Shape Factor Effect on Inclusion Sedimentation in Aluminum Melts

Metallurgical and Materials Transactions B - The quality requirements of aluminum products are steadily increasing, and the presence of non-metallic inclusions have a large impact on the quality of...     

The role of tyrosine-114 in the enzymatic activity of the Shiga-like toxin I A-chain

Shiga-like toxin I (SLT-I), the potent cytotoxin produced by certain pathogenic strains of Escherichia coli, is a member of a burgeoning family of ribosome-in-activating proteins (RIPs), which share common structural and mechanistic features. The prototype of the group is the plant toxin ricin. Recently we proposed a structural model for the Slt-IA active site, based in part on the known geometry of the enzymatic subunit of the ricin toxin. The model places three aromatic residues within the putative Slt-IA active site cleft: tyrosine 77, tyrosine 114, and tryptophan 203. Here we present biochemical and biophysical data regarding, the phenotypes of conservative point mutants of Slt-IA in which tyrosine 114 is altered. We used oligonucleotide-directed mutagenesis to replace tyrosine 114 with either phenylalanine (Y114F) or serine (Y114S). Periplasmic extracts of E. coli containing wild-type or mutant Slt-IA were tested for their ability to inhibit protein synthesis in vitro. Relative to wild-type, the activity of mutant Y114F was attenuated about 30-fold, while the mutant Y114S was attenuated about 500 to 1000-fold. In order to address the possibility that differential activation of the mutants rather than local effects at the active site might account for their diminished activity, we engineered the same mutations into a truncated slt-IA cassette that directs expression of a product corresponding to the activated A1 form of Slt-IA (wild-type-delta). The same general relationships held: relative to wild type-delta, Y114F-delta was attenuated about 7-fold, and Y114S-delta about 300-fold.(ABSTRACT TRUNCATED AT 250 WORDS)     

A decision-making approach to the operation of flexible manufacturing systems

This paper introduces a generic decision-making framework for assigning resources of a manufacturing system to production tasks. Resources are broadly defined production units, such as machines, human operators, or material handling vehicles; and tasks are activities performed by resources. In the specific context of FMS, resources correspond to individual machines; tasks correspond to operations to be performed on parts. The framework assumes a hierarchical structure of the system and calls for the execution of four consecutive steps to make a decision for the assignment of a resource to a task. These steps are 1) establishment of decision-making criteria, 2) formation of alternative assignments, 3) estimation of the consequences of the assignments, and 4) selection of the best alternative assignment. This framework has been applied to an existing FMS as an operational policy that decides what task will be executed on which resource of this FMS. Simulation runs provide some initial results of the application of this policy. It is shown that the policy provides flexibility in terms of system performance and computational effort.     

The influence of hydroelectric power generation on the body composition of juvenile Atlantic salmon

The fat and protein content, and thus energy resources of young (parr) Atlantic salmon (Salmo salar) were examined in a temperate river. Juvenile salmon exhibited distinct seasonal patterns of energy storage and use. The lowest levels of energy were found towards the end of winter (mean mass specific energy about 4.3 kJ·g^?1). There was a rapid accumulation of fat in spring/early summer in spite of low‐water temperatures (highest mean content of mass specific energy of about 5.0 kJ·g^?1 in June). By early autumn (August) there was a rapid depletion of fat and energy resources. The decline in specific energy during late summer was of the same magnitude as the corresponding winter decline. Furthermore, total fat and protein content, and thus energy resources of juveniles below a hydroelectric power plant (hydrostation (HS)) differed from those at a (lower) reference station (RS). The younger fish exhibited higher gains, but also larger losses of energy resources compared to corresponding values at the RS. Specifically during the summer, young of year (YOY) had 31% lower total energy content at the regulated site (mean 1.27 kJ per individual) than the RS (mean 1.84 kJ). Higher mortality may occur at the site most affected by the hydroelectric plant, where energy resources on average were higher, but where depletion was also most severe. Copyright © 2006 John Wiley & Sons, Ltd.     

An Extended Replication of an Experiment for Assessing Methods for Software Requirements Inspections

We have performed an extended replication of the Porter-Votta-Basili experiment comparing the Scenario method and the Checklist method for inspecting requirements specifications using identical instruments. The experiment has been conducted in our educational context represented by a more general definition of a defect compared to the original defect list. Our study involving 24 undergraduate students manipulated three independent variables: detection method, requirements specification, and the order of the inspections. The dependent variable measured is the defect detection rate. We found the requirements specification inspected and not the detection method to be the most probable explanation for the variance in defect detection rate. This suggests that it is important to gather knowledge of how a requirements specification can convey an understandable view of the product and to adapt inspection methods accordingly. Contrary to the original experiment, we can not significantly support the superiority of the Scenario method. This is in accordance with a replication conducted by Fusaro, Lanubile and Visaggio, and might be explained by the lack of individual defect detection skill of our less experienced subjects.     

Case-Based Learning: Predictive Features in Indexing

Interest in psychological experimentation from the Artificial Intelligence community often takes the form of rigorous post-hoc evaluation of completed computer models. Through an example of our own collaborative research, we advocate a different view of how psychology and AI may be mutually relevant, and propose an integrated approach to the study of learning in humans and machines. We begin with the problem of learning appropriate indices for storing and retrieving information from memory. From a planning task perspective, the most useful indices may be those that predict potential problems and access relevant plans in memory, improving the planner's ability to predict and avoid planning failures. This predictive features hypothesis is then supported as a psychological claim, with results showing that such features offer an advantage in terms of the selectivity of reminding because they more distinctively characterize planning situations where differing plans are appropriate.We present a specific case-based model of plan execution, RUNNER, along with its indices for recognizing when to select particular plans—appropriateness conditions—and how these predictive indices serve to enhance learning. We then discuss how this predictive features claim as implemented in the RUNNER model is then tested in a second set of psychological studies. The results show that learning appropriateness conditions results in greater success in recognizing when a past plan is in fact relevant in current processing, and produces more reliable recall of the related information. This form of collaboration has resulted in a unique integration of computational and empirical efforts to create a model of case-based learning.     

Formalizing process-based risk with Value-Focused Process Engineering

Following calls to advance the integration of risk and business process modeling paradigms, this paper formalizes the process of incorporating risk into business process models through the principles of Value-Focused Process Engineering (VFPE). In doing so, the paper aims to extend the existing VFPE modeling notation to reflect a set of necessary constructs required to adequately represent risk in goal-oriented business-process models. The extended set of constructs is proposed to support a formal systems view of process-based risk. Process-based risk is formalized on the one hand, as a product of complex interactions between activity-based elements, and on the other hand, as a natural component of the value creation mechanism of an elementary function or a complex process. The proposed risk-aware VFPE formalism also formulates rules for decomposing risk in process models according to the organizational values, thereby enabling better risk visibility, reducing process complexity, and ensuring continuity of business processes.     

Decision-theoretic planning with generalized first-order decision diagrams

Many tasks in AI require representation and manipulation of complex functions. First-Order Decision Diagrams (FODD) are a compact knowledge representation expressing functions over relational structures. They represent numerical functions that, when constrained to the Boolean range, use only existential quantification. Previous work has developed a set of operations for composition and for removing redundancies in FODDs, thus keeping them compact, and showed how to successfully employ FODDs for solving large-scale stochastic planning problems through the formalism of relational Markov decision processes (RMDP). In this paper, we introduce several new ideas enhancing the applicability of FODDs. More specifically, we first introduce Generalized FODDs (GFODD) and composition operations for them, generalizing FODDs to arbitrary quantification. Second, we develop a novel approach for reducing (G)FODDs using model checking. This yields – for the first time – a reduction that maximally reduces the diagram for the FODD case and provides a sound reduction procedure for GFODDs. Finally we show how GFODDs can be used in principle to solve RMDPs with arbitrary quantification, and develop a complete solution for the case where the reward function is specified using an arbitrary number of existential quantifiers followed by an arbitrary number of universal quantifiers.     

TimeLapseAnalyzer: multi-target analysis for live-cell imaging and time-lapse microscopy

The direct observation of cells over time using time-lapse microscopy can provide deep insights into many important biological processes. Reliable analyses of motility, proliferation, invasive potential or mortality of cells are essential to many studies involving live cell imaging and can aid in biomarker discovery and diagnostic decisions. Given the vast amount of image- and time-series data produced by modern microscopes, automated analysis is a key feature to capitalize the potential of time-lapse imaging devices. To provide fast and reproducible analyses of multiple aspects of cell behaviour, we developed TimeLapseAnalyzer. Apart from general purpose image enhancements and segmentation procedures, this extensible, self-contained, modular cross-platform package provides dedicated modalities for fast and reliable analysis of multi-target cell tracking, scratch wound healing analysis, cell counting and tube formation analysis in high throughput screening of live-cell experiments. TimeLapseAnalyzer is freely available (MATLAB, Open Source) at http://www.informatik.uni-ulm.de/ni/mitarbeiter/HKestler/tla.