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Assessing the sustainability of urbanization at the sub-national level: The Ecological Footprint and Biocapacity accounts of the Budapest Metropolitan Region, Hungary

Jenő Zsolt Farkas Gabor Harangozo Cecília Szigeti Kovács Zoltán

Publication Name: Sustainable Cities and Society

Publication Date: 2022-09-01

Volume: 84

Issue: Unknown

Page Range: Unknown

Description:

The growing concentration of people and wealth often results in imbalances of resource consumption and carrying capacity, therefore, the sustainability assessment of urbanization can offer an important basis for global sustainable transition. This paper aims to provide an analysis of the environmental sustainability of urbanization in Hungary focusing on the long-term changes of ecological footprint and biocapacity at the sub-national level, with a special attention to the Budapest Metropolitan Region (BMR). During the research a hybrid method considering an input-output model and household consumption data was used for the calculation of regional ecological footprint, whereas biocapacity was measured on the basis of land use data. Findings suggest, that even though the ecological deficit of the country has been gradually decreasing since the early 2000s, due to a shrinking population and increasing biocapacity, the ecological overshoot is still significant in the case of Budapest and its agglomeration (30 fold and 2.4 fold respectively). The unsustainability of the BMR is caused partly by demographic factors (7.6% population growth as opposed to the the 7.7% decrease in the countryside) and partly by rising per capita ecological footprint values (especially in the agglomeration from 2.73 to 2.92 gha/capita), which are not balanced by biocapacity on the supply side. This research concluded that policy makers in ageing societies with a highly centralized urban system like Hungary should launch programmes targeted specifically to primary metropolitan areas to improve environmental efficiency and encourage people to change their consumption behaviour.

Open Access: Yes

DOI: 10.1016/j.scs.2022.104022

Network-Analysis-Supported Design Aspects and Performance Optimization of Floating Water Wheels

Viola Somogyi Róbert Koch Viktor Sebestyén Mátyás Horváth Endre Domokos

Publication Name: Energies

Publication Date: 2022-09-01

Volume: 15

Issue: 18

Page Range: Unknown

Description:

Among the numerous renewable energy resources, the main advantage of water energy is that it utilizes the current of the streams and rivers regardless of the given time of the day or season. The main purpose of this study was to create a low capacity, floating hydropower plant that is suitable for shallow and even narrow water bodies. The device was designed to create electric energy while floating on the water’s surface; therefore, it can be used not only in natural streams but also in drainage channels and wastewater treatment plants. The prototype was tested under real circumstances to identify the impacts of various settings on the energy efficiency. Measurements were conducted in Veszprém, Hungary on the Brook Séd. The average depth of the riverbed was 36 cm. Based on the field measurements, optimal efficiency was achieved by using six paddles. On the other hand, much lower efficiency was achieved when low (two or three) or high numbers (12 or 15) of paddles were used. A design framework was elaborated that can facilitate the construction of a floating water wheel for any watercourse. The sensitivity analysis of the sizing variables used in the estimation of performance is supported by network analysis techniques.

Open Access: Yes

DOI: 10.3390/en15186747

NFTs and Cryptocurrencies—The Metamorphosis of the Economy under the Sign of Blockchain: A Time Series Approach

Laszlo Vasa Constanta Mihaescu Simona Andreea Apostu Zbyslaw Dobrowolski Mirela Panait

Publication Name: Mathematics

Publication Date: 2022-09-01

Volume: 10

Issue: 17

Page Range: Unknown

Description:

Although NFTs (non-fungible tokens) and cryptocurrencies are active on the same market, their prices are not so closely related over time. The objective of this paper is to identify the relationship between the two types of assets (NFTs and the cryptocurrencies Ethereum, Crypto Coin, and Bitcoin), using data for the period between September 2020 until February 2022. The conclusions of the study are useful for cryptocurrency and NFT issuers, but also for investors on the financial market who are reconfiguring their portfolios with increasing frequency, and use these new assets for speculative or hedging purposes based on blockchain technology. The results highlighted relationships between NFTs and Ethereum, between Ethereum and Crypto Coin, and between Bitcoin and Ethereum, Ethereum being a bridge between all four. Therefore, NFTs present a relationship with Ethereum, the NFTs price had a causal effect on the price of Ethereum.

Open Access: Yes

DOI: 10.3390/math10173218

Calibration of an Arduino-based low-cost capacitive soil moisture sensor for smart agriculture

G. Milics Viktoria Vona Ákos Bede-Fazekas Márk Kovács István Mihály Kulmány Laszló Bede Ana Beslin Bálint Ambrus Barna Kovács Zsolt Giczi

Publication Name: Journal of Hydrology and Hydromechanics

Publication Date: 2022-09-01

Volume: 70

Issue: 3

Page Range: 330-340

Description:

Agriculture faces several challenges to use the available resources in a more environmentally sustainable manner. One of the most significant is to develop sustainable water management. The modern Internet of Things (IoT) techniques with real-time data collection and visualisation can play an important role in monitoring the readily available moisture in the soil. An automated Arduino-based low-cost capacitive soil moisture sensor has been calibrated and developed for data acquisition. A sensor- and soil-specific calibration was performed for the soil moisture sensors (SKU:SEN0193 - DFROBOT, Shanghai, China). A Repeatability and Reproducibility study was conducted by range of mean methods on clay loam, sandy loam and silt loam soil textures. The calibration process was based on the data provided by the capacitive sensors and the continuously and parallelly measured soil moisture content by the thermogravimetric method. It can be stated that the response of the sensors to changes in soil moisture differs from each other, which was also greatly influenced by different soil textures. Therefore, the calibration according to soil texture was required to ensure adequate measurement accuracy. After the calibration, it was found that a polynomial calibration function (R2 ≥ 0.89) was the most appropriate way for modelling the behaviour of the sensors at different soil textures.

Open Access: Yes

DOI: 10.2478/johh-2022-0014

General formulation of resilience for designing process networks

Ákos Orosz Jean Pimentel Ferenc Friedler Andres Argoti

Publication Name: Computers and Chemical Engineering

Publication Date: 2022-09-01

Volume: 165

Issue: Unknown

Page Range: Unknown

Description:

Herein, the formula proposed for quantifying the resilience of engineering systems, including processing systems, is general in several aspects. The structure of a system can be highly complex where the numbers of loops, raw materials, and products are not limited. The mathematical models of the operating units can be either linear or nonlinear for simulating the effect of the failures. The damage caused by an unexpected event can result in various levels of operation for the operating units. The proposed formula is also general in the sense that all possible combinations of failures are considered. The problem formulation, the related structure representation, the enumeration and evaluation of possible failures are based on the P-graph framework and its algorithms. The proposed formula for resilience is applicable to any complex engineering system whose behavior is primarily determined by its structure, including supply chains, information systems, municipal infrastructures, and electrical transmission networks.

Open Access: Yes

DOI: 10.1016/j.compchemeng.2022.107932

Correlation Analysis of Factors Affecting Firm Performance and Employees Wellbeing: Application of Advanced Machine Learning Analysis

Miklós Illéssy Sina Ardabili Amir Mosavi József Pap Bernat Torok Zef Dedaj Csaba Makó

Publication Name: Algorithms

Publication Date: 2022-09-01

Volume: 15

Issue: 9

Page Range: Unknown

Description:

Given the importance of identifying key performance points in organizations, this research intends to determine the most critical intra- and extra-organizational elements in assessing the performance of firms using the European Company Survey (ECS) 2019 framework. The ECS 2019 survey data were used to train an artificial neural network optimized using an imperialist competitive algorithm (ANN-ICA) to forecast business performance and employee wellbeing. In order to assess the correctness of the model, root mean square error (RMSE), mean absolute percentage error (MAPE), mean square error (MSE), correlation coefficient (r), and determination coefficient (R2) have been employed. The mean values of the performance criteria for the impact of internal and external factors on firm performance were 1.06, 0.002, 0.041, 0.9, and 0.83, and the value of the performance metrics for the impact of internal and external factors on employee wellbeing were 0.84, 0.0019, 0.0319, 0.83, and 0.71 (respectively, for MAPE, MSE, RMSE, r, and R2). The great performance of the ANN-ICA model is indicated by low values of MAPE, MSE, and RMSE, as well as high values of r and R2. The outcomes showed that “skills requirements and skill matching” and “employee voice” are the two factors that matter most in enhancing firm performance and wellbeing.

Open Access: Yes

DOI: 10.3390/a15090300

Evaluation of the biostimulant effects of two Chlorophyta microalgae on tomato (Solanum lycopersicum)

Attila Farkas Gergely Maróti Margaret Mukami Gitau Vince Ördög

Publication Name: Journal of Cleaner Production

Publication Date: 2022-09-01

Volume: 364

Issue: Unknown

Page Range: Unknown

Description:

Eukaryotic microalgae from the Chlorophyta division are used in various bio-industries due to their ability to produce high value compounds. Some of these compounds show plant biostimulant properties when applied to plants, soil or growth medium in hydroponic chambers. The first objective of this study was to evaluate if Chlamydomonas reinhardtii cc 124 and Chlorella sp. MACC-360 had biostimulant effect on Solanum lycopersicum L. The second objective was to investigate the importance of the application mode and time. The third goal was to reveal strain-specific actions of the two algae strains. Tomato plants were grown in pots layered with clay at the bottom and filled with the mixture of soil and vermiculate. In two sets of experiments the soil and plant leaves were treated with living algae and algal extract, respectively. In the first set, the culture suspension (CS) was centrifuged, the algae pellet was re-suspended in water (CCS), and this was applied weekly to soil, while algae extract (cell disrupted algae suspension – CDS) was sprayed on leaves bi-weekly. The flowering process, plant morphology, fruit features and pigment contents were analyzed. In the second set of experiments, the culture suspension per se (CS) was applied to the soil weekly and CDS was sprayed on leaves bi-weekly. Flowering kinetics, reproductive capacity and photosynthetic parameters were examined. Both algae strains increased pigment content, fruit weight and fruit diameter of tomato. Plants that received initial algae treatment at an advanced age performed better than those initially treated at a young age. Chlorella induced early flowering and fruit development while Chlamydomonas significantly delayed these milestone functions. Chlorella promoted conversion of light energy to chemical energy, while Chlamydomonas enhanced protection of photosynthetic parameters. Both strains increased leaf temperature differential as well as leaf thickness. Overall, both algae strains stimulated important agronomic-valuable functions in tomato.

Open Access: Yes

DOI: 10.1016/j.jclepro.2022.132689

Laser powder bed fusion and casting for an advanced hybrid prototype mold

Martin Zobač Imre Fekete J. G. Kovacs Béla Zink István Hatos Dániel Török Tatyana Ageyeva Róbert Boros H. Hargitai

Publication Name: Journal of Manufacturing Processes

Publication Date: 2022-09-01

Volume: 81

Issue: Unknown

Page Range: 748-758

Description:

One of the factors limiting the throughput of injection molding is cooling time, which is the most significant part of the total cycle time. The cooling efficiency of molds can be considerably improved with additive manufacturing techniques. A 3D printed injection mold with conformal cooling channels reduces cooling time by 30–40 %. However, the cooling efficiency of these molds can be further improved with a multi-material approach and the use of materials with excellent thermal and mechanical properties. In this study, we propose a hybrid mold insert made of steel and copper, produced with the combination of Laser Powder Bed Fusion (L-PBF) and casting. The steel shell that contains conformal cooling channels was printed by L-PBF. Then this shell was cast with copper. We found that the hybrid mold insert we developed has lower residual cooling time and heat extraction is more uniform than the conventional printed steel insert. The developed hybrid mold insert enables a reduction of residual cooling time by 15 %.

Open Access: Yes

DOI: 10.1016/j.jmapro.2022.07.034

Experimental Investigation and Applicability of Multi-Stage Simulations in the Case of a Thick-Walled Injection-Moulded Composite

Ferenc Ronkay Tamás Morauszki Gabor Dogossy

Publication Name: Applied Sciences Switzerland

Publication Date: 2022-09-01

Volume: 12

Issue: 17

Page Range: Unknown

Description:

The structure and mechanical properties of an injection-moulded short glass fibre (GF)-reinforced polymer composite were analysed through simulation methods. Fibre orientation, which evolves during the production of a thick-walled automotive part, was determined with an injection moulding simulation. Next, using the material model for the injected product, the force that resulted from the given deformation was determined with finite element software. To validate the simulation results, the examined products were manufactured with 30% reinforced GF, and then measurements were carried out. The validation of the fibre orientation tensor was achieved with optical microscope images, while the validation of the finite element, which analysed the flexural tests, was carried out through a comparison of flexural rigidity. The aim of the project was to verify the reliability of multi-stage finite element software. According to the results, in the case of a thick-walled GF-reinforced product, it was demonstrated that the integration of a different finite element software could be used reliably.

Open Access: Yes

DOI: 10.3390/app12178415