Distorted symptom perception in patients with medically unexplained symptoms.

The present study investigated differences in symptom perception between a clinical sample with medically unexplained symptoms (MUS) and a matched healthy control group. Participants (N = 58, 29 patients) were told that they would inhale different gas mixtures that might induce symptoms. Next, they went through 2 subsequent rebreathing trials consisting of a baseline (60 s room air breathing), a rebreathing phase (150 s, which gradually increased ventilation, PCO2 in the blood, and perceived dyspnea), and a recovery phase (150 s, returning to room air breathing). Breathing behavior was continuously monitored, and dyspnea was rated every 10 s. The within-subject correlations between dyspnea on the one hand and end-tidal CO2 and minute ventilation on the other were used to index the degree to which perceived dyspnea was related to specific relevant respiratory changes. The results showed that perceived symptoms were less strongly related to relevant physiological parameters in MUS patients than in healthy persons, specifically when afferent physiological input was relatively weak. This suggests a stronger role for top-down psychological processes in the symptom perception of patients with MUS. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Bootstrapping Inference in the IDP Knowledge Base System

Declarative systems aim at solving tasks by running inference engines on a specification, to free their users from having to specify how a task should be tackled. In order to provide such functionality, declarative systems themselves apply complex reasoning techniques, and, as a consequence, the development of such systems can be laborious work. In this paper, we demonstrate that the declarative approach can be applied to develop such systems, by tackling the tasks solved inside a declarative system declaratively. In order to do this, a meta-level representation of those specifications is often required. Furthermore, by using the language of the system for the meta-level representation, it opens the door to bootstrapping: an inference engine can be improved using the inference it performs itself.One such declarative system is the IDP knowledge base system, based on the language \(\rm FO(\cdot)^{\rm IDP}\), a rich extension of first-order logic. In this paper, we discuss how \(\rm FO(\cdot)^{\rm IDP}\) can support meta-level representations in general and which language constructs make those representations even more natural. Afterwards, we show how meta-\(\rm FO(\cdot)^{\rm IDP}\) can be applied to bootstrap its model expansion inference engine. We discuss the advantages of this approach: the resulting program is easier to understand, easier to maintain, and more flexible.     

Monitoring of crevice corrosion with the electrochemical frequency modulation technique

In this work, it is investigated whether electrochemical frequency modulation can be used to monitor crevice corrosion. With this novel technique, a potential signal consisting of two sine waves of different frequencies is applied to a corroding system. As a corroding system is non-linear in nature, the ac-response will contain non-linear components at harmonic and intermodulation frequencies. Analysis of these components can give information about the corrosion behavior of the system under investigation like the uniform corrosion rate. Crevice corrosion has been investigated by measuring the so-called “causality factors”, which are calculated from the ratio of the current components in the ac-response.According to ASTM standard G48, crevice corrosion has been investigated under the rubber band and cylindrical TFE-fluorocarbon block. Tests were also conducted by creating crevice between circular boundary of metallic sample and epoxy in which metal is engraved. Thus, three patterns of crevice corrosion have been used to see the response of causality factors for AISI 304. Besides some simulations with a simple mathematical model, experiments with artificial crevices were carried out in chloride containing water. The results show that in most cases these causality factors do change when the system goes from uniform corrosion to crevice corrosion.     

Activity of plasma membrane H+-ATPase and expression of PMA1 and PMA2 genes in Saccharomyces cerevisiae cells grown at optimal and low pH

Cells of Saccharomyces cerevisiae grown in media with an initial pH of 2.5-6.0, acidified with a strong acid (HCl), exhibited the highest plasma membrane H+-ATPase-specific activity at an initial pH of 6.0. At a lower pH (above pH 2.5) ATPase activity (62-83% of the maximum level) still allowed optimal growth. At pH 2.5, ATPase activity was about 30% of the maximum value and growth was impaired. Quantitative immunoassays showed that the content of ATPase protein in the plasma membrane was similar across the entire pH range tested, although slightly lower at pH 2.5. The decrease of plasma membrane ATPase activity in cells grown at low pH was partially accounted for by its in vitro stability, which decreased sharply at pH below 5.5, although the reduction of activity was far below the values expected from in vitro measurements. Yeast growth under acid stress changed the pattern of gene expression observed at optimal pH. The level of mRNA from the essential plasma-membrane-ATPase-encoding gene PMA1 was reduced by 50% in cells grown at pH 2.5 as compared with cells grown at the optimal pH 5.0, although the content of ATPase in the plasma membrane was only modestly reduced. As observed in response to other kinds of stress, the PMA2 promoter at the optimal pH was up to eightfold more efficient in cells grown at pH 2.5, although it remained several hundred times less efficient than that of the PMA1 gene.     

分子动力学模拟不同入射能量的CH与碳氢薄膜的相互作用

本文使用分子动力学方法模拟低能CH与碳氢薄膜的相互作用,以探讨在核聚变过程中CH的再沉积行为及对面向等离子体材料性质变化的影响。选择的入射能量分别为0.3,1,5,10 eV。模拟结果表明随着入射能量的增加C原子与H原子的吸附率增加,且在入射能量大于CH离解能的情况下,同一能量下H原子的吸附率小于C原子的吸附率。随着入射能量的增加,薄膜的厚度增加,薄膜中含有Csp2的范围变宽,并且表面逐渐转变为Csp2表面。薄膜中的C主要以Csp3形式存在,其次是Csp2,几乎不含Csp1。通过统计薄膜中的CHx(x为1~4)发现CH占优势,其次是CH2,而CH4的量非常少。     

Hybrid extended Luenberger-asymptotic observer for bioprocess state estimation

State observers generate estimates of non-measured variables based on a mathematical model of the process and some available hardware sensor signals. On the one hand, exponential observers, such as Luenberger observers or Kalman filters, have an adjustable rate of convergence, but strongly rely on the accuracy of the process model. On the other hand, asymptotic observers use a state transformation in order to avoid using the (usually uncertain) kinetic model, but have a rate of convergence imposed by the process dilution rate. In an attempt to combine the advantages of both techniques, a hybrid observer is developed, which evaluates a level of confidence in the process model and, accordingly, evolves between the two above-mentioned limit cases (exponential or asymptotic observer). In particular, attention is focused on a hybrid “Luenberger-asymptotic” observer, for which a rigorous stability/convergence analysis is provided. The efficiency and usefulness of the proposed observer is demonstrated with a bioprocess application example.