Control policies for an industrial acetylene hydrogenation reactor

This paper addresses the problem of finding optimal operational policies for an acetylene reactor for day to day operation. A lumped parameter model based on four main reactions is developed and used to examine the effects of the reactor manipulated variables on key reaction parameters. An optimal and a sub-optimal operational policy which minimize the ethylene loss over time are formulated and the solution techniques are presented. The results indicate that the reactor model is in good agreement with industrial plant data. The performance of the optimal control policy is very similar to the performance of the sub-optimal control policy. However, the sub-optimal formulation, while retaining the dominant features of the optimal response, reduces the computational requirements. Finally, some issues concerning the real-time implementation of an advanced acetylene reactor control scheme are presented. These include the estimation of the optimum regeneration cycle, a recursive model update algorithm, the process optimizer and their overall coordination. A preliminary analysis of the benefits associated with the advanced control scheme suggests a considerable reduction in the yearly ethylene loss.     

Isolation of erucic acid from rapeseed oil by lipase-catalyzed hydrolysis

Three lipases were compared for their ability to hydrolyze high erucic acid rapeseed oil, with the objective of concentrating the erucic acid in a single glyceride fraction. Lipase fromPseudomonas cepacia released all fatty acids rapidly and did not result in selective distribution of erucic acid.Geotrichum candidum lipase released C20 and C22 fatty acids extremely slowly, resulting in their accumulation in the di- and triglyceride fractions. Less than 2% of the total erucic acid was found in the free fatty acid (FFA) fraction. Lipase fromCandida rugosa released erucic acid more slowly than C20 and C18 fatty acids at 35°C but only resulted in a limited accumulation of the erucic acid in the di- and triglyceride fractions. However, when hydrolysis catalyzed byC. rugosa lipase was carried out below 20°C, the reaction mixture solidified and was composed solely of FFAs and diglycerides. The diglyceride fraction contained approximately 95% erucic acid while about 20% of the total erucic acid was found in the FFA fraction. It is concluded that hydrolysis at low temperature withC. rugosa lipase results in a higher purity of erucic acid in the glyceride fraction than can be obtained withG. candidum lipase, but with considerable loss of erucic acid to the FFA fraction.     

Associations between apolipoprotein E genotype and circulating F<Subscript>2</Subscript>-isoprostane levels in humans

Apolipoprotein E (apoE), an important determinant of plasma lipoprotein metabolism, has three common alleles (ε2, ε3, and ε4). Population studies have shown that the risk of diseases characterized by oxidative damage, such as coronary heart disease and Alzheimer’s disease, is significantly higher in ɛ4 carriers. We evaluated the association between apoE genotypes and plasma F₂-isoprostane levels, an index of lipid peroxidation, in humans. Two hundred seventy-four healthy subjects (104 males, 170 females; 46.9±13.0 yr; 200 whites, 74 blacks; 81 nonsmokers, 64 passive smokers, and 129 active smokers) recruited for a randomized clinical antioxidant intervention trial were included in this analysis. ApoE genotype was determined by PCR and restriction enzyme digestion. Free plasma F₂-isoprostane was measured by GC-MS. Genotype groups were compared using multiple regression analysis with adjustment for sex, age, race, smoking status, body mass index, plasma ascorbic acid, and β-carotene. Subjects with ε3/ε4 and ε4/ε4 genotype (ε4-carriers) and with ε2/ε3 and ε3/ε3 (non-ε4-carriers) were pooled for analysis. In subjects with high cholesterol levels (total cholesterol above 200 mg/dl), plasma F₂-isoprostane levels were 29% higher in ε4 carriers than in non-ε4-carriers (P=0.0056). High-cholesterol subjects that are ε4 carriers have significantly higher levels of lipid peroxidation as assessed by circulating F₂-isoprostane levels.     

Sustainable end-of-life vehicle recycling: R&;D collaboration between industry and the U.S. DOE

Approximately 15 million cars and trucks reach the end of their useful life in the United States each year. More than 75% of the materials from end-of-life vehicles are profitably recovered and recycled by the private sector; automotive materials recycling is a success story. To achieve greater fuel efficiency and safety, today’s cars incorporate an increasing share of innovative light-weight materials. While these materials greatly enhance efficiency during vehicle use, they can present special challenges for recycling. These challenges will persist as automotive designs and the mix of materials used in vehicles continue evolving to further improve safety and performance. To meet the challenges of automotive materials recycling, the U.S. Department of Energy has recently expanded its collaborative research with industry in this area. This article discusses this collaborative government/industry approach to sustainable end-of-life vehicle recycling. For more information, contact Edward J. Daniels, Argonne National Laboratory, 9700 S. Cass Avenue, Building 362, Room C393, Argonne, IL 60439-4815; (630) 252-5279; fax (630) 252-1342; e-mail edaniels@anl.gov.     

A Hybrid Color Quantization Algorithm Incorporating a Human Visual Perception Model

Color quantization is a common image processing technique where full color images are to be displayed using a limited palette of colors. The choice of a good palette is crucial as it directly determines the quality of the resulting image. Standard quantization approaches aim to minimize the mean squared error (MSE) between the original and the quantized image, which does not correspond well to how humans perceive the image differences. In this article, we introduce a color quantization algorithm that hybridizes an optimization scheme based with an image quality metric that mimics the human visual system. Rather than minimizing the MSE, its objective is to maximize the image fidelity as evaluated by S‐CIELAB, an image quality metric that has been shown to work well for various image processing tasks. In particular, we employ a variant of simulated annealing with the objective function describing the S‐CIELAB image quality of the quantized image compared with its original. Experimental results based on a set of standard images demonstrate the superiority of our approach in terms of achieved image quality.     

Evaluation of Sensors and Mapping Approaches for Disasters in Tunnels

Ground or aerial robots equipped with advanced sensing technologies, such as three‐dimensional laser scanners and advanced mapping algorithms, are deemed useful as a supporting technology for first responders. A great deal of excellent research in the field exists, but practical applications at real disaster sites are scarce. Many projects concentrate on equipping robots with advanced capabilities, such as autonomous exploration or object manipulation. In spite of this, realistic application areas for such robots are limited to teleoperated reconnaissance or search. In this paper, we investigate how well state‐of‐the‐art and off‐the‐shelf components and algorithms are suited for reconnaissance in current disaster‐relief scenarios. The basic idea is to make use of some of the most common sensors and deploy some widely used algorithms in a disaster situation, and to evaluate how well the components work for these scenarios. We acquired the sensor data from two field experiments, one from a disaster‐relief operation in a motorway tunnel, and one from a mapping experiment in a partly closed down motorway tunnel. Based on these data, which we make publicly available, we evaluate state‐of‐the‐art and off‐the‐shelf mapping approaches. In our analysis, we integrate opinions and replies from first responders as well as from some algorithm developers on the usefulness of the data and the limitations of the deployed approaches, respectively. We discuss the lessons we learned during the two missions. These lessons are interesting for the community working in similar areas of urban search and rescue, particularly reconnaissance and search.     

An Integrated Approach to Locality-Conscious Processor Allocation and Scheduling of Mixed-Parallel Applications

Complex parallel applications can often be modeled as directed acyclic graphs of coarse-grained application tasks with dependences. These applications exhibit both task and data parallelism, and combining these two (also called mixed parallelism) has been shown to be an effective model for their execution. In this paper, we present an algorithm to compute the appropriate mix of task and data parallelism required to minimize the parallel completion time (makespan) of these applications. In other words, our algorithm determines the set of tasks that should be run concurrently and the number of processors to be allocated to each task. The processor allocation and scheduling decisions are made in an integrated manner and are based on several factors such as the structure of the task graph, the runtime estimates and scalability characteristics of the tasks, and the intertask data communication volumes. A locality-conscious scheduling strategy is used to improve intertask data reuse. Evaluation through simulations and actual executions of task graphs derived from real applications and synthetic graphs shows that our algorithm consistently generates schedules with a lower makespan as compared to Critical Path Reduction (CPR) and Critical Path and Allocation (CPA), two previously proposed scheduling algorithms. Our algorithm also produces schedules that have a lower makespan than pure task- and data-parallel schedules. For task graphs with known optimal schedules or lower bounds on the makespan, our algorithm generates schedules that are closer to the optima than other scheduling approaches.     

Hyperprolactinemia in end‐stage renal disease and effects of frequent hemodialysis

Introduction: End‐stage renal disease is associated with elevations in circulating prolactin concentrations, but the association of prolactin concentrations with intermediate health outcomes and the effects of hemodialysis frequency on changes in serum prolactin have not been examined. Methods: The FHN Daily and Nocturnal Dialysis Trials compared the effects of conventional thrice weekly hemodialysis with in‐center daily hemodialysis (6 days/week) and nocturnal home hemodialysis (6 nights/week) over 12 months and obtained measures of health‐related quality of life, self‐reported physical function, mental health and cognition. Serum prolactin concentrations were measured at baseline and 12‐month follow‐up in 70% of the FHN Trial cohort to examine the associations among serum prolactin concentrations and physical, mental and cognitive function and the effects of hemodialysis frequency on serum prolactin. Findings: Among 177 Daily Trial and 60 Nocturnal Trial participants with baseline serum prolactin measurements, the median serum prolactin concentration was 65 ng/mL (25th–75th percentile 48–195 ng/mL) and 81% had serum prolactin concentrations >30 ng/mL. While serum prolactin was associated with sex (higher in women), we observed no association between baseline serum prolactin and age, dialysis vintage, and baseline measures of physical, mental and cognitive function. Furthermore, there was no significant effect of hemodialysis frequency on serum prolactin in either of the two trials. Discussion: Serum prolactin concentrations were elevated in the large majority of patients with ESRD, but were not associated with several measures of health status. Circulating prolactin levels also do not appear to decrease in response to more frequent hemodialysis over a one‐year period.