Structural and Superconducting Property Variations with Nominal Mg Non‐Stoichiometry in MgxB2 and Its Enhancement of Upper Critical Field

By applying a combination of characterisation tools, changes in structural and superconducting properties with nominal Mg non‐stoichiometry in Mg_xB₂ are found. The non‐stoichiometry produces enhanced in‐field critical current densities (J_c's) and upper critical field / irreversibility field (H_c2/H_irr(T)) values. Upper critical fields of ～ 21 T (4.2 K) were obtained in nominal Mg‐deficient samples compared to ～ 17 T (4.2 K) for near‐stoichiometric samples.     

Performance evaluation of a water/silicone oil two‐phase partitioning bioreactor using Rhodococcus erythropolis T902.1 to remove volatile organic compounds from gaseous effluents

BACKGROUND: In the framework of biological processes used for waste gas treatment, the impact of the inoculum size on the start‐up performance needs to be better evaluated. Moreover, only a few studies have investigated the behaviour of elimination capacity and biomass viability in a two‐phase partitioning bioreactor (TPPB) used for waste gas treatment. Lastly, the impact of ethanol as a co‐substrate remains misunderstood. RESULTS: Firstly, no benefit of inoculation with a high cellular density (>1.5 g L^?1) was observed in terms of start‐up performance. Secondly, the TPPB was monitored for 38 days to characterise its behaviour under several operational conditions. The removal efficiency remained above 63% for an inlet concentration of 7 g isopropylbenzene (IPB) m^?3 and at some time points reached 92% during an intermittent loading phase (10 h day^?1), corresponding to a mean elimination capacity of 4 × 10^?3 g L^?1 min^?1 (240 g m^?3 h^?1) for a mean IPB inlet load of 6.19 × 10^?3 g L^?1 min^?1 (390 g m^?3 h^?1). Under continuous IPB loading, the performance of the TPPB declined, but the period of biomass acclimatisation to this operational condition was shorter than 5 days. The biomass grew to approximately 10 g L^?1 but the cellular viability changed greatly during the experiment, suggesting an endorespiration phenomenon in the bioreactor. It was also shown that simultaneous degradation of IPB and ethanol occurred, suggesting that ethanol improves the biodegradation process without causing oxygen depletion. CONCLUSION: A water/silicone oil TPPB with ethanol as co‐substrate allowed the removal of a high inlet load of IPB during an experiment lasting 38 days. Copyright © 2008 Society of Chemical Industry     

Simultaneous sulfide and acetate oxidation under denitrifying conditions using an inverse fluidized bed reactor

BACKGROUND: Simultaneous removal of sulfur, nitrogen and carbon compounds from wastewaters is a commercially important biological process. The objective was to evaluate the influence of the CH₃COO^?/NO₃^? molar ratio on the sulfide oxidation process using an inverse fluidized bed reactor (IFBR). RESULTS: Three molar ratios of CH₃COO^?/NO₃^? (0.85, 0.72 and 0.62) with a constant S^2?/NO₃^? molar ratio of 0.13 were evaluated. At a CH₃COO^?/NO₃^? molar ratio of 0.85, the nitrate, acetate and sulfide removal efficiencies were approximately 100%. The N₂ yield (g N₂ g^?1 NO₃^?‐N consumed) was 0.81. Acetate was mineralized, resulting in a yield of 0.65 g inorganic‐C g^?1 CH₃COO^?‐C consumed. Sulfide was partially oxidized to S⁰, and 71% of the S^2? consumed was recovered as elemental sulfur by a settler installed in the IFBR. At a CH₃COO^?/NO₃^? molar ratio of 0.72, the efficiencies of nitrate, acetate and sulfide consumption were of 100%, with N₂ and inorganic‐C yields of 0.84 and 0.69, respectively. The sulfide was recovered as sulfate instead of S⁰, with a yield of 0.92 g SO₄^2?‐S g^?1 S^2? consumed. CONCLUSIONS: The CH₃COO^?/NO₃^? molar ratio was shown to be an important parameter that can be used to control the fate of sulfide oxidation to either S⁰ or sulfate. In this study, the potential of denitrification for the simultaneous removal of organic matter, sulfide and nitrate from wastewaters was demonstrated, obtaining CO₂, S⁰ and N₂ as the major end products. Copyright © 2008 Society of Chemical Industry     

Comparison of copper emission rates from wood treated with different preservatives to the environment

This study describes a laboratory method for the estimation of emission from preservative-treated wood in the different situations where emissions could enter the environment for use classes 3 (not in contact with ground) and 4 and 5 (in contact with the ground, fresh water or sea water) according to OECD Guidelines. Samples of scotch pine sapwood (Pinus sylvestris L.) were treated with CCA (1% and 2%), ACQ-1900 (3% and 7%), ACQ-2200 (2%), Tanalith E 3491 (2% and 2.8%), and Wolmanit CX-8 (2%).     

Inverted Solution Processable OLEDs Using a Metal Oxide as an Electron Injection Contact.

A new type of bottom‐emission electroluminescent device is described in which a metal oxide is used as the electron‐injecting contact. The preparation of such a device is simple. It consists of the deposition of a thin layer of a metal oxide on top of an indium tin oxide covered glass substrate, followed by the solution processing of the light‐emitting layer and subsequently the deposition of a high‐workfunction (air‐stable) metal anode. This architecture allows for a low‐cost electroluminescent device because no rigorous encapsulation is required. Electroluminescence with a high brightness reaching 5700 cd m^–2 is observed at voltages as low as 8 V, demonstrating the potential of this new approach to organic light‐emitting diode (OLED) devices. Unfortunately the device efficiency is rather low because of the high current density flowing through the device. We show that the device only operates after the insertion of an additional hole‐injection layer in between the light‐emitting polymer (LEP) and the metal anode. A simple model that explains the experimental results and provides avenues for further optimization of these devices is described. It is based on the idea that the barrier for electron injection is lowered by the formation of a space–charge field over the metal‐oxide–LEP interface due to the build up of holes in the LEP layer close to this interface.     

Optimal and self‐tuning fusion Kalman filters for discrete‐time stochastic singular systems

Based on the optimal fusion estimation algorithm weighted by scalars in the linear minimum variance sense, a distributed optimal fusion Kalman filter weighted by scalars is presented for discrete‐time stochastic singular systems with multiple sensors and correlated noises. A cross‐covariance matrix of filtering errors between any two sensors is derived. When the noise statistical information is unknown, a distributed identification approach is presented based on correlation functions and the weighted average method. Further, a distributed self‐tuning fusion filter is given, which includes two stage fusions where the first‐stage fusion is used to identify the noise covariance and the second‐stage fusion is used to obtain the fusion state filter. A simulation verifies the effectiveness of the proposed algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

A framework to integrate software behavior into dynamic probabilistic risk assessment

Software plays an increasingly important role in modern safety-critical systems. Although, research has been done to integrate software into the classical probabilistic risk assessment (PRA) framework, current PRA practice overwhelmingly neglects the contribution of software to system risk. Dynamic probabilistic risk assessment (DPRA) is considered to be the next generation of PRA techniques. DPRA is a set of methods and techniques in which simulation models that represent the behavior of the elements of a system are exercised in order to identify risks and vulnerabilities of the system. The fact remains, however, that modeling software for use in the DPRA framework is also quite complex and very little has been done to address the question directly and comprehensively. This paper develops a methodology to integrate software contributions in the DPRA environment. The framework includes a software representation, and an approach to incorporate the software representation into the DPRA environment SimPRA. The software representation is based on multi-level objects and the paper also proposes a framework to simulate the multi-level objects in the simulation-based DPRA environment. This is a new methodology to address the state explosion problem in the DPRA environment. This study is the first systematic effort to integrate software risk contributions into DPRA environments.     

Note on ‘Construction of Double Sampling s‐Control Charts for Agile Manufacturing’

He and Grigoryan (Quality and Reliability Engineering International 2002; 18 :343–355) formulated the design of a double‐sampling (DS) s control chart as an optimization problem and solved it with a genetic algorithm. They concluded that the DS s control charts can be a more economically preferable alternative in detecting small shifts than traditional s control charts. We explain that, since they only considered the average sample size when the process is in control, their conclusion is questionable. Copyright © 2006 John Wiley & Sons, Ltd.     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.