Histological analysis of gallbladder diseases in relation to opisthorchiasis in endemic areas of Thailand

Chronic gallbladder disease frequently accompanies infection with the liver fluke, Opisthorchis viverrini, in Northeast Thailand. However, the pathology and pathogenesis of the gallbladder disease have not been described. Accordingly, gallbladder specimens from 187 consecutive patients who had undergone cholecystectomy at a referral hospital in an endemic area in Thailand were histologically characterized in relation to O. viverrini infection. The infection was assessed by the presence of parasite eggs in the bile and/or antibody response to the liver fluke. The average level of parasite-specific IgG was significantly higher in patients with Opisthorchis eggs in the bile than those without (P < 0.001). The main histopathologic features of the gallbladder included inflammation, mucosal atrophy/or hyperplasia, goblet cell metaplasia, mucous gland hyperplasia, Rokitansky-Aschoff sinus formation, dysplasia and fibrosis. The fibrosis was strongly associated with elevated levels of Opisthorchis-specific antibody (P < 0.001) but not with the presence of parasite eggs. Other pathologic features did not vary in frequency or severity with parasitological status. Our results show that severe fibrosis of the gallbladder is a more common histologic feature of cholecystitis among those with O. viverrini infection compared to those without infection. The close relationship between parasite-specific IgG and severe fibrosis suggests that specific immune response to the parasite play an important role in the pathogenesis of the fibrotic change. (C) 2003 Elsevier B.V. All rights reserved.

Age-related differences in rapid muscle activation after rate of force development training of the elbow flexors

In young adults, improvements in the rate of force development as a result of resistance training are accompanied by increases in neural drive in the very initial phase of muscle activation. The purpose of this experiment was to determine if older adults also exhibit similar adaptations in response to rate of force development (RFD) training. Eight young (21-35 years) and eight older (60-79 years) adults were assessed during the production of maximum rapid contractions, before and after four weeks of progressive resistance training for the elbow flexors. Young and older adults exhibited significant increases (P< 0.01) in peak RFD, of 25.6% and 28.6% respectively. For both groups the increase in RFD was accompanied by an increase in the root mean square (RMS) amplitude and in the rate of rise (RER) in the electromyogram (EMG) throughout the initial 100 ms of activation. For older adults, however, this training response was only apparent in the brachialis and brachioradialis muscles. This response was not observed in surface EMG recorded from the biceps brachii muscle during either RFD testing or throughout training, nor was it observed in the pronator teres muscle. The minimal adaptations observed for older adults in the bifunctional muscles biceps brachii and pronator teres are considered to indicate a compromise of the neural adaptations older adults might experience in response to resistance training.

Description and training of neural network dynamics

Attractor properties of a popular discrete-time neural network model are illustrated through numerical simulations. The most complex dynamics is found to occur within particular ranges of parameters controlling the symmetry and magnitude of the weight matrix. A small network model is observed to produce fixed points, limit cycles, mode-locking, the Ruelle-Takens route to chaos, and the period-doubling route to chaos. Training algorithms for tuning this dynamical behaviour are discussed. Training can be an easy or difficult task, depending whether the problem requires the use of temporal information distributed over long time intervals. Such problems require training algorithms which can handle hidden nodes. The most prominent of these algorithms, back propagation through time, solves the temporal credit assignment problem in a way which can work only if the relevant information is distributed locally in time. The Moving Targets algorithm works for the more general case, but is computationally intensive, and prone to local minima.

Efficient training of RBF networks for classification.

Radial Basis Function networks with linear outputs are often used in regression problems because they can be substantially faster to train than Multi-layer Perceptrons. For classification problems, the use of linear outputs is less appropriate as the outputs are not guaranteed to represent probabilities. We show how RBFs with logistic and softmax outputs can be trained efficiently using the Fisher scoring algorithm. This approach can be used with any model which consists of a generalised linear output function applied to a model which is linear in its parameters. We compare this approach with standard non-linear optimisation algorithms on a number of datasets.

Bayesian training of mixture density networks

Mixture Density Networks (MDNs) are a well-established method for modelling the conditional probability density which is useful for complex multi-valued functions where regression methods (such as MLPs) fail. In this paper we extend earlier research of a regularisation method for a special case of MDNs to the general case using evidence based regularisation and we show how the Hessian of the MDN error function can be evaluated using R-propagation. The method is tested on two data sets and compared with early stopping.

Efficient training of RBF networks for classification

Radial Basis Function networks with linear outputs are often used in regression problems because they can be substantially faster to train than Multi-layer Perceptrons. For classification problems, the use of linear outputs is less appropriate as the outputs are not guaranteed to represent probabilities. In this paper we show how RBFs with logistic and softmax outputs can be trained efficiently using algorithms derived from Generalised Linear Models. This approach is compared with standard non-linear optimisation algorithms on a number of datasets.

Discriminative training of the hidden vector state model for semantic parsing

In this paper, we discuss how discriminative training can be applied to the hidden vector state (HVS) model in different task domains. The HVS model is a discrete hidden Markov model (HMM) in which each HMM state represents the state of a push-down automaton with a finite stack size. In previous applications, maximum-likelihood estimation (MLE) is used to derive the parameters of the HVS model. However, MLE makes a number of assumptions and unfortunately some of these assumptions do not hold. Discriminative training, without making such assumptions, can improve the performance of the HVS model by discriminating the correct hypothesis from the competing hypotheses. Experiments have been conducted in two domains: the travel domain for the semantic parsing task using the DARPA Communicator data and the Air Travel Information Services (ATIS) data and the bioinformatics domain for the information extraction task using the GENIA corpus. The results demonstrate modest improvements of the performance of the HVS model using discriminative training. In the travel domain, discriminative training of the HVS model gives a relative error reduction rate of 31 percent in F-measure when compared with MLE on the DARPA Communicator data and 9 percent on the ATIS data. In the bioinformatics domain, a relative error reduction rate of 4 percent in F-measure is achieved on the GENIA corpus.

Ties that bind:understanding why and how diversity management relates to black and ethnic minority employees’ experience of organisational life

Despite much anecdotal and oftentimes empirical evidence that black and ethnic minority employees do not feel integrated into organisational life and the implications of this lack of integration for their career progression, there is a dearth of research on the nature of the relationship black and ethnic minority employees have with their employing organisations. Additionally, research examining the relationship between diversity management and work outcomes has returned mixed findings. Scholars have attributed this to the lack of an empirically validated measure of workforce diversity management. Accordingly, I sought to address these gaps in the extant literature in a two-part study grounded in social exchange theory. In Study 1, I developed and validated a measure of workforce diversity management practices. Data obtained from a sample of ethnic minority employees from a cross section of organisations provided support for the validity of the scale. In Study 2, I proposed and tested a social-exchange-based model of the relationship between black and ethnic minority employees’ and their employing organisations, as well as assessed the implications of this relationship for their work outcomes. Specifically, I hypothesised: (i) perception of support for diversity, perception of overall justice, and developmental experiences (indicators of integration into organisational life) as mediators of the relationship between diversity management and social exchange with organisation; (ii) the moderating influence of diversity climate on the relationship between diversity management and these indicators of integration; and (iii) the work outcomes of social exchange with organisation defined in terms of career satisfaction, turnover intention and strain. SEM results provide support for most of the hypothesised relationships. The findings of the study contribute to the literature on workforce diversity management in a number of ways. First, the development and validation of a diversity management practice scale constitutes a first step in resolving the difficulty in operationalising and measuring the diversity management construct. Second, it explicates how and why diversity management practices influence a social exchange relationship with an employing organisation, and the implications of this relationship for the work outcomes of black and ethnic minority employees. My study’s focus on employee work outcomes is an important corrective to the predominant focus on organisational-level outcomes of diversity management. Lastly, by focusing on ethno-racial diversity my research complements the extant research on such workforce diversity indicators as age and gender.