Search results for: polluting industry

Authors: Atabaev I. G., Fayziev Sh. A., Irmatova Sh. K.

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Raw materials with high content of Kalium oxide widely used in ceramic technology for prevention or decreasing of deformation of ceramic goods during drying process and under thermal annealing. Becouse to low melting temperature it is also used to decreasing of the temperature of thermal annealing during fabrication of ceramic goods [1,2]. So called “Porceline or China stones” - quartz-sericite (muscovite) minerals is also can be used for prevention of deformation as the content of Kalium oxide in muscovite is rather high (SiO2, + KAl2[AlSi3O10](OH)2). [3] . To estimation of possibility of use of this mineral for ceramic manufacture, in the presented article the influence of thermal processing on phase and a chemical content of this raw material is investigated. As well as to other ceramic raw materials (kaoline, white burning clays) the basic requirements of the industry to quality of "a porcelain stone» are following: small size of particles, relative high uniformity of disrtribution of components and phase, white color after burning, small content of colorant oxides or chromophores (Fe2O3, FeO, TiO2, etc) [4,5]. In the presented work natural minerale from the Boynaksay deposit (Uzbekistan) is investigated. The samples was mechanically polished for investigation by Scanning Electron Microscope. Powder with size of particle up to 63 μm was used to X-ray diffractometry and chemical analysis. The annealing of samples was performed at 900, 1120, 1350oC during 1 hour. Chemical composition of Boynaksay raw material according to chemical analysis presented in the table 1. For comparison the composition of raw materials from Russia and USA are also presented. In the Boynaksay quartz – sericite the average parity of quartz and sericite makes 55-60 and 30-35 % accordingly. The distribution of quartz and sericite phases in raw material was investigated using electron probe scanning electronic microscope «JEOL» JXA-8800R. In the figure 1 the scanning electron microscope (SEM) micrograps of the surface and the distributions of Al, Si and K atoms in the sample are presented. As it seen small granular, white and dense mineral includes quartz, sericite and small content of impurity minerals. Basically, crystals of quartz have the sizes from 80 up to 500 μm. Between quartz crystals the sericite inclusions having a tablet form with radiant structure are located. The size of sericite crystals is ~ 40-250 μm. Using data on interplanar distance [6,7] and ASTM Powder X-ray Diffraction Data it is shown that natural «a porcelain stone» quartz – sericite consists the quartz SiO2, sericite (muscovite type) KAl2[AlSi3O10](OH)2 and kaolinite Al203SiO22Н2О (See Figure 2 and Table 2). As it seen in the figure 3 and table 3a after annealing at 900oC the quartz – sericite contains quartz – SiO2 and muscovite - KAl2[AlSi3O10](OH)2, the peaks related with Kaolinite are absent. After annealing at 1120oC the full disintegration of muscovite and formation of mullite phase Al203 SiO2 is observed (the weak peaks of mullite appears in fig 3b and table 3b). After annealing at 1350oC the samples contains crystal phase of quartz and mullite (figure 3c and table 3с). Well known Mullite gives to ceramics high density, abrasive and chemical stability. Thus the obtained experimental data on formation of various phases during thermal annealing can be used for development of fabrication technology of advanced materials. Conclusion: The influence of thermal annealing in the interval 900-1350oC on phase composition and structure of quartz-sericite minerale is investigated. It is shown that during annealing the phase content of raw material is changed. After annealing at 1350oC the samples contains crystal phase of quartz and mullite (which gives gives to ceramics high density, abrasive and chemical stability).

Keywords: quartz-sericite, kaolinite, mullite, thermal processing

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Authors: Jana Heimel, Franziska Drescher, Lauren Ugur, Graciela Kuchle

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Sharing platforms are a widely investigated field. However, there is a research gap with a lack of focus on ‘real’ (non-profit-orientated) sharing platforms. The research project addresses this gap by conducting an empirical study on a private peer-to-peer (P2P) network to investigate cooperative behavior from a socio-psychological perspective. In recent years the conversion from possession to accessing is increasingly influencing different sectors, particularly the traveling industry. The number of people participating in hospitality exchange platforms like Airbnb, Couchsurfing, and Warmshowers (WS) is rapidly growing. WS is an increasingly popular online community that is linking cycling tourists and locals. It builds on the idea of the “sharing economy” as a not-for-profit hospitality network for bicycle tourists. Hosts not only provide a sleeping berth and warm shower free of charge but also offer additional services to their guests, such as cooking and washing clothes for them. According to previous studies, they are motivated by the idea of promoting cultural experience and forming new friendships. Trust and reciprocity are supposed to play major roles in the success of such platforms. The objective of this research project is to analyze the reciprocity behavior within the WS community. Reciprocity is the act of giving and taking among each other. Individuals feel obligated to return a favor and often expect to increase their own chances of receiving future benefits for themselves. Consequently, the drivers that incite giving and taking, as well as the motivation for hosts and guests, are examined. Thus, the project investigates a particular tourism offer that contributes to sustainable tourism by analyzing P2P resp. cyclist-to-cyclist, C2C) tourism. C2C tourism is characterized by special hospitality and generosity. To find out what motivations drive the hosts and which determinants drive the sharing cycling economy, an empirical study has been conducted globally through an online survey. The data was gathered through the WS community and comprised responses from more than 10,000 cyclists around the globe. Next to general information mostly comprising quantitative data on bicycle tourism (year/tour distance, duration and budget), qualitative information on traveling with WS as well as hosting was collected. The most important motivations for a traveler is to explore the local culture, to save money, and to make friends. The main reasons to host a guest are to promote the use of bicycles and to make friends, but also to give back and pay forward. WS members prefer to stay with/host cyclists. The results indicate that C2C tourists share homogenous characteristics and a similar philosophy, which is crucial for building mutual trust. Members of WS are generally extremely trustful. The study promotes an ecological form of tourism by combining sustainability, regionality, health, experience and the local communities' cultures. The empirical evidence found and analyzed, despite evident limitations, enabled us to shed light, especially on the issue of motivations and social capital, and on the functioning of ‘sharing’ platforms. Final research results are intended to promote C2C tourism around the globe to further replace conventional by sustainable tourism.

Keywords: bicycle tourism, homogeneity, reciprocity, sharing economy, trust

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Authors: Wafaa Hasan

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In May of 2022, Palestinian parents in Toronto, Canada, became aware that educators and staff in the Toronto District School Board were attempting to include the International Holocaust and Remembrance Definition of Antisemitism (IHRA) in The Child Abuse and Neglect Policy of the largest school board in Canada, The Toronto District School Board (TDSB). The idea was that if students were to express any form of antisemitism, as defined by the IHRA, then an investigation could follow with Child Protective Services (CPS). That is, the student’s parents could be reported to the state and investigated for custodial rights to their children. The TDSB has set apparent goals for “Decolonizing Pedagogy” (“TDSB Equity Leadership Competencies”), Culturally Responsive and Relevant Practices (CRRP) and inclusive education. These goals promote the centering of colonized, racialized and marginalized voices. CRRP cannot be effective without the application of anti-racist and settler colonial analyses. In order for CRRP to be effective, school boards need a comprehensive understanding of the ways in which the vilification of Palestinians operates through anti-indigenous and white supremacist systems and logic. Otherwise, their inclusion will always be in tension with the inclusion of settler colonial agendas and worldviews. Feminist maternalism frames racial mothering as degenerate (viewing the contributions of racialized students and their parents as products of primitive and violent cultures) and also indirectly inhibits the actualization of the tenets of CRRP and inclusive education through its extensions into the welfare state and public education. The contradiction between the tenets of CRRP and settler colonial systems of erasure and repression is resolved by the continuation of tactics to 1) force assimilation, 2) punish those who push back on that assimilation and 3) literally fragment familial and community structures of racialized students, educators and parents. This paper draws on interdisciplinary (history, philosophy, anthropology) critiques of white feminist “maternalism” from the 19th century onwards in North America and Europe (Jacobs, Weber), as well as “anti-racist education” theory (Dei), and more specifically,” culturally responsive learning,” (Muhammad) and “bandwidth” pedagogy theory (Verschelden) to make its claims. This research contributes to vibrant debates about anti-racist and decolonial pedagogies in public education systems globally. This paper also documents first-hand interviews and experiences of diasporic Palestinian mothers and motherhoods and situates their experiences within longstanding histories of white feminist maternalist (and eugenicist) politics. This informal qualitative data from "participatory conversations" (Swain) is situated within a set of formal interview data collected with Palestinian women in the West Bank (approved by the McMaster University Humanities Research Ethics Board) relating to white feminist maternalism in the peace and dialogue industry.

Keywords: decolonial feminism, maternal feminism, anti-racist pedagogies, settler colonial studies, motherhood studies, pedagogy theory, cultural theory

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Authors: Sarah M. Schoellhammer, Stephen Gibb

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Bureaucracy, in particular, its core element, a formal and stable hierarchy of authority, is proving less and less appropriate under the conditions of today’s knowledge economy. Centralization and formalization were consistently found to hinder innovation, undermining cross-functional collaboration, personal responsibility, and flexibility. With its focus on systematical planning, controlling and monitoring the development of new or improved solutions for customers, even innovation management as a discipline is to a significant extent based on a mechanistic understanding of organizations. The most important drivers of innovation, human creativity, and initiative, however, can be more hindered than supported by central elements of classic innovation management, such as predefined innovation strategies, rigid stage gate processes, and decisions made in management gate meetings. Heterarchy, as an alternative network form of organization, is essentially characterized by its dynamic influence structures, whereby the biggest influence is allocated by the collective to the persons perceived the most competent in a certain issue. Theoretical arguments that the non-hierarchical concept better supports innovation than bureaucracy have been supported by empirical research. These prior studies either focus on the structure and general functioning of non-hierarchical organizations or on their innovativeness, that means innovation as an outcome. Complementing classic innovation management approaches, this work aims to shed light on how innovations are initiated and realized in heterarchies in order to identify alternative solutions practiced under conditions of the post-bureaucratic organization. Through an initial individual case study, which is part of a multiple-case project, the innovation practices of an innovative and highly heterarchical medium-sized company in the German fire engineering industry are investigated. In a pragmatic mixed methods approach media resonance, company documents, and workspace architecture are analyzed, in addition to qualitative interviews with the CEO and employees of the case company, as well as a quantitative survey aiming to characterize the company along five scaled dimensions of a heterarchy spectrum. The analysis reveals some similarities and striking differences to approaches suggested by classic innovation management. The studied heterarchy has no predefined innovation strategy guiding new product and service development. Instead, strategic direction is provided by the CEO, described as visionary and creative. Procedures for innovation are hardly formalized, with new product ideas being evaluated on the basis of gut feeling and flexible, rather general criteria. Employees still being hesitant to take responsibility and make decisions, hierarchical influence is still prominent. Described as open-minded and collaborative, culture and leadership were found largely congruent with definitions of innovation culture. Overall, innovation efforts at the case company tend to be coordinated more through cultural than through formal organizational mechanisms. To better enable innovation in mainstream organizations, responsible practitioners are recommended not to limit changes to reducing the central elements of the bureaucratic organization, formalization, and centralization. The freedoms this entails need to be sustained through cultural coordination mechanisms, with personal initiative and responsibility by employees as well as common innovation-supportive norms and values. These allow to integrate diverse competencies, opinions, and activities and, thus, to guide innovation efforts.

Keywords: bureaucracy, heterarchy, innovation management, values

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Authors: O. Lopez, F. Pedro, A. Tadeu, J. Antonio, A. Coelho

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The future of the railway industry lies in the innovation of lighter, more efficient and more sustainable trains. Weight optimizations in railway vehicles allow reducing power consumption and CO₂ emissions, increasing the efficiency of the engines and the maximum speed reached. Additionally, they reduce wear of wheels and rails, increase the space available for passengers, etc. Among the various systems that integrate railway interiors, the flooring system is one which has greater impact both on passenger safety and comfort, as well as on the weight of the interior systems. Due to the high weight saving potential, relative high mechanical resistance, good acoustic and thermal performance, ease of modular design, cost-effectiveness and long life, the use of new sustainable composite materials and panels provide the latest innovations for competitive solutions in the development of flooring systems. However, one of the main drawbacks of the flooring systems is their relatively poor resistance to point loads. Point loads in railway interiors can be caused by passengers or by components fixed to the flooring system, such as seats and restraint systems, handrails, etc. In this way, they can originate higher fatigue solicitations under service loads or zones with high stress concentrations under exceptional loads (higher longitudinal, transverse and vertical accelerations), thus reducing its useful life. Therefore, to verify all the mechanical and functional requirements of the flooring systems, many physical prototypes would be created during the design phase, with all of the high costs associated with it. Nowadays, the use of virtual prototyping methods by computer-aided design (CAD) and computer-aided engineering (CAE) softwares allow validating a product before committing to making physical test prototypes. The scope of this work was to current computer tools and integrate the processes of innovation, development, and manufacturing to reduce the time from design to finished product and optimise the development of the product for higher levels of performance and reliability. In this case, the mechanical response of several sandwich panels with different cores, polystyrene foams, and composite corks, were assessed, to optimise the weight and the mechanical performance of a flooring solution for railways. Sandwich panels with aluminum face sheets were tested to characterise its mechanical performance and determine the polystyrene foam and cork properties when used as inner cores. Then, a railway flooring solution was fully modelled (including the elastomer pads to provide the required vibration isolation from the car body) and perform structural simulations using FEM analysis to comply all the technical product specifications for the supply of a flooring system. Zones with high stress concentrations are studied and tested. The influence of vibration modes on the comfort level and stability is discussed. The information obtained with the computer tools was then completed with several mechanical tests performed on some solutions, and on specific components. The results of the numerical simulations and experimental campaign carried out are presented in this paper. This research work was performed as part of the POCI-01-0247-FEDER-003474 (coMMUTe) Project funded by Portugal 2020 through COMPETE 2020.

Keywords: cork agglomerate core, mechanical performance, numerical simulation, railway flooring system

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Authors: K. Karapetyan, F. Tkhruni, A. Aghajanyan, T. S. Balabekyan, L. Arstamyan

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Introduction: Globalization of the food supply has created the conditions favorable for the emergence and spread of food-borne and especially dangerous pathogens (EDP) in developing countries. The fresh-cut fruit and vegetable industry is searching for alternatives to replace chemical treatments with biopreservative approaches that ensure the safety of the processed foods product. Antimicrobial compounds of lactic acid bacteria (LAB) possess bactericidal or bacteriostatic activity against intestinal pathogens, spoilage organisms and food-borne pathogens such as Listeria monocytogenes, Staphylococcus aureus and Salmonella. Endemic strains of LAB were isolated. The strains, showing broad spectrum of antimicrobial activity against food spoiling microorganisms, were selected. The genotyping by 16S rRNA sequencing, GS-PCR, RAPD PCR methods showed that they were presented by Lactobacillus rhamnosus109, L.plantarum 65, L.plantarum 66 and Enterococcus faecium 64 species. LAB are deposited in "Microbial Depository Center" (MDC) SPC "Armbiotechnology". Methods: LAB strains were isolated from different dairy products from rural households from the highland regions of Armenia. Serially diluted samples were spread on MRS (Merck, Germany) and hydrolyzed milk agar (1,2 % w/v). Single colonies from each LAB were individually inoculated in liquid MRS medium and incubated at 37oC for 24 hours. Culture broth with biomass was centrifuged at 10,000 g during 20 min for obtaining of cell free culture broth (CFC). The antimicrobial substances from CFC broth were purified by the combination of adsorption-desorption and ion-exchange chromatography methods. Separation of bacteriocins was performed using a HPLC method on "Avex ODS" C18 column. Mass analysis of peptides recorded on the device API 4000 in the electron ionization mode. The spot-on-lawn method on the test culture plated in the solid medium was applied. The antimicrobial activity is expressed in arbitrary units (AU/ml). Results. Purification of CFC broth of LAB allowed to obtain partially purified antimicrobial preparations which contains bacteriocins with broad spectrum of antimicrobial activity. Investigation of their main biochemical properties shown, that inhibitory activity of preparations is partially reduced after treatment with proteinase K, trypsin, pepsin, suggesting a proteinaceous nature of bacteriocin-like substances containing in CFC broth. Preparations preserved their activity after heat treatment (50-121 oC, 20 min) and were stable in the pH range 3–8. The results of SDS PAAG electrophoresis show that L.plantarum 66 and Ent.faecium 64 strains have one bacteriocin (BCN) with maximal antimicrobial activity with approximate molecular weight 2.0-3.0 kDa. From L.rhamnosus 109 two BCNs were obtained. Mass spectral analysis indicates that these bacteriocins have peptide bonds and molecular weight of BCN 1 and BCN 2 are approximately 1.5 kDa and 700 Da. Discussion: Thus, our experimental data shown, that isolated endemic strains of LAB are able to produce bacteriocins with high and different inhibitory activity against broad spectrum of microorganisms of different taxonomic group, such as Salmonella sp., Esherichia coli, Bacillus sp., L.monocytogenes, Proteus mirabilis, Staph. aureus, Ps. aeruginosa. Obtained results proved the perspectives for use of endemic strains in the preservation of foodstuffs. Acknowledgments: This work was realized with financial support of the Project Global Initiatives for Preliferation Prevention (GIPP) T2- 298, ISTC A-1866.

Keywords: antimicrobial activity, bacteriocins, endemic strains, food safety

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Authors: Lynette Lincoln, Sunil S. More

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With the rising demand of sugar used today, it is proposed that world sugar is expected to escalate up to 203 million tonnes by 2021. Hydrolysis of sucrose (table sugar) into glucose and fructose equimolar mixture is catalyzed by β-D-fructofuranoside fructohydrolase (EC 3.2.1.26), commonly called as invertase. For fluid filled center in chocolates, preparation of artificial honey, as a sweetener and especially to ensure that food stuffs remain fresh, moist and soft for longer spans invertase is applied widely and is extensively being used. From an industrial perspective, properties such as increased solubility, osmotic pressure and prevention of crystallization of sugar in food products are highly desired. Screening for invertase does not involve plate assay/qualitative test to determine the enzyme production. In this study, we use a three-step screening strategy for identification of a novel bacterial isolate from soil which is positive for invertase production. The primary step was serial dilution of soil collected from sugarcane fields (black soil, Maddur region of Mandya district, Karnataka, India) was grown on a Czapek-Dox medium (pH 5.0) containing sucrose as the sole C-source. Only colonies with the capability to utilize/breakdown sucrose exhibited growth. Bacterial isolates released invertase in order to take up sucrose, splitting the disaccharide into simple sugars. Secondly, invertase activity was determined from cell free extract by measuring the glucose released in the medium at 540 nm. Morphological observation of the most potent bacteria was examined by several identification tests using Bergey’s manual, which enabled us to know the genus of the isolate to be Bacillus. Furthermore, this potent bacterial colony was subjected to 16S rDNA PCR amplification and a single discrete PCR amplicon band of 1500 bp was observed. The 16S rDNA sequence was used to carry out BLAST alignment search tool of NCBI Genbank database to obtain maximum identity score of sequence. Molecular sequencing and identification was performed by Xcelris Labs Ltd. (Ahmedabad, India). The colony was identified as Bacillus sp. BAB-3434, indicating to be the first novel strain for extracellular invertase production. Molasses, a by-product of the sugarcane industry is a dark viscous liquid obtained upon crystallization of sugar. An enhanced invertase production and optimization studies were carried out by one-factor-at-a-time approach. Crucial parameters such as time course (24 h), pH (6.0), temperature (45 °C), inoculum size (2% v/v), N-source (yeast extract, 0.2% w/v) and C-source (molasses, 4% v/v) were found to be optimum demonstrating an increased yield. The findings of this study reveal a simple screening method of an extracellular invertase from a rapidly growing Bacillus sp., and selection of best factors that elevate enzyme activity especially utilization of molasses which served as an ideal substrate and also as C-source, results in a cost-effective production under submerged conditions. The invert mixture could be a replacement for table sugar which is an economic advantage and reduce the tedious work of sugar growers. On-going studies involve purification of extracellular invertase and determination of transfructosylating activity as at high concentration of sucrose, invertase produces fructooligosaccharides (FOS) which possesses probiotic properties.

Keywords: Bacillus sp., invertase, molasses, screening, submerged fermentation

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Authors: Ana Fonseca, Ana Gouveia, Edgar Ramalho, Rita Henriques, Filipa Figueiredo, João Nunes

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Due to persistent climate pressures, there is a need to find a resilient economic system that is regenerative in nature. Bioeconomy offers the possibility of replacing non-renewable and non-biodegradable materials derived from fossil fuels with ones that are renewable and biodegradable, while a Circular Economy aims at sustainable and resource-efficient operations. The term "Circular Bioeconomy", which can be summarized as all activities that transform biomass for its use in various product streams, expresses the interaction between these two ideas. Portugal has a very favourable context to promote a Circular Bioeconomy due to its variety of climates and ecosystems, availability of biologically based resources, location, and geomorphology. Recently, there have been political and legislative efforts to develop the Portuguese Circular Bioeconomy. The Action Plan for a Sustainable Bioeconomy, approved in 2021, is composed of five axes of intervention, ranging from sustainable production and the use of regionally based biological resources to the development of a circular and sustainable bioindustry through research and innovation. However, as some statistics show, Portugal is still far from achieving circularity. According to Eurostat, Portugal has circularity rates of 2.8%, which is the second lowest among the member states of the European Union. Some challenges contribute to this scenario, including sectorial heterogeneity and fragmentation, prevalence of small producers, lack of attractiveness for younger generations, and absence of implementation of collaborative solutions amongst producers and along value chains.Regarding the Portuguese industrial sector, there is a tendency towards complex bureaucratic processes, which leads to economic and financial obstacles and an unclear national strategy. Together with the limited number of incentives the country has to offer to those that pretend to abandon the linear economic model, many entrepreneurs are hesitant to invest the capital needed to make their companies more circular. Absence of disaggregated, georeferenced, and reliable information regarding the actual availability of biological resources is also a major issue. Low literacy on bioeconomy among many of the sectoral agents and in society in general directly impacts the decisions of production and final consumption. The WinBio project seeks to outline a strategic approach for the management of weaknesses/opportunities in the technology transfer process, given the reality of the territory, through road mapping and national and international benchmarking. The developed work included the identification and analysis of agents in the interior region of Portugal, natural endogenous resources, products, and processes associated with potential development. Specific flow of biological wastes, possible value chains, and the potential for replacing critical raw materials with bio-based products was accessed, taking into consideration other countries with a matured bioeconomy. The study found food industry, agriculture, forestry, and fisheries generate huge amounts of waste streams, which in turn provide an opportunity for the establishment of local bio-industries powered by this biomass. The project identified biological resources with potential for replication and applicability in the Portuguese context. The richness of natural resources and potentials known in the interior region of Portugal is a major key to developing the Circular Economy and sustainability of the country.

Keywords: circular bioeconomy, interior region of portugal, regional development., public policy

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Authors: Nahid Nariman

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The prosperity of any nation depends on its ability to use human potential, in particular, to offer an education that builds learners' competencies to become effective workforce participants and true citizens of the world. Ever since the Second World War, the United States has been a dominant player in the world politically, economically, socially, and culturally. The rapid rise of technological advancement and consumer technologies have made it clear that science, technology, engineering, and math (STEM) play a crucial role in today’s world economy. Exploring the top qualities demanded from new hires in the industry—i.e., problem-solving skills, teamwork, dependability, adaptability, technical and communication skills— sheds light on the kind of path that is needed for a successful educational system to effectively support STEM. The focus of 21st century education has been to build student competencies by preparing them to acquire and apply knowledge, to think critically and creatively, to competently use information, be able to work in teams, to demonstrate intellectual and moral values as well as cultural awareness, and to be able to communicate. Many educational reforms pinpoint various 'ideal' pathways toward STEM that educators, policy makers, and business leaders have identified for educating the workforce of tomorrow. This study will explore how problem-based learning (PBL), an instructional strategy developed in the medical field and adopted with many successful results in K-12 through higher education, is the proper approach to stimulate underrepresented high school students' interest in pursuing STEM careers. In the current study, the effect of a problem-based STEM model on students' attitudes and career interests was investigated using qualitative and quantitative methods. The participants were 71 low-income, native Hawaiian high school students who would be first-generation college students. They were attending a summer STEM camp developed as the result of a collaboration between the University of Hawaii and the Upward Bound Program. The project, funded by the National Science Foundation's Innovative Technology Experiences for Students and Teachers (ITEST) program, used PBL as an approach in challenging students to engage in solving hands-on, real-world problems in their communities. Pre-surveys were used before camp and post-surveys on the last day of the program to learn about the implementation of the PBL STEM model. A Career Interest Questionnaire provided a way to investigate students’ career interests. After the summer camp, a representative selection of students participated in focus group interviews to discuss their opinions about the PBL STEM camp. The findings revealed a significantly positive increase in students' attitudes towards STEM disciplines and STEM careers. The students' interview results also revealed that students identified PBL to be an effective form of instruction in their learning and in the development of their 21st-century skills. PBL was acknowledged for making the class more enjoyable and for raising students' interest in STEM careers, while also helping them develop teamwork and communication skills in addition to scientific knowledge. As a result, the integration of PBL and a STEM learning experience was shown to positively affect students’ interest in STEM careers.

Keywords: problem-based learning, science education, STEM, underrepresented students

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Authors: Benjamin Thomas Greer, Grace Cotulla, Mandy Johnson

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Human trafficking is one of the fastest growing international crimes and human rights violations in the world. The United States Department of State (State Department) approximates some 800,000 to 900,000 people are annually trafficked across sovereign borders, with approximately 14,000 to 17,500 of these people coming into the United States. Today’s slavery is conducted by unscrupulous individuals who are often connected to organized criminal enterprises and transnational gangs, extracting huge monetary sums. According to the International Labour Organization (ILO), human traffickers collect approximately $32 billion worldwide annually. Surpassed only by narcotics dealing, trafficking of humans is tied with illegal arms sales as the second largest criminal industry in the world and is the fastest growing field in the 21st century. Perpetrators of this heinous crime abound. They are not limited to single or “sole practitioners” of human trafficking, but rather, often include Transnational Criminal Organizations (TCO), domestic street gangs, labor contractors, and otherwise seemingly ordinary citizens. Monetary gain is being elevated over territorial disputes and street gangs are increasingly operating in a collaborative effort with TCOs to further disguise their criminal activity; to utilizing their vast networks, in an attempt to avoid detection. Traffickers rely on a network of clandestine routes to sell their commodities with impunity. As law enforcement agencies seek to retard the expansion of transnational criminal organization’s entry into human trafficking, it is imperative that they develop reliable trafficking mapping of known exploitative routes. In a recent report given to the Mexican Congress, The Procuraduría General de la República (PGR) disclosed, from 2008 to 2010 they had identified at least 47 unique criminal networking routes used to traffic victims and that Mexico’s estimated domestic victims number between 800,000 adults and 20,000 children annually. Designing a reliable mapping system is a crucial step to effective law enforcement response and deploying a successful victim support system. Creating this mapping analytic is exceedingly difficult. Traffickers are constantly changing the way they traffic and exploit their victims. They swiftly adapt to local environmental factors and react remarkably well to market demands, exploiting limitations in the prevailing laws. This article will highlight how human trafficking has become one of the fastest growing and most high profile human rights violations in the world today; compile current efforts to map and illustrate trafficking routes; and will demonstrate how the proprietary analytical mapping analysis of point-source and destination-source mapping can help local law enforcement, governmental agencies and victim services providers effectively respond to the type and nature of trafficking to their specific geographical locale. Trafficking transcends state and international borders. It demands an effective and consistent cooperation between local, state, and federal authorities. Each region of the world has different impact factors which create distinct challenges for law enforcement and victim services. Our mapping system lays the groundwork for a targeted anti-trafficking response.

Keywords: human trafficking, mapping, routes, law enforcement intelligence

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Authors: Loreta Serniene, Dalia Sekmokiene, Justina Tomkeviciute, Lina Lauciene, Vaida Andruleviciute, Ingrida Sinkeviciene, Kristina Kondrotiene, Neringa Kasetiene, Mindaugas Malakauskas

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One of the most important areas of product development and research in the dairy industry is the product enrichment with active ingredients as well as leading to increased product safety and sustainability. The most expanding field of the active ingredients is the various plants' CO₂ extracts with aromatic, antioxidant and antimicrobial properties. In this study, 15 plant extracts were evaluated based on their antioxidant, antimicrobial properties as well as sensory acceptance indicators for the development of new dairy products. In order to increase the total antioxidant capacity of the milk products, it was important to determine the content of phenolic compounds and antioxidant activity of CO₂ extract. The total phenolic content of fifteen different commercial CO₂ extracts was determined by the Folin-Ciocalteu reagent and expressed as milligrams of the Gallic acid equivalents (GAE) in gram of extract. The antioxidant activities were determined by 2.2′-azinobis-(3-ethylbenzthiazoline)-6-sulfonate (ABTS) methods. The study revealed that the antioxidant activities of investigated CO₂ extract vary from 4.478-62.035 µmole Trolox/g, while the total phenolic content was in the range of 2.021-38.906 mg GAE/g of extract. For the example, the estimated antioxidant activity of Chinese cinnamon (Cinammonum aromaticum) CO₂ extract was 62.023 ± 0.15 µmole Trolox/g and the total flavonoid content reached 17.962 ± 0.35 mg GAE/g. These two parameters suggest that cinnamon could be a promising supplement for the development of new cheese. The inhibitory effects of these essential oils were tested by using agar disc diffusion method against pathogenic bacteria, most commonly found in dairy products. The obtained results showed that essential oil of lemon myrtle (Backhousia citriodora) and cinnamon (Cinnamomum cassia) has antimicrobial activity against E. coli, S. aureus, B. cereus, P. florescens, L. monocytogenes, Br. thermosphacta, P. aeruginosa and S. typhimurium with the diameter of inhibition zones variation from 10 to 52 mm. The sensory taste acceptability of plant extracts in combination with a dairy product was evaluated by a group of sensory evaluation experts (31 individuals) by the criteria of overall taste acceptability in the scale of 0 (not acceptable) to 10 (very acceptable). Each of the tested samples included 200g grams of natural unsweetened greek yogurt without additives and 1 drop of single plant extract (essential oil). The highest average of overall taste acceptability was defined for the samples with essential oils of orange (Citrus sinensis) - average score 6.67, lemon myrtle (Backhousia citriodora) – 6.62, elderberry flower (Sambucus nigra flos.) – 6.61, lemon (Citrus limon) – 5.75 and cinnamon (Cinnamomum cassia) – 5.41, respectively. The results of this study indicate plant extracts of Cinnamomum cassia and Backhousia citriodora as a promising additive not only to increase the total antioxidant capacity of the milk products and as alternative antibacterial agent to combat pathogenic bacteria commonly found in dairy products but also as a desirable flavour for the taste pallet of the consumers with expressed need for safe, sustainable and innovative dairy products. Acknowledgment: This research was funded by the European Regional Development Fund according to the supported activity 'Research Projects Implemented by World-class Researcher Groups' under Measure No. 01.2.2-LMT-K-718.

Keywords: antioxidant properties, antimicrobial properties, cinnamon, CO₂ plant extracts, dairy products, essential oils, lemon myrtle

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Authors: Carly Cummings, Maria Soledad Peresin

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Alabama has a long history of racial injustice and unsatisfactory educational performance. In the 1870s Jim Crow laws segregated public schools and disproportionally allocated funding and resources to white institutions across the South. Despite the Supreme Court ruling to integrate schools following Brown vs. the Board of Education in 1954, Alabama’s school system continued to exhibit signs of segregation, compounded by “white flight” and the establishment of exclusive private schools, which still exist today. This discriminatory history has had a lasting impact of the state’s education system, reflected in modern school demographics and achievement data. It is well known that Alabama struggles with education performance, especially in science education. On average, minority groups scored the lowest in science proficiency. In Alabama, minority populations are concentrated in a region known as the Black Belt, which was once home to countless slave plantations and was the epicenter of the Civil Rights Movement. Today the Black Belt is characterized by a high density of woodlands and plays a significant role in Alabama’s leading economic industry-forest products. Given the economic importance of forestry and agriculture to the state, environmental science proficiency is essential to its stability; however, it is neglected in areas where it is needed most. To better understand the inequity of science education within Alabama, our study first investigates how geographic location, demographics and school funding relate to science achievement scores using ArcGIS and Pearson’s correlation coefficient. Additionally, our study explores the implementation of a relevant, problem-based, active learning lesson in schools. Relevant learning engages students by connecting material to their personal experiences. Problem-based active learning involves real-world problem-solving through hands-on experiences. Given Alabama’s significant woodland coverage, educational materials on forest products were developed with consideration of its relevance to students, especially those located in the Black Belt. Furthermore, to incorporate problem solving and active learning, the lesson centered around students using forest products to solve environmental challenges, such as water pollution- an increasing challenge within the state due to climate change. Pre and post assessment surveys were provided to teachers to measure the effectiveness of the lesson. In addition to pedagogical practices, community and mentorship programs are known to positively impact educational achievements. To this end, our work examines the results of surveys measuring educational professionals’ attitudes toward a local mentorship group within the Black Belt and its potential to address environmental and science literacy. Additionally, our study presents survey results from participants who attended an educational community event, gauging its effectiveness in increasing environmental and science proficiency. Our results demonstrate positive improvements in environmental awareness and science literacy with relevant pedagogy, mentorship, and community involvement. Implementing these practices can help provide equitable and inclusive learning environments and can better equip students with the skills and knowledge needed to bridge this historic educational gap within Alabama.

Keywords: equitable education, environmental science, environmental education, science education, racial injustice, sustainability, rural education

Procedia PDF Downloads 68

Authors: Pradipta Chandra, Titas Bhattacharjee, Bhaskar Bhowmick

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The foundation of economy in India is primarily based on agriculture while this is the most neglected in the rural setting. More significantly, household women take part in agriculture with higher involvement. However, because of lower education of women they have limited access towards financial decisions, land ownership and technology but they have vital role towards the individual family level. There are limited studies on the institution-wise training barriers with the focus of gender disparity. The main purpose of this paper is to find out the factors of institution-wise training (non-formal education) barriers in technology transfer with the focus of participation of rural women in agriculture. For this study primary and secondary data were collected in the line of qualitative and quantitative approach. Qualitative data were collected by several field visits in the adjacent areas of Seva-Bharati, Seva Bharati Krishi Vigyan Kendra through semi-structured questionnaires. In the next level detailed field surveys were conducted with close-ended questionnaires scored on the seven-point Likert scale. Sample size was considered as 162. During the data collection the focus was to include women although some biasness from the end of respondents and interviewer might exist due to dissimilarity in observation, views etc. In addition to that the heterogeneity of sample is not very high although female participation is more than fifty percent. Data were analyzed using Exploratory Factor Analysis (EFA) technique with the outcome of three significant factors of training barriers in technology adoption by farmers: (a) Failure of technology transfer training (TTT) comprehension interprets that the technology takers, i.e., farmers can’t understand the technology either language barrier or way of demonstration exhibited by the experts/ trainers. (b) Failure of TTT customization, articulates that the training for individual farmer, gender crop or season-wise is not tailored. (c) Failure of TTT generalization conveys that absence of common training methods for individual trainers for specific crops is more prominent at the community level. The central finding is that the technology transfer training method can’t fulfill the need of the farmers under an economically challenged area. The impact of such study is very high in the area of dry lateritic and resource crunch area of Jangalmahal under Paschim Medinipur district, West Bengal and areas with similar socio-economy. Towards the policy level decision this research may help in framing digital agriculture for implementation of the appropriate information technology for the farming community, effective and timely investment by the government with the selection of beneficiary, formation of farmers club/ farm science club etc. The most important research implication of this study lies upon the contribution towards the knowledge diffusion mechanism of the agricultural sector in India. Farmers may overcome the barriers to achieve higher productivity through adoption of modern farm practices. Corporates will be interested in agro-sector through investment under corporate social responsibility (CSR). The research will help in framing public or industry policy and land use pattern. Consequently, a huge mass of rural farm-women will be empowered and farmer community will be benefitted.

Keywords: dry lateritic zone, institutional barriers, technology transfer in India, farm-women participation

Procedia PDF Downloads 373

Authors: Daniele Lerede, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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The European Green Deal is the first internationally agreed set of measures to contrast climate change and environmental degradation. Besides the main target of reducing emissions by at least 55% by 2030, it sets the target of accompanying European countries through an energy transition to make the European Union into a modern, resource-efficient, and competitive net-zero emissions economy by 2050, decoupling growth from the use of resources and ensuring a fair adaptation of all social categories to the transformation process. While the general purpose to allow the realization of the purposes of the Green Deal already dates back to 2019, strategies and policies keep being developed coping with recent circumstances and achievements. However, general long-term measures like the Circular Economy Action Plan, the proposals to shift from fossil natural gas to renewable and low-carbon gases, in particular biomethane and hydrogen, and to end the sale of gasoline and diesel cars by 2035, will all have significant effects on energy supply and demand evolution across the next decades. The interactions between energy supply and demand over long-term time frames are usually assessed via energy system models to derive useful insights for policymaking and to address technological choices and research and development. TEMOA-Europe is a newly developed energy system optimization model instance based on the minimization of the total cost of the system under analysis, adopting a technologically integrated, detailed, and explicit formulation and considering the evolution of the system in partial equilibrium in competitive markets with perfect foresight. TEMOA-Europe is developed on the TEMOA platform, an open-source modeling framework totally implemented in Python, therefore ensuring third-party verification even on large and complex models. TEMOA-Europe is based on a single-region representation of the European Union and EFTA countries on a time scale between 2005 and 2100, relying on a set of assumptions for socio-economic developments based on projections by the International Energy Outlook and a large technological dataset including 7 sectors: the upstream and power sectors for the production of all energy commodities and the end-use sectors, including industry, transport, residential, commercial and agriculture. TEMOA-Europe also includes an updated hydrogen module considering its production, storage, transportation, and utilization. Besides, it can rely on a wide set of innovative technologies, ranging from nuclear fusion and electricity plants equipped with CCS in the power sector to electrolysis-based steel production processes and steel in the industrial sector – with a techno-economic characterization based on public literature – to produce insightful energy scenarios and especially to cope with the very long analyzed time scale. The aim of this work is to examine in detail the scheme of measures and policies for the realization of the purposes of the Green Deal and to transform them into a set of constraints and new socio-economic development pathways. Based on them, TEMOA-Europe will be used to produce and comparatively analyze scenarios to assess the consequences of Green Deal-related measures on the future evolution of the energy mix over the whole energy system in an economic optimization environment.

Keywords: European Green Deal, energy system optimization modeling, scenario analysis, TEMOA-Europe

Procedia PDF Downloads 105

Authors: Diogo José Morgado Rebelo, Francisco António Carneiro Pacheco de Andrade, Paulo Jorge Freitas de Oliveira Novais

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Not everything in AI-power consumer credit scoring turns out to be a wonder. When using AI in Creditworthiness Assessment (CWA), opacity and unfairness ‘sins’ must be considered to the task be deemed Responsible. AI software is not always 100% accurate, which can lead to misclassification. Discrimination of some groups can be exponentiated. A hetero personalized identity can be imposed on the individual(s) affected. Also, autonomous CWA sometimes lacks transparency when using black box models. However, for this intended purpose, human analysts ‘on-the-loop’ might not be the best remedy consumers are looking for in credit. This study seeks to explore the legality of implementing a Multi-Agent System (MAS) framework in consumer CWA to ensure compliance with the regulation outlined in Article 14(4) of the Proposal for an Artificial Intelligence Act (AIA), dated 21 April 2021 (as per the last corrigendum by the European Parliament on 19 April 2024), Especially with the adoption of Art. 18(8)(9) of the EU Directive 2023/2225, of 18 October, which will go into effect on 20 November 2026, there should be more emphasis on the need for hybrid oversight in AI-driven scoring to ensure fairness and transparency. In fact, the range of EU regulations on AI-based consumer credit will soon impact the AI lending industry locally and globally, as shown by the broad territorial scope of AIA’s Art. 2. Consequently, engineering the law of consumer’s CWA is imperative. Generally, the proposed MAS framework consists of several layers arranged in a specific sequence, as follows: firstly, the Data Layer gathers legitimate predictor sets from traditional sources; then, the Decision Support System Layer, whose Neural Network model is trained using k-fold Cross Validation, provides recommendations based on the feeder data; the eXplainability (XAI) multi-structure comprises Three-Step-Agents; and, lastly, the Oversight Layer has a 'Bottom Stop' for analysts to intervene in a timely manner. From the analysis, one can assure a vital component of this software is the XAY layer. It appears as a transparent curtain covering the AI’s decision-making process, enabling comprehension, reflection, and further feasible oversight. Local Interpretable Model-agnostic Explanations (LIME) might act as a pillar by offering counterfactual insights. SHapley Additive exPlanation (SHAP), another agent in the XAI layer, could address potential discrimination issues, identifying the contribution of each feature to the prediction. Alternatively, for thin or no file consumers, the Suggestion Agent can promote financial inclusion. It uses lawful alternative sources such as the share of wallet, among others, to search for more advantageous solutions to incomplete evaluation appraisals based on genetic programming. Overall, this research aspires to bring the concept of Machine-Centered Anthropocentrism to the table of EU policymaking. It acknowledges that, when put into service, credit analysts no longer exert full control over the data-driven entities programmers have given ‘birth’ to. With similar explanatory agents under supervision, AI itself can become self-accountable, prioritizing human concerns and values. AI decisions should not be vilified inherently. The issue lies in how they are integrated into decision-making and whether they align with non-discrimination principles and transparency rules.

Keywords: creditworthiness assessment, hybrid oversight, machine-centered anthropocentrism, EU policymaking

Procedia PDF Downloads 34

Authors: Samuel Escandón, María J. Peñaherrera-Vélez, Signe Vargas-Rosvik, Carlos Jerves Córdova, Ximena Vélez-Calvo, Angélica Ochoa-Avilés

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Overweight and obesity are considered risk factors in childhood for developing nutrition-related non-communicable diseases (NCDs), such as diabetes, cardiovascular diseases, and cancer. In Ecuador, 35.4% of 5- to 11-year-olds and 29.6% of 12- to 19-year-olds are overweight or obese. Globally, unhealthy food environments characterized by high consumption of processed/ultra-processed food and rapid urbanization are highly related to the increasing nutrition-related non-communicable diseases. The evidence shows that in low- and middle-income countries (LMICs), fiscal policies and regulatory measures significantly reduce unhealthy food environments, achieving substantial advances in health. However, in some LMICs, little is known about the impact of governments' action to implement healthy food-environment policies. This study aimed to generate evidence on the state of implementation of public policy focused on food environments for the prevention of overweight and obesity in children and adolescents in Ecuador compared to global best practices and to target key recommendations for reinforcing the current strategies. After adapting the INFORMAS' Healthy Food Environment Policy Index (Food‐EPI) to the Ecuadorian context, the Policy and Infrastructure support components were assessed. Individual online interviews were performed using fifty-one indicators to analyze the level of implementation of policies directly or indirectly related to preventing overweight and obesity in children and adolescents compared to international best practices. Additionally, a participatory workshop was conducted to identify the critical indicators and generate recommendations to reinforce or improve the political action around them. In total, 17 government and non-government experts were consulted. From 51 assessed indicators, only the one corresponding to the nutritional information and ingredients labelling registered an implementation level higher than 60% (67%) compared to the best international practices. Among the 17 indicators determined as priorities by the participants, those corresponding to the provision of local products in school meals and the limitation of unhealthy-products promotion in traditional and digital media had the lowest level of implementation (34% and 11%, respectively) compared to global best practices. The participants identified more barriers (e.g., lack of continuity of effective policies across government administrations) than facilitators (e.g., growing interest from the Ministry of Environment because of the eating-behavior environmental impact) for Ecuador to move closer to the best international practices. Finally, within the participants' recommendations, we highlight the need for policy-evaluation systems, information transparency on the impact of the policies, transformation of successful strategies into laws or regulations to make them mandatory, and regulation of power and influence from the food industry (conflicts of interest). Actions focused on promoting a more active role of society in the stages of policy formation and achieving more articulated actions between the different government levels/institutions for implementing the policy are necessary to generate a noteworthy impact on preventing overweight and obesity in children and adolescents. Including systems for internal evaluation of existing strategies to strengthen successful actions, create policies to fill existing gaps and reform policies that do not generate significant impact should be a priority for the Ecuadorian government to improve the country's food environments.

Keywords: children and adolescents, food-EPI, food policies, healthy food environment

Procedia PDF Downloads 63

Authors: Artur Tyliszczak, Ewa Szymanek, Maciej Marek

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Flow through granular materials is important to a vast array of industries, for instance in construction industry where granular layers are used for bulkheads and isolators, in chemical engineering and catalytic reactors where large surfaces of packed granular beds intensify chemical reactions, or in energy production systems, where granulates are promising materials for heat storage and heat transfer media. Despite the common usage of granulates and extensive research performed in this field, phenomena occurring between granular solid elements or between solids and fluid are still not fully understood. In the present work we analyze the heat exchange process between the flowing medium (gas, liquid) and solid material inside the granular layers. We consider them as a composite of isolated solid elements and inter-granular spaces in which a gas or liquid can flow. The structure of the layer is controlled by shapes of particular granular elements (e.g., spheres, cylinders, cubes, Raschig rings), its spatial distribution or effective characteristic dimension (total volume or surface area). We will analyze to what extent alteration of these parameters influences on flow characteristics (turbulent intensity, mixing efficiency, heat transfer) inside the layer and behind it. Analysis of flow inside granular layers is very complicated because the use of classical experimental techniques (LDA, PIV, fibber probes) inside the layers is practically impossible, whereas the use of probes (e.g. thermocouples, Pitot tubes) requires drilling of holes inside the solid material. Hence, measurements of the flow inside granular layers are usually performed using for instance advanced X-ray tomography. In this respect, theoretical or numerical analyses of flow inside granulates seem crucial. Application of discrete element methods in combination with the classical finite volume/finite difference approaches is problematic as a mesh generation process for complex granular material can be very arduous. A good alternative for simulation of flow in complex domains is an immersed boundary-volume penalization (IB-VP) in which the computational meshes have simple Cartesian structure and impact of solid objects on the fluid is mimicked by source terms added to the Navier-Stokes and energy equations. The present paper focuses on application of the IB-VP method combined with large eddy simulation (LES). The flow solver used in this work is a high-order code (SAILOR), which was used previously in various studies, including laminar/turbulent transition in free flows and also for flows in wavy channels, wavy pipes and over various shape obstacles. In these cases a formal order of approximation turned out to be in between 1 and 2, depending on the test case. The current research concentrates on analyses of the flows in dense granular layers with elements distributed in a deterministic regular manner and validation of the results obtained using LES-IB method and body-fitted approach. The comparisons are very promising and show very good agreement. It is found that the size, number of elements and their distribution have huge impact on the obtained results. Ordering of the granular elements (or lack of it) affects both the pressure drop and efficiency of the heat transfer as it significantly changes mixing process.

Keywords: granular layers, heat transfer, immersed boundary method, numerical simulations

Procedia PDF Downloads 136

Authors: Nursuhaili Najwa Masrol, Nur Hafizah Mohammed, Nur Nadhirah Rusyda Rosnan, Vijaya Subramaniam, Sim Choon Cheak

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Replanting in oil palm cultivation is vital to enable the introduction of planting materials and provides an opportunity to improve the road, drainage, terrace design, and planting density. Oil palm replanting is fundamentally necessary every 25 years. The adoption of the digital replanting blueprint is imperative as it can assist the Malaysia Oil Palm industry in addressing challenges such as labour shortages and limited expertise related to replanting tasks. Effective replanting planning should commence at least 6 months prior to the actual replanting process. Therefore, this study will help to plan and design the replanting blueprint with high-precision translation on the ground. With the advancement of geospatial technology, it is now feasible to engage in thoroughly researched planning, which can help maximize the potential yield. A blueprint designed before replanting is to enhance management’s ability to optimize the planting program, address manpower issues, or even increase productivity. In terrace planting blueprints, geographic tools have been utilized to design the roads, drainages, terraces, and planting points based on the ARM standards. These designs are mapped with location information and undergo statistical analysis. The geospatial approach is essential in precision agriculture and ensuring an accurate translation of design to the ground by implementing high-accuracy technologies. In this study, geospatial and remote sensing technologies played a vital role. LiDAR data was employed to determine the Digital Elevation Model (DEM), enabling the precise selection of terraces, while ortho imagery was used for validation purposes. Throughout the designing process, Geographical Information System (GIS) tools were extensively utilized. To assess the design’s reliability on the ground compared with the current conventional method, high-precision GPS instruments like EOS Arrow Gold and HIPER VR GNSS were used, with both offering accuracy levels between 0.3 cm and 0.5cm. Nearest Distance Analysis was generated to compare the design with actual planting on the ground. The analysis revealed that it could not be applied to the roads due to discrepancies between actual roads and the blueprint design, which resulted in minimal variance. In contrast, the terraces closely adhered to the GPS markings, with the most variance distance being less than 0.5 meters compared to actual terraces constructed. Considering the required slope degrees for terrace planting, which must be greater than 6 degrees, the study found that approximately 65% of the terracing was constructed at a 12-degree slope, while over 50% of the terracing was constructed at slopes exceeding the minimum degrees. Utilizing blueprint replanting promising strategies for optimizing land utilization in agriculture. This approach harnesses technology and meticulous planning to yield advantages, including increased efficiency, enhanced sustainability, and cost reduction. From this study, practical implementation of this technique can lead to tangible and significant improvements in agricultural sectors. In boosting further efficiencies, future initiatives will require more sophisticated techniques and the incorporation of precision GPS devices for upcoming blueprint replanting projects besides strategic progression aims to guarantee the precision of both blueprint design stages and its subsequent implementation on the field. Looking ahead, automating digital blueprints are necessary to reduce time, workforce, and costs in commercial production.

Keywords: replanting, geospatial, precision agriculture, blueprint

Procedia PDF Downloads 82

Authors: Do-Won Kim, Andy Eu Jin Lim, Raja Muthusamy Kumarasamy, Vishal Vinayak, Jacky Wang Yu-Shun, Jason Liow Tsung Yang, Patrick Lo Guo Qiang

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In this study, we demonstrate 4-channel coarse wavelength division multiplexing (CWDM) optical transceiver based on silicon photonics integrated circuits (PIC) of waveguide Ge-photodiode (Ge-PD) and Mach Zehnder (MZ)-modulator. 4-channel arrayed PICs of Ge-PD and MZ-modulator are verified to operate at 25 Gbps/ch achieving 4x25 Gbps of total data rate. 4 bare dies of single-channel commercial electronics ICs (EICs) of trans-impedance amplifier (TIA) for Ge-PD and driver IC for MZ-modulator are packaged with PIC on printed circuit board (PCB) in a chip-on-board (COB) manner. Each single-channel EIC is electrically connected to the one channel of 4-channel PICs by wire bonds to trace. The PICs have 4-channel multiplexer for MZ-modulator and 4-channel demultiplexer for Ge-PD. The 4-channel multiplexer/demultiplexer have echelle gratings for4 CWDM optic signals of which center wavelengths are 1511, 1531, 1553, and 1573 nm. Its insertion loss is around 4dB with over 15dB of extinction ratio.The dimension of 4-channel Ge-PD is 3.6x1.4x0.3mm, and its responsivity is 1A/W with dark current of less than 20 nA.Its measured 3dB bandwidth is around 20GHz. The dimension of the 4-channel MZ-modulator is 3.6x4.8x0.3mm, and its 3dB bandwidth is around 11Ghz at -2V of reverse biasing voltage. It has 2.4V•cmbyVπVL of 6V for π shift to 4 mm length modulator.5x5um of Inversed tapered mode size converter with less than 2dB of coupling loss is used for the coupling of the lensed fiber which has 5um of mode field diameter.The PCB for COB packaging and signal transmission is designed to have 6 layers in the hybrid layer structure. 0.25 mm-thick Rogers Duroid RT5880 is used as the first core dielectric layer for high-speed performance over 25 Gbps. It has 0.017 mm-thick of copper layers and its dielectric constant is 2.2and dissipation factor is 0.0009 at 10 GHz. The dimension of both single ended and differential microstrip transmission lines are calculated using full-wave electromagnetic (EM) field simulator HFSS which RF industry is using most. It showed 3dB bandwidth at around 15GHz in S-parameter measurement using network analyzer. The wire bond length for transmission line and ground connection from EIC is done to have less than 300 µm to minimize the parasitic effect to the system.Single layered capacitors (SLC) of 100pF and 1000pF are connected as close as possible to the EICs for stabilizing the DC biasing voltage by decoupling. Its signal transmission performance is under measurement at 25Gbps achieving 100Gbps by 4chx25Gbps. This work can be applied for the active optical cable (AOC) and quad small form-factor pluggable (QSFP) for high-speed optical interconnections. Its demands are quite large in data centers targeting 100 Gbps, 400 Gbps, and 1 Tbps. As the demands of high-speed AOC and QSFP for the application to intra/inter data centers increase, this silicon photonics based high-speed 4 channel CWDM scheme can have advantages not only in data throughput but also cost effectiveness since it reduces fiber cost dramatically through WDM.

Keywords: active optical cable(AOC), 4-channel coarse wavelength division multiplexing (CWDM), communication system, data center, ge-photodiode, Mach Zehnder (MZ) modulator, optical interconnections, optical transceiver, photonics integrated circuits (PIC), quad small form-factor pluggable (QSFP), silicon photonics

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Authors: Leo Byrne, Neil Watts

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In the complex and evolving landscape of global trade, maritime sanctions emerge as a critical tool wielded by the international community to curb illegal activities and alter the behavior of non-compliant states and entities. These sanctions, designed to restrict or prohibit trade by sea with sanctioned jurisdictions, entities, or individuals, face continuous challenges due to the sophisticated evasion tactics employed by countries like North Korea. As the Democratic People's Republic of Korea (DPRK) diverts significant resources to circumvent these measures, understanding the nuances of their methodologies becomes imperative for maintaining the integrity of global trade systems. The DPRK, one of the most sanctioned nations globally, has developed an intricate network to facilitate its trade in illicit goods, ensuring the flow of revenue from designated activities continues unabated. Given its geographic and economic conditions, North Korea predominantly relies on maritime routes, utilizing foreign ports to route its illicit trade. This reliance on the sea is exploited through various sophisticated methods, including the use of front companies, falsification of documentation, commingling of bulk cargos, and physical alterations to vessels. These tactics enable the DPRK to navigate through the gaps in regulatory frameworks and lax oversight, effectively undermining international sanctions regimes Maritime sanctions carry significant implications for global trade, imposing heightened risks in the maritime domain. The deceptive practices employed not only by the DPRK but also by other high-risk jurisdictions, necessitate a comprehensive understanding of UN targeted sanctions. For stakeholders in the maritime sector—including maritime authorities, vessel owners, shipping companies, flag registries, and financial institutions serving the shipping industry—awareness and compliance are paramount. Violations can lead to severe consequences, including reputational damage, sanctions, hefty fines, and even imprisonment. To mitigate risks associated with these deceptive practices, it is crucial for maritime sector stakeholders to employ rigorous due diligence and regulatory compliance screening measures. Effective sanctions compliance serves as a protective shield against legal, financial, and reputational risks, preventing exploitation by international bad actors. This requires not only a deep understanding of the sanctions landscape but also the capability to identify and manage risks through informed decision-making and proactive risk management practices. As the DPRK and other sanctioned entities continue to evolve their sanctions evasion tactics, the international community must enhance its collective efforts to demystify and counter these practices. By leveraging more stringent compliance measures, stakeholders can safeguard against the illicit use of the maritime domain, reinforcing the effectiveness of maritime sanctions as a tool for global security. This paper seeks to dissect North Korea's adaptive strategies in the face of maritime sanctions. By examining up-to-date, geographically, and temporally relevant case studies, it aims to shed light on the primary nodes through which Pyongyang evades sanctions and smuggles goods via third-party ports. The goal is to propose multi-level interaction strategies, ranging from governmental interventions to localized enforcement mechanisms, to counteract these evasion tactics.

Keywords: maritime, maritime sanctions, international sanctions, compliance, risk

Procedia PDF Downloads 70

Authors: K. Kamal

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Structural sandwich panels with core of Advanced Composites Laminates l Honeycombs / PU-foams are used in aerospace applications and are also fabricated for use now in some civil engineering applications. An all Advanced Composites Foot Over Bridge (FOB) system, designed and developed for pedestrian traffic is one such application earlier, may be cited as an example here. During development stage of this FoB, a profile of its decks was then spurred as a single corrugate sheet core sandwiched between two Glass Fibre Reinforced Plastics(GFRP) flat laminates. Once successfully fabricated and used, these decks did prove suitable also to form other structure on assembly, such as, erecting temporary shelters. Such corrugated sheet core profile sandwiched panels were then also tried using the construction materials but any conventional method of construction only posed certain difficulties in achieving the required core profile monolithically within the sandwiched slabs and hence it was then abended. Such monolithic construction was, however, subsequently eased out on demonstration by dispensing building materials mix through a suitably designed multi-dispenser system attached to a 3D Printer. This study conducted at lab level was thus reported earlier and it did include the fabrication of a 3D printer in-house first as ‘3DcMP’ as well as on its functional operation, some required sandwich core profiles also been 3D-printed out producing panels hardware. Once a number of these sandwich panels in single corrugated sheet core monolithically printed out, panels were subjected to load test in an experimental set up as also their structural behavior was studied analytically, and subsequently, these results were correlated as reported in the literature. In achieving the required more depths and also to exhibit further the stronger and creating sandwiched decks of better structural and mechanical behavior, further more complex core configuration such as stack corrugate sheets core with a flat mid plane was felt to be the better sandwiched core. Such profile remained as an outcome that turns out merely on stacking of two separately printed out monolithic units of single corrugated sheet core developed earlier as above and bonded them together initially, maintaining a different orientation. For any required sequential understanding of the structural behavior of any such complex profile core sandwiched decks with special emphasis to study of the effect in the variation of corrugation orientation in each distinct tire in this core, it obviously calls for an analytical study first. The rectangular,simply supported decks have therefore been considered for analysis adopting the ‘Advanced Composite Technology(ACT), some numerical results along with some fruitful findings were obtained and these are all presented here in this paper. From this numerical result, it has been observed that a mid flat layer which eventually get created monolethically itself, in addition to eliminating the bonding process in development, has been found to offer more effective bending resistance by such decks subjected to UDL over them. This is understood to have resulted here since the existence of a required shear resistance layer at the mid of the core in this profile, unlike other bending elements. As an addendum to all such efforts made as covered above and was published earlier, this unique stack corrugate sheet core profile sandwiched structural decks, monolithically construction with ease at the site itself, has been printed out from a 3D Printer. On employing 3DcMP and using some innovative building construction materials, holds the future promises of such research & development works since all those several aspects of a 3D printing in construction are now included such as reduction in the required construction time, offering cost effective solutions with freedom in design of any such complex shapes thus can widely now be realized by the modern construction industry.

Keywords: advance composite technology(ACT), corrugated laminates, 3DcMP, foot over bridge (FOB), sandwiched deck units

Procedia PDF Downloads 171

Authors: Maari Sugawara

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This study investigates the constructed notion of “motherhood” and queered forms of care in contemporary Japan, focusing on rental family services. In Japan, the concept of motherhood is often equated with womanhood, reflecting a pervasive ideology that views motherhood as an essential aspect of a woman's societal role, particularly amidst economic recovery and an aging population. This study interrogates these gendered expectations by linking rental family services, particularly the role of rental mothers, to traditional caregiving roles. It critiques the gendered construction of domestic labor and aims to expand conceptions of alternative family structures and caregiving roles beyond normative frameworks. Emerging in the 1980s to provide companionship for the elderly, rental family services have evolved to meet diverse social needs, with paid actors fulfilling familial roles at various social events. Despite their growing prevalence, academic exploration of this phenomenon remains limited. This research aims to fill that gap by investigating the cultural, social, and economic factors fueling the popularity of rental family services and analyzing their implications for contemporary understandings of family dynamics and care labor in Japan. Furthermore, this study underscores the disproportionate domestic labor burden women in Japan bear, often managing time-intensive household tasks, which creates a "double burden" for those in full-time employment. Care work, including elderly and disability support, is undervalued and typically compensated at near-minimum wage levels, with women predominantly filling these low-wage roles. This gender disparity in Japan's care industry contributes to labor shortages in caregiving and childcare, highlighting broader structural inequities in the labor market. Through semi-structured qualitative interviews with fifteen rental mothers, this study investigates their experiences, motivations, role dynamics, and emotional labor. It critically examines whether the labor performed by rental family actors constitutes a subversive practice deserving of appropriate compensation. Utilizing a role-playing method, the author engages with rental mothers as if they were her own, reflecting the dynamics of compensated labor. This interaction delves into the economic and emotional aspects of constructed motherhood, facilitating a broader inquiry into the value of both productive and reproductive labor in Japan. The study also investigates the relationship between sex work and rental family services within the socio-economic landscape, recognizing the links between the welfare sector and female employment in legal sex work. Although distinct, these sectors merit joint consideration due to the commonality of male clients in both industries. This research engages with theoretical perspectives framing mobile sex work as inherently queer, directly challenging the dominance of heteronormativity. The agency exercised by sex workers complicates narratives of conformity and deviance, underscoring the need to reevaluate caregiving labor in both paid and unpaid contexts. Ultimately, this research critiques the intersection of gender, care, and labor in contemporary Japan by examining the undervaluation of traditional caregiving roles alongside the labor involved in rental family services. It challenges Japanese policies that equate womanhood with motherhood and explores the potential of viewing outsourced care as queered maternal and non-reproductive labor, advocating for the recognition of alternative family structures and non-reproductive forms of motherhood.

Keywords: motherhood, alternative family structures, carework, Japan, queer studies

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Authors: Ipsita Pujari, Abitha Thomas, Vidhu S. Babu, K. Satyamoorthy

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Orchids are esteemed as celebrities in cut flower industry globally, due to their long-lasting fragrance and freshness. Apart from splendor, the unique metabolites endowed with pharmaceutical potency have made them one of the most hunted in plant kingdom. This had led to their trafficking, resulting in habitat loss, subsequently making them occupiers of IUCN red list as RET species. Many of the orchids especially wild varieties still remain undiscovered. In view to protect and conserve the wild germplasm, researchers have been inventing novel micropropagation protocols; thereby conserving Orchids. India is overflowing with exclusive wild cultivars of Orchids, whose pharmaceutical properties remain untapped and are not marketed owing to relatively small flowers. However, their germplasm is quite pertinent to be preserved for making unusual hybrids. Dendrobium genus is the second largest among Orchids exists in India and has highest demand attributable to enduring cut flowers and significant therapeutic uses in traditional medicinal system. Though the genus is quite endemic in Western Ghat regions of the country, many species are still anonymous with their unknown curative properties. A standard breeding cycle in Orchids usually takes five to seven years (Dendrobium hybrids taking a long juvenile phase of two to five years reaching maturity and flowering stage) and this extensive life cycle has always hindered the development of Dendrobium breeding. Dendrobium is reported with essential therapeutic plant bio-chemicals and ‘Moscatilin’ is one, found exclusive to this famous Dendrobium genus. Moscatilin is reported to have anti-mutagenic and anti-cancer properties, whose positive action has very recently been demonstrated against a range of cancers. Our preliminary study here established a simple and economic small-scale propagation protocol of Dendrobium ovatum describing in vitro production of Moscatilin. Subsequently for enhancing the content of Moscatilin, an efficient experimental related to the organization of transgenic (hairy) D. ovatum root cultures through infection of Agrobacterium rhizogenes 2364 strain on MS basal medium is being reported in the present study. Hairy roots generated on almost half of the explants used (spherules, in vitro plantlets and calli) maintained through suspension cultures, after 8 weeks of co-cultivation with Agrobacterium rhizogenes. GFP assay performed with isolated hairy roots has confirmed the integrative transformation which was further positively confirmed by PCR using rolB gene specific primers. Reverse phase-high performance liquid chromatography and mass spectrometry techniques were used for quantification and accurate identification of Moscatilin respectively from transgenic systems. A noticeable ~3 fold increase in contents were observed in transformed D. ovatum root cultures as compared to the simple in vitro culture, callus culture and callus regeneration plantlets. Role of elicitors e.g., Methyl jasmonate, Salicylic acid, Yeast extract and Chitosan were tested for elevating the Moscatilin content to obtain a comprehensive optimized protocol facilitating the in vitro production of valuable Moscatilin with larger yield. This study would provide evidence towards the in vitro assembly of Moscatilin within a short time-period through not a so-expensive technology for the first time. It also serves as an appropriate basis for bioreactor scale-up resulting in commercial bioproduction of Moscatilin.

Keywords: bioproduction, Dendrobium ovatum, hairy root culture, moscatilin

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Eduardo Lanzagorta Garcia, Chaitra Venkatesh, Romina Pezzoli, Laura Gabriela Rodriguez Barroso, Declan Devine, Margaret E. Brennan Fournet

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New antimicrobial interventions are urgently required to combat rising global health and medical infection challenges. Here, an innovative antimicrobial technology, providing price competitive alternatives to antibiotics and readily integratable with currently technological systems is presented. Two cutting edge antimicrobial materials, antimicrobial peptides (AMPs) and uncompromised sustained Ag+ action from triangular silver nanoplates (TSNPs) reservoirs, are merged for versatile effective antimicrobial action where current approaches fail. Antimicrobial peptides (AMPs) exist widely in nature and have recently been demonstrated for broad spectrum of activity against bacteria, viruses, and fungi. TSNP’s are highly discrete, homogenous and readily functionisable Ag+ nanoreseviors that have a proven amenability for operation within in a wide range of bio-based settings. In a design for advanced antimicrobial sustainable plastics, antimicrobial TSNPs are formulated for processing within biodegradable biopolymers. Histone H5 AMP was selected for its reported strong antimicrobial action and functionalized with the TSNP (AMP-TSNP) in a similar fashion to previously reported TSNP biofunctionalisation methods. A synergy between the propensity of biopolymers for degradation and Ag+ release combined with AMP activity provides a novel mechanism for the sustained antimicrobial action of biopolymeric thin films. Nanoplates are transferred from aqueous phase to an organic solvent in order to facilitate integration within hydrophobic polymers. Extrusion is used in combination with calendering rolls to create thin polymerc film where the nanoplates are embedded onto the surface. The resultant antibacterial functional films are suitable to be adapted for food packing and biomedical applications. TSNP synthesis were synthesized by adapting a previously reported seed mediated approach. TSNP synthesis was scaled up for litre scale batch production and subsequently concentrated to 43 ppm using thermally controlled H2O removal. Nanoplates were transferred from aqueous phase to an organic solvent in order to facilitate integration within hydrophobic polymers. This was acomplised by functionalizing the TSNP with thiol terminated polyethylene glycol and using centrifugal force to transfer them to chloroform. Polycaprolactone (PCL) and Polylactic acid (PLA) were individually processed through extrusion, TSNP and AMP-TSNP solutions were sprayed onto the polymer immediately after exiting the dye. Calendering rolls were used to disperse and incorporate TSNP and TSNP-AMP onto the surface of the extruded films. Observation of the characteristic blue colour confirms the integrity of the TSNP within the films. Antimicrobial tests were performed by incubating Gram + and Gram – strains with treated and non-treated films, to evaluate if bacterial growth was reduced due to the presence of the TSNP. The resulting films successfully incorporated TSNP and AMP-TSNP. Reduced bacterial growth was observed for both Gram + and Gram – strains for both TSNP and AMP-TSNP compared with untreated films indicating antimicrobial action. The largest growth reduction was observed for AMP-TSNP treated films demonstrating the additional antimicrobial activity due to the presence of the AMPs. The potential of this technology to impede bacterial activity in food industry and medical surfaces will forge new confidence in the battle against antibiotic resistant bacteria, serving to greatly inhibit infections and facilitate patient recovery.

Keywords: antimicrobial, biodegradable, peptide, polymer, nanoparticle

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Authors: Carlotta D’Alessandro, Giuseppe Ioppolo, Katarzyna Szopik-Depczyńska

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— The growing scarcity of resources and the mounting pressures of climate change, water pollution, and chemical contamination have prompted societies, governments, and businesses to seek ways to minimize their environmental impact. To combat climate change, and foster sustainability, Industrial Symbiosis (IS) offers a powerful approach, facilitating the shift toward a circular economic model. IS has gained prominence in the European Union's policy framework as crucial enabler of resource efficiency and circular economy practices. The essence of IS lies in the collaborative sharing of resources such as energy, material by-products, waste, and water, thanks to geographic proximity. It can be exemplified by eco-industrial parks (EIPs), which are natural environments for boosting cooperation and resource sharing between businesses. EIPs are characterized by group of businesses situated in proximity, connected by a network of both cooperative and competitive interactions. They represent a sustainable industrial model aimed at reducing resource use, waste, and environmental impact while fostering economic and social wellbeing. IS, combined with Artificial Intelligence (AI)-driven technologies, can further optimize resource sharing and efficiency within EIPs. This research, supported by the “CE_IPs” project, aims to analyze the potential for IS and AI, in advancing circularity and sustainability at Fosso Imperatore. The Fosso Imperatore Industrial Park in Nocera Inferiore, Italy, specializes in agriculture and the industrial transformation of agricultural products, particularly tomatoes, tobacco, and textile fibers. This unique industrial cluster, centered around tomato cultivation and processing, also includes mechanical engineering enterprises and agricultural packaging firms. To stimulate the shift from a traditional to a circular economic model, an AI-powered Local Development Plan (LDP) is developed for Fosso Imperatore. It can leverage data analytics, predictive modeling, and stakeholder engagement to optimize resource utilization, reduce waste, and promote sustainable industrial practices. A comprehensive SWOT analysis of the AI-powered LDP revealed several key factors influencing its potential success and challenges. Among the notable strengths and opportunities arising from AI implementation are reduced processing times, fewer human errors, and increased revenue generation. Furthermore, predictive analytics minimize downtime, bolster productivity, and elevate quality while mitigating workplace hazards. However, the integration of AI also presents potential weaknesses and threats, including significant financial investment, since implementing and maintaining AI systems can be costly. The widespread adoption of AI could lead to job losses in certain sectors. Lastly, AI systems are susceptible to cyberattacks, posing risks to data security and operational continuity. Moreover, an Analytic Hierarchy Process (AHP) analysis was employed to yield a prioritized ranking of the outlined AI-driven LDP practices based on the stakeholder input, ensuring a more comprehensive and representative understanding of their relative significance for achieving sustainability in Fosso Imperatore Industrial Park. While this study provides valuable insights into the potential of AIpowered LDP at the Fosso Imperatore, it is important to note that the findings may not be directly applicable to all industrial parks, particularly those with different sizes, geographic locations, or industry compositions. Additional study is necessary to scrutinize the generalizability of these results and to identify best practices for implementing AI-driven LDP in diverse contexts.

Keywords: artificial intelligence, climate change, Fosso Imperatore, industrial park, industrial symbiosis

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Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

Procedia PDF Downloads 250

Authors: Volker Wannack

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Regional, national, and international strategies focusing on hydrogen (H₂) and blockchain are driving significant advancements in hydrogen and blockchain technology worldwide. These strategies lay the foundation for the groundbreaking "Blockchain Based Hydrogen Market (BBH₂)" project. The primary goal of this project is to develop a functional Blockchain Minimum Viable Product (B-MVP) for the hydrogen market. The B-MVP will leverage blockchain as an enabling technology with a common database and platform, facilitating secure and automated transactions through smart contracts. This innovation will revolutionize logistics, trading, and transactions within the hydrogen market. The B-MVP has transformative potential across various sectors. It benefits renewable energy producers, surplus energy-based hydrogen producers, hydrogen transport and distribution grid operators, and hydrogen consumers. By implementing standardized, automated, and tamper-proof processes, the B-MVP enhances cost efficiency and enables transparent and traceable transactions. Its key objective is to establish the verifiable integrity of climate-friendly "green" hydrogen by tracing its supply chain from renewable energy producers to end users. This emphasis on transparency and accountability promotes economic, ecological, and social sustainability while fostering a secure and transparent market environment. A notable feature of the B-MVP is its cross-border operability, eliminating the need for country-specific data storage and expanding its global applicability. This flexibility not only broadens its reach but also creates opportunities for long-term job creation through the establishment of a dedicated blockchain operating company. By attracting skilled workers and supporting their training, the B-MVP strengthens the workforce in the growing hydrogen sector. Moreover, it drives the emergence of innovative business models that attract additional company establishments and startups and contributes to long-term job creation. For instance, data evaluation can be utilized to develop customized tariffs and provide demand-oriented network capacities to producers and network operators, benefitting redistributors and end customers with tamper-proof pricing options. The B-MVP not only brings technological and economic advancements but also enhances the visibility of national and international standard-setting efforts. Regions implementing the B-MVP become pioneers in climate-friendly, sustainable, and forward-thinking practices, generating interest beyond their geographic boundaries. Additionally, the B-MVP serves as a catalyst for research and development, facilitating knowledge transfer between universities and companies. This collaborative environment fosters scientific progress, aligns with strategic innovation management, and cultivates an innovation culture within the hydrogen market. Through the integration of blockchain and hydrogen technologies, the B-MVP promotes holistic innovation and contributes to a sustainable future in the hydrogen industry. The implementation process involves evaluating and mapping suitable blockchain technology and architecture, developing and implementing the blockchain, smart contracts, and depositing certificates of origin. It also includes creating interfaces to existing systems such as nomination, portfolio management, trading, and billing systems, testing the scalability of the B-MVP to other markets and user groups, developing data formats for process-relevant data exchange, and conducting field studies to validate the B-MVP. BBH₂ is part of the "Technology Offensive Hydrogen" funding call within the research funding of the Federal Ministry of Economics and Climate Protection in the 7th Energy Research Programme of the Federal Government.

Keywords: hydrogen, blockchain, sustainability, innovation, structural change

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Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

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Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

Procedia PDF Downloads 150