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Abstract

In literature as well as in the university debate, we can observe the increase of interest regarding converting agricultural residues into energy. Furthermore, the energy and climate policies have encouraged the development of biogas plants for energy production. One of the most significant reasons of this escalation is that this technology may be both convenient and beneficial. The produced biogas is not only supposed to cover the energy demand like heat and electricity, the resulting digestate has the prospect of a beneficial fertilizer and can thereby influence the energy management plans. This technology is widely introduced to countries, which have large income from agriculture. Not only does this reduce the use of industrial fertilizers, but also finds use for agricultural residues. One of the countries of this type is Vietnam, which is the fifth largest exporter of rice in the world. Over 55% of greenhouse gas emission in Vietnam comes from agriculture. Using innovative technologies such as biogas, may decrease this value in near future. It may also contribute to more sustainable agriculture by decreasing traditional fields burning after the harvesting period. The goal of this research paper is to estimate the possible production of biogas from rice straw to cover the energy demand of the rice mill. Four possible scenarios have been considered in this paper, the present situation and where electricity, energy or both were covered by biogas from agricultural residues. An attempt was made to answer the question whether the amount of biogas produced from agricultural residues is enough for both: electricity and energy supply, for the rice mill. If not, how much rice straw must be delivered from other sources, from which rice is not delivered to the rice mill. The base of the assumptions during the estimation of various values were statistics from FAO and other organizations, secondary sources and data from the existing rice mill in Hậu Mỹ Bắc B in Mekong delta in Vietnam.

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Authors and Affiliations

Berenika Lewicka
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Abstract

Biochemical Oxygen Demand (BOD) is an important factor used to measure water pollution. This article reviews recent developments of microbial biosensors with respect to their applications for low BOD estimation. Four main methods to measure BOD using a biosensor are described: microbial fuel cells, optical methods, oxygen electrode based methods and mediator-based methods. Each of them is based on different principles, thus a different approach is required to improve the limit of detection. A proper choice of microorganisms used in the biosensor construction and/or sample pre-treatment processes is also essential to improve the BOD lower detection limit.

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Authors and Affiliations

Elżbieta Malinowska
Łukasz Górski
Kamil F. Trzebuniak
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Abstract

Industry 4.0 will affect the complexity of supply chain networks. It will be necessary to

adapt more and more to the customer and respond within a time interval that is willing

to accept the product waiting. From these considerations, there is a need for a different way

of managing the supply chain. The traditional concept of supply chain as a linear system,

which allows optimizing individual subsystems, thus obtaining an optimized supply chain, is

not enough. The article deals with the issue of supply chain management reflecting demand

behaviour using the methodology Demand Driven MRP system. The aim of the publication

is to extend the knowledge base in the area of demand-driven supply logistics in the

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Authors and Affiliations

Miriam Pekarcıkova
Peter Trebuna
Marek Kliment
Jozef Trojan
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Abstract

In this article, we review the research state of the bullwhip effect in supply chains with

stochastic lead times. We analyze problems arising in a supply chain when lead times are

not deterministic. Using real data from a supply chain, we confirm that lead times are

stochastic and can be modeled by a sequence of independent identically distributed random

variables. This underlines the need to further study supply chains with stochastic lead times

and model the behavior of such chains.

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Authors and Affiliations

Peter Nielsen
Zbigniew Michna
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Abstract

The Internet of Vehicles (IoVs) has become a vital research area in order to enhance passenger and road safety, increasing traffic efficiency and enhanced reliable connectivity. In this regard, for monitoring and controlling the communication between IoVs, routing protocols are deployed. Frequent changes that occur in the topology often leads to major challenges in IoVs, such as dynamic topology changes, shortest routing paths and also scalability. One of the best solutions for such challenges is “clustering”. This study focuses on IoVs’ stability and to create an efficient routing protocol in dynamic environment. In this context, we proposed a novel algorithm called Cluster-based enhanced AODV for IoVs (AODV-CD) to achieve stable and efficient clustering for simplifying routing and ensuring quality of service (QoS). Our proposed protocol enhances the overall network throughput and delivery ratio, with less routing load and less delay compared to AODV. Thus, extensive simulations are carried out in SUMO and NS2 for evaluating the efficiency of the AODV-CD that is superior to the classic AODV and other recent modified AODV algorithms.
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Authors and Affiliations

Sahar Ebadinezhad
1

  1. Department of Computer Information System, Near East University. Nicosia TRNC, Mersin 10, Turkey
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Abstract

The stable supply of iron ore resources is not only related to energy security, but also to a country’s sustainable development. The accurate forecast of iron ore demand is of great significance to the industrialization development of a country and even the world. Researchers have not yet reached a consensus about the methods of forecasting iron ore demand. Combining different algorithms and making full use of the advantages of each algorithm is an effective way to develop a prediction model with high accuracy, reliability and generalization performance. The traditional statistical and econometric techniques of the Holt–Winters (HW) non-seasonal exponential smoothing model and autoregressive integrated moving average (ARIMA) model can capture linear processes in data time series. The machine learning methods of support vector machine (SVM) and extreme learning machine (ELM) have the ability to obtain nonlinear features from data of iron ore demand. The advantages of the HW, ARIMA, SVM, and ELM methods are combined in various degrees by intelligent optimization algorithms, including the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and simulated annealing (SA) algorithm. Then the combined forecast models are constructed. The contrastive results clearly show that how a high forecasting accuracy and an excellent robustness could be achieved by the particle swarm optimization algorithm combined model, it is more suitable for predicting data pertaining to the iron ore demand.
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Bibliography

1. Al-Fattah, S.M. 2020. A new artificial intelligence GANNATS model predicts gasoline demand of Saudi Arabia. Journal of Petroleum Science and Engineering 194.
2. Al-Hnaity, B. and Abbod, M. 2016. Predicting Financial Time Series Data Using Hybrid Model. Intelligent Systems and Applications 650, pp. 19–41.
3. Bates, J.M. and Granger, C.W.J. 1969. The combination of forecasts. Journal of the Operational Research Society 20(4), pp. 451–468.
4. Bikcora et al. 2018 – Bikcora, C., Verheijen, L. and Weiland, S. 2018. Density forecasting of daily electricity demand with ARMA-GARCH, CAViaR, and CARE econometric models. Sustainable Energy Grids and Networks 13, pp. 148–156.
5. Box, G.E.P. and Jenkins, G.M. 1976. Time Series Analysis: Forecasting and Control. Holden-Day, San Francisco.
6. Davies, N.J.P. and Petruccelli, J.D. 1988. An Automatic Procedure for Identification, Estimation and Forecasting Univariate Self Exiting Threshold Autoregressive Models. Journal of the Royal Statistical Society 37(2), pp. 199–204.
7. D’Amico et al. 2020 – D’Amico, A., Ciulla, G., Tupenaite, L. and Kaklauskas, A. 2020. Multiple criteria assessment of methods for forecasting building thermal energy demand. Energy and Buildings 224, 110220.
8. Eberhart, R. and Kennedy, J. 1995. A new optimizer using particle swarm theory. [In:] MHS’95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science, pp. 39–43.
9. Holland, J.M. 1975. Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor.
10. Huang et al. 2006 – Huang, G.B., Zhu, Q.Y. and Siew, C.K. 2006. Extreme learning machine: theory and applications. Neurocomputing 70, pp. 489–501.
11. Jia, L.W. and Xu, D.Y. 2014. Analysis and Prediction of the Demand for Iron Ore: Using Panel, Grey, Co-Integration and ARIMA Models. Resources Science 36(7), pp. 1382–1391.
12. Kazemzadeh et al. 2020 – Kazemzadeh, M.R., Amjadian, A. and Amraee, T. 2020. A hybrid data mining driven algorithm for long term electric peak load and energy demand forecasting. Energy 204, 117948
13. Liu et al. 2016 – Liu, X.L., Moreno, B. and Garcia, A.S. 2016. A grey neural network and input-output combined forecasting model. Primary energy consumption forecasts in Spanish economic sectors. Energy 115, pp. 1042–1054.
14. Ma et al. 2013 – Ma, W.M., Zhu, X.X. and Wang, M.M. 2013. Forecasting iron ore import and consumption of China using grey model optimized by particle swarm optimization algorithm. Resources Policy 38, pp. 613–620.
15. Mi et al. 2018 – Mi, J., Fan, L., Duan, X. and Qiu, Y. 2018. Short-Term Power Load Forecasting Method Based on Improved Exponential Smoothing Grey Model. Mathematical Problems in Engineering 2018, pp. 1–11.
16. National Bureau of Statistics of China. Output of Industrial Products. [Online] https://data.stats.gov.cn/easyquery. htm?cn=C01&zb=A0E0H&sj=2019 [Accessed: 2020-12-30].
17. National Bureau of Statistics of China, 2018. Chinese Mining Yearbook. Beijing: China Statistics Press.
18. Song et al. 2018 – Song, J.J., Wang, J.Z. and Lu, H.Y.2018. A novel combined model based on advanced optimization algorithm for short-term wind speed forecasting. Applied Energy 215, pp. 643–658.
19. Vapnik, V.N. 1995. The Nature of Statistical Learning Theory. New York: Springer.
20. Wang et al. 2018 – Wang, J., Luo, Y.Y., Tang, T.Y. and Peng, G. 2018. Modeling a combined forecast algorithm based on sequence patterns and near characteristics: An application for tourism demand forecasting. Chaos, Solitons and Fractals 108, pp. 136–147.
21. Wang et al. 2012 – Wang, J.J., Wang, J.Z., Zhang, Z.G. and Guo, S.P. 2012. Stock index forecasting based on a hybrid model. Omega-International Journal of Management Science 40, pp. 758–766.
22. Wang et al. 2010 – Wang, J.Z., Zhu, S.L., Zhang, W.Y. and Lu, H.Y. 2010. Combined modeling for electric load forecasting with adaptive particle swarm optimization. Energy 35, pp. 1671–1678.
23. Wang et al. 2020 – Wang, Z.X., Zhao, Y.F. and He, L.Y. 2020. Forecasting the monthly iron ore import of China using a model combining empirical mode decomposition, non-linear autoregressive neural network, and autoregressive integrated moving average. Applied Soft Computing 94.
24. Winters, P.R. 1960. Forecasting sales by exponentially weighted moving averages. Management Science 6(3), pp. 324–42.
25. Zhang et al. 2019 – Zhang, S.H., Wang, J.Y. and Guo, Z.H. 2019. Research on combined model based on multi- -objective optimization and application in time series forecast. Soft Computing 23, pp. 11493–11521.
26. Zhang et al. 2017 – Zhang, Y., Li, C. and Li, L. 2017. Electricity price forecasting by a hybrid model, combining wavelet transform, ARMA and kernel-based extreme learning machine methods. Applied Energy 190, pp. 291–305.
27. Zhou et al. 2019 – Zhou, Z., Si, G.Q., Zheng, K., Xu, X., Qu, K. and Zhang, Y.B. 2019. CMBCF: A Cloud Model Based Hybrid Method for Combining Forecast. Applied Soft Computing 85, 105766.
28. Zhou, Z.H. 2016. Machine Learning. Beijing: Tsinghua University Press, 425 pp. ( in Chinese).

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Authors and Affiliations

Min Ren
1
Jianyong Dai
2
Wancheng Zhu
3
Feng Dai
3
ORCID: ORCID

  1. Northeastern University, Shenyang, China
  2. University of South China, Hengyang, China
  3. Northeastern University, Shenyang
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Abstract

In cities with large educational institutions, the inflow of educational migrants is important for con-sumption demand, and can trigger multiplier effects. The main aim of this article is to show the mecha-nism of the aggregate demand-income effect created by educational migration in the Polish city of Opole. An estimate of this effect is provided, based on questionnaire research among a sample of 1 075 students from all institutions of higher education located in the city. The estimated effects analysed concern the direct consumption impulse, as well as the indirect job creation and increase in income for providers of accommodation for students, in turn triggering increased consumption demand. While the results must be interpreted with care, an estimated 15 per cent of consumption demand created through expenditure of migrant students (about PLN 175 400 000) and 485 extra job show the significance of such expenditure for the local economy.

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Authors and Affiliations

Diana Rokita-Poskart
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Abstract

A lot of interest has recently been put into the so-called ‘virtual cryptographic currencies’, commonly known as cryptocurrencies, along with its surrounding market. The blockchain technology that stands behind them is also becoming increasingly popular. From the perspective of maintaining energy security, an important issue is the process of mining individual cryptocurrencies, which is associated with very high energy consumption. This operation is usually related to the approval of new blocks in the blockchain network and attaching them to the chain. This process is carried out through performing complex mathematical operations by various devices, which in turn require high power and respectively consume a lot of energy. The impact of cryptocurrency miners on the power and energy demand level might gradually increase over time, therefore this issue shouldn’t be ignored. Comparing the above information in parallel with the growing need for providing demand side response (DSR) services in the Polish Power System, raises the question whether devices used for mining cryptocurrencies can be used for the purpose of balancing the power system. This paper presents an analysis of the possibility to provide the demand side response services by groups of cryptocurrency miners users. The analysis was carried out taking basic functional, technological and economical aspects of these devices’ operations into account.

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Authors and Affiliations

Damian Mrowiec
Piotr Saługa
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Abstract

The pressure on the use of water and climate change has caused a decreased availability of water resources in semi-arid areas in the last decades. The Setif Province is one of the semi-arid zones of Algeria as it receives an average less than 400 mm∙year–1. The question of the evolution of demographic pressures and their impacts on water resources arise. By applying WEAP software (water evaluation and planning), the aim is to develop a model of water resources management and its uti-lization, assess the proportion of the resource-needs balance and analyse the future situation of water according to different scenarios. This approach allows to identify the most vulnerable sites to climatic and anthropogenic pressures. The estima-tion of the needs for drinking water and wastewater in the Setif Province has shown that these needs increase over time and happening when the offer is not able to cover the demand in a suitable way. It is acknowledged that there is a poor exploita-tion of water resources including underground resources, which translates into unmet demand in all sites of demand.

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Authors and Affiliations

Imad E. Bouznad
Omar Elahcene
Mohamed S. Belksier
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Abstract

In this paper, the results of correlations between air temperature and electricity demand by linear regression and Wavelet Coherence (WTC) approach for three different European countries are presented. The results show a very close relationship between air temperature and electricity demand for the selected power systems, however, the WTC approach presents interesting dynamics of correlations between air temperature and electricity demand at different time-frequency space and provide useful information for a more complete understanding of the related consumption.

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Authors and Affiliations

Samir Avdakovic
Alma Ademovic
Amir Nuhanovic
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Abstract

Results of the studies for determining fractions of organic contaminants in a pretreated petrochemical wastewater flowing into a pilot Aerated Submerged Fixed-Bed Biofilm Reactor (ASFBBR) are presented and discussed. The method of chemical oxygen demand (COD) fractionation consisted of physical tests and biological assays. It was found that the main part of the total COD in the petrochemical, pretreated wastewater was soluble organic substance with average value of 57.6%. The fractions of particulate and colloidal organic matter were found to be 31.8% and 10.6%, respectively. About 40% of COD in the influent was determined as readily biodegradable COD. The inert fraction of the soluble organic matter in the petrochemical wastewater constituted about 60% of the influent colloidal and soluble COD. Determination of degree of hydrolysis (DH) of the colloidal fraction of COD was also included in the paper. The estimated value of DH was about 62%. Values of the assayed COD fractions were compared with the same parameters obtained for municipal wastewater by other authors.

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Authors and Affiliations

Włodzimierz Wójcik
Karol Trojanowicz
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Abstract

In the over 150 years of hydrocarbon history, the year 2017 will be one of the many similar. However, it will be a breakthrough year for liquefied natural gas. In Asia, China grew to become the leader of import growth, becoming the second world importer, overtaking even South Korea and chasing Japan. The Panama Canal for LNG trade and the “Northern Passage” was opened, so that Russian LNG supplies appeared in Europe. The year 2017 was marked by a dramatic shortening of the length of long-term concluded contracts, their shorter tenure and reduction of volumes – that is, it was another period of market commoditization of this energy resource. The article describes the current state of LNG production and trade till 2018. It focuses on natural gas production in the United States, Qatar, Australia, Russia as countries that can produce and supply LNG to the European Union. The issue of prices and the contracts terms in 2017 was analyzed in detail. The authors stress that the market is currently characterized by an oversupply and will last at least until mid–2020. Novatek, Total – Yamal-LNG project leaders have put the condensing facility at 5.5 million tons into operation. The Christophe de Margerie oil tanker was the first commercial unit to cross the route to Norway and then further to the UK without icebreakers and set a new record on the North Sea Road. In 2017, the Russian company increased its share in the European gas market from 33.1 to 34.7%. In 2017, Russia and Norway exported record volumes of „tubular” – classic natural gas to Europe (and Turkey), 194 and 122 billion m3 respectively, which is 15 and 9 billion m3 more natural gas than in 2016. The thesis was put forward that Russia would not easily give up its sphere of influence and would do everything and use various mechanisms, not only on the market, that it would simply be more expensive and economically unprofitable than natural gas. It was also emphasized that the pressure of the technically possible and economically viable redirection to European terminals of methane carriers landed in the American LNG, results in Gazprom not having a choice but to adjust its prices. The Americans, but also any other supplier (Australia?) can simply do the same and this awareness alone is enough for Russian gas to be present in Europe at a good price.

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Authors and Affiliations

Andrzej P. Sikora
Mateusz Sikora
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Abstract

The road network development programme, as well as planning and design of transport systems of cities and agglomerations require complex analyses and traffic forecasts. It particularly applies to higher-class roads (motorways and expressways), which in urban areas, support different types of traffic. Usually there is a conflict between the needs of long-distance traffic, in the interest of which higher-class roads run through undeveloped areas, and the needs of bringing such road closer to potential destinations, cities [1]. By recognising the importance of this problem it is necessary to develop the research and methodology of traffic analysis, especially trip models. The current experience shows that agglomeration models are usually simplified in comparison to large city models, what results from misunderstanding of the significance of these movements for the entire model functioning, or the lack of input data. The article presents the INMOP 3 research project results, within the framework of which it was attempted to increase the accuracy of traffic generation in agglomeration model owing to the use of BigData – the mobile operator’s data on SIM card movements in the Warsaw agglomeration.

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Authors and Affiliations

A. Brzeziński
T. Dybicz
Ł. Szymański
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Abstract

Load profiles of residential consumers are very diverse. This paper proposes the usage of a continuous wavelet transform and wavelet coherence to perform analysis of residential power consumer load profiles. The importance of load profiles in power engineering and common shapes of profiles along with the factors that cause them are described. The continuous wavelet transform and wavelet coherence has been presented. In contrast with other studies, this research has been conducted using detailed (not averaged) load profiles. Presented load profiles were measured separately on working day and weekend during winter in two urban households. Results of applying the continuous wavelet transform for load profiles analysis are presented as coloured scalograms. Moreover, the wavelet coherence was used to detect potential relationships between two consumers in power usage patterns. Results of coherence analysis are also presented in a colourful plots. The conducted studies show that the Morlet wavelet is slightly better suitable for load profiles analysis than the Meyer’s wavelet. Research of this type may be valuable for a power system operator and companies selling electricity in order to match their offer to customers better or for people managing electricity consumption in buildings.
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Authors and Affiliations

Piotr Kapler
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Abstract

This paper discusses three variants of how e-mobility development will affect the Polish Power System. Multivariate forecasts of annual new registrations of electric vehicles for up to seven years are developed. The forecasts use the direct trend extrapolation methods, methods based on the deterministic chaos theory, multiple regression models, and the Grey model. The number of electric vehicles in use was determined for 2019‒2025 based on the forecast new registrations. The forecasts were conducted in three variants for the annual electric energy demand in 2019‒2025, using the forecast number of electric vehicles and the forecast annual demand for electric energy excluding e-mobility. Forecasts were conducted in three variants for the daily load profile of power system for winter and summer seasons in the Polish Power system in 2019‒2025 based on three variants of the forecast number of electric vehicles and forecast relative daily load profiles.

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Authors and Affiliations

P. Piotrowski
D. Baczyński
S. Robak
M. Kopyt
M. Piekarz
M. Polewaczyk
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Abstract

In recent decades, two different approaches to mine ventilation control have been developed: ventilation on demand (VOD) and automatic ventilation control (AVC) systems. The latter was primarily developed in Russia and the CIS countries. This paper presents a comparative analysis of these two approaches; it was concluded that the approaches have much in common. The only significant difference between them is the optimal control algorithm used in automatic ventilation control systems. The paper describes in greater detail the algorithm for optimal control of ventilation devices that was developed at the scientific school of the Perm Mining Institute with the direct participation of the authors. One feature of the algorithm is that the search for optimal airflow distribution in the mine is performed by the system in a fully automated mode. The algorithm does not require information about the actual topology of the mine and target airflows for the fans. It can be easily programmed into microcontrollers of main fans and ventilation doors. Based on this algorithm, an automated ventilation control system was developed, which minimizes energy consumption through three strategies: automated search for optimal air distribution, dynamic air distribution control depending on the type of shift, and controlled air recirculation systems. Two examples of the implementation of an automated ventilation control system in potash mines in Belarus are presented. A significant reduction in the energy consumption for main fans’ operation obtained for both potash mines.

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Authors and Affiliations

Mikhail A. Semin
Lev Y. Levin
Stanislav V. Maltsev
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Abstract

This article reviews the literature on the relationship between the region’s innovation and its development. Various concepts are discussed in the scheme of the four forces of regional and local competitiveness. The main determinants of the region’s innovation and competitiveness can be viewed in a four-force system: domination forces when the region exploits its advantage over others, network power – when the development potential is strengthened by cooperation, external demand and internal resources. In this framework of literature analysis, the article points to both entities and processes that represent the possibilities of the „innovation being” region.

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Authors and Affiliations

Wojciech Dziemianowicz
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Abstract

The study of the possibility of removing organic compounds from wastewater originating from the biodiesel purification stage by two catalytic processes, HSO5-/transition metal and Fenton method has been presented. The source of the ion HSO5- is potassium monopersulphate (2KHSO5·KHSO4·K2SO4) (Oxone) that may be decomposed into radicals (OH., SO4-., SO5-.) by means of transition metal as Co(II). Different concentrations were used for both compounds and the combination ([Co2+] = 1.00μM/[HSO5-] = 5.00·10-2 M) achieved the highest COD removal (60%) and complete decomposition of the oxidant was verified for contact times of 45 min. This process has some advantages comparing to the conventional Fenton method such as the absence of the costly pH adjustment and the Fe(III) hydroxide sludge which characterize this treatment process. The Fenton process showed that the combination of [H2O2] = 2.00M/[Fe2+] = 0.70 M was the best and archived COD removal of 80%. The treatments studied in this research have achieved high COD removal, but the wastewater from the biodiesel purification stage presents very high parametric values of Chemical Oxygen Demand (667,000 mgO2/L), so the final COD concentration reached is still above the emission limit of discharge in surface water, according the Portuguese Law (Decree-Law 236/98). However, both treatments have proved to be feasible techniques for the pre-oxidation of the wastewater under study and can be considered as a suitable pre-treatment for this type of wastewaters. A rough economic analysis of both processes was, also, made.

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Authors and Affiliations

Teresa Borralho
Solange Coelho
Andreia Estrelo
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Abstract

The paper attempted to define the basis of city transformations that conform to the smart concept. The objective of the paper is to relate the concept of a smart city, which is quite frequently discussed in literature related to the subject, with functioning and development of the city’s economy, in a way that would allow monitoring economic processes taking place in the city, and also to find a response to the question as to the extent to which the smart city creates a new city economy. Does it expand the city economy by new elements, generate new economic mechanisms, allow the implementation of growth paths different than those to date? This objective is particularised by a description of selected issues of urban economics. With this in mind the paper discusses an approach to managing supply and demand on the basis of theoretical assumptions defined by Mudie and Cottam (1993) transposed on realities connected with provision of municipal public services in conditions of a smart city. Furthermore, sample solutions were presented related to the smart city, which reflect theoretical conclusions contained in the paper. The paper ends with a presentation of logics related to growing economy in a smart city. The economy of a smart city, ultimately an intelligent economy of the city, is created in a laminar way. Under the pressure of technological, social and political surroundings the city is permeated by social and culture intelligence, forming gradually a new economic quality. In the paper we emphasised that the concept of a smart city still remains a question of the future to a much bigger extent than one of the present time. A smart city slowly emerges from the combination of diverse megatrends and development trends characteristic for communities and economies of the second decade of the 21st century.

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Authors and Affiliations

Marcin Baron
Florian Kuźnik
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Abstract

In the academic community within Poland, there is an ongoing debate about the optimal strategies for a redesign of PhD programs; however, the views of PhD students in relation to contemporary doctoral study programs are not widely known. Therefore, in this article, we aim to answer the following questions: (1) what are the demands and the resources for doctoral studies at the Jagiellonian University (JU) as experienced by PhD students? (2) how are these demands and resources related to study burnout and engagement? To gain answers to these questions, we conducted an on-line opinion-based survey of doctoral students. As a result, 326 JU PhD students completed a questionnaire measuring 26 demands and 23 resources along with measures of study burnout and levels of engagement. The results revealed that the demands of doctoral studies at the JU (as declared by at least half of the respondents) are: the requirement to participate in classes that are perceived as an unproductive use of time, the lack of remuneration for tutoring courses with students, a lack of information about possible career paths subsequent to graduation, the use of PhD students as low-paid workers at the university, a lack of opportunities for financing their own research projects, and an inability to take up employment while studying for a doctoral degree. In terms of resources, at least half of the doctoral students pointed to: discounts on public transport and the provision of free-of-charge access to scientific journals. Analyzing both the frequency and strength of the relationships between resources/demands and burnout/engagement, we have identified four key problem areas: a lack of support from their supervisor, role ambiguity within University structures for PhD students, the conflict between paid work and doctoral studies, and the mandatory participation in classes as a student.

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Authors and Affiliations

Konrad Kulikowski
Rafał Damaziak
Anna Kańtoch
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Abstract

The factor which essentially affects sludge biodegradation rate is the degree of fluidization of insoluble organic polymers to the solved form, which is a precondition for availability of nutrients for microorganisms. The phases which substantially limit the rate of anaerobic decomposition include hydrolytic and methanogenic phase.

Subjecting excess sludge to the process of initial disintegration substantially affects the effectiveness of the process of anaerobic stabilization. As a result of intensification of the process of hydrolysis, which manifests itself in the increase in the value and rate of generating volatile fatty acids (VFA), elongation of methanogenic phase of the process and increase in the degree of fermentation of modified sludge can be observed. Use of initial treatment of sewage sludge i.e. thermal disintegration is aimed at breaking microorganisms' cells and release of intracellular organic matter to the liquid phase. As a result of thermal hydrolysis in the sludge, the volatile fatty acids (VFA) are generated as early as at the stage of the process of conditioning. The obtained value of VFA determines the course of biological hydrolysis which is the first phase of anaerobic stabilization.

The aim of the present study was to determine the effect of thermal disintegration of excess sludge on the effectiveness of the process of hydrolysis in anaerobic stabilization i.e. the rate of production of volatile fatty acids, changes in the level of chemical oxygen demand (COD) and increase in the degree of reduction in organic matter. During the first stage of the investigations, the most favourable conditions of thermal disintegration of excess sludge were identified using the temperatures of 50°C, 70°C, 90°C and heating times of 1.5 h - 6 h. The sludge was placed in laboratory flasks secured with a glass plug with liquid-column gauge and subjected to thermal treatment in water bath with shaker option. Another stage involved 8-day process of anaerobic stabilization of raw and thermally disintegrated excess sludge. Stabilization was carried out in mesophilic temperature regime i.e. at 37°C, under periodical conditions. In the case of the process of anaerobic stabilization of thermally disintegrated excess sludge at the temperature of 50°C and heating time of 6 h (mixture B) and 70°C and heating time of 4.5% (mixture C), the degree of fermentation of 30.67% and 33.63%, respectively, was obtained. For the studied sludge, i.e. mixture B and mixture C, maximal level of volatile fatty acids i.e. 874.29 mg CH3COOH/dm3 and 1131.43 mg CH3COOH/dm3 was found on the 2nd day of the process. The maximal obtained value of VFA was correlated on this day with maximal COD level, which was 1344 mg O2/dm3 for mixture B and 1778 mg O2/dm3 for mixture C.

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Authors and Affiliations

I. Zawieja
P. Wolski

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