A new nematode species, Rhabdochona (Globochona) kurdistanensis sp. n. (Rhabdochonidae), is decribed based on specimens collected from the intestine of the barbel Luciobarbus kersin (Heckel) (Cyprinidae) in the Greater Zab (type locality) and the Lesser Zab Rivers, Tigris River basin, Kurdistan Region, northern Iraq. It is mainly characterized by a prostom with 8 anterior teeth, the presence of basal prostomal teeth, bifurcated deirids, length ratio of the muscular and glandular portions of oesophagus (1:14.4-17.8), conspicuously short left spicule (180-204 µm), arrangement of genital papillae, nonfilamented eggs, and by having cuticular ornamentations on the tail tip (2 lateral denticular outgrowths in female and numerous fine spines in male). Description of a gravid female of Rhabdochona (Rhabdochona) sp. with 14 anterior prostomal teeth and filamented eggs, recorded from L. kersin of the Greater Zab River, is also provided. R. kurdistanensis sp. n. is the fifth valid species of Rhabdochona Railliet, 1916 and the only representative of the subgenus Globochona Moravec, 1972 recorded from Iraq.
Effects of low-frequency electromagnetic fields (LF EMF) on the
activation of different tissue recovery processes have not yet
been fully understood. The detailed quantification of LF EMF
effects on the angiogenesis were analysed in our experiments by
using cultured human and mouse endothelial cells. Two types of
fields were used in the tests as follows: the LF EMF with
rectangular pulses, 340-microsecond mode at a frequency of
72 Hz and peak intensity 4 mT, and the LF EMF with sinusoidal
alternating waveform 5 000 Hz, amplitude-modulated by means
of a special interference spectrum mode set to a frequency linear
sweep from 1 to 100 Hz for 6 s and from 100 Hz to 1 Hz return
also for 6 s, swing period of 12 second. Basic parameters of
cultured cells measured after the LF EMF stimulus were viability
and proliferation acceleration. Both types of endothelial cells
(mouse and human ones) displayed significant changes in the
proliferation after the application of the LF EMF under conditions
of a rectangular pulse mode. Based on the results, another test
of the stimulation on a more complex endothelial-fibroblast
coculture model will be the future step of the investigation.
The purpose of this paper is to introduce some new generalized double difference sequence spaces using summability with respect to a two valued measure and an Orlicz function in $2$-normed spaces which have unique non-linear structure and to examine some of their properties. This approach has not been used in any context before.
In this paper, following the methods of Connor \cite {connor}, we extend the idea of statistical convergence of a double sequence (studied by Muresaleen and Edely \cite {moe}) to $\mu $-statistical convergence and convergence in $\mu $-density using a two valued measure $\mu $. We also apply the same methods to extend the ideas of divergence and Cauchy criteria for double sequences. We then introduce a property of the measure $\mu $ called the (APO$_2$) condition, inspired by the (APO) condition of Connor \cite {jc}. We mainly investigate the interrelationships between the two types of convergence, divergence and Cauchy criteria and ultimately show that they become equivalent if and only if the measure $\mu $ has the condition (APO$_2$).
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.
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.
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