Biotransformation of l‐menthol by twelve isolates of soil‐borne plant pathogenic fungi (Rhizoctonia solani) and classification of fungi

The microbial transformation of l‐menthol ( 1 ) was investigated by using 12 isolates of soil‐borne plant pathogenic fungi, Rhizoctonia solani (AG‐1‐IA Rs24, Joichi‐2, RRG97‐1; AG‐1‐IB TR22, R147, 110.4; AG‐1‐IC F‐1, F‐4, P‐1; AG‐1‐ID RCP‐1, RCP‐3, and RCP‐7) as a biocatalyst. Rhizoctonia solani F‐1, F‐4 and P‐1 showed 89.7–99.9% yields of converted product from 1 , RCP‐1, RCP‐3, and RCP‐7 26.0–26.9% and the other isolates 0.1–12.0%. In the cases of F‐1, F‐4 and P‐1, substrate 1 was converted to (?)‐(1S,3R,4S,6S)‐6‐hydroxymenthol ( 2 ), (?)‐(1S,3R,4S)‐1‐hydroxymenthol ( 3 ) and (+)‐(1S,3R,4R,6S)‐6,8‐dihydroxymenthol ( 4 ), which was a new compound. Substrate 1 was converted to 2 and/or 3 by RRG97‐1, 110.4, RCP‐1, RCP‐3 and RCP‐7. The structures of the metabolic products were elucidated on the basis of their spectral data. In addition, metabolic pathways of the biotransformation of 1 by Rhizoctonia solani are discussed. Finally, from the main component analysis and the differences in the yields of converted product from 1 , the 12 isolates of Rhizoctonia solani were divided into three groups based on an analysis of the metabolites. Copyright © 2003 Society of Chemical Industry     

Dissolved organic carbon dynamics in the upper rhone: The influence of side-arms?

Dissolved organic carbon (DOC) dynamics were investigated over a two year period in the Upper Rhǒne River to examine the role of side-arms in providing DOC to the main channel in relation to discharge fluctuations, especially floods. Concentrations of DOC are shown to remain low in space and in time (average 1.5 mg ^?1) and to be more related to global hydrological events (precipitation) than to any local flushing for backwaters during floods. The results do not support the general assumption that side-arms are the providers of DOC to the main channel.     

DCS在50MW供热机组上的应用

介绍I/A’S系统在巨化热电厂八号50MW供热机组上应用实例,并从DCS系统的整体设计到实现的功能、控制效果等多方面进行了分折,总结了调试和运行经验。     

Markov analysis of qualitative dynamics1

Common sense sometimes predicts events to be likely or unlikely rather than merely possible. We extend methods of qualitative reasoning to predict the relative likelihoods of possible qualitative behaviors by viewing the dynamics of a system as a Markov chain over its transition graph. This involves adding qualitative or quantitative estimates of transition probabilities to each of the transitions and applying the standard theory of Markov chains to distinguish persistent states from transient states and to calculate recurrence times, settling times, and probabilities for ending up in each state. Much of the analysis depends solely on qualitative estimates of transition probabilities, which follow directly from theoretical considerations and which lead to qualitative predictions about entire classes of systems. Quantitative estimates for specific systems are derived empirically and lead to qualitative and quantitative conclusions, most of which are insensitive to small perturbations in the estimated transition probabilities. The algorithms are straightforward and efficient.     

Uncertainty,belief, and probability1

We introduce a new probabilistic approach to dealing with uncertainty, based on the observation that probability theory does not require that every event be assigned a probability. For a nonmeasurable event (one to which we do not assign a probability), we can talk about only the inner measure and outer measure of the event. In addition to removing the requirement that every event be assigned a probability, our approach circumvents other criticisms of probability-based approaches to uncertainty. For example, the measure of belief in an event turns out to be represented by an interval (defined by the inner and outer measures), rather than by a single number. Further, this approach allows us to assign a belief (inner measure) to an event E without committing to a belief about its negation -E (since the inner measure of an event plus the inner measure of its negation is not necessarily one). Interestingly enough, inner measures induced by probability measures turn out to correspond in a precise sense to Dempster-Shafer belief functions. Hence, in addition to providing promising new conceptual tools for dealing with uncertainty, our approach shows that a key part of the important Dempster-Shafer theory of evidence is firmly rooted in classical probability theory. Cet article présente une nouvelle approche probabiliste en ce qui concerne le traitement de l'incertitude; celle-ci est basée sur l'observation que la théorie des probabilityés n'exige pas qu'une probabilityé soit assignée à chaque événement. Dans le cas d'un événement non mesurable (un événement pour lequel on n'assigne aucune probabilityé), nous ne pouvons discuter que de la mesure intérieure et de la mesure extérieure de l'évenément. En plus d'éliminer la nécessité d'assigner une probabilityéà l'événement, cette nouvelle approche apporte une réponse aux autres critiques des approches à l'incertitude basées sur des probabilityés. Par exemple, la mesure de croyance dans un événement est représentée par un intervalle (défini par la mesure intérieure et extérieure) plutǒt que par un nombre unique. De plus, cette approche nous permet d'assigner une croyance (mesure intérieure) à un événement E sans se compromettre vers une croyance à propos de sa négation -E (puisque la mesure intérieure d'un événement et la mesure intérieure de sa négation ne sont pas nécessairement une seule et unique mesure). II est intéressant de noter que les mesures intérieures qui résultent des mesures de probabilityé correspondent d'une manière précise aux fonctions de croyance de Dempster-Shafer. En plus de constituer un nouvel outil conceptuel prometteur dans le traitement de l'incertitude, cette approche démontre qu'une partie importante de la théorie de l'évidence de Dempster-Shafer est fermement ancrée dans la theorie classique des probabilityés.     

Synthesizing plans that contain actions with context-dependent effects1

This paper presents a method of solving planning problems that involve actions whose effects change according to the situations in which they are performed. The approach is an extension of the conventional planning methodology in which plans are constructed through an iterative process of scanning for goals that are not yet satisfied, inserting actions to achieve them, and introducing subgoals to these actions. This methodology was originally developed under the assumption that one would be dealing exclusively with actions that produce the same effects in every situation. The extension involves introducing additional subgoals to actions above and beyond the preconditions of execution normally introduced. These additional subgoals, called secondary preconditions, ensure that the actions are performed in contexts conducive to producing the effects we desire. This paper defines and analyzes secondary preconditions from a mathematically rigorous standpoint and demonstrates how they can be derived from regression operators.     

Casual reasoning in planning1

Reasoning about actions necessarily involves tracking the truth of assertions about the world over time. The SIPE planning system retains the efficiency of the STRIPS assumption for this while enhancing expressive power by allowing the specification of a causl theory. Separation of knowledge about causality from knowledge about actions relieves operators of much of their representational burden and allows them to be applicable in a wide range of contexts. The implementation of causal theories is described, together with examples and evaluations of the system's expressive power and efficiency.     

Bridging the generation gap between text planning and linguistic realization

Text planning is traditionally done as a separate process, independent of linguistic realization. However, I show in this paper that it is essential for a text planner to know the linguistic consequences of its actions. The choice of how to realize an element affects how much information is conveyed (e.g., “Floyd arrived safely in Boston” vs. “Floyd landed safely at Logan”) and what other information can be added (e.g., “Peter was deciding for an hour” vs. *“Peter made a decision for an hour”). The choice of realization also affects how the relative salience of the elements being expressed will be perceived (e.g., “The green car is in the garage” vs. “The car in the garage is green”). I have defined an intermediate level of representation for text planning, called the Text Structure. It is an abstract linguistic level that reflects germane linguistic constraints while abstracting away from syntactic detail. This representation allows the text planner to have greater control over the decisions, so that it can take advantage of the expressiveness of language to convey subtleties of meaning. More importantly, the Text Structure allows the generation process overall to be incremental, since it ensures that the text plan being composed will always be expressible in the language. La planification de textes est habituellement réalisée séparément, sans tenir compte de la réalisation linguistique. Cependant, ľauteur demontre dans cet article qu'il est essentiel à un planificateur de textes de connai̊tre les conséquences linguistiques de ses actions. Le choix de la méhode de réalisation ?un élément influe sur la quantité?informations qui est transmise (par ex.: 〈〈 Floyd est arrivé sain et sauf à Boston 〉〉 et 〈〈 Floyd a atterri sain et sauf àľaéroport Logan 〉〉) et sur quelle autre information peut ětre ajoutée. Le choix de la méthode de réalisation influe également sur la façon dont les caractères saillants des ééments qui sont exprimés seront perçus (par ex.: 〈〈 la voiture verte est dans le garage 〉〉 et 〈〈 la voiture dans le garage est verte 〉〉). L'auteur a défini un niveau intérmediaire de représentation pour la planification de textes qu'il a appelé structure de texte. Il; s'agit ?'un niveau linguistique abstrait qui refléte les contraintes linguistiques appropriées tout en s'éloignant du détail syntaxique. Cette représentation permet au planificateur de textes ?avoir un meilleur contrǒle des décisions, et done de tirer profit de la force ?expression du langage afin de tenir compte des subtiliés de sens. Plus important encore, la structure de texte permet au processus de génération ?ětre incrémentiel, car elle s'assure que le plan de texte en voie de composition soit toujours exprimable dans le langage.