Standardized event pair based test generation method using TSS&TP

In the software engineering test development takes significant resources. A general method for the creation of appropriate test suites could solve the problems of the often ad-hoc and time-consuming test generation process. The recent method uses formal specifications to support systematic derivation of complete test suites. From the formal specification using a special procedure a formalized document, the so-called Test Suite Structure (TSS) and Test Purposes (TP) can be created. With the help of this document developers can easily, automatically implement the test suites. The TSS&TP document also enables the persons who perform the tests to understand the test criteria and the steps, even if they do not actually know the protocol itself. We present a thorough picture of our test derivation method and show its efficiency on the Wireless Transaction Protocol (WTP) of the Wireless Application Protocol family (WAP). During our work in the validation phase we also found some operational flaws in the protocol specification

Optimális vedlési stratégiák = Optimal moult strategies

A pályázat fő célja annak kiderítése volt, hogy a különböző állapotváltozók hogyan befolyásolják az optimális viselkedést, speciálisan a hogyan befolyásolják a fő életmenet események időzítését az éves cikluson belül. E cél elérése érdekében több modellt fejlesztettünk, és változatos terepi megfigyeléseket és aviáriumi kísérleteket folytattunk. Fő modelljeink azt mutatják, hogy az állapotváltozók (pl. tollminőség, energiatartalékok) jelentősen befolyásolhatják a vedlés és vándorlás időzítését, de a táplálékforrás időbeli eloszlása és szezonalitása is jelentős hatással lehet. Fő empirikus eredményeink szerint a táplálék minősége és a paraziták fertőzése jelentősen befolyásolhatja a tollminőséget. Egy komparatív vizsgálatban kimutattuk, hogy a vándorlás időzítését a különféle életmenet jellemzők jelentősen befolyásolják, de a szezuálisan szelektált jellegeknek nincs ilyen hatása. | The main aim of the project was to investigate how state variables effect optimal behaviour in general, and the optimal timing of major life history events over the annual cycle, in particular. To accomplish this aim we developed a couple of annual routine models and performed various field observations and aviary experiments. Our main models show that state variables (quality of feathers, energy reserves) can significantly influence the timing of optimal behaviour (moult, migration) but they also underline the importance of the temporal distribution and seasonality of food sources. Our main empirical results show that diet quality and parasite infection influence feather quality considerably. By a comparative study we found that life history traits (e.g. migration distance and diet) but not sexually selected traits influence the timing of migration

Optimális éves viselkedési modellek: út a fiziológiától a populációkig? = Optimal annual routines: a path from physiology to populations?

A pályázat fő célja annak kiderítése volt, hogy a különböző állapotváltozók hogyan befolyásolják az optimális viselkedést, speciálisan a hogyan befolyásolják a fő életmenet események időzítését az éves cikluson belül. E cél elérése érdekében több modellt fejlesztettünk, és változatos terepi megfigyeléseket és aviáriumi kísérleteket folytattunk. Fő modelljeink azt mutatják, hogy az állapotváltozók (pl. tollminőség, energiatartalékok) jelentősen befolyásolhatják a vedlés és vándorlás időzítését, de a táplálékforrás időbeli eloszlása és szezonalitása is jelentős hatással lehet. Fő empirikus eredményeink szerint a táplálék minősége és a paraziták fertőzése jelentősen befolyásolhatja a tollminőséget. Egy komparatív vizsgálatban kimutattuk, hogy a vándorlás időzítését a különféle életmenet jellemzők jelentősen befolyásolják, de a szexuálisan szelektált jellegeknek nincs ilyen hatása. | The main aim of the project was to investigate how state variables effect optimal behaviour in general, and the optimal timing of major life history events over the annual cycle, in particular. To accomplish this aim we developed a couple of annual routine models and performed various field observations and aviary experiments. Our main models show that state variables (quality of feathers, energy reserves) can significantly influence the timing of optimal behaviour (moult, migration) but they also underline the importance of the temporal distribution and seasonality of food sources. Our main empirical results show that diet quality and parasite infection influence feather quality considerably. By a comparative study we found that life history traits (e.g. migration distance and diet) but not sexually selected traits influence the timing of migration

Observing population changes of thrips (Thysanoptera) species damaging forced pepper and their natural enemies

By the strengthening of environmental protection and food safety efforts in Hungary, integrated and especially biological pest control methods should increasingly put forward, for which a solid knowledge on the life course and efficiency of natural enemies applied against certain pests is necessary. Pepper has distinguished significance in domestic vegetable forcing, and the profitability of production is determined primarily by the efficiency of the control of thrips pests. This is why we attached great importance to study what results may be expected by introducing arthropod predators (Amblyseius cucumeris, Orius laevigatus) to control thrips species under domestic conditions on rock wool in a long vegetation period pepper culture. We also liked to find out what kind of role the cultivars play in the change of phytophagous and zoophagous populations. The A. cucumeris predatory mite introduced in late January proved to be effective in controlling thrips pests until mid-April. Despite repeated introductions, the predatory bug O. laevigatus (Heteroptera: Anthocoridae) did not proliferate. Among the three pepper cultivars (Hó, Keceli, Titán) grown at Ráckeve, thrips species proliferated in the highest number on cultivar ‘Hó’, while the population of predatory mites was lowest on the cultivar ‘Titán’, compared to the other two cultivars

Automatic test selection based on CEFSM specifications

Mutation analysis is a fault based testing method used initially for code based software testing. In this paper, this method is applied to formal specifications and used for automatic conformance test selection. This paper defines formally a set of mutation operators for CEFSM (Communicating Extended Finite State Machine) systems to enable the automated creation of mutant specifications. Mutants of a specification are used as selection criteria to pick out adequate test cases. Two different algorithms are proposed for the generation and selection of efficient test suites. Additionally, the operators and algorithms provide the basis of an automatic tool developed at the Budapest University of Technology and Economics. We present the results of an empirical study on the well-known INRES protocol acquired using the tool

Mycorrhizal inoculation of onion (Allium cepa l.) in the early developement stages

The onion (Allium cepa) is one of the most widely cultivated vegetables. As a food item, it is usually served cooked, as a vegetable or part of a prepared savoury dish, but can also be eaten raw or used to make pickles or chutneys. Mycorrhiza fungi are special fungi, which live in connection with plant roots. These are symbiotic fungi which have three main types: arbuscular mycorrhiza (AM), ectomycorrhiza and ectendomycorrhiza. AM are probably the most widespread plant symbionts and are formed by 80–90% of land plant species. Crops inoculated with AM have higher yield and quality, and those plants react to stress factors better (e.g. drought, high temperature). Several Allium spp. responded with growth promotion on AM inoculation. According to studies AM fungi also has a positive effect on nutrient content. The aim of our experiment was to find an appropriate method for inoculation of onion seedlings, and define the minimum time for the appearance of symbiosis under greenhouse conditions. The experiment took place at Szent István University Faculty of Horticultural Science, at the experimental glasshouse of the Department of Vegetable and Mushroom growing, from 11th September 2017. We used Daytona F1 onion seeds, the media was Latagro KB2 type peat and two types of mycorrhizal products: MycoGrow and Aegis Irriga. The experiment was made with 12 treatments with 30-30 seeds per each treatment. During the experiment, chemically treated and non-treated seeds were used. The seedlings were sampled 5, 7 and 14 weeks after sowing, 5-5 seedlings from each treatment per time. Altogether 96 painted and prepared samples were checked, each with 3-3 roots with a Zeiss Axio Imager A2 microscope. The results showed the appearance of mycorrhizal fungi in a few treatments. In our examination not only typical AM fungi were found, but also in a treatment we found hyphaes with big amount of septas. The results show opportunity of artificially infecting transplants after a few weeks with mycorrhizal products. However, continuing the experiment is necessary with some modification of the factors, to make the procedure more effective

Training models employing physico-chemical properties of DNA for protein binding site detection

Transcription Factors (TFs) are one of the most important agents acting on gene expression regulation, fundamentally determining the organized functional operation of cellular machinery. At a molecular level, this effect is achieved by the sequence specific physical binding of TF proteins to particular parts of the DNA. Transcription Factors regulate gene expression in complex ways and the detection of their binding sites is an important part of many experiments. Predicting Transcription Factor Binding Sites (TFBS) from DNA sequence data has been a challenging task in the field of bioinformatics. The abundance of available DNA sequences strongly encourages the use of machine learning for this problem. Until now most of these efforts were primarily based on the traditional nucleotide-based representation of DNA. To elaborate a more detailed description of this macromolecule, we have worked out a new Physico-Chemical Descriptor (PCD) based DNA representation and used it as input for training neural networks to predict TFBSs. We show that the PCD representation is a viable format for deep learning models, and our feature selection investigation highlights the importance of proper PCD subset choices. The distinct prediction efficiencies detected upon the usage of arbitrarily selected feature subsets indicates that the different DNA features affect the DNA binding process of TFs to various extent