A previously reported procedure for the introduction of Borrelia spirochetes into tick larvae by immersion in a suspension of spirochetes was tested on Ixodes ricinus (L.) ticks and three of the most medically important European Borrelia genomic species, B. burgdorferi sensu stricto, B. garinii and B. afzelii. The procedure was compared with ''classical'' infection of nymphs by feeding on infected mice. Both methods yielded comparable results (infection rate 44-65%) with the exception of B. afzelii, which produced better results using the immersion method (44%) compared with feeding on infected mice (16%). Nymphs infected by the immersion method at the larval stage were able to transmit the infection to naïve mice as shown by serology and PCR detection of spirochetal DNA in organs. The immersion method is faster than feeding on infected mice and provides more reproducible conditions for infection. It can be exploited for studies on both pathogen transmission and Borrelia-vector interactions.
Two closely related parasitoid wasp species with different host specificities were used for experimental studies on the biology of host finding, a crucial element of parasitoid life history: The habitat and host specialist Nasonia vitripennis and the habitat and host generalist Dibrachys microgastri (Chalcidoidea: Pteromalidae). The host finding parameters tested included reaction to olfactory cues, aspects of locomotor activity, ability to locate hidden hosts and day-night-activity. The results revealed distinct interspecific differences that match the respective host and habitat ranges of the two species. In N. vitripennis host finding is dominated by olfactory reaction to hosts and host habitat, i.e., fly puparia and birds' nests. In D. microgastri olfactory cues have only a minor role. Its host finding is characterized by rapid searching at random. Both species are able to locate hidden hosts. Although still incomplete, these insights into host finding by two parasitoid species with different life history strategies indicate they can be characterized by specific combinations of behavioural host finding features. and Ralph S. Peters.
A refined common generalization of known theorems (Arhangel’skii, Michael, Popov and Rančin) on the Fréchetness of products is proved. A new characterization, in terms of products, of strongly Fréchet topologies is provided.
The aim of our study was to develop a model producing obese mice in early adulthood (4-6 weeks) based on their over-nutrition during fetal and early postnatal development. The fertilized dams of the parental generation were fed the standard diet supplemented with high-energy nutritional product Ensure Plus during gestation and lactation. De livered weanlings were then fed with standard or supplemented diet and assessed for body fat deposits using EchoMRI at the ti me of early and late adulthood. Maternal over-feeding during th e period before weaning had the most significant effect on obesity development in the filial generation. In weanlings, signific antly higher body fat deposits and average body weight were recorded. Later, further significant increase in percentage of body fat in both male and female mice was observed. Withdrawal of the Ensure Plus supplement caused a decrease in the percentage of body fat in part of the filial generation. In offspring fed the standard diet, higher fat deposits persisted till the time of late adulthood. We conclude that this diet-induced obesity model might be used in exploration of the effects of elevated body fat on physiological functions of various organ systems during juvenile and early adulthood periods of life of a human being., J. Kubandová ... [et al.]., and Obsahuje bibliografii a bibliografické odkazy
This paper focuses on a two-layer approach to genetic programming algorithm and the improvement of the training process using ensemble learning. Inspired by the performance leap of deep neural networks, the idea of a multilayered approach to genetic programming is proposed to start with two-layered genetic programming. The goal of the paper was to design and implement a twolayer genetic programming algorithm, test its behaviour in the context of symbolic regression on several basic test cases, to reveal the potential to improve the learning process of genetic programming and increase the accuracy of the resulting models. The algorithm works in two layers. In the first layer, it searches for appropriate sub-models describing each segment of the data. In the second layer, it searches for the final model as a non-linear combination of these sub-models. Two-layer genetic programming coupled with ensemble learning techniques on the experiments performed showed the potential for improving the performance of genetic programming.
In many natural language processing applications two or more models usually have to be involved for accuracy. But it is difficult for minor models, such as “backoff” taggers in part-of-speech tagging, to cooperate smoothly with the major probabilistic model. We introduce a two-stage approach for model selection between hidden Markov models and other minor models. In the first stage, the major model is extended to give a set of candidates for model selection. Parameters weighted hidden Markov model is presented using weighted ratio to create the candidate set. In the second stage, heuristic rules and features are used as evaluation functions to give extra scores to candidates in the set. Such scores are calculated using a diagnostic likelihood ratio test based on sensitivity and specificity criteria. The selection procedure can be fulfilled using swarm optimization technique. Experiment results on public tagging data sets show the applicability of the proposed approach.
The purpose of the paper is to present existing and discuss modified optimization models and solution techniques which are suitable for engineering decision-making problems containing random elements with emphasis on two decision stages. The developed aproach is called two-stage stochastic programming and the paper links motivation, applicability, theoretical remarks, transformations, input data generation techniques, and selected decomposition algorithms for generalized class of engineering problems. The considered techniques have been found applicable by the experience of the authors in various areas of engineering problems. They have been applied to engineering design problems involving constraints based on differential equations to achieve reliable solutions. They have served for technological process control e.g. in melting, casting, and sustainable energy production. They have been used for industrial production technologies involving related logistics, as e.g. fixed interval scheduling under uncertainty. The paper originally introduces several recent improvements in the linked parts and it focuses on the unified two-stage stochastic programming approach to engineering problems in general. It utilizes authentic experience and ideas obtained in certain application areas and advises their fruitful utilization for other cases. The paper follows the paper published in 2000 which deals with the applicability of static stochastic programs to engineering design problems. Therefore, it refers to the basic concepts and notation introduced there and reviews only the principal ideas in the beginning. Then. it focuses on motivation of recourse concepts and two decision stages from engineering point of view. The principal models are introduced and selected theoretical features are reviewed. They are also accompanied by the discussion about difficulties caused by real-world cases. Scenario-based approach is detailed as the important one for the solution of engineering problems, discussion in data input generation is added together with model transformation remarks. Robust algorithms suitable for engineering problems involving nonlinearities and integer variable are selected and scenario-based decomposition is preferred. An original experience with using heuristics is shared. Several postprocessing remarks are added at the end of the paper, which is followed by an extensive literature review. and Obsahuje seznam literatury
Type populations of four fossil species of voles belonging to the genus Mimomys are redescribed. Mimomys ostramosensis is a large-sized, hypsodont Mimomys with enamel islet, Mimomys-ridge and relatively abundant cement. Mimomys tornensis, a medium-sized vole, is characterized by lack of typical Mimomys-ridge and islet present only in M3/, with very abundant cement accumulation. Mimomys pitymyoides, a medium-sized Mimomys, with broadly confluent triangles, is distinguished by the presence of islets and Mimomys-ridge in most specimens relatively low tracts and differentiation of enamel thickness not so distinct as in other Mimomys species. Mimomys pusillus is a small-sized vole with islet present only in younger wear stages, relatively frequent Mimomys-ridge and relatively low tracts.
The microanatomy of several oribatid and one acaridid mite was studied to determine the role of free cells (haemocytes) in mites. Mites from the field as well as laboratory cultures were observed and analyzed histologically using Masson triple stain. The mites were offered various foods and kept in fluctuating moisture conditions. The presence of haemocytes was significantly correlated with the transport between internal organs of various substance. Three types of transport were recorded: (i) enzymes into the alimentary tract, including the incorporation of haemocytes into the gut walls. This process seemed to be correlated with the amount and type of food and frequently with the presence of internal extraintestinal bacteria associated with mesenchyma; (ii) metabolites, like guanine from mesenchyma into the alimentary tract followed by expulsion from the body via the gut. This process is correlated with food of high nitrogen content or dry conditions; (iii) resorption of nutrients from eggs during an induced quiescent state under unfavourable conditions by small haemocytes.