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     

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.     

洞穴——从微中子研究到地下空间规划

微中子研究需要很大很深的洞穴，以便在没有太多宇宙射线噪音的情况下捕获重要事件。大型的自然洞穴往往出现在喀斯特石灰岩地区，少数大型洞穴也会出现在矿区，而民用洞穴则被广泛用作发电站、火车站、仓库及其他用途。应力控制被认为是在洞穴深挖中消除巨大应力的普遍方法。如果能够在大型洞穴使用应力控制方法，我们就可以建造安全的洞室来进行微中子研究；从另一方面来讲，大而浅的洞穴也能解决城市规划的很多问题。     

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.     

Maximum Cardinality Search for Computing Minimal Triangulations of Graphs

We present a new algorithm, called MCS-M, for computing minimal triangulations of graphs. Lex-BFS, a seminal algorithm for recognizing chordal graphs, was the genesis for two other classical algorithms: LEX M and MCS. LEX M extends the fundamental concept used in Lex-BFS, resulting in an algorithm that not only recognizes chordality, but also computes a minimal triangulation of an arbitrary graph. MCS simplifies the fundamental concept used in Lex-BFS, resulting in a simpler algorithm for recognizing chordal graphs. The new algorithm MCS-M combines the extension of LEX M with the simplification of MCS, achieving all the results of LEX M in the same time complexity.     

Predicting Acute Renal Failure after Cardiac Surgery: Validation and Re‐definition of a Risk‐Stratification Algorithm

Background:  Acute renal failure (ARF) after cardiac surgery is associated with significant morbidity and mortality, irrespective of the need for dialysis. Previous studies have attempted to identify predictors of ARF and develop risk stratification algorithms. This study aims to validate the algorithm in an independent cohort of patients that includes a significant proportion of female and black patients and compares two different definitions of renal outcome.
Methods:  A large single center cardiac surgery database was examined (n, 24,660; 1993–2000) which included 29.9% females and 3.7% black patients. Post‐operative ARF was defined as: a) ARF requiring dialysis, b) > 50% reduction in creatinine clearance relative to baseline or requiring dialysis. Clinical variables related to baseline renal function and cardiovascular disease were used in recursive partitioning analysis for both outcome definitions. Chi‐square goodness of fit analysis was performed to validate the algorithm.
Results:  The frequency of post‐operative ARF requiring dialysis ranged between 0.5 and 15.5% based on the risk categories with the area under the receiver operating characteristic (ROC) curve of 0.78. Using the more inclusive definition of ARF, the frequency was significantly higher ranging from 2.6 to 25%(P < 0.001) with an area under ROC curve of 0.65.
Conclusions:  The renal risk stratification algorithm is valid in predicting post‐operative ARF in an independent cohort of patients, well represented by differences in gender and race. Since the need for dialysis remains subjective, a more objective and inclusive definition of ARF may help in identifying a larger number of patients 'at‐risk'.     

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.