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Impact of environmental and soil factors in the prediction of soil carbon dioxide emissions under different tillage systems

Renato Kalocsai Viktoria Vona István Mihály Kulmány Laszló Bede Ana Beslin Zsolt Giczi

Publication Name: Ecocycles

Publication Date: 2022-01-01

Volume: 8

Issue: 1

Page Range: 27-39

Description:

Understanding the roles of natural drivers in greenhouse gas (GHG) emissions of arable fields is crucial for adequate agricultural management. This study investigated the combined effect of two tillage treatments (NT - no-tillage; CT - tillage with mouldboard ploughing) and environmental (air pressure, air temperature) and soil factors (total organic carbon, gravimetric water content and soil penetration resistance) on soil carbon dioxide (CO2) emissions in maize in 2020 and 2021. The soil tubes required for the laboratory measurement were derived from three different altitudes of the two differently cultivated fields from Fejér county, Hungary. The typical soil type was Chernozem in both fields. At the time of soil sampling, soil penetration resistance was measured with a 06.15SA Penetrologger in 10 repetitions. To preserve the moisture content of the soil columns during the investigation, moisture replenishment was performed equal to the degree of weekly theoretical evapotranspiration. Emissions measurements of soil columns were performed by close chamber technique for five weeks from sampling, 15 times, in 3 repetitions in laboratory conditions. The data were evaluated by two-way ANOVA, followed by the Tukey HSD multiple comparison test and two-tailed Student's T-test at a significance level of p<0.05. The combined effect of environmental factors on soil carbon dioxide emissions was investigated using stepwise multiple linear regression. It has been proved that the observed difference between soil penetration resistance and soil carbon dioxide emissions was significant between CT and NT cultivation at different stages of the growing season. The analysis of the interaction of the experimental factors revealed that the combined effect of soil penetration resistance, total organic carbon and moisture content in tillage system (adjusted R2=0.92 at a significance level of p=0.05) in 2020, while the combined effect of moisture content and air temperature in the no-tillage system (adjusted R2=0.79 at a significance level of p=0.085) has the most significant effect on soil CO2 emissions in 2020. In 2021, the air temperature for the tillage system (adjusted R2=0.74 at a significance level of p=0.05) and the combined effect of air temperature and pressure for no-tillage systems (adjusted R2=0.69 at a significance level of p=0.1) played an important role in soil CO2 emissions. These observations highlight that different soil and environmental factors of different tillage significantly impact the soil carbon dioxide emissions in different years.

Open Access: Yes

DOI: 10.19040/ecocycles.v8i1.216

Reducing resource use and emissions by integrating technology and policy solutions

Raymond R. Tan Yee Van Fan Petar Sabev Varbanov Ferenc Friedler

Publication Name: Clean Technologies and Environmental Policy

Publication Date: 2022-01-01

Volume: 24

Issue: 1

Page Range: Unknown

Description:

No description provided

Open Access: Yes

DOI: 10.1007/s10098-021-02237-2

Real‐time lidar‐based urban road and sidewalk detection for autonomous vehicles

Claudiu Radu Pozna Ernö Horváth Miklos Unger

Publication Name: Sensors

Publication Date: 2022-01-01

Volume: 22

Issue: 1

Page Range: Unknown

Description:

Road and sidewalk detection in urban scenarios is a challenging task because of the road imperfections and high sensor data bandwidth. Traditional free space and ground filter algorithms are not sensitive enough for small height differences. Camera‐based or sensor‐fusion solutions are widely used to classify drivable road from sidewalk or pavement. A LIDAR sensor contains all the necessary information from which the feature extraction can be done. Therefore, this paper focuses on LIDAR‐based feature extraction. For road and sidewalk detection, the current paper presents a real‐time (20 Hz+) solution. This solution can also be used for local path planning. Sidewalk edge detection is the combination of three algorithms working parallelly. To validate the result, the de facto standard benchmark dataset, KITTI, was used alongside our measurements. The data and the source code to reproduce the results are shared publicly on our GitHub repository.

Open Access: Yes

DOI: 10.3390/s22010194

Auditory and Haptic Solutions for Access and Feedback in Internet of Digital Reality Applications

Adam Csapo Gyorgy Wersenyi

Publication Name: 2022 IEEE 2nd Conference on Information Technology and Data Science Citds 2022 Proceedings

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 319-323

Description:

The concept of Internet of Digital Reality (IoD) was introduced as the next level organization of cognitive entities following the concept of the Internet of Things (IoT) and Internet of Everything (IoE). As virtual-immersive environments are a fundamental component of IoD which allow human and non-human entities to interact in real time, the ability a wide range of communication modalities is crucial. This paper briefly presents the concept of IoD together with an overview of various I/O solutions for human users, with a focus on research directions and (re)emerging technologies in the near future.

Open Access: Yes

DOI: 10.1109/CITDS54976.2022.9914161

CONDITION ASSESSMENT OF SIDE CORRIDORS WITH THE USE OF AGGREGATIONS BASED ON FUZZY INFERENCE METHOD

Adam Bukovics Ferenc Lilik Mate Liszi Ĺaszĺo T. Ḱoczy

Publication Name: Rehabend

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 864-872

Description:

Professional maintenance of the residential building stock and completion of the necessary renovation works on time will increase the life of the residential buildings and improve their condition. For this reason, it is important to create and apply condition assessment and decision support systems that uniformly and accurately determine the condition of individual building structures and buildings. Thus, the necessary interventions -taking into account the available financial resources-can be performed at the right time and in the right way. The ultimate goal of our research is to develop a decision support system that evaluates the damage of individual structural members and determines the condition of each load bearing structure, ultimately evaluating the entire building. It then suggests (if necessary) which of the available renovation methods to choose. In addition to the damage of the load bearing structures, the decision among the proposed methods of reinforcement is also influenced by architectural requirements and economic aspects. In the present phase of the research we have developed a method that determines the condition of side corridor structures based on the observed damage detected by visual building diagnostics (e.g. steel cantilever corrosion, stone plate cracks, stone plate abrasion). The side corridors are divided into three well-separable structural elements (cantilever, plate, balustrade) and their damage is analyzed separately. Qualification is made by a fuzzy signature based decision making system. In this, aggregations are based on classical fuzzy inference methods. The rule bases of the aggregation were constructed during this research. The final condition of the side corridor structure is affected by the combined condition of the three structural elements.

Open Access: Yes

DOI: DOI not available

Effect of fermented liquid feeds on production parameters and gut microbiota composition of weaned piglets and growing pigs

Tóth Tamás Alpár Botond László Varga

Publication Name: Magyar Allatorvosok Lapja

Publication Date: 2022-01-01

Volume: 144

Issue: 8

Page Range: 463-472

Description:

In their review, the authors present the results of research evaluating the effect of fermented liquid feed on the performance and digestive health of weaned piglets and fattening pigs. Based on the available literature, it is advisable to carry out controlled fermentation instead of spontaneous fermentation, because by inoculating the feed / raw materials with specific lactic acid bacteria, the fermentation process goes in the right direction, lower pH values can be achieved within the same timeframe, which all help to control the acid-sensitive pathogenic microbes. The fermentation of only certain raw materials, as opposed to a complete diet, has the advantage of better controllability, and the incorporation of these fermented end products into final diets provides farms with increased flexibility. During fermentation, the particle size of the feed / raw materials and the levels of antinutritive substances are reduced, thereby increasing their digestibility. Feeding studies have shown that improvement in nutrient utilization is primarily due to better bioavailability of nutrients, as opposed to increased feed intake. Several works have demon-strated that fermented liquid feeds significantly reduce the pH of gastric juice, Salmonella spp. levels and the chance of developing diarrhoea caused by coliforms in piglets. Fermented feeds support gut health, thus also playing an immunomod-ulatory role. Taking all this into account, the authors believe that fermented liquid feeds in nutrition of pigs may be an effective alternative after the antibiotic reduction provisions come into force in the European Union in 2022.

Open Access: Yes

DOI: DOI not available

Application of Machine Learning to Automatic Gear Shift Schedule Design of Alternative Drive Systems

Adrienn Dineva Szabolcs Szurke Kocsis Adam Zsuga

Publication Name: 2022 22nd International Symposium on Electrical Apparatus and Technologies Siela 2022 Proceedings

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Intelligent automatic transmission shift schedule design has been well established in the last decade. However, due to the paradigm change is currently taking place in mobility sector, which resulted in a rapid progress of Electric Vehicles and Autonomous Vehicles, intelligent automatic gear shift strategies are still in the focus of much research. In addition, the proper transmission shift schedule generation is especially important from the viewpoint of energy efficiency optimizing algorithms, which is affected by the driving style, power losses, etc. Fundamentally, conventional shift schedule design relies on lookup tables obtained from test-bench measurements and real-world driving measurements. During real time test data collection, the measurement of some variables may be impractical and/or patterns of important driving conditions may be unavailable during short-distance routes neglecting the comprehensive effects of the transient operation. Machine Learning methods in combination with model-based data generation is a promising alternative, which allows a significant reduction in development time and a more precise calibration by using rich historical data rich. Such models can be easily fitted to alternative drive systems also, which may raise more specific requirements regarding gear shift scheduling issues coupled with efficiency. In this paper the performances of Machine Learning models are investigated in automatic gear shift schedule generation based on simulated driving cycle test data. Results of simulation investigations validate the applicability and efficiency of the proposed approach.

Open Access: Yes

DOI: 10.1109/SIELA54794.2022.9845718

The Resilience Barriers of Automated Ground Vehicles from Military Perspectives

Árpád Tóth Rudolf Krecht Alex Suta Attila Hajdu Ferenc Friedler

Publication Name: Chemical Engineering Transactions

Publication Date: 2022-01-01

Volume: 94

Issue: Unknown

Page Range: 1195-1200

Description:

In the case of autonomous and semi-autonomous unmanned ground vehicles (UGVs), the military application of these systems is becoming more evident and is expected to play an increasingly important role in the future. This paper aims to present and analyse the military applicability and resilience of currently available autonomous ground vehicle perception and control systems. It is important to underline that the paper, after a comprehensive literature review and a presentation of the currently applied methods, attempts to provide a methodological classification of these complex vehicle platforms from the resilience perspective. The methodological classification is based on observations from both economic and engineering perspectives as a result of the systematic review. Furthermore, possible results of resilience are also discussed: survivability, supportability, agility and reusability of the analysed autonomous ground vehicle systems. All these factors can be significant from the point of view of sustainability. As UGVs used under challenging conditions get damaged or outdated, they tend to be dismissed without reusing expensive components, thus generating additional waste. UGVs designed with resilience in mind could be kept in service for a longer period, or their components could be reused more successfully, which supports sustainability. Based on findings there are not yet widely adopted estimation methods to measure the long-term resilience of autonomous military ground vehicles. Thus, a possible theoretical solution for system-autonomy resilience quantification was discussed relying on sensory components and perception methods extracted from the literature as input variables.

Open Access: Yes

DOI: 10.3303/CET2294199

Cultural Conceptualisations of TREE: A Cross-Cultural Analysis of Hungarian and Russian Folksongs

Judit Baranyiné Kóczy Júlia Hamsovszki

Publication Name: Second Language Learning and Teaching

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 21-49

Description:

One of the key issues of recent linguistic trends is to understand the interaction between language and culture, which can be well observed through the identification of cultural conceptualizations (Sharifian, 2011, 2017). This study explores and compares the basic cultural conceptualizations of tree, a concept which holds a universal symbolic status in human cognition, in Russian and Hungarian folk songs (e.g., Baranyiné Kóczy, 2018b), relying on approximately 800 + 600 texts presented in two Hungarian and Russian corpora of folksongs (Kireevsky, 1986). The study addresses the following questions: How is tree conceptualized in general in folk songs by the Hungarian vs. Russian folk cultural communities? Are specific conceptualizations attached to different tree-types in the two corpora? What similarities and differences of the underlying metaphors can be distinguished in these two systems of cultural conceptualizations? What specific conceptualizations are attached to various tree-species in these corpora? The study utilizes the methodological framework of Cultural Linguistics in that it identifies conceptual metaphors and metonymies in the texts and relates them to underlying cultural models. The research shows that, (a) Russian folk songs tend to employ various tree-types with distinct conceptualizations, whereas tree-species are less dominantly represented in the Hungarian folk songs; (b) the most frequent type of tree is дyб “oak” in Russian whereas rózsafa “rose-tree” in Hungarian; (c) despite some similar generic ideas behind cultural conceptualizations, their representations and the image schemas related to them can be quite different; (d) there are conceptualizations which are only present in either corpus. Overall, it is argued that the figurative uses of trees and parts of trees rely on cultural conceptualizations and are deeply embedded in the cognition of folk cultural communities.

Open Access: Yes

DOI: 10.1007/978-3-030-96099-5_2