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Jelen kötet a 27. alkalommal megrendezett Magyar Alkalmazott Nyelvészeti Kong- resszus előadásainak terminológiával, lexikográfiával és fordítással kapcsolatos előadásainak írott változatát tartalmazza. A kongresszust 2019. április 15. és 16. között rendezte meg közösen a Magyar Alkalmazott Nyelvészek és Nyelvtanárok Egyesülete (MANYE), valamint a Károli Gáspár Református Egyetem Bölcsészet- és Társadalomtudományi Karának Magyar Nyelvtudományi Tanszéke.

Multidrug-resistant bacteria can cause severe nosocomial infections in both human and veterinary clinics. The aim of this study was to investigate the presence and antibiotic susceptibility of Enterococcus, Staphylococcus and Pseudomonas strains at four small animal clinics of Hungary in 2018, as these bacteria can reliably represent the level of antimicrobial resistance in the investigated environment. A total of 177 Staphylococcus colonies were found, including 22 Staphylococcus pseudintermedius and 13 Staphylococcus aureus. As regards enterococci, 9 Enterococcus faecium, 2 E. faecalis and further 286 Enterococcus strains were isolated. The number of Pseudomonas aeruginosa isolates (n = 34) was considered too low for relevant susceptibility testing. Among staphylococci, the highest resistance was found to sulphamethoxazole (82.9%), penicillin (65.7%) and erythromycin (54.3%), while in the case of enterococci, resistance to norfloxacin and rifampicin was the most common, with 25.5% of the strains being resistant to both antibiotics. Ten methicillin-resistant S. pseudintermedius (MRSP) and six vancomycin-resistant Enterococcus (VRE) strains could be identified. Only 5.7% of the Staphylococcus isolates were susceptible to all tested agents, while this ratio was 36.2% among enterococci. The results of this study have revealed a high prevalence of antibiotic-resistant bacteria in Hungarian small animal clinics, which highlights the importance of regular disinfection processes and stringent hygiene measures in veterinary clinics.

Guided inquiry-based learning has been shown to be a promising method for science education; however, despite its advantages it is rarely used in chemistry teaching in Hungary. One of the reasons for this is the lack of tried-and-tested inquiry-based teaching materials with detailed guides that teachers can readily use in their classrooms. As part of a four-year research project, new teaching materials were designed to foster scientific reasoning and scientific process skills in chemistry education in Hungary. From these materials, in this study, a guided inquiry-based chemistry task was tested with 9th-grade students (N = 88) who had no previous experience with the method. Before the activity, the students’ mid-term grades were collected, and the Lawson Classroom Test of Scientific Reasoning (LCTSR) was administered to describe the sample. During the activity, students worked in groups (n = 21). Data were collected through content analysis of the student worksheets, classroom observations using a rubric, and student questionnaires to explore the learning paths and identify possible obstacles. Our findings support that guided inquiry learning is suitable for students who are new to the method if appropriate scaffolding is given. The data showed the phases of the inquiry cycle in which more guidance is necessary. Formulating hypotheses, recording observations, and evaluating the hypotheses based on the evidence were found to be the most critical steps in the learning process. More than half of the groups disregarded the collected evidence and accepted their original hypotheses, despite their unproven validity, suggesting that they did not understand the true nature of the scientific inquiry. Chemistry grades and the LCTSR scores could not predict reliably the students’ success in solving the inquiry task. The results of the student questionnaire showed that the students enjoyed the inquiry session. They mostly found their work successful, but they overestimated the level of their inquiry skills in some cases.

Excised animal and human skins are frequently used in permeability testing in pharmaceutical research. Several factors exist that may have influence on the results. In the current study some of the skin parameters that may affect drug permeability were analysed for human, mouse, rat and pig skin.Classic biophysical skin parameters were measured (e.g. pH, hydration, permittivity, transepidermal water loss). Physiological characteristics of the skins were also analysed by confocal Raman spectroscopy, scanning electron microscopy and two-photon microscopy.Based on biophysical testing, skin barrier function was damaged in psoriatic mouse skin and in marketed pig skin. Hydration and pH values were similar among the species, but freezing and thawing reduced the water content of the skins and shifted the surface pH to acidic. Aging reduced hydration and permittivity, resulting in impaired barrier function. Mechanical sensitization used in permeability studies resulted in proportional thinning of dead epidermis.Results indicate that depending on the scientific question it should be considered whether fresh or frozen tissue is used, and for certain purposes rodent skins are well usable. The structure of the skin tissue (ceramide, cholesterol, keratin, natural moisturizing factor or urea) is similar in rats and mice, but due to the higher skin thickness the lipid distribution is different in porcine skin. Psoriasis led to irregular chemical composition of the skin.A comprehensive evaluation of skin samples of four species was performed. The biophysical and microscopic observations should be considered when selecting drug penetration models and experimental conditions.

A spectacular measurement campaign was carried out on a real-world motorway stretch of Hungary with the participation of international industrial and academic partners. The measurement resulted in vehicle based and infrastructure based sensor data that will be extremely useful for future automotive R&D activities due to the available ground truth for static and dynamic content. The aim of the measurement campaign was twofold. On the one hand, road geometry was mapped with high precision in order to build Ultra High Definition (UHD) map of the test road. On the other hand, the vehicles—equipped with differential Global Navigation Satellite Systems (GNSS) for ground truth localization—carried out special test scenarios while collecting detailed data using different sensors. All of the test runs were recorded by both vehicles and infrastructure. The paper also showcases application examples to demonstrate the viability of the collected data having access to the ground truth labeling. This data set may support a large variety of solutions, for the test and validation of different kinds of approaches and techniques. As a complementary task, the available 5G network was monitored and tested under different radio conditions to investigate the latency results for different measurement scenarios. A part of the measured data has been shared openly, such that interested automotive and academic parties may use it for their own purposes.

This chapter is entirely dedicated to automatic speech recognition (ASR) which is one of the most complex fields of machine learning. Topics from signal processing and the properties of the acoustic signal to acoustic and language modeling, pronunciation modeling and performance analysis will all be explained in an easily comprehensible manner. After reading this chapter you will also understand how the open source software package in the AI-TOOLKIT, called VoiceBridge, works.

The first chapter of this book explained what machine learning is and why it is needed. This chapter now gives an in-depth overview of the subject. The most important machine learning algorithms (models) are explained in detail and several important questions are answered: Which algorithm should we select for the task? What are the advantages and disadvantages of the model? This chapter focuses on the practical uses of machine learning; the mathematical background is only explained when it is really necessary—typically in separate ‘expert sections’ to aid comprehension and to allow interested readers to dive deeper into the subject. Several examples are provided to help explain the different applications of machine learning.

In the earlier chapters of this book we have seen how machine learning works and what the different machine learning techniques are. This chapter will explain how to apply these machine learning techniques to real-world problems: automatic classification (clustering) of an unknown dataset, dimensionality reduction of large datasets, recommendation models, anomaly detection, root cause analysis, engineering applications of supervised learning regression, predictive maintenance, image recognition, detection of different diseases, business process improvement, etc. Not only the specific applications will be explained but also tips and tricks and important sector-dependent machine learning recommendations. After reading this chapter you will be able to apply the machine learning techniques explained in the previous chapters to your own machine learning problems, even if they are different from the examples presented here.

Machine learning models (algorithms) learn from data. This chapter explains how to collect, store and preprocess the data for machine learning. We will also look at the data strategy and the connection to machine learning data strategy. All data related subjects are very important because the quality of the machine learning model depends greatly on the data quality! We will look at data pre-processing (cleaning, transformation, sampling, resampling, feature selection, normalization, etc.) in more detail because of its importance.

It is not always clear to people, especially if they are new to the subject, what we mean by machine learning and when and why we need it. A lot of people are aware of artificial intelligence (AI) from science fiction but they may not really understand the reality and the connection to machine learning. This chapter will explain in clear lay terms what machine learning and AI are, and it will also introduce the three major forms of machine learning: supervised, unsupervised and reinforcement learning. The aim is that after reading this chapter you will understand what, exactly, machine learning is and why we need it.

After learning about the most important machine learning models in the previous chapter, this chapter explains how to evaluate the performance of machine learning models. Evaluating the performance means that we determine how well the model learns the given subject (data) and how well it applies this learning in practice. Each major form of machine learning has its own performance measures and they are often application dependent. This chapter explains the different types of performance evaluations and how and where to apply them. After reading this chapter you will be able to understand the performance measures reported by machine learning algorithms.

In this chapter you will learn how the AI-TOOLKIT works and how to use it. The full version of the AI-TOOLKIT is free, for non-commercial purposes, and therefore you can experiment with all of the examples in this book and apply the knowledge you have learned about machine learning in the previous chapters without any programming! The AI-TOOLKIT supports all three major forms of machine learning: supervised, unsupervised and reinforcement learning! No programming skills are needed at all to build and use state-of-the-art machine learning models!

Recent studies suggest that climate change will lead to the local extinction of many tree species from large areas during this century, affecting the functioning and ecosystem services of many forests. This study reports on projected carbon losses due to the assumed local climate change-driven extinction of European beech (Fagus sylvatica L.) from Zala County, South-Western Hungary, where the species grows at the xeric limit of its distribution. The losses were calculated as a difference between carbon stocks in climate change scenarios assuming an exponentially increasing forest decline over time, and those in a baseline scenario assuming no climate change. In the climate change scenarios, three different sets of forest management adaptation measures were studied: (1) only harvesting damaged stands, (2) additionally salvaging dead trees that died due to climate change, and (3) replacing, at an increasing rate over time, beech with sessile oak (Quercus petraea Matt. Lieb.) after final harvest. Projections were made using the open access carbon accounting model CASMOFOR based on modeling or assuming effects of climate change on mortality, tree growth, root-to-shoot ratio and decomposition rates. Results demonstrate that, if beech disappears from the region as projected by the end of the century, over 80% of above-ground biomass carbon, and over 60% of the carbon stocks of all pools (excluding soils) of the forests will be lost by 2100. Such emission rates on large areas may have a discernible positive feedback on climate change, and can only partially be offset by the forest management adaptation measures.

Recent concepts of environmental sustainability have focused on narrative economic and societal aspects rather than quantitative ones. Many key sustainability indicators also lack a consistent definition of sustainability, have perspectives that are too short-term, and are unable to model the dynamics of complex environmental utilization which can then result in inappropriate projection of long-term sustainability and/or sustainability indication. Here I propose a generalized quantitative framework of environmental sustainability requiring that (1) environmental capacities and utilization rates are identified, (2) their complex temporal dynamics are quantitatively modeled or estimated (3) while also adjusting for uncertainties, and finally, (4) using one of three options, determining which cumulative utilization pathways can be sustained for a (usually well-defined) period of time. Using the example of wood volume and its growth as capacities and harvest as utilization, and the example of global greenhouse gas emissions as the utilization component and the capacity of the air to absorb these emissions, I demonstrate how the proposed framework can be applied in practice, how sustainability indicators could be developed, and also how they can inform policies and measures to ensure sustainability.

This article reports experiences gathered in 12 developing countries in Latin America and Africa with capacity development for national GHG inventory systems. The national systems and their ability to deliver on measurement, reporting and verification (MRV) requirements is assessed using a scorecard that covers the transparency, accuracy, completeness, consistency, and comparability of the GHG inventory as well as its institutional set-up and management aspects. The analysis shows that a quantitative assessment of GHG inventory systems with a scorecard is feasible and useful, and could commonly be used for tracking progress in MRV capacity development.Policy relevanceA large number of capacity development initiatives are underway to advance national GHG inventory systems in developing countries, particularly in the land-use sector. These aim to promote the reliable MRV of GHG emissions and removals, which is expected to underpin developing countries’ contributions to global mitigation efforts, including t...

The studied beech forest is situated in south-west Hungary. This paper describe the surveyed forest stand and try to introducing the influence of applied forest management method. The analysis use phytosociological characters, flora elements, life forms and social behaviour types of plant spe-cies. The composition of herb layer was changed in the steps of regeneration cutting.

International agreements require countries to annually report on greenhouse gas emissions and removals. For the land-use sector, this includes estimating stock changes in various carbon pools. For carbon pools like mineral forest soil where a country-level statistical inventory based on measurements is very difficult, models are usually applied together with data from case studies. In this paper, we present a country-specific model together with case studies that aim at capturing major soil processes due to forestry activity. These processes include “hot moments”, e.g., disturbances that occur rarely but might result in relatively high emissions. The model only aims at developing a conservative estimate, rather than a central one, of net country-level carbon stock change with emissions overestimated and removals underestimated. The model is partially parameterised using paired sampling of soil organic carbon in the uppermost 30-cm layer, applying standard methods including those suggested by IPCC, in afforestations on former croplands and in artificial regenerations. Results show that soils of afforested croplands act as a sink, and carbon stock after regeneration might decrease due to disturbance by forest operations, but might also increase due to transfer of carbon from dead roots to soil depending on disturbance levels. The estimation at the country level, which involves additional considerations and data from the literature, suggests that overall, forest soils are a net sink in Hungary, but also that artificially limiting soil organic carbon changes estimation to the uppermost 30-cm layer as applied in the IPCC methodology might lead to artefacts.

Selenium soil chemistry is complex. It is dominated by selenates, selenites and selenides. Selenate seems to be more toxic for soil animals than selenite. However, bioavailability of different selenium forms as selenate and selenite on soil animals is poorly known. In order to investigate whether higher toxicity of selenate over selenite is a stable phenomenon to the potworm Enchytraeus albidus , standard laboratory tests were conducted on a chernozem brown forest soil and on a meadow chernozem. Toxicity was expressed in terms of adult mortality (LC 50 ) and juvenile production (EC 50 ). Selenate toxicity, expressed on adult mortality and juvenile production, was more substantial than that of selenite if total (conc. HNO 3 + conc. H 2 O 2 soluble) concentrations were considered. No such difference was observed in the case of available (NH 4 -acetate + EDTA soluble) concentrations. E. albidus proved to be more sensitive to selenate and selenite status of the soil than any other animal species tested before. Soil pH between 5.8 and 7.6 did not influence toxicity. The toxicity of selenate and selenite is reverse in aquatic and soil environment in most cases. The reason for this needs further investigations.

The investigated illyrian beech forest is situated in SW Hungary. Its canopy is dominated by Tilia tomentosa and Fagus sylvatica. Statistics of phytosociological characters, flora elements, life forms and social behaviour types are given. The surveyed stands are near-natural characterised by following specialists: Ruscus hypoglossum, Lathyrus venetus, Aremonia agrimonioides, Staphylea pinnata, Galanthus nivalis, Isopyrum thalictroides, Listera ovata, Anemone nemorosa, Hepatica nobilis

The results of phytosociological survey made in 1957-1960 years are compared to 2009-year survey in Vicio oroboidi-Fagetum (SW Hungary). Fifty years ago, the condition of phytocoenosis was more natural than that of condition in 2009. The result of the investigation shows that the rates of weed and disturbance tolerant species were considerably increased.

Climate change particularly threatens the xeric limits of temperate-continental forests. In Hungary, annual temperatures have increased by 1.2 °C–1.8 °C in the last 30 years and the frequency of extreme droughts has grown. With the aim to gain stand-level prospects of sustainability, we have used local forest site variables to identify and project effects of recent and expected changes of climate. We have used a climatic descriptor (FAI index) to compare trends estimated from forest datasets with climatological projections; this is likely for the first time such a comparison has been made. Four independent approaches confirmed the near-linear decline of growth and vitality with increasing hot droughts in summer, using sessile oak as model species. The correlation between droughts and the expansion of pest and disease damages was also found to be significant. Projections of expected changes of main site factors predict a dramatic rise of future drought frequency and, consequently, a substantial shift of forest climate classes, especially at low elevation. Excess water-dependent lowland forests may lose supply from groundwater, which may change vegetation cover and soil development processes. The overall change of site conditions not only causes economic losses, but also challenges long-term sustainability of forest cover at the xeric limits.

This paper analyses the recent recurring dieback and growth decline of Black pine (P. nigra Arn. var austriaca) in the Keszthely mountains of south-west Hungary, and their relations to water deficits due to droughts. These relations were studied in five stands with low soil water storage capacity for the period 1981&ndash, 2016. The vitality was assessed using 60 tree-ring samples and changes in remotely sensed vegetation activity indices, i.e., the normalized difference vegetation index (NDVI) and the normalized difference infrared index (NDII). Water deficit was estimated by using meteorological drought indices such the standardized precipitation&ndash, evapotranspiration index (SPEI) and the forestry aridity index (FAI), as well as the relative extractable water (REW), calculated by the Brook90 hydrological model. Results revealed a strong dependency of annual tree ring width on the amount of water deficit as measured by all the above estimators, with the highest correlation shown by the summer REW. Droughts also showed a long-term superimposed effect on tree growth. NDII seemed to be more sensitive to drought conditions than NDVI. The robust dependency of tree growth on the summer water availability combined with the projected increasing aridity might lead to decreasing growth of Black pine in Hungary towards the end of the century. We thus argue that the suggestion by several papers that Black pine can be a possible substitute species in the Alpine and Mediterranean region in the future should be revisited.

Parties to the Kyoto Protocol and/or the United Nations Framework Convention on Climate Change (UNFCCC) are required to account for their direct human-induced carbon emissions and removals including those from forestry and other land use related activities. In most European countries, the forestry related greenhouse gas inventories are largely or exclusively based on converting tree volume data from national forest inventories to biomass using biomass conversion and expansion factors (BCEFs). However, country specific data for many species are often lacking, which considerably increases the uncertainties of the greenhouse gas inventories. The focus of this research was to develop, using internationally published datasets that cover a large geographical area, an extended set of generalized curves of such biomass expansion factors for several species or species groups by age, growing stock and site index.

The "Allometric, Biomass and Carbon factors" database (ABC factors database) was designed to facilitate the estimation of the biomass carbon stocks of forests in order to support the development and the verification of greenhouse gas inventories in the LULUCF sector (Land Use, Land Use Change and Forestry). The database contains several types of expansion, conversion and combined factors, by various tree species or species groups that can be used to calculate biomass or carbon of forests of Eurasian region from proxy variables (e.g., tree volume) that may come from forest inventories. In addition to the factors, and depending on the information that was available in the cited source, the database indicates: (1) the biomass compartments involved when the factor was developed; and (2) the possible applicability of the factor, e.g. by country or by ecological regions. The applicability of the factors is either suggested by the source itself, or the type of source (e.g. National Greenhouse Gas Inventory Report), or was based on the expert judgement by the compilers of the database. Finally, in order to facilitate the selection of the most appropriate of the data, the web-based interface provides the possibility to compare several factors that may come from different sources. The ABC factors database is freely available at the URL: http://afoludata.jrc.it/data_fs.cfm, in the web site AFOLU-DATA, funded and hosted by the Joint Research Centre (European Commission, DG-JRC)., JRC.H.2-Climate change

This paper presents a framework that encompasses a full range of options for including land use, land-use change, and forestry (LULUCF) within future agreements under the United Nations Convention on Climate Change (UNFCCC). The intent is to provide options that can address the broad range of greenhouse gas (GHG) emissions and removals as well as to bring the broadest possible range of nations into undertaking mitigation efforts. We suggest that the approach taken for the Kyoto Protocol's first commitment period is only one within a much larger universe of possible approaches. This larger universe includes partially or completely “de-linking” LULUCF commitments from those in other sectors, and allowing commitments specified in terms other than tonnes of greenhouse gases. Such approaches may provide clarity and transparency concerning the role of the various sectors in the agreements and encourage participation in agreements by a more inclusive, diverse set of countries, resulting in a more effective use of LULUCF in addressing climate change.

Little information is available about the toxicity of inorganic selenium forms in soil animals. Therefore, the effects of selenate and selenite on the mortality and reproduction of Enchytraeus albidus were examined in standard laboratory tests with chronic exposure. Total and available amount of selenate and selenite were tested in a calcareous loamy chernozem soil. The LC(50) of selenate was 5.69 (2.7-8.12) mg kg(-1) dry wt. for total Se and 4.74 (2.14-6.98) mg kg(-1) dry wt. for available Se. Selenite LC(50) was as high as 22.5 (19.6-25.7) mg kg(-1) dry wt. for total Se and 8.10 (6.8-9.6) mg kg(-1) dry wt. for available Se. The EC(50) of selenate was 0.41 (0.35-0.48) mg kg(-1) dry wt. for total Se and 0.28 (0.24-0.34) mg kg(-1) dry wt. for available Se. Selenite EC(50) was as high as 7.3 (6.2-8.5) mg kg(-1) dry wt. for total Se and 2.46 (2.05-2.91) mg kg(-1) dry wt. for available Se. The response in reproduction was more sensitive to Se toxicity than the response in mortality. Selenate proved to be more toxic than selenite. Available data show that E. albidus may function as a biological indicator for some inorganic selenium forms in the soil.

Forest biomass and its change over time have been measured at both local and large scales, an example for the latter being forest greenhouse gas inventories. Currently used methodologies to obtain stock change estimates for large forest areas are mostly based on forest inventory information as well as various factors, referred to as biomass factors, or biomass equations, which transform diameter, height or volume data into biomass estimates. However, while forest inventories usually apply statistically sound sampling and can provide representative estimates for large forest areas, the biomass factors or equations used are, in most cases, not representative, because they are based on local studies. Moreover, their application is controversial due to the inconsistent or inappropriate use of definitions involved. There is no standardized terminology of the various factors, and the use of terms and definitions is often confusing. The present contribution aims at systematically summarizing the main types of biomass factors (BF) and biomass equations (BE) and providing guidance on how to proceed when selecting, developing and applying proper factors or equations to be used in forest biomass estimation. The contribution builds on the guidance given by the IPCC (Good practice guidance for land use, land-use change and forestry, 2003) and suggests that proper application and reporting of biomass factors and equations and transparent and consistent reporting of forest carbon inventories are needed in both scientific literature and the greenhouse gas inventory reports of countries.

Az Enchytraeidae (Oligochaeta, Annelida) családba tartozó kistestű televényférgek, fontos szerepet töltenek be sok ökoszisztémában. Rendkívül érzékenyek az antropogén stresszfaktorokra, mégis sokáig elhanyagolták őket, mint tesztállatokat. Az Enchytraeus Reprodukciós Teszt (ERT) különböző kémiai anyagok hatásvizsgálatára, valamint talajminőség megállapításához fejlesztették ki. A kidolgozott új módszer révén lehetőség nyílt a korábbi, különböző tesztek eredményeiben megfigyelhető nagy változatosság csökkentésére, valamint tanulmányozhatóvá vált a televényférgek különböző antropo­gén stressz­faktorokkal szemben mutatott érzékenysége. Az ERT alapján dolgoztak ki és fogadtak el több szabványosított teszteljárást (ASTM E 1676-97; ISO 16387; OECD 220). Mindezek mellett folyamatban van új eljárások kidolgozása is, melyek egyrészt a televényférgek magatartás vizsgálatán, másrészt a bioakkumulációs hatásokon alapulnak. A számos különböző kísérlet, a már elfogadott és a még folyamatban lévő nemzetközi szabványok mind-mind megerősítik, hogy ez az állatcsoport (Enchytraeidae) és ezen belül is alapvetően három faj ( E. albidus, E. crypticus és E. luxuriosus ) különösen alkalmas talajokon végzett ökotoxikológiai tesztekre.

Krónikus toxicitási vizsgálatokat végeztünk laboratóriumban a közönséges televényféreg (Enchytraeus albidus) faj segítségével egy 1991 tavaszán beállított mikroelem-terhelési szabadföldi tartamkísérlet szántott rétegébol származó talajokon. Hét elem - a Cd, Cr, Cu, Hg, Pb, Zn és a Se - hosszú távú hatásait teszteltük a faj mortalitásán és reprodukciós képességén. A kísérletben alkalmazott elemeknek (Cd, Cr, Cu, Hg, Pb, Zn, Se) a talajba kerülésüket követoen 7 évvel is van kimutatható hatása a toxicitási tesztekben vizsgált paraméterekre. Megállapítottuk, hogy a szelén növekvo koncentrációi a mortalitást és a reprodukciós képességet is szignifikánsan csökkentik. A vizsgált talajtípuson a LOEC érték 2 mg/kg NH4-acetát + EDTA-oldható Se volt. A legmagasabb koncentrációban (810 kg/ha) kijuttatott hat nehézfém (Cd, Cr, Cu, Hg, Pb, Zn) hét évvel a kezelés után a közönséges televényféreg mortalitására nincs statisztikailag igazolható hatással, ugyanakkor a reprodukciós képességet szignifikánsan csökkentik. Alacsonyabb koncentrációban (270 kg/ha) statisztikailag kimutatható hatása már csak a cinknek van, amely a reprodukciós képességet csökkenti.