Post-treatment of effluents from the sulfate reduction process by anaerobic sequencing batch biofilm reactors

The main objective of this research was to evaluate the potential use of a bench-scale anaerobic sequencing batch biofilm reactor (ASBBR) containing mineral coal as inert support for removal Of Sulfide and organic matter effluents from an ASBBR (1.2 m(3)) utilized for treatment of sulfate-rich wastewater. The cycle time was 48 h, including the steps of feeding (2 h), reaction with continuous liquid recirculation (44 h) and discharge (2 h). COD removal efficiency was up to 90% and the effluents total sulfide concentrations (H(2)S, HS(-), S(2-)) remained in the range of 1.5 to 7.5 mg.l(-1) during the 50 days of operation (25 cycles). The un-ionized Sulfide and ionized sulfides were converted by biological process to elemental sulfur (S(0)) under oxygen limited conditions. The results obtained in the bench-scale reactor were used to design an ASBBR in pilot scale for use in post-treatment to achieve the emission standards (sulfide and COD) for sulfate reduction. The pilot-scale reactor, with a total volume of 0.43 m(3), the COD and total sulfide removal achieved 88% and 57%, respectively, for a cycle time of 48 h (70 days of operation or 35 cycles).

Attribute reduction and missing value imputing with ANN: prediction of learning disabilities

Learning disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 10% of children enrolled in schools. There is no cure for learning disabilities and they are lifelong. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Just as there are many different types of LDs, there are a variety of tests that may be done to pinpoint the problem The information gained from an evaluation is crucial for finding out how the parents and the school authorities can provide the best possible learning environment for child. This paper proposes a new approach in artificial neural network (ANN) for identifying LD in children at early stages so as to solve the problems faced by them and to get the benefits to the students, their parents and school authorities. In this study, we propose a closest fit algorithm data preprocessing with ANN classification to handle missing attribute values. This algorithm imputes the missing values in the preprocessing stage. Ignoring of missing attribute values is a common trend in all classifying algorithms. But, in this paper, we use an algorithm in a systematic approach for classification, which gives a satisfactory result in the prediction of LD. It acts as a tool for predicting the LD accurately, and good information of the child is made available to the concerned

Influence of processing parameters on nanomaterials synthesis efficiency by a carbothermal reduction process

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Synthesis of SnO2 nanoribbons by a carbothermal reduction process

This communication describes, for the first time, the growth of SnO2 nanoribbons by a controlled carbothermal reduction process. An analysis of the transmission electron microscopy image revealed that these nanoribbons have a well-defined shape, with a typical width in the range of 70-300 nm. In general, the nanostructured ribbons were more than 100 mum in length. The results reported here support the hypothesis that this ribbon-like nanostructured material grows by a vapor-solid process. This study introduces two hypotheses to explain the SnO2 nanoribbon growth process.

A Distance-Based Method for Attribute Reduction in Incomplete Decision Systems

There are limitations in recent research undertaken on attribute reduction in incomplete decision systems. In this paper, we propose a distance-based method for attribute reduction in an incomplete decision system. In addition, we prove theoretically that our method is more effective than some other methods.

Generalized Discernibility Function Based Attribute Reduction in Incomplete Decision Systems

A rough set approach for attribute reduction is an important research subject in data mining and machine learning. However, most attribute reduction methods are performed on a complete decision system table. In this paper, we propose methods for attribute reduction in static incomplete decision systems and dynamic incomplete decision systems with dynamically-increasing and decreasing conditional attributes. Our methods use generalized discernibility matrix and function in tolerance-based rough sets.

Improving the Scalability of Reduct Determination in Rough Sets

Rough Set Data Analysis (RSDA) is a non-invasive data analysis approach that solely relies on the data to find patterns and decision rules. Despite its noninvasive approach and ability to generate human readable rules, classical RSDA has not been successfully used in commercial data mining and rule generating engines. The reason is its scalability. Classical RSDA slows down a great deal with the larger data sets and takes much longer times to generate the rules. This research is aimed to address the issue of scalability in rough sets by improving the performance of the attribute reduction step of the classical RSDA - which is the root cause of its slow performance. We propose to move the entire attribute reduction process into the database. We defined a new schema to store the initial data set. We then defined SOL queries on this new schema to find the attribute reducts correctly and faster than the traditional RSDA approach. We tested our technique on two typical data sets and compared our results with the traditional RSDA approach for attribute reduction. In the end we also highlighted some of the issues with our proposed approach which could lead to future research.

Delay reduction in courts of justice – possibilities and challenges of process improvement in professional public organizations

Delays in the justice system have been undermining the functioning and performance of the court system all over the world for decades. Despite the widespread concern about delays, the solutions have not kept up with the growth of the problem. The delay problem existing in the justice courts processes is a good example of the growing need and pressure in professional public organizations to start improving their business process performance.This study analyses the possibilities and challenges of process improvement in professional public organizations. The study is based on experiences gained in two longitudinal action research improvement projects conducted in two separate Finnish law instances; in the Helsinki Court of Appeal and in the Insurance Court. The thesis has two objectives. First objective is to study what kinds of factors in court system operations cause delays and unmanageable backlogs and how to reduce and prevent delays. Based on the lessons learned from the case projects the objective is to give new insights on the critical factors of process improvement conducted in professional public organizations. Four main areas and factors behind the delay problem is identified: 1) goal setting and performance measurement practices, 2) the process control system, 3) production and capacity planning procedures, and 4) process roles and responsibilities. The appropriate improvement solutions include tools to enhance project planning and scheduling and monitoring the agreed time-frames for different phases of the handling process and pending inventory. The study introduces the identified critical factors in different phases of process improvement work carried out in professional public organizations, the ways the critical factors can be incorporated to the different stages of the projects, and discusses the role of external facilitator in assisting process improvement work and in enhancing ownership towards the solutions and improvement. The study highlights the need to concentrate on the critical factors aiming to get the employees to challenge their existing ways of conducting work, analyze their own processes, and create procedures for diffusing the process improvement culture instead of merely concentrating of finding tools, techniques, and solutions appropriate for applications from the manufacturing sector

Reduction of mercury(II) by tropical river humic substances (Rio Negro) - A possible process of the mercury cycle in Brazil

The evolution of elemental Hg from its environmental compounds has already been supposed to be an important process within the global mercury cycle. The present study characterizes the abiotic reduction of Hg(II) ions by typical river humic substances (HS) conventionally pre-isolated by the adsorbent XAD 8 from the Rio Negro near Manaus, Brazil. For the investigation of this reduction process a special reaction and Hg(0) trapping unit combined with cold-vapor atomic absorption spectrometry (CVAAS) was developed. Preconcentration of traces of mercury(II), if required, was obtained by a home-made FIA system using microcolumns filled with the Hg(II)-selective collector CheliteS(R) (Serva Company). The effect of environmentally relevant parameters such as the pH value, the Hg(II)/HS ratio and the HS concentration on the I-IE;(II) reduction process was studied as a function of the time. The Hg(0) production was highest at pH 8.0 and in the case of decreasing HS amounts (0.5 mg) when about 65% of initially 1.0 mug Hg(H) was reduced within 50 h. Moreover, the reduction efficiency of HS towards HE;(II) strongly depended on the HS concentration but hardly on the Hg(II)/HS ratio. The reduction kinetics followed a relatively slow two-step first-order mechanism with formal rate constants of about 0.1 and 0.02 h(-1), respectively. Based on these findings the possible relevance of the abiotic evolution of mercury in humic-rich aquatic environments is considered. (C) 2000 Elsevier B.V. B.V. All rights reserved.

The inducing NO-vasodilation by chemical reduction of coordinated nitrite ion in cis-[Ru(NO(2))L(bpy)(2)](+) complex

The synthesis of [Ru(NO(2)) L(bpy)(2)](+) (bpy = 2,2'-bipyridine and L = pyridine (py) and pyrazine (pz)) can be accomplished by addition of [Ru(NO) L(bpy) 2](PF(6))(3) to aqueous solutions of physiological pH. The electrochemical processes of [Ru(NO2) L(bpy) 2]+ in aqueous solution were studied by cyclic voltammetry and differential pulse voltammetry. The anodic scan shows a peak around 1.00 V vs. Ag/AgCl attributed to the oxidation process centered on the metal ion. However, in the cathodic scan a second peak around-0.60 V vs. Ag/AgCl was observed and attributed to the reduction process centered on the nitrite ligand. The controlled reduction potential electrolysis at-0.80 V vs. Ag/AgCl shows NO release characteristics as judged by NO measurement with a NO-sensor. This assumption was confirmed by ESI/MS(+) and spectroelectrochemical experiment where cis-[Ru(bpy)(2)L(H(2)O)](2+) was obtained as a product of the reduction of cis-[Ru(II)(NO(2)) L(bpy)(2)](+). The vasorelaxation observed in denuded aortic rings pre-contracted with 0.1 mu mol L(-1) phenylephrine responded with relaxation in the presence of cis-[RuII(NO2) L(bpy) 2]+. The potential of rat aorta cells to metabolize cis-[RuII(NO(2)) L(bpy)(2)](+) was also followed by confocal analysis. The obtained results suggest that NO release happens by reduction of cis-[RuII(NO(2)) L(bpy)(2)](+) inside the cell. The maximum vasorelaxation was achieved with 1 x 10(-5) mol L(-1) of cis-[RuII(NO(2)) L(bpy)(2)](+) complex.

High Carbon Ferro-chromium Production by Self-reducing Process: Effects of Fe-Si and Fluxing Agent Additions

The technology of self-reducing pellets for ferro-alloys production is becoming an emerging process due to the lower electric energy consumption and the improvement of metal recovery in comparison with the traditional process. This paper presents the effects of reduction temperature, addition of ferro-silicon and addition of slag forming agents for the production of high carbon ferro-chromium by utilization of self-reducing pellets. These pellets were composed of Brazilian chromium ore (chromite) concentrate, petroleum coke, Portland cement, ferro-silicon and slag forming components (silica and hydrated lime). The pellets were processed at 1 773 K, 1 823 K and 1 873 K using an induction furnace. The products obtained, containing slag and metallic phases, were analyzed by scanning electron microscopy and chemical analyses (XEDS). A large effect on the reduction time was observed by increasing the temperature from 1 773 K to 1 823 K for pellets without Fe-Si addition: around 4 times faster at 1 823 K than at 1 773 K for reaction fraction close to one. However, when the temperature was further increased from 1 823 K to 1 873 K the kinetics improved by double. At 1 773 K, the addition of 2% of ferro-silicon in the pellet resulted in an increasing reaction rate of around 6 times, in comparison with agglomerate without it. The addition of fluxing agents (silica and lime), which form initial slag before the reduction is completed, impaired the full reduction. These pellets became less porous after the reduction process.

Process intensification: From optimised flow patterns to microprocess technology

This thesis is focused on process intensification. Several significant problems and applications of this theme are covered. Process intensification is nowadays one of the most popular trends in chemical engineering and attempts have been made to develop a general, systematic methodology for intensification. This seems, however, to be very difficult, because intensified processes are often based on creativity and novel ideas. Monolith reactors and microreactors are successful examples of process intensification. They are usually multichannel devices in which a proper feed technique is important for creating even fluid distribution into the channels. Two different feed techniques were tested for monoliths. In the first technique a shower method was implemented by means of perforated plates. The second technique was a dispersion method using static mixers. Both techniques offered stable operation and uniform fluid distribution. The dispersion method enabled a wider operational range in terms of liquid superficial velocity. Using dispersion method, a volumetric gas-liquid mass transfer coefficient of 2 s-1 was reached. Flow patterns play a significant role in terms of the mixing performance of micromixers. Although the geometry of a T-mixer is simple, channel configurations and dimensions had a clear effect on mixing efficiency. The flow in the microchannel was laminar, but the formation of vortices promoted mixing in micro T-mixers. The generation of vortices was dependent on the channel dimensions, configurations and flow rate. Microreactors offer a high ratio of surface area to volume. Surface forces and interactions between fluids and surfaces are, therefore, often dominant factors. In certain cases, the interactions can be effectively utilised. Different wetting properties of solid materials (PTFE and stainless steel) were applied in the separation of immiscible liquid phases. A micro-scale plate coalescer with hydrophilic and hydrophobic surfaces was used for the continuous separation of organic and aqueous phases. Complete phase separation occurred in less than 20 seconds, whereas the separation time by settling exceeded 30 min. Fluid flows can be also intensified in suitable conditions. By adding certain additives into turbulent fluid flow, it was possible to reduce friction (drag) by 40 %. Drag reduction decreases frictional pressure drop in pipelines which leads to remarkable energy savings and decreases the size or number of pumping facilities required, e.g., in oil transport pipes. Process intensification enables operation often under more optimal conditions. The consequent cost savings from reduced use of raw materials and reduced waste lead to greater economic benefits in processing.