A model for predicting black tea quality from the carotenoid and chlorophyll composition of fresh green tea leaf

The plant pigment (carotenoid and chlorophyll) composition of fresh green leaf of tea for a selection of clones was studied in relation to the quality of black tea produced from processing the same green leaf. The plant pigment composition of the green leaf for nine Kenyan clones was monitored by HPLC at 450 nm. Using discriminant analysis it was shown that clones could be distinguished from one another on the basis of their green leaf plant pigment composition. Using step-wise multiple regression analysis, a linear relationship was established between the levels of six green leaf plant pigments peak 5 (neochrome), peak 17 and 18 (isomers of lutein and/or lutein epoxide), peak 23 (chlorophyll b type compound), peak 26 (aurochrome) and peak 28 (β-carotene)) and the quality of the manufactured black tea for the selected clones as assessed by tea tasters' evaluations. The model had an adjusted R-square value of 0.912 and was significant at P≤ 0.05. The value of the relationship as a means of predicting black tea quality is discussed.     

Part I: A computer program for the simulation of telecommunication systems: application to optical transmission systems

The conception and analysis of optical transmission systems employing various optical devices (semiconductor lasers, optical fibre, optical amplifiers, photo-diodes,…) require the support supplied by simulation software dedicated to the new components. The objective of thecnet/ipsis collaboration is to respond to this need. In this first article we present the simulation tools which characterize the quality of a digital transmission system, as well as the modelling of the optical elements. In order to show its full range of capabilities in the optical domain, a second article describes the results obtained from the simulation of digital transmission system using wavelength multiplexing.     

Enhancing the effectiveness of relaxation-thermal biofeedback training with propranolol hydrochloride.

This article evaluated the ability of propranolol to enhance results achieved with relaxation-biofeedback training. Thirty-three patients were randomized to relaxation-biofeedback training alone (administered in a limited-contact treatment format), or to relaxation-biofeedback training accompanied by long-acting propranolol (with dosage individualized at 60, 120, or 180 mg/day). Concomitant propranolol therapy significantly enhanced the effectiveness of relaxation-biofeedback training when either daily headache recordings (79% vs. 54% reduction in migraine activity) or neurologist clinical evaluations (90% vs. 66% reduction) were used to assess treatment outcome. Concomitant propranolol therapy also yielded larger reductions in analgesic medication use and greater improvements of quality of life measures than relaxation-biofeedback training alone but was more frequently associated with side effects. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Hiring preferences of diagnostic radiology groups: results of a 1994 survey

RATIONALE AND OBJECTIVES: We surveyed diagnostic radiology group preferences and considerations in hiring radiologists and compared these findings with those of a survey performed in 1990. We sought to identify changes in hiring practices that might have occurred because of socioeconomic changes. We also sought to identify features of job candidates that make them more attractive to hiring groups. METHODS: One hundred surveys were mailed to a stratified random sample of diagnostic radiology groups identified by the American College of Radiology. We solicited information on the importance of various attributes and the level of experience of a candidate, the fellowship training considered most desirable, and the effect of changes in the health care socioeconomic environment. The responses were weighted by group size and geographic location to estimate what results might have been obtained if we had surveyed all groups in the United States. RESULTS: Seventy-five groups returned the survey. The two most important factors in choosing a candidate were motivation and radiologic knowledge. The fellowships that groups that were hiring considered to be the most desirable were body imaging, neuroradiology, and angiography/interventional radiology. Groups overwhelmingly preferred recent training over long experience. CONCLUSION: Fellowship training increases a candidate's marketability, but the two factors that hiring groups consider the most important are motivation and radiologic knowledge.     

Differential effects of lipoxygenase products on FMLP and LTB4 evoked neutrophil aggregation

There is evidence that the endogenous biosynthesis of LTB₄ is involved in the aggregation of human neutrophils induced by the chemotactic peptide f-met-leu-phe (FMLP). If LTB₄ mediates this aggregatory response, then agents which desensitize neutrophils to LTB₄ should inhibit the cellular response to FMLP. Since many lipoxygenase products modulate other neutrophil responses to LTB₄ and FMLP, we have investigated the effects of lipoxygenase products on LTB₄- and FMLP-initiated aggregation. Prior exposure to low concentrations of LTB₄ (0.5–10nM) inhibited subsequent aggregation to the same agent (50nM), but it did not influence the response to FMLP (10⁻⁷ M). Relatively high concentrations of 5-HETE (5–50μM) inhibited aggregation initiated by either stimulus. Although the hydroperoxy derivative 5-HPETE also inhibited the response to LTB₄, in the relatively narrow concentration range of 1–4μM it stimulated FMLP-induced aggregation. This latter effect was confirmed using 12 cell preparations from six separate donors; it (the activity of 5-HPETE) was not mimicked by other 5-lipoxygenase products, including LTB₄, nor the dihydroperoxide 8,15-DiHPETE. Our results indicate that neutrophil aggregation in response to LTB₄ or FMLP can be selectively potentiated or inhibited. On the basis of these data we conclude that the endogenous synthesis of LTB₄ is not directly involved in the neutrophil aggregatory response to FMLP, although the hydroperoxy intermediate 5-HPETE may act to enhance the cellular response.     

Development of a knowledge-based manufacturing modelling system based on IDEF0 for the metal-cutting industry

This paper looks into a new area for knowledge-based system application, that of manufacturing modelling. The objective is to develop a knowledge-based manufacturing modelling system that can be used to build company-specific as-is and to-be IDEF0 models, and can therefore greatly reduce the turnaround time and effort involved in IDEF0 modelling of manufacturing systems, which can be time-consuming if done manually or even with the aid of a commercially available software package like DESIGN/IDEF. This is especially so when the systems being modelled are large and complex. Besides, there is also the inconsistency problem associated with conventional IDEF0 modelling systems owing to the terms and terminologies in IDEF0 not being precisely defined, and hence being subject to individual interpretations. In this paper, a knowledge-based IDEF0 modelling system that can not only automate the tiresome and time-consuming process of manufacturing modelling but can also eliminate the inconsistency problem is proposed. The paper explains the knowledge-based approach to automated generation of IDEF0 models, and also identifies the kinds of domain knowledge that are required for the construction of the knowledge-based manufacturing modelling system.     

A user parameter-free approach for mining robust sequential classification rules

Recent years have witnessed extensive studies of graph classification due to the rapid increase in applications involving structural data and complex relationships. To support graph classification, all existing methods require that training graphs should be relevant (or belong) to the target class, but cannot integrate graphs irrelevant to the class of interest into the learning process. In this paper, we study a new universum graph classification framework which leverages additional “non-example” graphs to help improve the graph classification accuracy. We argue that although universum graphs do not belong to the target class, they may contain meaningful structure patterns to help enrich the feature space for graph representation and classification. To support universum graph classification, we propose a mathematical programming algorithm, ugBoost, which integrates discriminative subgraph selection and margin maximization into a unified framework to fully exploit the universum. Because informative subgraph exploration in a universum setting requires the search of a large space, we derive an upper bound discriminative score for each subgraph and employ a branch-and-bound scheme to prune the search space. By using the explored subgraphs, our graph classification model intends to maximize the margin between positive and negative graphs and minimize the loss on the universum graph examples simultaneously. The subgraph exploration and the learning are integrated and performed iteratively so that each can be beneficial to the other. Experimental results and comparisons on real-world dataset demonstrate the performance of our algorithm.     

Yada: Straightforward parallel programming

Now that multicore chips are common, providing an approach to parallel programming that is usable by regular programmers has become even more important. This cloud has one silver lining: providing useful speedup on a program is useful in and of itself, even if the resulting performance is lower than the best possible parallel performance on the same program. To help achieve this goal, Yada is an explicitly parallel programming language with sequential semantics. Explicitly parallel, because we believe that programmers need to identify how and where to exploit potential parallelism, but sequential semantics so that programmers can understand and debug their parallel programs in the way that they already know, i.e. as if they were sequential.The key new idea in Yada is the provision of a set of types that support parallel operations while still preserving sequential semantics. Beyond the natural read-sharing found in most previous sequential-like languages, Yada supports three other kinds of sharing. Writeonce locations support a single write and multiple reads, and two kinds of sharing for locations updated with an associative operator generalise the reduction and parallel-prefix operations found in many data-parallel languages. We expect to support other kinds of sharing in the future.We have evaluated our Yada prototype on eight algorithms and four applications, and found that programs require only a few changes to get useful speedups ranging from 2.2 to 6.3 on an 8-core machine. Yada performance is mostly comparable to parallel implementations of the same programs using OpenMP or explicit threads.