Search results for: Design techniques

Authors: Al-Tammar M. Shahah

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Background and Objective: A novel pneumonia caused by coronavirus disease 2019 (COVID-19), which is spreading domestically and internationally, has been identified by the Chinese city of Wuhan since the end of December 2019. Limited studies examined the psychological experience such as anxiety, depression, and stress during Corona pandemic. Moreover, to the best of author's knowledge, there is no study to date has examined the psychological resilience and mental health during Corona pandemic in Kuwait. Therefore, the present research investigates the role of psychological resilience in predicting psychological distress among Kuwaiti adults during Corona pandemic. Method: Kuwaiti citizens (N = 735) completed an online survey, which includes four scales the Hospital Anxiety and Depression Scale HADS (anxiety and depression), the Connor-Davidson Resilience Scale (CD-RISC-25), and the Perceived Stress Scale (PSS). A cross-sectional correlational design was used. Results: A high level of stress was observed, with 59% reported moderate to severe stress. In contrast, low levels of anxiety and depression were observed; with 70% reporting no anxiety symptoms and 74% report no depression symptoms. Psychological resilience was negatively correlated with anxiety, depression, and stress, consistent with previous studies. As expected, resilience was found to account for significant variance in anxiety and stress after controlling for quarantine variables and demographic variables. Conclusion: The findings suggest that increasing psychological resilience might help reduce psychological distress after confronting with stressful live events in Kuwaiti citizen.

Keywords: anxiety, corona, depression, psychological resilience, stress

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Authors: Suzanne Strauss, Leandi Steenkamp

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The Finnish symphonic metal band Nightwish is the brainchild of songwriter and lyricist TuomasHolopainen and the band recorded their first demonstration recording in 1996. The band has since produced nine full-length studio albums, the most recent being the 2020 album Human. :||: Nature., and has reached massive international success. The band is well known for songs about fantasy and escapism and employs many sonic, visual and branding tools and techniques to communicate these constructs to the audience. Among these, is the band’s creation of the so-called “Nightwish world and mythology” with a set of recurring characters and narratives which, in turn, creates a psychological anchor and safe space for Nightwish fans around the globe. Nature and the reverence of nature are central themes in Nightwish’s self-created mythology.Swiss psychologist Carl Jung’s theory of the collective unconscious identified a mysterious reservoir of psychological constructs common to all people, being derived from ancestral memory and experience, common to all humankind, and distinct from the individual’s personal unconscious. Furthermore, he defined archetypes as timeless collective patterns and images that springs forth from the collective unconscious. Archetypes can be actualized when they enter consciousness as images in interaction with the outside world. Archetypal patterns or images can manifest in different ways across world cultures, but follow common patterns, also known as archetypal themes and symbols. The Jungian approach to the psyche places great emphasis on nature, positing a direct link betweenthe concept of wholeness and responsible care for nature and the environment.In our proposed paper, we examine, by means of thematic content analysis, how Nightwish makes use of archetypal themes and symbols referring to nature and the environment in selected songs from their ninth full-length album Human. II Nature. Furthermore, we argue that the longing for and reverence of nature in selected Nightwish songs may serve as a type of “social intervention” and social critique on modern capitalist society. The type of social critique that the band offers is generally connoted intertextually and is not equally explicit in their songs. The band uses a unique combination of escapism, fantasy, and nature narratives to inspire a sense of wonder, enchantment, and magic in the listener. In this way, escapism, fantasy, and nature serve as postmodern frames of reference that aim to “re-enchant” the disenchanted and de-spiritualized. In this way, re-enchantment could also refer to spiritual and/or psychological healing and rebirth.

Keywords: archetypes, metal music, nature, Nightwish, social interventions

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Authors: Rajini Murugesan, Anantharaj Sengeni, Arthanareeswari Maruthapillai

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The global transition to renewable energy hinges on breakthroughs in catalysis for the oxygen evolution reaction (OER) a bottleneck in fuel cell and water-splitting technologies. The 3D nanostructured Mn-doped CoFe-LDH catalyst merges high-performance engineering with next-generation material design. By leveraging the synergistic effects of Mn doping within the CoFe-LDH framework, this self-supported catalyst achieves a quantum leap in OER efficiency. The strategically tailored 3D architecture amplifies active surface areas and facilitates seamless electron transport, while Mn incorporation fine-tunes the electronic structure, unlocking new catalytic pathways. Synthesized through an accessible hydrothermal approach, the material redefines scalability in catalyst production. The Mn-doped CoFe-LDH delivers industry-leading performance, with an impressively low overpotential of 255 mV at 20 mA cm⁻², combined with enduring stability over 24 hours of rigorous operation in alkaline media. This remarkable performance not only rivals state-of-the-art alternatives but also offers a sustainable, cost-effective solution tailored for real-world energy applications. Our findings bridge the gap between material innovation and practical implementation, setting a benchmark for OER catalysis in the era of clean energy. The Mn-doped CoFe-LDH isn’t just a catalyst; it’s a vision for the future of sustainable energy technologies.

Keywords: clean energy, fuel cells, layered double hydroxides (LDH), oxygen evolution reaction (OER).

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Authors: Bina Gupta, Rashmi Singh, Harshit Mahandra

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Molybdenum is a strategic metal and finds applications in petroleum refining, thermocouples, X-ray tubes and in making of steel alloy owing to its high melting temperature and tensile strength. The growing significance and economic value of molybdenum have increased interest in the development of efficient processes aiming its recovery from secondary sources. Main secondary sources of Mo are molybdenum catalysts which are used for hydrodesulphurisation process in petrochemical refineries. The activity of these catalysts gradually decreases with time during the desulphurisation process as the catalysts get contaminated with toxic material and are dumped as waste which leads to environmental issues. In this scenario, recovery of molybdenum from spent catalyst is significant from both economic and environmental point of view. Recently ionic liquids have gained prominence due to their low vapour pressure, high thermal stability, good extraction efficiency and recycling capacity. Present study reports recovery of molybdenum from Mo-Co spent leach liquor using Cyphos IL 102[trihexyl(tetradecyl)phosphonium bromide] as an extractant. Spent catalyst was leached with 3 mol/L HCl and the leach liquor containing Mo-870 ppm, Co-341 ppm, Al-508 ppm and Fe-42 ppm was subjected to extraction step. The effect of extractant concentration on the leach liquor was investigated and almost 85% extraction of Mo was achieved with 0.05 mol/L Cyphos IL 102. Results of stripping studies revealed that 2 mol/L HNO3 can effectively strip 94% of the extracted Mo from the loaded organic phase. McCabe-Thiele diagrams were constructed to determine the number of stages required for quantitative extraction and stripping of molybdenum and were confirmed by counter current simulation studies. According to McCabe-Thiele extraction and stripping isotherms, two stages are required for quantitative extraction and stripping of molybdenum at A/O= 1:1. Around 95.4% extraction of molybdenum was achieved in two stage counter current at A/O= 1:1 with negligible extraction of Co and Al. However, iron was coextracted and removed from the loaded organic phase by scrubbing with 0.01 mol/L HCl. Quantitative stripping (~99.5 %) of molybdenum was achieved with 2.0 mol/L HNO3 in two stages at O/A=1:1. Overall ~95.0% molybdenum with 99 % purity was recovered from Mo-Co spent catalyst. From the strip solution, MoO3 was obtained by crystallization followed by thermal decomposition. The product obtained after thermal decomposition was characterized by XRD, FE-SEM and EDX techniques. XRD peaks of MoO3correspond to molybdite Syn-MoO3 structure. FE-SEM depicts the rod like morphology of synthesized MoO3. EDX analysis of MoO3 shows 1:3 atomic percentage of molybdenum and oxygen. The synthesised MoO3 can find application in gas sensors, electrodes of batteries, display devices, smart windows, lubricants and as catalyst.

Keywords: cyphos IL 102, extraction, Mo-Co spent catalyst, recovery

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Authors: Khumbuzile M. Ngcobo, Seraphin D. Eyono Obono

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Science and technology has a major impact on many societal domains such as communication, medicine, food, transportation, etc. However, this dominance of modern technology can have a negative unintended impact on indigenous systems, and in particular on indigenous foods. This problem serves as a motivation to this study whose aim is to examine the perceptions of learners on the usefulness of Information and Communication Technologies (ICT's) for learning about indigenous foods. This aim will be subdivided into two types of research objectives. The design and identification of theories and models will be achieved using literature content analysis. The objective on the empirical testing of such theories and models will be achieved through the survey of Hospitality studies learners from different schools in the iLembe and Umgungundlovu Districts of the South African Kwazulu-Natal province. SPSS is used to quantitatively analyse the data collected by the questionnaire of this survey using descriptive statistics and Pearson correlations after the assessment of the validity and the reliability of the data. The main hypothesis behind this study is that there is a connection between the demographics of learners, their perceptions on the usefulness of ICTs for learning about indigenous foods and the following personality an e-learning related theories constructs: computer self-efficacy, trust in ICT systems, and conscientiousness; as suggested by existing studies on learning theories. This hypothesis was fully confirmed by the survey conducted by this study except for the demographic factors where gender and age were not found to be determinant factors of learners’ perceptions on the usefulness of ICT's for learning about indigenous foods.

Keywords: e-learning, indigenous foods, information and communication technologies, learning theories, personality

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Authors: Christoph Opperer

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Space syntax is a theory and method for analyzing the spatial layout of buildings and urban environments to understand how they can influence patterns of human movement, social interaction, and behavior. While direct visibility is a key factor in space syntax research, important visual information such as light, color, texture, etc., are typically not considered, even though psychological studies have shown a strong correlation to the human perceptual experience within physical space – with light and color, for example, playing a crucial role in shaping the perception of spaciousness. Furthermore, these surface properties are often the visual features that are most salient and responsible for drawing attention to certain elements within the environment. This paper explores the potential of integrating these factors into general space syntax methods and visibility-based analysis of space, particularly for architectural spatial layouts. To this end, we use a combination of geometric (isovist) and topological (visibility graph) approaches together with image-based methods, allowing a comprehensive exploration of the relationship between spatial geometry, visual aesthetics, and human experience. Custom-coded ray-tracing techniques are employed to generate spherical panorama images, encoding three-dimensional spatial data in the form of two-dimensional images. These images are then processed through computer vision algorithms to generate saliency-maps, which serve as a visual representation of areas most likely to attract human attention based on their visual properties. The maps are subsequently used to weight the vertices of isovists and the visibility graph, placing greater emphasis on areas with high saliency. Compared to traditional methods, our weighted visibility analysis introduces an additional layer of information density by assigning different weights or importance levels to various aspects within the field of view. This extends general space syntax measures to provide a more nuanced understanding of visibility patterns that better reflect the dynamics of human attention and perception. Furthermore, by drawing parallels to traditional isovist and VGA analysis, our weighted approach emphasizes a crucial distinction, which has been pointed out by Ervin and Steinitz: the difference between what is possible to see and what is likely to be seen. Therefore, this paper emphasizes the importance of including surface properties in visibility-based analysis to gain deeper insights into how people interact with their surroundings and to establish a stronger connection with human attention and perception.

Keywords: space syntax, visibility analysis, isovist, visibility graph, visual features, human perception, saliency detection, raytracing, spherical images

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Authors: Noor Akhmazillah Fauzi, Mohammed Mehdi Farid, Filipa V. Silva

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The aim of this paper is to investigate if different concentration of Manuka honey (as a model food) has a major influence on the inactivation of Saccharomyces cerevisiae (as the testing microorganism) after subjecting it to HPP. Honey samples with different sugar concentrations (20, 30, 40, 50, 60 and 70 °Brix) were prepared aseptically using sterilized distilled water. No dilution of honey was made for the 80 °Brix sample. For the 0 °Brix sample (control), sterilized distilled water was used. Thermal treatment at 55 °C for 10 min (conventionally applied in honey pasteurisation in industry) was carried out for comparison purpose. S. cerevisiae cell numbers in honey samples were established before and after each HPP and thermal treatment. The number of surviving cells was determined after a proper dilution of the untreated and treated samples by the viable plate count method. S. cerevisiae cells, in different honey concentrations (0 to 80 °Brix), subjected to 600 MPa (at ambient temperature) showed an increasing resistance to inactivation with °Brix. A significant correlation (p < 0.05) between cell reduction and °Brix was found. Cell reduction in high pressure-treated samples varied linearly with °Brix (R2 > 0.9), confirming that the baroprotective effect of the food is due to sugar content. This study has practical implications in establishing efficient process design for commercial manufacturing of high sugar food products and on the potential use of HPP for such products.

Keywords: high pressure processing, honey, Saccharomyces cerevisiae, °Brix

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Authors: Ragini Trehan, D.K. Srivastava

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In the post-planning era, India’s fiscal transfers from the central to state governments are solely determined by the Finance Commissions (FCs). While in some of the well-established federations such as Australia, Canada, and Germany, equalization serves as the guiding principle of fiscal transfers and is constitutionally mandated, in India, it is not explicitly mandated, and FCs attempt to implement it indirectly by a combination of a formula-based share in the divisible pool of central taxes supplemented by a set of grants. In this context, it is important to measure the extent of equalization that is achieved through FC transfers with a view to improving the design of such transfers. This study uses an index-based methodology for measuring the degree of equalization achieved through FC-transfers covering the period from FC12 to the first year of FC15 spanning from 2005-06 to 2020-21. The ‘Index of Equalization’ shows that the extent of equalization has remained low in the range of 30% to 37% for the four Commission periods under review. The highest degree of equalization at 36.7% was witnessed in the FC12 period and the lowest equalization at 29.5% was achieved during the FC15(1) period. The equalizing efficiency of recommended transfers also shows a consistent fall from 11.4% in the FC12 period to 7.5% by the FC15 (1) period. Further, considering progressivity in fiscal transfers as a special case of equalizing transfers, this study shows that the scheme of per capita total transfers when determined using the equalization approach is more progressive and is characterized by minimal deviations as compared to the profile of transfers recommended by recent FCs.

Keywords: fiscal transfers, index of equalization, equalizing efficiency, fiscal capacity, expenditure needs, finance Commission, tax effort

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Authors: Nicola G. G. Cecca

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In Italian IPSSEOAs, high schools that give a vocational education to students that will work in the field of Enogastronomy and Hotel Management, the course of Food Science allows the students to start and see food as a mixture of substances that they will transform during their profession. These substances are characterized not only by a chemical composition but also by a molecular structure that makes them nutritionally active. But the increasing number of new products proposed by Food Industry, the modern techniques of production and transformation, the innovative preparations required by customers have made many information reported in the most wide spread Food Science textbooks not up-to-date or too poor for the people who will work in catering sector. Often Authors offer information aged to Bohr’s Atomic Model and to the ‘Octet Rule’ proposed by G.N. Lewis to describe the Chemical Bond, without giving any reference to new as Orbital Atomic Model and Molecular Orbital Theory that, in the meantime, start to be old themselves. Furthermore, this antiquated information precludes an easy understanding of a wide range of properties of nutritive substances and many reactions in which the food constituents are involved. In this paper, our attention is pointed out to use GEOMAG™ to represent the dynamics with which the chemical bond is formed during the synthesis of the molecules. GEOMAG™ is a toy, produced by the Swiss Company Geomagword S.A., pointed to stimulate in children, aged between 6-10 years, their fantasy and their handling ability and constituted by metallic spheres and metallic magnetic bars coated by coloured plastic materials. The simulation carried out with GEOMAG™ is based on the similitude existing between the Coulomb’s force and the magnetic attraction’s force and in particular between the formulae with which they are calculated. The electrostatic force (F in Newton) that allows the formation of the chemical bond can be calculated by mean Fc = kc q1 q2/d2 where: q1 e q2 are the charge of particles [in Coulomb], d is the distance between the particles [in meters] and kc is the Coulomb’s constant. It is surprising to observe that the attraction’s force (Fm) acting between the magnetic extremities of GEOMAG™ used to simulate the chemical bond can be calculated in the same way by using the formula Fm = km m1 m2/d2 where: m1 e m2 represent the strength of the poles [A•m], d is the distance between the particles [m], km = μ/4π in which μ is the magnetic permeability of medium [N•A-2]. The magnetic attraction can be tested by students by trying to keep the magnetic elements of GEOMAG™ separate by hands or trying to measure by mean an appropriate dynamometric system. Furthermore, by using a dynamometric system to measure the magnetic attraction between the GEOMAG™ elements is possible draw a graphic F=f(d) to verify that the curve obtained during the simulation is very similar to that one hypnotized, around the 1920’s by Linus Pauling to describe the formation of H2+ in according with Molecular Orbital Theory.

Keywords: chemical bond, molecular orbital theory, magnetic attraction force, GEOMAG™

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Authors: Anna Ivanovskaya, Alexandra E. L. Overland, Swetha Chandrasekaran, Buddhinie S. Jayathilake

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Iron-based redox flow batteries (IRFB) are promising for grid-scale storage because of their low-cost and environmental safety. Earth-abundant iron can enable affordable grid-storage to meet DOE’s target material cost <$20/kWh and levelized cost for storage $0.05/kWh. In conventional redox flow batteries, energy is stored in external electrolyte tanks and electrolytes are circulated through the cell units to achieve electrochemical energy conversions. However, IRFBs are hybrid battery systems where metallic iron deposition at the negative side of the battery controls the storage capacity. This adds complexity to the design of a porous structure of 3D-electrodes to achieve a desired high storage capacity. In addition, there is a need to control parasitic hydrogen evolution reaction which accompanies the metal deposition process, increases the pH, lowers the energy efficiency, and limits the durability. To achieve sustainable operation of IRFBs, electrolyte pH, which affects the solubility of reactants and the rate of parasitic reactions, needs to be dynamically readjusted. In the present study we explore the impact of complexing agents on maintaining solubility of the reactants and find the optimal electrolyte conditions and battery operating regime, which are specific for IRFBs with additives, and demonstrate the robust operation.

Keywords: flow battery, iron-based redox flow battery, IRFB, energy storage, electrochemistry

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Authors: Soumya Bhattacharjya, Avinandan Sahoo, Gaurav Datta

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Wind fragility analysis of chimney is often carried out disregarding temperature effect. However, the combined effect of wind and temperature is the most critical limit state for chimney design. Hence, in the present paper, an efficient fragility analysis for concrete chimney is explored under combined wind and temperature effect. Wind time histories are generated by Davenports Power Spectral Density Function and using Weighed Amplitude Wave Superposition Technique. Fragility analysis is often carried out in full Monte Carlo Simulation framework, which requires extensive computational time. Thus, in the present paper, an efficient adaptive metamodelling technique is adopted to judiciously approximate limit state function, which will be subsequently used in the simulation framework. This will save substantial computational time and make the approach computationally efficient. Uncertainty in wind speed, wind load related parameters, and resistance-related parameters is considered. The results by the full simulation approach, conventional metamodelling approach and proposed adaptive metamodelling approach will be compared. Effect of disregarding temperature in wind fragility analysis will be highlighted.

Keywords: adaptive metamodelling technique, concrete chimney, fragility analysis, stochastic extreme wind load, temperature effect

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Authors: V. Samulionis, J. Banys, A. Sánchez-Ferrer

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Inorganic nanoparticles are used for fabrication of various composites based on polymer materials because they exhibit a good homogeneity and solubility of the composite material. Multifunctional materials based on composites of a polymer containing inorganic nanotubes are expected to have a great impact on industrial applications in the future. An emerging family of such composites are polyurea elastomers with inorganic MoS2 nanotubes or MoSI nanowires. Polyurea elastomers are a new kind of materials with higher performance than polyurethanes. The improvement of mechanical, chemical and thermal properties is due to the presence of hydrogen bonds between the urea motives which can be erased at high temperature softening the elastomeric network. Such materials are the combination of amorphous polymers above glass transition and crosslinkers which keep the chains into a single macromolecule. Polyurea exhibits a phase separated structure with rigid urea domains (hard domains) embedded in a matrix of flexible polymer chains (soft domains). The elastic properties of polyurea can be tuned over a broad range by varying the molecular weight of the components, the relative amount of hard and soft domains, and concentration of nanoparticles. Ultrasonic methods as non-destructive techniques can be used for elastomer composites characterization. In this manner, we have studied the temperature dependencies of the longitudinal ultrasonic velocity and ultrasonic attenuation of these new polyurea elastomers and composites with inorganic nanoparticles. It was shown that in these polyurea elastomers large ultrasonic attenuation peak and corresponding velocity dispersion exists at 10 MHz frequency below room temperature and this behaviour is related to glass transition Tg of the soft segments in the polymer matrix. The relaxation parameters and Tg depend on the segmental molecular weight of the polymer chains between crosslinking points, the nature of the crosslinkers in the network and content of MoS2 nanotubes or MoSI nanowires. The increase of ultrasonic velocity in composites modified by nanoparticles has been observed, showing the reinforcement of the elastomer. In semicrystalline polyurea elastomer matrices, above glass transition, the first order phase transition from quasi-crystalline to the amorphous state has been observed. In this case, the sharp ultrasonic velocity and attenuation anomalies were observed near the transition temperature TC. Ultrasonic attenuation maximum related to glass transition was reduced in quasicrystalline polyureas indicating less influence of soft domains below TC. The first order phase transition in semicrystalline polyurea elastomer samples has large temperature hysteresis (> 10 K). The impact of inorganic MoS2 nanotubes resulted in the decrease of the first order phase transition temperature in semicrystalline composites.

Keywords: inorganic nanotubes, polyurea elastomer composites, ultrasonic velocity, ultrasonic attenuation

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Authors: Jasim Azhar, Morten Gjerde

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A city’s space is comprehended as a phenomenon that emerges from the ongoing negotiation between the constructed environment, urban processes, and bodily experience. Many spaces do not represent a static notion but are continually challenged and reconstituted. The ability to recognize those leftover spaces in the urban context is an integral part of an urban redevelopment process, where structured and layered approaches become useful in understanding to transform these spaces into places. Contemporary urban leftover spaces exist as a result of several factors and are present in every major city that often disrupts the flow of districts by creating visually unappealing places. These spaces can be designed, transformed and integrated so as to achieve environmental gains and social preferences. The paper explores how those small changes in visual quality of an urban leftover spaces in Wellington city influence a person’s experience significantly and its potential usage. These spaces can be seen as a catalyst for a change through an ecological sustainability’s framework. A creative and flexible design would lead to psychologically healthy places by improving the image of a city from within. The qualitative research is undertaken through the visual preference studies which will inform the planning initiatives by knowing what people feel about those visual changes in these leftover spaces. Those visual preferences can guide behavior and the emotional responses of different users for the redesign of those spaces with the meaningful attributes. The research is driven by the hypothesis that if the attributes are made visible, the likelihood of stimulating the interest of users should increase.

Keywords: leftover spaces, visual preferences, tactical urbanism, ecological sustainability

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Authors: P. Suresh, K. Gunasekaran, R. Thanigaivelan

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Radio frequency identification (RFID) technology has been attracting considerable attention with the expectation of improved supply chain visibility for consumer goods, apparel, and pharmaceutical manufacturers, as well as retailers and government procurement agencies. It is also expected to improve the consumer shopping experience by making it more likely that the products they want to purchase are available. Recent announcements from some key retailers have brought interest in RFID to the forefront. A modified K- Means Cluster based Heuristic approach, Hybrid Genetic Algorithm (GA) - Simulated Annealing (SA) approach, Hybrid K-Means Cluster based Heuristic-GA and Hybrid K-Means Cluster based Heuristic-GA-SA for Open Loop Supply Chain Network problem are proposed. The study incorporated uniform crossover operator and combined crossover operator in GAs for solving open loop supply chain distribution network problem. The algorithms are tested on 50 randomly generated data set and compared with each other. The results of the numerical experiments show that the Hybrid K-means cluster based heuristic-GA-SA, when tested on 50 randomly generated data set, shows superior performance to the other methods for solving the open loop supply chain distribution network problem.

Keywords: RFID, supply chain distribution network, open loop supply chain, genetic algorithm, simulated annealing

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Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

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Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

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Authors: Amir Asadi, Karim Habib, Robert J. Moon, Kyriaki Kalaitzidou

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There has been considerable interest in cellulose nanomaterials (CN) as polymer and polymer composites reinforcement due to their high specific modulus and strength, low density and toxicity, and accessible hydroxyl side groups that can be readily chemically modified. The focus of this study is making lightweight composites for better fuel efficiency and lower CO2 emission in auto industries with no compromise on mechanical performance using a scalable technique that can be easily integrated in sheet molding compound (SMC) manufacturing lines. Light weighting will be achieved by replacing part of the heavier components, i.e. glass fibers (GF), with a small amount of cellulose nanocrystals (CNC) in short GF/epoxy composites made using SMC. CNC will be introduced as coating of the GF rovings prior to their use in the SMC line. The employed coating method is similar to the fiber sizing technique commonly used and thus it can be easily scaled and integrated to industrial SMC lines. This will be an alternative route to the most techniques that involve dispersing CN in polymer matrix, in which the nanomaterials agglomeration limits the capability for scaling up in an industrial production. We have demonstrated that incorporating CNC as a coating on GF surface by immersing the GF in CNC aqueous suspensions, a simple and scalable technique, increases the interfacial shear strength (IFSS) by ~69% compared to the composites produced by uncoated GF, suggesting an enhancement of stress transfer across the GF/matrix interface. As a result of IFSS enhancement, incorporation of 0.17 wt% CNC in the composite results in increases of ~10% in both elastic modulus and tensile strength, and 40 % and 43 % in flexural modulus and strength respectively. We have also determined that dispersing 1.4 and 2 wt% CNC in the epoxy matrix of short GF/epoxy SMC composites by sonication allows removing 10 wt% GF with no penalty on tensile and flexural properties leading to 7.5% lighter composites. Although sonication is a scalable technique, it is not quite as simple and inexpensive as coating the GF by passing through an aqueous suspension of CNC. In this study, the above findings are integrated to 1) investigate the effect of CNC content on mechanical properties by passing the GF rovings through CNC aqueous suspension with various concentrations (0-5%) and 2) determine the optimum ratio of the added CNC to the removed GF to achieve the maximum possible weight reduction with no cost on mechanical performance of the SMC composites. The results of this study are of industrial relevance, providing a path toward producing high volume lightweight and mechanically enhanced SMC composites using cellulose nanomaterials.

Keywords: cellulose nanocrystals, light weight polymer-matrix composites, mechanical properties, sheet molding compound (SMC)

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Authors: Mirvat Shamseddine, Issam Lakkis

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We present an efficient, three-dimensional parallel multi-scale Direct Simulation Monte Carlo (DSMC) algorithm for the simulation of unsteady rarefied gas flows in micro/nanosystems. The algorithm employs a novel spatiotemporal adaptivity scheme. The scheme performs a fully dynamic multi-level grid adaption based on the gradients of flow macro-parameters and an automatic temporal adaptation. The computational domain consists of a hierarchical octree-based Cartesian grid representation of the flow domain and a triangular mesh for the solid object surfaces. The hybrid mesh, combined with the spatiotemporal adaptivity scheme, allows for increased flexibility and efficient data management, rendering the framework suitable for efficient particle-tracing and dynamic grid refinement and coarsening. The parallel algorithm is optimized to run DSMC simulations of strongly unsteady, non-equilibrium flows over multiple cores. The presented method is validated by comparing with benchmark studies and then employed to improve the design of micro-scale hotwire thermal sensors in rarefied gas flows.

Keywords: DSMC, oct-tree hierarchical grid, ray tracing, spatial-temporal adaptivity scheme, unsteady rarefied gas flows

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Authors: Mary Ann Cristine R. Olgado

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Diversity in the classroom might make it difficult to promote individualized learning, but differentiated instruction that caters to students' various learning preferences may prove to be beneficial. Hence, this study examined the effectiveness of Hybrid-Differentiated Mathematics Instruction (HDMI) in improving the students’ academic performance in Mathematics. It employed the quasi-experimental research design by using a comparative analysis of the two variables: the experimental and control groups. The learning styles of the students were identified using the Grasha-Riechmann Student Learning Style Scale (GRSLSS), which served as the basis for designing differentiated action plans in Mathematics. In addition, adapted survey questionnaires, pre-tests, and post-tests were used to gather information and were analyzed using descriptive and correlational statistics to find the relationship between variables. The experimental group received differentiated instruction for a month, while the control group received traditional teaching instruction. The study found that Hybrid-Differentiated Mathematics Instruction (HDMI) improved the academic performance of Grade 11-TVL students, with the experimental group performing better than the control group. This program has effectively tailored the teaching methods to meet the diverse learning needs of the students, fostering and enhancing a deeper understanding of mathematical concepts in Statistics & Probability, both within and beyond the classroom.

Keywords: differentiated instruction, hybrid, learning styles, academic performance

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Authors: Marcin Zieliński, Marcin Dębowski, Mirosław Krzemieniewski

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This publication presents a device designed for mechanical fragmentation of plant substrate before methane fermentation. The device is equipped with a perforated rotary cylindrical drum coated with a thermal layer, connected to a substrate feeder and driven by a motoreducer. The drum contains ball- or cylinder-shaped weights of different diameters, while its interior is mounted with lateral permanent magnets with an attractive force ranging from 100 kg to 2 tonnes per m2 of the surface. Over the perforated rotary drum, an infrared radiation generator is mounted, producing 0.2 kW to 1 kW of infrared radiation per 1 m2 of the perforated drum surface. This design reduces the energy consumption required for the biomass destruction process by 10-30% in comparison to the conventional ball mill. The magnetic field generated by the permanent magnets situated within the perforated rotary drum promotes this process through generation of free radicals that act as powerful oxidants, accelerating the decomposition rate. Plant substrate shows increased susceptibility to biodegradation when subjected to magnetic conditioning, reducing the time required for biomethanation by 25%. Additionally, the electromagnetic radiation generated by the radiator improves substrate destruction by 10% and the efficiency of the process. The magnetic field and the infrared radiation contribute synergically to the increased efficiency of destruction and conversion of the substrate.

Keywords: biomass pretreatment, mechanical fragmentation, biomass, methane fermentation

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Authors: Saiyeed Jakaria Baksh Imran

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The earth is being endangered by many of the climate related issues today. The most serious issue for the world today is the global warming. Increase in Greenhouse gas (GHG) emissions post-industrial revolution period is the prime reason for global warming. Shipping is the fifth largest GHG emitting sector worldwide. The key reason for this is because, over 90% of the world trade is conducted through ocean as the ocean alone covers 70% of the earth surface. While the countries continue to develop, trade and commerce continue to increase between them simultaneously. However, there is no sign of reduction in GHG emission from shipping because of many concerned issues. Firstly, there is technological barrier for which ships cannot just become environment friendly immediately. Secondly, there is no alternative fuel available as well. Thirdly, there is no proper mechanism to measure how much ships emit as emission from ships vary according to the size, engine type and loading capacity of ships. The International Maritime Organization (IMO) being the governing body of the international shipping has implemented MARPOL Annex VI. However, the policy alone is not enough unless there is a proper data available regarding ship emissions, which the IMO is yet to figure out. This paper will present a critical analysis of existing IMO policies such as the Energy Efficiency Design Index (EEDI), Ship Energy Efficiency Management Plan (SEEMP), Data Collection System (SEEMP) and the IMO’s Initial Strategy on Reduction of Greenhouse Gas emissions from shipping. Also, the challenges exist in implementing such policies have been presented in the paper.

Keywords: GHG, IMO, EEDI, SEEMP, DCS, greenhouse gas, decarbonization, shipping

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Authors: Ncoza Dlova, Tivani Mashamba-Thompson

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Garcinia livingstonei (Clusiaceae) extracts, morelloflavone- 7″- sulphate and sargaol were shown to be effective against hyper-pigmentation through inhibition of tyrosinase enzyme, in vitro . The aim of this study is to elucidate the structural mechanism through which morelloflavone- 7″- sulphate and sargaol binds human tyrosinase. Implementing a homology model to construct a tyrosinase model using the crystal structure of a functional unit from Octopus hemocyanin (PDB: 1JS8) as a reference template enabled us to create a human tyrosinase model. Molecular dynamics and binding free energy calculations were optimized to enable molecular dynamics simulation of the copper dependent inhibitors. Results show the importance of the hydrogen bond formation morelloflavone- 7″- sulphate and sargaol between compound and active site residues. Both complexes demonstrated the metallic coordination between compound and arginine residue as well as copper ions within the active site. The comprehensive molecular insight gained from this study should be vital in understanding the binding mechanism morelloflavone- 7″- sulphate and sargaol. Moreover, these results will assist in the design of novel of metal ion dependent enzyme inhibitors as potential anti-hyper-pigmentation disorder therapies.

Keywords: hyper-pigmentation disorders, dyschromia African skin, morelloflavone- 7″- sulphate, sagoal

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Iyabo Aremu

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The role of the teacher in stirring a qualitative and distinctive knowledge-driven and value-laden environment with modern teaching practices cannot be over accentuated. In spite of the myriad advantages the use of Information and Communication Technology (ICT) promises, many teachers are still at the rear of this archetypical transition. These teachers; notable forces needed to elicit positive academic performances of students of higher learning are ill-equipped for the task. In view of this, the research work sought to assess how teachers have been able to effectively apply ICT tools to improve students’ academic performance in the higher institution and to evaluate the challenges faced by teachers in using these tools. Thus, the research adopted descriptive survey research design and involved a sample of 25 lecturers from five schools in the study area: Adeniran Ogunsanya College of Education (AOCOED). The barrier to Teachers’ Use of ICT Questionnaire (BTUICTQ) was used to gather data from these respondents. The data gathered was tested with chi-square at 0.05 level of significance. The results revealed that the perception and attitude of teachers towards the use of ICT is not favourable. It was also discovered that teachers suffer from gaps in ICT knowledge and skills. Finally, the research showed that lack of training and inadequate support is a major challenge teacher contend with. The study recommended that teachers should be given adequate training and support and that teachers’ unrestricted access to ICT gadgets should be ensured by schools.

Keywords: ICT, teachers, AOCOED, academic performance

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Teerapon Pirom, Ura Pancharoen

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Amoxicillin is an antibiotic which is widely used to treat various infections in both human beings and animals. However, when amoxicillin is released into the environment, it is a major problem. Amoxicillin causes bacterial resistance to these drugs and failure of treatment with antibiotics. Liquid membrane is of great interest as a promising method for the separation and recovery of the target ions from aqueous solutions due to the use of carriers for the transport mechanism, resulting in highly selectivity and rapid transportation of the desired metal ions. The simultaneous processes of extraction and stripping in a single unit operation of liquid membrane system are very interesting. Therefore, it is practical to apply liquid membrane, particularly the HFSLM for industrial applications as HFSLM is proved to be a separation process with lower capital and operating costs, low energy and extractant with long life time, high selectivity and high fluxes compared with solid membranes. It is a simple design amenable to scaling up for industrial applications. The extraction and recovery for (Amoxicillin) through the hollow fiber supported liquid membrane (HFSLM) using aliquat336 as a carrier were explored with the experimental data. The important variables affecting on transport of amoxicillin viz. extractant concentration and operating time were investigated. The highest AMOX- extraction percentages of 85.35 and Amoxicillin stripping of 80.04 were achieved with the best condition at 6 mmol/L [aliquat336] and operating time 100 min. The extraction reaction order (n) and the extraction reaction rate constant (kf) were found to be 1.00 and 0.0344 min-1, respectively.

Keywords: aliquat336, amoxicillin, HFSLM, kinetic

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Authors: I. P. Ogbuewu, I. F. Etuk, V. U. Odoemelam, I. C. Okoli, M. U. Iloeje

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The effect of dietary ginger rhizome meal on libido and semen characteristics of post-pubertal rabbit bucks was investigated in an experiment that lasted for 12 weeks. Thirty-six post-pubertal bucks were randomly assigned to 4 dietary groups of 9 rabbits each in a completely randomized design. Four experimental diets were formulated to contain ginger rhizome meal at 0 g/kg feed (BT0), 5g/kg feed (BT5), 10 g/kg feed (BT10), and 15g/kg feed (BT15) were fed ad libitum to the experimental animals. Results revealed that semen colour changed from cream milky to milky. Data on semen pH and sperm concentration were similar (p>0.05) among the dietary groups. Semen volume for the bucks in BT0 (0.64 mL) and BT5 (0.60 mL) groups were significantly (p<0.05) higher than those in BT10 (0.44 mL) and BT15 (0.46 mL) groups. Total spermatozoa concentration value was significantly (p<0.05) higher in BT0 and BT5 groups than those in BT10 and BT15 groups. Sperm motility and percent live sperm declined (p<0.05) progressively among the treatment groups. Percent dead sperm were significantly (p<0.05) lower for bucks in BT0 group than in BT10 and BT15 groups. Reaction time had a dose-dependent increase; however, the observed difference was not significant (p>0.05). These results indicate that the inclusion of ginger rhizome meal at 5-15g per kg feed in ration for post-pubertal rabbit bucks could cause mild depressive effect on semen production and quality.

Keywords: rabbits, semen, libido, ginger

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Authors: Felsy J. Sandi

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There is a potential of growth in the spa industry due to the influx of domestic and international tourist coming to Sabah, Malaysia. It is a good opportunity to venture into this industry for the country’s economic future growth, and therefore, it is essential for this area to be researched. Being one of the fastest growing industries in the world, has led to enormous challenges, which need to be addressed. Malaysia is also riding with this phenomenon. The President of the Malaysian Association of Wellness and Spa stated that the misconception about the Spa industry’s image, especially amongst the elderly is the biggest challenge faced by the industry, as they perceived the spa industry is equivalent to a prostitution center. Therefore, the objective of this study is to explore the issue by analyzing whether image can be added in the theory of planned behavior to better understand the consumer’s intention to visit, in the spa context. The Theory of Planned Behavior by Ajzen, a theory or model in predicting intention, has three constructs; such as Attitude as the first construct, the second construct is Subjective Norm and the third construct is Perceived Behavioral Control. Qualitative research is used as this is an exploratory research. The site of study will be at Jari Jari Spa, located in Kota Kinabalu, the only spa in Sabah that was awarded as the Center of Excellence (CoE) by the Ministry of Tourism and Culture in Malaysia. The findings propose to provide useful information to the relevant stakeholders on ways to approach local customers to convince them to visit the spa and for spa marketers to help them develop and design effective marketing strategies. Future investigation should consider more on the perception and loyalty of the local customers.

Keywords: consumer's perception, image, local customer, spa, visit intention

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Authors: Teresa Azevedo PerdicoúLis, Paulo Lopes Dos Santos

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The conceptualisation of the problem of network optimisation as a noncooperative game sets up a holistic interactive approach that brings together different network features (e.g., com-pressor stations, sources, and pipelines, in the gas context) where the optimisation objectives are different, and a single optimisation procedure becomes possible without having to feed results from diverse software packages into each other. A mathematical model of this type, where independent entities take action, offers the ideal modularity and subsequent problem decomposition in view to design a decentralised algorithm to optimise the operation and management of the network. In a game framework, compressor stations and sources are under-stood as players which communicate through network connectivity constraints–the pipeline model. That is, in a scheme similar to tatonnementˆ, the players appoint their best settings and then interact to check for network feasibility. The devolved degree of network unfeasibility informs the players about the ’quality’ of their settings, and this two-phase iterative scheme is repeated until a global optimum is obtained. Due to network transients, its optimisation needs to be assessed at different points of the control interval. For this reason, the proposed approach to optimisation has two stages: (i) the first stage computes along the period of optimisation in order to fulfil the requirement just mentioned; (ii) the second stage is initialised with the solution found by the problem computed at the first stage, and computes in the end of the period of optimisation to rectify the solution found at the first stage. The liability of the proposed scheme is proven correct on an abstract prototype and three example networks.

Keywords: connectivity matrix, gas network optimisation, large-scale, noncooperative game, system decomposition

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Authors: Rajkumar Ghosh

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Fly ash, a byproduct of coal combustion, has become a prevalent environmental concern due to its potential impact on both groundwater quality and local climate change. This study aims to provide an in-depth analysis of the various mechanisms through which fly ash contaminates groundwater, as well as the possible consequences of this contamination on local climate change. The presence of fly ash in groundwater not only poses a risk to human health but also has the potential to influence local climate change through complex interactions. Although fly ash has various applications in construction and other industries, improper disposal and lack of containment measures have led to its infiltration into groundwater systems. Through a comprehensive review of existing literature and case studies, the interactions between fly ash and groundwater systems, assess the effects on hydrology, and discuss the implications for the broader climate. This section reviews the pathways through which fly ash enters groundwater, including leaching from disposal sites, infiltration through soil, and migration from surface water bodies. The physical and chemical characteristics of fly ash that contribute to its mobility and persistence in groundwater. The introduction of fly ash into groundwater can alter its chemical composition, leading to an increase in the concentration of heavy metals, metalloids, and other potentially toxic elements. The mechanisms of contaminant transport and highlight the potential risks to human health and ecosystems. Fly ash contamination in groundwater may influence the hydrological cycle through changes in groundwater recharge, discharge, and flow dynamics. This section examines the implications of altered hydrology on local water availability, aquatic habitats, and overall ecosystem health. The presence of fly ash in groundwater may have direct and indirect effects on local climate change. The role of fly ash as a potent greenhouse gas absorber and its contribution to radiative forcing. Additionally, investigation of the possible feedback mechanisms between groundwater contamination and climate change, such as altered vegetation patterns and changes in local temperature and precipitation patterns. In this section, potential mitigation and remediation techniques to minimize fly ash contamination in groundwater are analyzed. These may include improved waste management practices, engineered barriers, groundwater remediation technologies, and sustainable fly ash utilization. This paper highlights the critical link between fly ash contamination in groundwater and its potential contribution to local climate change. It emphasizes the importance of addressing this issue promptly through a combination of preventive measures, effective management strategies, and continuous monitoring. By understanding the interconnections between fly ash contamination, groundwater quality, and local climate, towards creating a more resilient and sustainable environment for future generations. The findings of this research can assist policymakers and environmental managers in formulating sustainable strategies to mitigate fly ash contamination and minimize its contribution to climate change.

Keywords: groundwater, climate, sustainable environment, fly ash contamination

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Authors: Lela Pintarić, Iva Rezić, Ana Vrsalović Presečki

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Considering an enormous increase of the use of metal nanoparticles with the exactly defined characteristics, the main goal of this research was to found the optimal and environmental friendly method of their synthesis. The synthesis of the inorganic core-shell nanoparticles was optimized as a model. The core-shell nanoparticles are composed of the enzyme core belted with the metal ions, oxides or salts as a shell. In this research, enzyme urease was the core catalyst and the shell nanoparticle was made of silver. Silver nanoparticles are widespread utilized and some of their common uses are: as an addition to disinfectants to ensure an aseptic environment for the patients, as a surface coating for neurosurgical shunts and venous catheters, as an addition to implants, in production of socks for diabetics and athletic clothing where they improve antibacterial characteristics, etc. Characteristics of synthesized nanoparticles directly depend on of their size, so the special care during this optimization was given to the determination of the size of the synthesized nanoparticles. For the purpose of the above mentioned optimization, sixteen experiments were generated by the Design of Experiments (DoE) method and conducted under various temperatures, with different initial concentration of the silver nitrate and constant concentration of the urease of two separate manufacturers. Synthesized nanoparticles were analyzed by the Nanoparticle Tracking Analysis (NTA) method on Malvern NanoSight NS300. Results showed that the initial concentration of the silver ions does not affect the concentration of the synthesized silver nanoparticles neither their size distribution. On the other hand, temperature of the experiments has affected both of the mentioned values.

Keywords: core-shell nanoparticles, optimization, silver, urease

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