quality of semantic representation was tested by means of synonym finding task using the TOEFL test on the TASA corpus. Dimension reduction was found to improve the quality of semantic representation but it is hard to find the optimal parameter settings. Even though dimension reduction by RP was found to be more generally applicable than SVD, the semantic vectors produced by RP are somewhat unstable. The effect of encoding word order into the semantic vector representation via HRR did not lead to any increase in scores over vectors constructed from word co-occurrence in context information. In this regard, very small context windows resulted in better semantic vectors for the TOEFL test.

Residence time investigation in a co-axial dielectric barrier discharge reactor

The residence time distribution (RTD) is a crucial parameter when treating engine exhaust emissions with a Dielectric Barrier Discharge (DBD) reactor. In this paper, the residence time of such a reactor is investigated using a finite element based software: COMSOL Multiphysics 4.3. Non-thermal plasma (NTP) discharge is being introduced as a promising method for pollutant emission reduction. DBD is one of the most advantageous of NTP technologies. In a two cylinder co-axial DBD reactor, tubes are placed between two electrodes and flow passes through the annuals between these barrier tubes. If the mean residence time increases in a DBD reactor, there will be a corresponding increase in reaction time and consequently, the pollutant removal efficiency can increase. However, pollutant formation can occur during increased mean residence time and so the proportion of fluid that may remain for periods significantly longer than the mean residence time is of great importance. In this study, first, the residence time distribution is calculated based on the standard reactor used by the authors for ultrafine particle (10-500 nm) removal. Then, different geometrics and various inlet velocities are considered. Finally, for selected cases, some roughness elements added inside the reactor and the residence time is calculated. These results will form the basis for a COMSOL plasma and CFD module investigation.

Identification of copper species present in Cu-ZSM-5 catalysts for NOx reduction

The structure of Cu-ZSM-5 catalysts that show activity for direct NO decomposition and selective catalytic reduction of NOx by hydrocarbons has been investigated by a multitude of modern surface analysis and spectroscopy techniques including X-ray photoelectron spectroscopy, thermogravimetric analysis, and in situ Fourier transform infrared spectroscopy. A series of four catalysts were prepared by exchange of Na-ZSM-5 with dilute copper acetate, and the copper loading was controlled by variation of the solution pH. Underexchanged catalysts contained isolated Cu2+OH-(H2O) species and as the copper loading was increased Cu2+ ions incorporated into the zeolite lattice appeared. The sites at which the latter two copper species were located were fundamentally different. The Cu2+OH-(H2O) moieties were bound to two lattice oxygen ions and associated with one aluminum framework species. In contrast, the Cu2+ ions were probably bound to four lattice oxygen ions and associated with two framework aluminum ions. Once the Cu-ZSM-5 samples attained high levels of exchange, the development of [Cu(μ-OH)2Cu]n2+OH-(H2O) species along with a small concentration of Cu(OH)2 was observed. On activation in helium to 500°C the Cu2+OH-(H2O) species transformed into Cu2+O- and Cu+ moieties, whereas the Cu2+ ions were apparently unaffected by this treatment (apart from the loss of ligated water molecules). Calcination of the precursors resulted in the formation of Cu2+O2- and a one-dimensional CuO species. Temperature-programmed desorption studies revealed that oxygen was removed from the latter two species at 407 and 575°C, respectively. © 1999 Academic Press.