In an increased urbanized world, cities face several challenges and threats, and struggle to propose credible urban futures and new opportunities for their citizens. Social services and health facilities are significantly affected in negative ways owed to the increase in urban populations (70% by 2050). Air pollution and urban heat islands are exacerbating. Nature will struggle to compensate in the future city, as rural land is predicted to shrink by 30% affecting liveability. VARCITIES is an ambitious EU research project that puts the citizens and the “human communities” at the centre of future cities’ vision, in the belief that future cities should become fully human-centred cities. The project started in September 2020. Seven Pilot Cities are testing and implementing a series of innovative nature-based actions. The vision of VARCITIES is to implement real, visionary ideas and add value by establishing sustainable models for increasing health and well-being of citizens who are exposed to diverse climatic conditions and challenges around Europe through shared public spaces that make cities liveable and welcoming. VARCITIES sets the ambitious target to advance innovation across different urban scales by fully exploiting nature-based solutions from a digital, social and cultural perspective. Public spaces are envisioned as people-centred areas that support creativity, inclusivity, health and happiness for the citizens.
The purpose of this study was the conversion of calcareous lignite fly ash (LFA) into synthetic zeolite by hydrothermal, fusion‐hydrothermal and hydrothermal ‐sonochemical processes. Experiments were carried out using raw and washed (5 N HCl) fly ash. Initially, the fractional factorial experimental design was used to plan the hydrothermal experiments and assess the process parameters such as solid to liquid ratio (S/L), silica to aluminum oxide ratio (SiO 2 /Al 2 O 3 ), calcium oxide content (% CaO), time and temperature of the hydrothermal process. The optimized conditions were then applied to a two‐stage fusion‐hydrothermal process, while the influence of sonication on the conversion efficiency was tested before and after the hydrothermal process. Mineralogical analysis was performed by X‐ray diffractometer (XRD) to detect zeolite formation. Further characterization was conducted by X‐ray fluorescence (XRF), specific surface area and laser particle analysis to assess process efficiency. The results indicated the formation of four types of zeolite crystals. The washed LFA yielded the maximum zeolite yield, when it was hydrothermally treated for 6 h at 150 o C, S/L=1:2, and SiO 2 /Al 2 O 3 =6.3. In such conditions, phillipsite was synthesized at 27%. The yield of phillipsite zeolite was improved to 32% when hydrothermal was followed by a 30 min sonication process. At the same processing conditions, the use of raw LFA produced 72% crystalline tobermorite. The hydrothermal‐late sonication process can effectively convert waste fly ash into valuable products. This article is protected by copyright. All rights reserved.
Satellite geodesy, an indispensable modern tool for determining upper-crust deformation, can be used to assess tectonically active structures and improve our understanding of the geotectonic evolution in tectonically active regions. A region fulfilling these criteria is the North Aegean, part of the Eastern Mediterranean. It is one of the most tectonically, and hence, seismically, active regions worldwide, which makes it ideal for applying a satellite geodesy investigation. Although many regional studies have been carried out across the entire Aegean region, there are three more focused case studies that provide better resolution for different parts of the North Aegean. The synthesis of these case studies can lead to an overall geodynamic assessment of the North Aegean. The North Aegean Sea case study is characterized by the North Aegean Trough (NAT), which is directly associated with the westward prolongation of the North Anatolian Fault (NAF). Both NE–SW normal and strike-slip faulting have been documented in this offshore region. Geodetic analysis considers geodetic data, derived from 32 permanent GPS/GNSS stations (recorded for the 2008–2014 time period). This results in the estimation of the Maximum (MaHE) and Minimum (MiHE) Horizontal Extension, Maximum Shear Strain (MSS) and Area Strain (AS) parameters, based on triangular methodology implementation; the same strain parameters have similarly been estimated for the Strymon and Thessalian basins, respectively. The Strymon basin (first case study) is located in the central part of the northern Greek mainland, and it is dominated by NW–SE (up to E–W) dip-slip normal faults; this area has been monitored by 16 permanent GPS/GNSS stations for seven consecutive years. Regarding the Thessalian basin case study, E–W, dip-slip and normal faults are noted at the basin boundaries and within the Thessalian plain. This region has also been monitored for seven consecutive years by 27 permanent GPS/GNSS stations. However, this case study is characterized by a strong seismic event (Mw6.3; 3 March 2021), and thus all strain parameters depicted the pre-seismic deformation. Analysis of these three different case studies confirmed the current tectonic setting of the North Aegean region, while revealing new aspects about the geodynamic evolution of the wider region, such as highlighting areas with significant tectonic activity and the crucial role of strike-slip faulting in the broader Aegean region.
This work offers design and implementation of in-network inference, using message passing among ambiently powered wireless sensor network (WSN) terminals. The stochastic nature of ambient energy harvesting dictates intermittent operation of each WSN terminal and as such, the message passing inference algorithms should be robust to asynchronous operation. It is shown, perhaps for the first time in the literature (to the best of our knowledge), a proof of concept, where a WSN harvests energy from the environment and processes itself the collected information in a distributed manner, by converting the (network) inference task to a probabilistic, in-network message passing problem, often at the expense of increased total delay. Examples from Gaussian belief propagation and Average Consensus are provided, along with the derivation of a statistical convergence metric for the latter case. A k-means method is offered that maps the elements of the calculated vector to the different WSN terminals and overall execution delay (in number of iterations) is quantified. Interestingly, it is shown that there are divergent instances of the in-network message passing algorithms that become convergent, under asynchronous operation. Ambient solar energy harvesting availability is also studied, controlling the probability of successful (or not) message passing. Hopefully, this work will spark further interest for asynchronous message passing algorithms and technologies that enable in-network inference, towards ambiently-powered, batteryless Internet-of-Things-That-Think.
3D virtual prototyping for garment development, although not much exploited and appreciated by the clothing industry in the early days of its appearance two decades ago, has now been explored (research-wise) extensively especially in the pandemic period and its impact on the whole supply chain of garments and fashion products. This virtual prototype which allows the company to visualize the status and condition of a clothing product that may be thousands of kilometers away, providing insights into how products can be better designed, manufactured, operated and serviced before companies invest in physical prototypes and assets, is often called digital twin. At the same time, laser-cut as a creative design technique on clothing materials have emerged in recent times, as fashion moguls are seeing the benefits that the technology presents. Laser cut technology with its benefits of accuracy, speed, precision, applicability in various materials, flexibility in geometry, interoperability with other systems like CAD/CAM and CIM, sustainability in resources and source of inspiration for several upcoming designers, provides an excellent approach for creating bridges between the past, the present and the future in history of fashion design. The aim of this paper was to provide a decision-making framework for the selection of an effective digital twinning process with the use of two different 3D virtual prototyping tools. For this purpose, a methodological framework is proposed which guides the creator according to the final use of the digital garment twin: evaluation of actual fit and actual representation of the produced physical, or as a shared digital asset for an exclusive digital environment.
This work introduces a methodology for the automatic unmineable inclusions detection and Bucket Wheel Excavator (BWE) collision prevention, using electromagnetic (EM) inspection and a fuzzy inference system. EM data are collected continuously ahead from the bucket wheel of a BWE and subjected to processing. Two distinct methodologies for data processing were developed and integrated into the MATLAB programming environment. The first approach, named “Simple Mode”, utilizes statistical process control to generate real-time alerts in the event of a potential collision involving the excavator’s bucket and hard rock inclusions. The advanced processing flow (“Advanced Mode”) requires accurate instrument positioning and data from successive EM scans. It incorporates techniques of local resistivity maxima detection (Position Prominence Index) as well as Neural Network-based Pattern Recognition (NNPR). A decision support process based on a Fuzzy Inference System (FIS) has been developed to assist BWE operators in avoiding collision when digging hard rock inclusions. The proposed methodology was extensively tested using synthetic EM data. Limited real data, acquired with a CMD2 (GF Instruments) EM instrument equipped with GPS, were used to control its efficiency. Increased accuracy in the automatic detection of unmineable inclusions was observed using the Advanced Mode. On the other hand, the Simple Mode processing technique offers the advantage of being independent of instrument positioning as well as it provides real-time inspection of the excavated mine slope. This work introduces a methodology for hard rock inclusion detection and can contribute to the optimization of mine operations by improving resource efficiency, safety, cost savings, and environmental sustainability.
Small mοdular reactors (SMRs) are nuclear reactors with a smaller capacity than traditional large-scale nuclear reactors, offering advantages such as increased safety, flexibility, and cost-effectiveness. By producing zero carbon emissions, SMRs represent an interesting alternative for the decarbonization of power grids. Additionally, they present a promising solution for the production of hydrogen by providing large amounts of energy for the electrolysis of water (pink hydrogen). The above hint at the attractiveness of coupling SMRs with hydrogen production and consumption centers, in order to form clusters of applications which use hydrogen as a fuel. This work showcases the techno-economic feasibility of the potential installation of an SMR system coupled with hydrogen production, the case study being the island of Crete. The overall aim of this approach is the determination of the optimal technical characteristics of such a system, as well as the estimation of the potential environmental benefits, in terms of reduction of CO2 emissions. The aforementioned system, which is also connected to the grid, is designed to serve a portion of the electric load of the island, while producing enough hydrogen to satisfy the needs of the nearby industries and hotels. The results of this work could provide an alternative sustainable approach on how a hydrogen economy, which would interconnect and decarbonize several industrial sectors, could be established on the island of Crete. The proposed systems achieve an LCOE between EUR 0.046/kWh and EUR 0.052/kWh while reducing carbon emissions by more than 5 million tons per year in certain cases.
A numerical investigation of masonry walls subjected to blast loads is presented in this article. A non-linear finite element model is proposed to describe the structural response of the walls. A unilateral contact–friction law is used in the interfaces of the masonry blocks to provide the discrete failure between the blocks. A continuum damage plasticity model is also used to account for the compressive and tensile failure of the blocks. The main goal of this article is to investigate the different collapse mechanisms that arise as an effect of the blast load parameters and the static load of the wall. Parametric studies are conducted to evaluate the effect of the blast source–wall (standoff) distance and the blast weight on the structural response of the system. It is shown that the traditional in-plane diagonal cracking failure mode may still dominate when a blast action is present, depending on the considered standoff distance and the blast weight when in-plane static loading is also applied to the wall. It is also highlighted that the presence of an opening in the wall may significantly reduce the effect of the blasting action.
Citation: Kurniawati, I.; Beaumont, B.; Varghese, R.; Kostadinović, D.; Sokol, I.; Hemida, H.; Alevras, P.; Baniotopoulos, C. Conceptual Design of a Floating Modular Energy Island for Energy Independency: A Case Study in Crete. Energies 2023, 16, 5921. Abstract: This paper aims to investigate the development of a floating artificial sustainable energy island at a conceptual design level that would enhance the energy independence of islands focusing on a case study on the island of Crete. This paper provides a baseline assessment showing the immense potential of wind and solar energy in and around Crete integrating the third significant renewable energy source (RES) of ocean waves into the energy island. The selection of the best location for the floating offshore platforms that compose the energy island is addressed through exploiting the great potential of the above-mentioned RES, taking into consideration criteria with regard to several significant human activities. To this end, the concept of an innovative floating modular energy island (FMEI) that integrates different renewable energy resources is proposed; in addition, a case study that focuses on the energy independency of a big island illustrates the concept referring to the substitution of the local thermal power plants that are currently in operation in Crete with sustainable energy power. Although focused on the renewable energy resources around Crete, the work of this paper provides a basis for a systematic offshore renewable energy assessment as it proposes a new methodology that could be used anywhere around the globe.
In May 2022, rot symptoms were observed 5 days after storage on fresh avocado fruits cv "Lamb Hass" harvested from a 3.4 ha organic orchard in Chania, Crete exhibiting 30% symptom incidence. Brownish-green sunken lesions and soft rot with dark brown lesions covering up to 50% of the mesocarp on fruits and blackish soft lesions on fruit stem ends were observed. To isolate the pathogens, fruits were surface sterilized using 1% NaOCl for 1 min, placed in 70% ethanol for 30 s and washed twice with sterile distilled water. Then, small pieces were excised from the fruit rot margins and transferred on PDA amended with 0.015% streptomycin-sulfate. Single-spore isolates were incubated on PDA for 10 days and subjected to morphological examination. Two distinct pathogenic fungal isolates were obtained, and their symptoms were re-examined on avocado fruits. The first isolate (A1) obtained from the fruit stem end, initially produced hyaline dense aerial mycelia, being gray and black on the upper and lower surface of the Petri dishes, respectively. The second isolate (A2) obtained from the main body of the fruit, formed round, grayish colonies, with orange conidial aggregates. Based on morphological characteristics (Phillips et al.,2013; Weir et al., 2012), isolates were preliminary identified as Neofusicoccum sp. (A1) and Colletotrichum sp. (A2). Isolates were molecularly identified by sequencing of the ITS-5.8S rRNA, translation elongation factor 1-alpha (tef1) and beta-tubulin (tub2) genes. PCRs were conducted using primer pairs ITS4/ITS5, EF1-728F/EF1986R and Bt2a/Bt2b as well as ITS4/ITS5 and 5'-tef1/3'-tef1 and Bt2a/Bt2b for isolates A1 and A2, respectively (Carbone & Kohn, 1999; Glass & Donaldson, 1995; Rojas et al., 2010; Weir et al., 2012; White et al., 1990). The sequences were deposited into GenBank under the accession numbers OQ852465, OQ867962, OQ867965 for N. luteum and, OQ852466, OQ867963 and OQ867964 for C. gloeosporioides. Based on Multilocus sequence analysis (MLSA), a phylogenetic tree was constructed using concatenated sequences, following Kimura's two parameter model (1980), which confirmed their identity as N luteum and C. gloeosporioides strains. Mature avocado fruits (cv. Hass) were surface sterilized and dried. Consequently, incised fruits were inoculated with mycelial agar plugs (5 mm in diameter) cut from the edge of rapidly growing colonies of N. luteum and C. gloeosporioides strains. Fruits incubated in moist chambers and at 25°C for 5 days in the dark. Fruit bodies and stems were inoculated with the respective isolates and sterile agar plugs in the case of the control. Five fruits were used for each pathogenic trial per fungal isolate, which was repeated twice. After symptom occurrence, these pathogenic isolates were re-isolated successfully and molecularly identified, while exhibiting similar to original symptoms confirming Koch's postulates. While other reports exist on the presence of these pathogens in different countries worldwide, this is the first report of C. gloeosporioides and N. luteum as post-harvest pathogens of avocado, which is an economically important crop of Crete, in Greece (Akgül et al., 2016). This study provides the means for the accurate identification of these fungal pathogens causing avocado fruit rots and taking into consideration the available treatment options can contribute to establishing effective management strategies.
The increasing use of natural gas as an efficient, reliable, affordable, and cleaner energy source, compared with other fossil fuels, has brought the catalytic CH4 complete oxidation reaction into the spotlight as a simple and economic way to control the amount of unconverted methane escaping into the atmosphere. CH4 emissions are a major contributor to the ‘greenhouse effect’, and therefore, they need to be effectively reduced. Catalytic CH4 oxidation is a promising method that can be used for this purpose. Detailed studies of the activity, oxidative thermal aging, and the time-on-stream (TOS) stability of pristine La1−xSrxMnO3 perovskites (LSXM; X = % substitution of La with Sr = 0, 30, 50 and 70%) and iridium-loaded Ir/La1−xSrxMnO3 (Ir/LSXM) perovskite catalysts were conducted in a temperature range of 400–970 °C to achieve complete methane oxidation under excess oxygen (lean) conditions. The effect of X on the properties of the perovskites, and thus, their catalytic performance during heating/cooling cycles, was studied using samples that were subjected to various pretreatment conditions in order to gain an in-depth understanding of the structure–activity/stability correlations. Large (up to ca. 300 °C in terms of T50) inverted volcano-type differences in catalytic activity were found as a function of X, with the most active catalysts being those where X = 0%, and the least active were those where X = 50%. Inverse hysteresis phenomena (steady-state rate multiplicities) were revealed in heating/cooling cycles under reaction conditions, the occurrence of which was found to depend strongly on the employed catalyst pre-treatment (pre-reduction or pre-oxidation), while their shape and the loop amplitude were found to depend on X and the presence of Ir. All findings were consistently interpreted, which involved a two-term mechanistic model that utilized the synergy of Eley–Rideal and Mars–van Krevelen kinetics.
Sensitive ecosystems play a major role in the future of the environment, economy, and society, as they affect and mitigate natural hazards, provide food, energy, and medicinal resources, and job opportunities, as well as cultural and recreational services. Meanwhile, the rapidly growing nature-based tourism sector is applying unsustainable pressures on such ecosystems, prioritizing the assessment of their sustainability, i.e., environmental, economic, and social functionality. To ensure long-term development and conservation, benefits from the natural capital must be valued and included in its management plan. The travel cost method (TCM), although heavily exploited in research, exhibits application challenges and methodological weaknesses. This paper seeks to comprehensively present the most recent applications of TCM, focusing on aquatic ecosystems that serve as tourist destinations, whereupon research gaps are identified, ultimately providing insights for future directions in the field. Quantifying the economic worth of sensitive ecosystems is a prerequisite to address issues, such as overexploitation, pollution, and climate change, so these problems can be alleviated in the long-run. In parallel, the critical long-term double effect of fair entrance fees is recognized, which not only motivate visitation by securing accessibility but also guarantee adequate financial resources to protect and maintain the ecosystems’ integrity.
This paper proposes a novel particle scheme that provides convergent approximations of a weak solution of the Navier‐Stokes equations for the 1‐D flow of a viscous compressible fluid. Moreover, it is shown that all differential inequalities that hold for the fluid model are preserved by the particle method: mass is conserved, mechanical energy is decaying, and a modified mechanical energy functional is also decaying. The proposed particle method can be used both as a numerical method and as a method of proving existence of solutions for compressible fluid models.
We establish robustness of string stability to delay uncertainty as well as positivity of spacing and speed states, for homogeneous vehicular platoons under predictor-feedback Cooperative Adaptive Cruise Control (CACC). Each individual vehicle’s dynamics are described by a second-order linear system with delayed desired acceleration, under acceleration information transmitted to the ego vehicle from a single, preceding vehicle. The nominal design (in the delay-free case) is a constant time-headway (CTH) policy and no restriction on the delay size, in relation with the desired time headway, is imposed. The proofs rely on combination of an input-output approach (on the frequency domain) and on deriving estimates on explicit, closed-loop solutions; under specific, sufficient conditions that are derived on initial conditions and parameters of the baseline, CTH controller. We illustrate in simulation and numerical examples, the guarantees of robust stability and string stability as well as of collisions avoidance, of CTH predictor-feedback CACC design. We also present extensions of our design and analysis approach to heterogeneous, third-order dynamic models of vehicles.
Following the knowledge-based and intellectual capital-based view of firms, where knowledge is at the center of corporate strategic management, this paper aims to examine the role of Green Intellectual Capital (GIC) in the environmental and financial dimensions of corporate performance. To do so, a methodological framework was developed to evaluate the progress of GIC and corporate environmental performance by utilizing information and data from sustainability reports. Also, the Return of Equity (ROE) indicator was used to assess corporate financial performance. The proposed methodology was applied in a sample of 80 firms to examine the mediator role of GIC in the relationship between financial and environmental performance. The findings show a positive relationship between GIC (as a result of Green Relational Capital (GRC) and Green Organizational Capital (GOC)) and financial performance (ROE), as well as a significant positive relationship between environmental performance and the components of Green Intellectual Capital. Finally, a nonlinear U-shaped relationship between environmental and financial performance is identified.
Institution pages aggregate content on ResearchGate related to an institution. The members listed on this page have self-identified as being affiliated with this institution. Publications listed on this page were identified by our algorithms as relating to this institution. This page was not created or approved by the institution. If you represent an institution and have questions about these pages or wish to report inaccurate content, you can contact us here.