Compliance aware business process design

Historically, business process design has been driven by business objectives, specifically process improvement. However this cannot come at the price of control objectives which stem from various legislative, standard and business partnership sources. Ensuring the compliance to regulations and industrial standards is an increasingly important issue in the design of business processes. In this paper, we advocate that control objectives should be addressed at an early stage, i.e., design time, so as to minimize the problems of runtime compliance checking and consequent violations and penalties. To this aim, we propose supporting mechanisms for business process designers. This paper specifically presents a support method which allows the process designer to quantitatively measure the compliance degree of a given process model against a set of control objectives. This will allow process designers to comparatively assess the compliance degree of their design as well as be better informed on the cost of non-compliance.

A simple design methodology for elliptical cross-section, transverse, asymmetric, head gradient coils for MRI

A simple design process for the design of elliptical cross-section, transverse gradient coils for use in magnetic resonance imaging (MRI) is presented. This process is based on a flexible stochastic optimization method and results in designs of high linearity and efficiency with low switching times. A design study of a shielded, transverse asymmetric elliptical coil set for use in neural imaging is presented and includes the minimization of the torques experienced by the gradient set.

Applications of NMR in drug design: Sructure-activity relationships in disulfide-rich peptides

NMR is a powerful technique for determining structures of biologically active molecules in solution. In recent years. our laboratory has focussed on the structure determination of small disulfide-rich proteins from both plants and animals which are valuable targets in drug design applications. This article will review these structural studies and their implications in drug design.

Asymmetric MRI magnet design using a hybrid numerical method

This paper describes a hybrid numerical method for the design of asymmetric magnetic resonance imaging magnet systems. The problem is formulated as a field synthesis and the desired current density on the surface of a cylinder is first calculated by solving a Fredholm equation of the first kind. Nonlinear optimization methods are then invoked to fit practical magnet coils to the desired current density. The field calculations are performed using a semi-analytical method. A new type of asymmetric magnet is proposed in this work. The asymmetric MRI magnet allows the diameter spherical imaging volume to be positioned close to one end of the magnet. The main advantages of making the magnet asymmetric include the potential to reduce the perception of claustrophobia for the patient, better access to the patient by attending physicians, and the potential for reduced peripheral nerve stimulation due to the gradient coil configuration. The results highlight that the method can be used to obtain an asymmetric MRI magnet structure and a very homogeneous magnetic field over the central imaging volume in clinical systems of approximately 1.2 m in length. Unshielded designs are the focus of this work. This method is flexible and may be applied to magnets of other geometries. (C) 1999 Academic Press.

Molecular characterization of the toxic cyanobacterium Cylindrospermopsis raciborskii and design of a species-specific PCR

Cylindrospermopsis raciborskii is a toxic-bloom-forming cyanobacterium that is commonly found in tropical to subtropical climatic regions worldwide, but it is also recognized as a common component of cyanobacterial communities in temperate climates. Genetic profiles of C. raciborskii were examined in 19 cultured isolates originating from geographically diverse regions of Australia and represented by two distinct morphotypes. A 609-bp region of rpoC1, a DNA-dependent RNA polymerase gene, was amplified by PCR from these isolates with cyanobacterium-specific primers. Sequence analysis revealed that all isolates belonged to the same species, including morphotypes with straight or coiled trichomes. Additional rpoC1 gene sequences obtained for a range of cyanobacteria highlighted clustering of C. raciborskii with other heterocyst-producing cyanobacteria (orders Nostocales and Stigonematales). In contrast, randomly amplified polymorphic DNA and short tandemly repeated repetitive sequence profiles revealed a greater level of genetic heterogeneity among C. raciborskii isolates than did rpoC1 gene analysis, and unique band profiles were also found among each of the cyanobacterial genera examined. A PCR test targeting a region of the rpoC1 gene unique to C. raciborskii was developed for the specific identification of C. raciborskii from both purified genomic DNA and environmental samples. The PCR was evaluated with a number of cyanobacterial isolates, but a PCR-positive result was only achieved with C, raciborskii. This method provides an accurate alternative to traditional morphological identification of C. raciborskii.

Approach to designing rotating drum bioreactors for solid-state fermentation on the basis of dimensionless design factors

The development of large-scale solid-stale fermentation (SSF) processes is hampered by the lack of simple tools for the design of SSF bioreactors. The use of semifundamental mathematical models to design and operate SSF bioreactors can be complex. In this work, dimensionless design factors are used to predict the effects of scale and of operational variables on the performance of rotating drum bioreactors. The dimensionless design factor (DDF) is a ratio of the rate of heat generation to the rate of heat removal at the time of peak heat production. It can be used to predict maximum temperatures reached within the substrate bed for given operational variables. Alternatively, given the maximum temperature that can be tolerated during the fermentation, it can be used to explore the combinations of operating variables that prevent that temperature from being exceeded. Comparison of the predictions of the DDF approach with literature data for operation of rotating drums suggests that the DDF is a useful tool. The DDF approach was used to explore the consequences of three scale-up strategies on the required air flow rates and maximum temperatures achieved in the substrate bed as the bioreactor size was increased on the basis of geometric similarity. The first of these strategies was to maintain the superficial flow rate of the process air through the drum constant. The second was to maintain the ratio of volumes of air per volume of bioreactor constant. The third strategy was to adjust the air flow rate with increase in scale in such a manner as to maintain constant the maximum temperature attained in the substrate bed during the fermentation. (C) 2000 John Wiley & Sons, Inc.

A hybrid, inverse approach to the design of magnetic resonance imaging magnets

This paper describes a hybrid numerical method of an inverse approach to the design of compact magnetic resonance imaging magnets. The problem is formulated as a field synthesis and the desired current density on the surface of a cylinder is first calculated by solving a Fredholm equation of the first, kind. Nonlinear optimization methods are then invoked to fit practical magnet coils to the desired current density. The field calculations are performed using a semi-analytical method. The emphasis of this work is on the optimal design of short MRI magnets. Details of the hybrid numerical model are presented, and the model is used to investigate compact, symmetric MRI magnets as well as asymmetric magnets. The results highlight that the method can be used to obtain a compact MRI magnet structure and a very homogeneous magnetic field over the central imaging volume in clinical systems of approximately 1 m in length, significantly shorter than current designs. Viable asymmetric magnet designs, in which the edge of the homogeneous region is very close to one end of the magnet system are also presented. Unshielded designs are the focus of this work. This method is flexible and may be applied to magnets of other geometries. (C) 2000 American Association of Physicists in Medicine. [S0094-2405(00)00303-5].

Conformational selection of inhibitors and substrates by proteolytic enzymes: Implications for drug design and polypeptide processing

Inhibitors of proteolytic enzymes (proteases) are emerging as prospective treatments for diseases such as AIDS and viral infections, cancers, inflammatory disorders, and Alzheimer's disease. Generic approaches to the design of protease inhibitors are limited by the unpredictability of interactions between, and structural changes to, inhibitor and protease during binding. A computer analysis of superimposed crystal structures for 266 small molecule inhibitors bound to 48 proteases (16 aspartic, 17 serine, 8 cysteine, and 7 metallo) provides the first conclusive proof that inhibitors, including substrate analogues, commonly bind in an extended beta-strand conformation at the active sites of all these proteases. Representative superimposed structures are shown for (a) multiple inhibitors bound to a protease of each class, (b) single inhibitors each bound to multiple proteases, and (c) conformationally constrained inhibitors bound to proteases. Thus inhibitor/substrate conformation, rather than sequence/composition alone, influences protease recognition, and this has profound implications for inhibitor design. This conclusion is supported by NMR, CD, and binding studies for HIV-1 protease inhibitors/ substrates which, when preorganized in an extended conformation, have significantly higher protease affinity. Recognition is dependent upon conformational equilibria since helical and turn peptide conformations are not processed by proteases. Conformational selection explains the resistance of folded/structured regions of proteins to proteolytic degradation, the susceptibility of denatured proteins to processing, and the higher affinity of conformationally constrained 'extended' inhibitors/substrates for proteases. Other approaches to extended inhibitor conformations should similarly lead to high-affinity binding to a protease.

Design of the multicenter Australian study of epidural anesthesia and analgesia in major surgery: The MASTER Trial

The Multicenter Australian Study of Epidural Anesthesia and Analgesia in Major Surgery (The MASTER Trial) was designed to evaluate the possible benefit of epidural block in improving outcome in high-risk patients. The trial began in 1995 and is scheduled to reach the planned sample size of 900 during 2001. This paper describes the trial design and presents data comparing 455 patients randomized in 21 institutions in Australia, Hong Kong, and Malaysia, with 237 patients from the same hospitals who were eligible but not randomized. Nine categories of high-risk patients were defined as entry criteria for the trial. Protocols for ethical review, informed consent, randomization, clinical anesthesia and analgesia, and perioperative management were determined following extensive consultation with anesthesiologists throughout Australia. Clinical and research information was collected in participating hospitals by research staff who may not have been blind to allocation. Decisions about the presence or absence of endpoints were made primarily by a computer algorithm, supplemented by blinded clinical experts. Without unblinding the trial, comparison of eligibility criteria and incidence of endpoints between randomized and nonrandomized patients showed only small differences. We conclude that there is no strong evidence of important demographic or clinical differences between randomized and nonrandomized patients eligible for the MASTER Trial. Thus, the trial results are likely to be broadly generalizable. Control Clin Trials 2000;21:244-256 (C) Elsevier Science Inc. 2000.

Decentralized control design for nonlinear plants: a v-metric approach

In this paper, a new v-metric based approach is proposed to design decentralized controllers for multi-unit nonlinear plants that admit a set of plant decompositions in an operating space. Similar to the gap metric approach in literature, it is shown that the operating space can also be divided into several subregions based on a v-metric indicator, and each of the subregions admits the same controller structure. A comparative case study is presented to display the advantages of proposed approach over the gap metric approach. (C) 2000 Elsevier Science Ltd. All rights reserved.

Eye design and color signaling in a stomatopod crustacean Gonodactylus smithii

Many species of stomatopod crustaceans have multiple spectral classes of photoreceptors in their retinas. Behavioral evidence also indicates that stomatopods are capable of discriminating objects by their spectral differences alone, Most animals use only two to four different types of photoreceptors in their color vision systems, typically with broad sensitivity functions, but the stomatopods apparently include eight or more narrowband photoreceptor classes for color recognition. It is also known that stomatopods use several colored body regions in social interactions. To examine why stomatopods may be so 'concerned' with color, we measured the absorption spectra of visual pigments and intrarhabdomal filters, and the reflectance spectra from different parts of the bodies of several individuals of the gonodactyloid stomatopod species, Gonodactylus smithii. We then applied a model of multiple dichromatic channels for color encoding to examine whether the finely tuned color vision was specifically co-evolved with their complex color signals. Although the eye design of stomatopods seems suitable for detecting color signals of their own, the detection of color signals from other animals, such as reef fishes, can be enhanced as well. Color vision in G. smithii is therefore not exclusively adapted to detect its own color signals, but the spectral tuning of some photoreceptors (e.g. midband Rows 2 and 3) enhances the contrast of certain color signals to a large enough degree to make co-evolution between color vision and these rather specific color signals likely. Copyright (C) 2000 S. Karger AG, Basel.

Simultaneous steady state and dynamic design of process systems using structural indicators

The simultaneous design of the steady-state and dynamic performance of a process has the ability to satisfy much more demanding dynamic performance criteria than the design of dynamics only by the connection of a control system. A method for designing process dynamics based on the use of a linearised systems' eigenvalues has been developed. The eigenvalues are associated with system states using the unit perturbation spectral resolution (UPSR), characterising the dynamics of each state. The design method uses a homotopy approach to determine a final design which satisfies both steady-state and dynamic performance criteria. A highly interacting single stage forced circulation evaporator system, including control loops, was designed by this method with the goal of reducing the time taken for the liquid composition to reach steady-state. Initially the system was successfully redesigned to speed up the eigenvalue associated with the liquid composition state, but this did not result in an improved startup performance. Further analysis showed that the integral action of the composition controller was the source of the limiting eigenvalue. Design changes made to speed up this eigenvalue did result in an improved startup performance. The proposed approach provides a structured way to address the design-control interface, giving significant insight into the dynamic behaviour of the system such that a systematic design or redesign of an existing system can be undertaken with confidence.

Minimum-order stable recursive filter design via the genetic algorithm approach

In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.