Search results for: complex event processing

Authors: Malla Vijayeta, Y. Vijaya Kumar, N. Ramakrishna Raju, K. Satyanarayana

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Global AEC (architecture, engineering, and construction) industry has been coined as one of the most resistive domains in embracing technology. Although this digital era has been inundated with software tools like CAD, STADD, CANDY, Microsoft Project, Primavera etc. the key stakeholders have been working in siloes and processes remain fragmented. Unlike the yesteryears’ simpler project delivery methods, the current projects are of fast-track, complex, risky, multidisciplinary, stakeholder’s influential, statutorily regulative etc. pose extensive bottlenecks in preventing timely completion of projects. At this juncture, a paradigm shift surfaced in construction industry, and Building Information Modeling, aka BIM, has been a panacea to bolster the multidisciplinary teams’ cooperative and collaborative work leading to productive, sustainable and leaner project outcome. Building information modeling has been integrative, stakeholder engaging and centralized approach in providing a common platform of communication. A common misconception that BIM can be used for building/high rise projects in Indian Construction Industry, while this paper discusses of the implementation of BIM processes/methodologies in water and waste water industry. It elucidates about BIM 4D planning and constructability reviews of a Sewage Treatment Plant in India. Conventional construction planning and logistics management involves a blend of experience coupled with imagination. Even though the excerpts or judgments or lessons learnt gained from veterans might be predictive and helpful, but the uncertainty factor persists. This paper shall delve about the case study of real time implementation of BIM 4D planning protocols for one of the Sewage Treatment Plant of Dravyavati River Rejuvenation Project in India and develops a Time Liner to identify logistics planning and clash detection. With this BIM processes, we shall find that there will be significant reduction of duplication of tasks and reworks. Also another benefit achieved will be better visualization and workarounds during conception stage and enables for early involvement of the stakeholders in the Project Life cycle of Sewage Treatment Plant construction. Moreover, we have also taken an opinion poll of the benefits accrued utilizing BIM processes versus traditional paper based communication like 2D and 3D CAD tools. Thus this paper concludes with BIM framework for Sewage Treatment Plant construction which will achieve optimal construction co-ordination advantages like 4D construction sequencing, interference checking, clash detection checking and resolutions by primary engagement of all key stakeholders thereby identifying potential risks and subsequent creation of risk response strategies. However, certain hiccups like hesitancy in adoption of BIM technology by naïve users and availability of proficient BIM trainers in India poses a phenomenal impediment. Hence the nurture of BIM processes from conception, construction and till commissioning, operation and maintenance along with deconstruction of a project’s life cycle is highly essential for Indian Construction Industry in this digital era.

Keywords: integrated BIM workflow, 4D planning with BIM, building information modeling, clash detection and visualization, constructability reviews, project life cycle

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Authors: Lia Mania, Ketevan Nanobashvili

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Background: The coronavirus disease COVID-19 has become the cause of a global health crisis during the current pandemic. This study aims to fill the paucity of epidemiological studies on the impact of COVID-19 on the oral health of pediatric populations. Methods: It was conducted an observational, cross-sectional study in Georgia, in Tbilisi (capital of Georgia), among 7 to 12-year-old PCR or rapid test-confirmed post-Covid populations in all districts of Tbilisi (10 districts in total). 332 beneficiaries who were infected with Covid within one year were included in the study. The population was selected in schools of Tbilisi according to the principle of cluster selection. A simple random selection took place in the selected clusters. According to this principle, an equal number of beneficiaries were selected in all districts of Tbilisi. By July 1, 2022, according to National Center for Disease Control and Public Health data (NCDC.Ge), the number of test-confirmed cases in the population aged 0-18 in Tbilisi was 115137 children (17.7% of all confirmed cases). The number of patients to be examined was determined by the sample size. Oral screening, microbiological examination of saliva, and administration of oral health questionnaires to guardians were performed. Statistical processing of data was done with SPSS-23. Risk factors were estimated by odds ratio and logistic regression with 95% confidence interval. Results: Statistically reliable differences between the averages of oral health indicators in asymptomatic and symptomatic covid-infected groups are: for caries intensity (DMF+def) t=4.468 and p=0.000, for modified gingival index (MGI) t=3.048, p=0.002, for simplified oral hygiene index (S-OHI) t=4.853; p=0.000. Symptomatic covid-infection has a reliable effect on the oral microbiome (Staphylococcus aureus, Candida albicans, Pseudomonas aeruginosa, Streptococcus pneumoniae, Staphylococcus epidermalis); (n=332; 77.3% vs n=332; 58.0%; OR=2.46, 95%CI: 1.318-4.617). According to the logistic regression, it was found that the severity of the covid infection has a significant effect on the frequency of pathogenic and conditionally pathogenic bacteria in the oral cavity B=0.903 AOR=2.467 (CL 1.318-4.617). Symptomatic covid-infection affects oral health indicators, regardless of the presence of other risk factors, such as parental employment status, tooth brushing behaviors, carbohydrate meal, fruit consumption. (p<0.05). Conclusion: Risk factors (parental employment status, tooth brushing behaviors, carbohydrate consumption) were associated with poorer oral health status in a post-Covid population of 7- to 12-year-old children. However, such a risk factor as symptomatic ongoing covid-infection affected the oral microbiome in terms of the abundant growth of pathogenic and conditionally pathogenic bacteria (Staphylococcus aureus, Candida albicans, Pseudomonas aeruginosa, Streptococcus pneumoniae, Staphylococcus epidermalis) and further worsened oral health indicators. Thus, a close association was established between symptomatic covid-infection and microbiome changes in the post-covid period; also - between the variables of oral health indicators and the symptomatic course of covid-infection.

Keywords: oral microbiome, COVID-19, population based research, oral health indicators

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Authors: Osman Adiguzel

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Shape-memory alloys are a new class of functional materials with a peculiar property known as shape memory effect. These alloys return to a previously defined shape on heating after deformation in low temperature product phase region and take place in a class of functional materials due to this property. The origin of this phenomenon lies in the fact that the material changes its internal crystalline structure with changing temperature. Shape memory effect is based on martensitic transitions, which govern the remarkable changes in internal crystalline structure of materials. Martensitic transformation, which is a solid state phase transformation, occurs in thermal manner in material on cooling from high temperature parent phase region. This transformation is governed by changes in the crystalline structure of the material. Shape memory alloys cycle between original and deformed shapes in bulk level on heating and cooling, and can be used as a thermal actuator or temperature-sensitive elements due to this property. Martensitic transformations usually occur with the cooperative movement of atoms by means of lattice invariant shears. The ordered parent phase structures turn into twinned structures with this movement in crystallographic manner in thermal induced case. The twinned martensites turn into the twinned or oriented martensite by stressing the material at low temperature martensitic phase condition. The detwinned martensite turns into the parent phase structure on first heating, first cycle, and parent phase structures turn into the twinned and detwinned structures respectively in irreversible and reversible memory cases. On the other hand, shape memory materials are very important and useful in many interdisciplinary fields such as medicine, pharmacy, bioengineering, metallurgy and many engineering fields. The choice of material as well as actuator and sensor to combine it with the host structure is very essential to develop main materials and structures. Copper based alloys exhibit this property in metastable beta-phase region, which has bcc-based structures at high temperature parent phase field, and these structures martensitically turn into layered complex structures with lattice twinning following two ordered reactions on cooling. Martensitic transition occurs as self-accommodated martensite with inhomogeneous shears, lattice invariant shears which occur in two opposite directions, <110 > -type directions on the {110}-type plane of austenite matrix which is basal plane of martensite. This kind of shear can be called as {110}<110> -type mode and gives rise to the formation of layered structures, like 3R, 9R or 18R depending on the stacking sequences on the close-packed planes of the ordered lattice. In the present contribution, x-ray diffraction and transmission electron microscopy (TEM) studies were carried out on two copper based alloys which have the chemical compositions in weight; Cu-26.1%Zn 4%Al and Cu-11%Al-6%Mn. X-ray diffraction profiles and electron diffraction patterns reveal that both alloys exhibit super lattice reflections inherited from parent phase due to the displacive character of martensitic transformation. X-ray diffractograms taken in a long time interval show that locations and intensities of diffraction peaks change with the aging time at room temperature. In particular, some of the successive peak pairs providing a special relation between Miller indices come close each other.

Keywords: Shape memory effect, martensite, twinning, detwinning, self-accommodation, layered structures

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Authors: Kathy Pain, Nalumino Akakandelwa

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The study explores the potential to fill a gap in health and wellbeing evidence for purposeful urban real estate asset management to make investment a powerful force for societal good. Part of a five-year programme investigating the root causes of unhealthy urban development funded by the United Kingdom Prevention Research Partnership (UKPRP), the study pilots the use of a systems mapping approach to identify drivers and barriers to the incorporation of health and wellbeing evidence in urban brownfield asset management decision-making. Urban real estate not only provides space for economic production but also contributes to the quality of life in the local community. Yet market approaches to urban land use have, until recently, insisted that neo-classical technology-driven efficient allocation of economic resources should inform acquisition, operational, and disposal decisions. Buildings in locations with declining economic performance have thus been abandoned, leading to urban decay. Property investors are recognising the inextricable connection between sustainable urban production and quality of life in local communities. The redevelopment and operation of brownfield assets recycle existing buildings, minimising embodied carbon emissions. It also retains established urban spaces with which local communities identify and regenerate places to create a sense of security, economic opportunity, social interaction, and quality of life. Social implications of urban real estate on health and wellbeing and increased adoption of benign sustainability guidance in urban production are driving the need to consider how they affect brownfield real estate asset management decisions. Interviews with real estate upstream decision-makers in the study, find that local social needs and impact analysis is becoming a commercial priority for large-scale urban real estate development projects. Evidence of the social value-added of proposed developments is increasingly considered essential to secure local community support and planning permissions, and to attract sustained inward long-term investment capital flows for urban projects. However, little is known about the contribution of population health and wellbeing to socially sustainable urban projects and the monetary value of the opportunity this presents to improve the urban environment for local communities. We report early findings from collaborations with two leading property companies managing major investments in brownfield urban assets in the UK to consider how the inclusion of health and wellbeing evidence in social valuation can inform perceptions of brownfield development social benefit for asset managers, local communities, public authorities and investors for the benefit of all parties. Using holistic case studies and systems mapping approaches, we explore complex relationships between public health considerations and asset management decisions in urban production. Findings indicate a strong real estate investment industry appetite and potential to include health as a vital component of sustainable real estate social value creation in asset management strategies.

Keywords: brownfield urban assets, health and wellbeing, social needs and impact, social valuation, sustainable real estate, systems mapping

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Authors: Heather Mroz

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Geothermal fluids can provide a nearly unlimited source of renewable energy but are often highly corrosive due to dissolved carbon dioxide (CO2), hydrogen sulphide (H2S), Ammonia (NH3) and chloride ions. The corrosive environment drives material selection for many components, including piping, heat exchangers and pressure vessels, to higher alloys of stainless steel, nickel-based alloys and titanium. The use of these alloys is cost-prohibitive and does not offer the pressure rating of carbon steel. One solution, explosion cladding, has been proven to reduce the capital cost of the geothermal equipment while retaining the mechanical and corrosion properties of both the base metal and the cladded surface metal. Explosion cladding is a solid-state welding process that uses precision explosions to bond two dissimilar metals while retaining the mechanical, electrical and corrosion properties. The process is commonly used to clad steel with a thin layer of corrosion-resistant alloy metal, such as stainless steel, brass, nickel, silver, titanium, or zirconium. Additionally, explosion welding can join a wider array of compatible and non-compatible metals with more than 260 metal combinations possible. The explosion weld is achieved in milliseconds; therefore, no bulk heating occurs, and the metals experience no dilution. By adhering to a strict set of manufacturing requirements, both the shear strength and tensile strength of the bond will exceed the strength of the weaker metal, ensuring the reliability of the bond. For over 50 years, explosion cladding has been used in the oil and gas and chemical processing industries and has provided significant economic benefit in reduced maintenance and lower capital costs over solid construction. The focus of this paper will be on the many benefits of the use of explosion clad in process equipment instead of more expensive solid alloy construction. The method of clad-plate production with explosion welding as well as the methods employed to ensure sound bonding of the metals. It will also include the origins of explosion cladding as well as recent technological developments. Traditionally explosion clad plate was formed into vessels, tube sheets and heads but recent advances include explosion welded piping. The final portion of the paper will give examples of the use of explosion-clad metals in geothermal energy recovery. The classes of materials used for geothermal brine will be discussed, including stainless steels, nickel alloys and titanium. These examples will include heat exchangers (tube sheets), high pressure and horizontal separators, standard pressure crystallizers, piping and well casings. It is important to educate engineers and designers on material options as they develop equipment for geothermal resources. Explosion cladding is a niche technology that can be successful in many situations, like geothermal energy recovery, where high temperature, high pressure and corrosive environments are typical. Applications for explosion clad metals include vessel and heat exchanger components as well as piping.

Keywords: clad metal, explosion welding, separator material, well casing material, piping material

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Authors: Jyh-Ping Chen, Yu-Tin Lai

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Wound healing is a complicated process involving overlapping hemostasis, inflammation, proliferation, and maturation phases. Ideal wound dressings can replace native skin functions in full thickness skin wounds through faster healing rate and also by reducing scar formation. Poly(lactic-co-glycolic acid) (PLGA) is an U.S. FDA approved biodegradable polymer to be used as ideal wound dressing material. Several in vitro and in vivo studies have demonstrated the effectiveness of curcumin in decreasing the release of inflammatory cytokines, inhibiting enzymes associated with inflammations, and scavenging free radicals that are the major cause of inflammation during wound healing. Heparin has binding affinities to various growth factors. With the unique and beneficial features offered by those molecules toward the complex process of wound healing, we postulate a composite wound dressing constructed from PLGA, curcumin and heparin would be a good candidate to accelerate scarless wound healing. In this work, we use electrospinning to prepare curcumin-loaded aligned PLGA nanofibrous membranes (PC NFMs). PC NFMs were further subject to oxygen plasma modification and surfaced-grafted with heparin through carbodiimide-mediated covalent bond formation to prepare curcumin-loaded PLGA-g-heparin (PCH) NFMs. The nanofibrous membranes could act as three-dimensional scaffolds to attract fibroblast migration, reduce inflammation, and increase wound-healing related growth factors concentrations at wound sites. From scanning electron microscopy analysis, the nanofibers in each NFM are with diameters ranging from 456 to 479 nm and with alignment angles within  0.5°. The NFMs show high tensile strength and good water absorptivity and provide suitable pore size for nutrients/wastes transport. Exposure of human dermal fibroblasts to the extraction medium of PC or PCH NFM showed significant protective effects against hydrogen peroxide than PLGA NFM. In vitro wound healing assays also showed that the extraction medium of PCH NFM showed significantly better migration ability toward fibroblasts than PC NFM, which is further better than PLGA NFM. The in vivo healing efficiency of the NFMs was further evaluated by a full thickness excisional wound healing diabetic rat model. After 14 days, PCH NFMs exhibits 86% wound closure rate, which is significantly different from other groups (79% for PC and 73% for PLGA NFM). Real-time PCR analysis indicated PC and PCH NFMs down regulated anti-oxidative enzymes like glutathione peroxidase (GPx) and superoxide dismutase (SOD), which are well-known transcription factors involved in cellular inflammatory responses to stimuli. From histology, the wound area treated with PCH NFMs showed more vascular lumen formation from immunohistochemistry of α-smooth muscle actin. The wound site also had more collagen type III (65.8%) expression and less collagen type I (3.5%) expression, indicating scar-less wound healing. From Western blot analysis, the PCH NFM showed good affinity toward growth factors from increased concentration of transforming growth factor-β (TGF-β) and fibroblast growth factor-2 (FGF-2) at the wound site to accelerate wound healing. From the results, we suggest PCH NFM as a promising candidate for wound dressing applications.

Keywords: Curcumin, heparin, nanofibrous membrane, poly(lactic-co-glycolic acid) (PLGA), wound dressing

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Authors: Emre Kara, Ali Kurşun, Halil Aykul

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The lightweight sandwiches obtained with the use of various core materials such as foams, honeycomb, lattice structures etc., which have high energy absorbing capacity and high strength to weight ratio, are suitable for several applications in transport industry (automotive, aerospace, shipbuilding industry) where saving of fuel consumption, load carrying capacity increase, safety of vehicles and decrease of emission of harmful gases are very important aspects. While the sandwich structures with foams and honeycombs have been applied for many years, there is a growing interest on a new generation sandwiches with micro lattice cores. In order to produce these core structures, various production methods were created with the development of the technology. One of these production technologies is an additive manufacturing technique called selective laser sintering/melting (SLS/SLM) which is very popular nowadays because of saving of production time and achieving the production of complex topologies. The static bending and the dynamic low velocity impact tests of the sandwiches with carbon fiber/epoxy skins and the micro lattice cores produced via SLS/SLM were already reported in just a few studies. The goal of this investigation was the analysis of the flexural response of the sandwiches consisting of glass fiber reinforced plastic (GFRP) skins and the micro lattice cores manufactured via SLS under thermo-mechanical loads in order to compare the results in terms of peak load and absorbed energy values respect to the effect of core cell size, temperature and support span length. The micro lattice cores were manufactured using SLS technology that creates the product drawn by a 3D computer aided design (CAD) software. The lattice cores which were designed as body centered cubic (BCC) model having two different cell sizes (d= 2 and 2.5 mm) with the strut diameter of 0.3 mm were produced using titanium alloy (Ti6Al4V) powder. During the production of all the core materials, the same production parameters such as laser power, laser beam diameter, building direction etc. were kept constant. Vacuum Infusion (VI) method was used to produce skin materials, made of [0°/90°] woven S-Glass prepreg laminates. The combination of the core and skins were implemented under VI. Three point bending tests were carried out by a servo-hydraulic test machine with different values of support span distances (L = 30, 45, and 60 mm) under various temperature values (T = 23, 40 and 60 °C) in order to analyze the influences of support span and temperature values. The failure mode of the collapsed sandwiches has been investigated using 3D computed tomography (CT) that allows a three-dimensional reconstruction of the analyzed object. The main results of the bending tests are: load-deflection curves, peak force and absorbed energy values. The results were compared according to the effect of cell size, support span and temperature values. The obtained results have particular importance for applications that require lightweight structures with a high capacity of energy dissipation, such as the transport industry, where problems of collision and crash have increased in the last years.

Keywords: light-weight sandwich structures, micro lattice cores, selective laser sintering, transport application

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Authors: Keith Schofield, Garry R. Prentice

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The perceptions of the work an academic does, and the environment in which they do it, contributes to the professional identity of that academic. In turn, this has implications for the level of involvement they have in their job, their satisfaction, and their work product. This research explores academic identities in British and Irish institutions and considers the complex interplay between identity, practice, and participation. Theoretical assumptions made in this paper assert that meaningful work has positive effects on work pride, organisational commitment, organisational citizenship, and motivation; when employees participate enthusiastically they are likely to be more engaged, more successful, and more satisfied. Further examination is given to the context in which this participation happens; the nature of institutional process, management, and relationships with colleagues, team members, and students is considered. The present study follows a mixed-methods approach to explore work satisfaction constructs in a number of academic contexts in the UK and Ireland. The quantitative component of this research (Convenience Sample: 155 academics, and support/ administrative staff; 36.1% male, 63.9% female; 60.8% academic staff, 39.2% support/ administration staff; across a number of universities in the UK and Ireland) was based on an established emotional labour model and was tested across gender groups, job roles, and years of service. This was complimented by qualitative semi-structured interviews (Purposive Sample: 10 academics, and 5 support/ administrative staff across the same universities in the UK and Ireland) to examine various themes including values within academia, work conditions, professional development, and transmission of knowledge to students. Experiences from both academic and support perspectives were sought in order to gain a holistic view of academia and to provide an opportunity to explore the dynamic of the academic/administrator relationship within the broader institutional context. The quantitative emotional labour model, tested via a path analysis, provided a robust description of the relationships within the data. The significant relationships found within the quantitative emotional labour model included a link between non-expression of true feelings resulting in emotional labourious work and lower levels of intrinsic motivation and higher levels of extrinsic motivation. Higher levels of intrinsic motivation also linked positively to work pride. These findings were further explored in the qualitative elements of the research where themes emerged including the disconnection between faculty management and staff, personal fulfilment and the friction between the identities of teacher, researcher/ practitioner and administrator. The implications of the research findings from this study are combined and discussed in relation to possible identity-related and emotional labour management-related interventions. Further, suggestions are made to institutions concerning the application of these findings including the development of academic practices, with specific reference to the duality of identity required to service the combined teacher/ researcher role. Broader considerations of the paper include how individuals and institutions may engage with the changing nature of students-as-consumers as well as a recommendation to centralise personal fulfillment through the development of professional academic identities.

Keywords: academic work, emotional labour, identity friction, mixed methods

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: Abdoulaye Maihatchi Ahamed, Zubin Arora, Benjamin Swobada, Jean-yves Lansot, Alexandre Chagnes

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Lithium-ion battery (LiB) is the technology of choice in the development of electric vehicles. But there are still many challenges, including the development of positive electrode materials exhibiting high cycle ability, high energy density, and low environmental impact. For this latter, LiBs must be manufactured in a circular approach by developing the appropriate strategies to reuse and recycle them. Presently, the recycling of LiBs is carried out by the pyrometallurgical route, but more and more processes implement or will implement the hydrometallurgical route or a combination of pyrometallurgical and hydrometallurgical operations. After producing the black mass by mineral processing, the hydrometallurgical process consists in leaching the black mass in order to uptake the metals contained in the cathodic material. Then, these metals are extracted selectively by liquid-liquid extraction, solid-liquid extraction, and/or precipitation stages. However, liquid-liquid extraction combined with precipitation/crystallization steps is the most implemented operation in the LiB recycling process to selectively extract copper, aluminum, cobalt, nickel, manganese, and lithium from the leaching solution and precipitate these metals as high-grade sulfate or carbonate salts. Liquid-liquid extraction consists in contacting an organic solvent and an aqueous feed solution containing several metals, including the targeted metal(s) to extract. The organic phase is non-miscible with the aqueous phase. It is composed of an extractant to extract the target metals and a diluent, which is usually aliphatic kerosene produced from the petroleum industry. Sometimes, a phase modifier is added in the formulation of the extraction solvent to avoid the third phase formation. The extraction properties of the diluent do not depend only on the chemical structure of the extractant, but it may also depend on the nature of the diluent. Indeed, the interactions between the diluent can influence more or less the interactions between extractant molecules besides the extractant-diluent interactions. Only a few studies in the literature addressed the influence of the diluent on the extraction properties, while many studies focused on the effect of the extractants. Recently, new low-carbon footprint aliphatic diluents were produced by catalytic dearomatisation and distillation of bio-based oil. This study aims at investigating the influence of the nature of the diluent on the extraction properties of three extractants towards cobalt, nickel, manganese, copper, aluminum, and lithium: Cyanex®272 for nickel-cobalt separation, DEHPA for manganese extraction, and Acorga M5640 for copper extraction. The diluents used in the formulation of the extraction solvents are (i) low-odor aliphatic kerosene produced from the petroleum industry (ELIXORE 180, ELIXORE 230, ELIXORE 205, and ISANE IP 175) and (ii) bio-sourced aliphatic diluents (DEV 2138, DEV 2139, DEV 1763, DEV 2160, DEV 2161 and DEV 2063). After discussing the effect of the diluents on the extraction properties, this conference will address the development of a low carbon footprint process based on the use of the best bio-sourced diluent for the production of high-grade cobalt sulfate, nickel sulfate, manganese sulfate, and lithium carbonate, as well as metal copper.

Keywords: diluent, hydrometallurgy, lithium-ion battery, recycling

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Authors: Elisabetta Cianfanelli, Maria Claudia Coppola, Margherita Tufarelli

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Design practices throughout history return a critical understanding of society since they always conveyed values and meanings aimed at (re)framing reality by acting in everyday life: here, design gains cultural and normative character, since its artifacts, services, and environments hold the power to intercept, influence and inspire thoughts, behaviors, and relationships. In this sense, design can be persuasive, engaging in the production of worlds and, as such, acting in the space between poietics and politics so that chasing preferable futures and their aesthetic strategies becomes a matter full of political responsibility. This resonates with contemporary landscapes of radical interdependencies challenging designers to focus on complex socio-technical systems and to better support values such as equality and justice for both humans and nonhumans. In fact, it is in times of crisis and structural uncertainty that designers turn into visionaries at the service of society, envisioning scenarios and dwelling in the territories of imagination to conceive new fictions and frictions to be added to the thickness of the real. Here, design’s main tasks are to develop options, to increase the variety of choices, to cultivate its role as scout, jester, agent provocateur for the public, so that design for transformation emerges, making an explicit commitment to society, furthering structural change in a proactive and synergic manner. However, the exploration of possible futures is both a trap and a trampoline because, although it embodies a radical research tool, it raises various challenges when the design process goes further in the translation of such vision into an artefact - whether tangible or intangible -, through which it should deliver that bit of future into everyday experience. Today designers are making up new tools and practices to tackle current wicked challenges, combining their approaches with other disciplinary domains: futuring through design, thus, rises from research strands like speculative design, design fiction, and critical design, where the blending of design approaches and futures thinking brings an action-oriented and product-based approach to strategic insights. The contribution positions at the intersection of those approaches, aiming at discussing design’s tools of inquiry through which it is possible to grasp the agency of imagined futures into present time. Since futures are not remote, they actively participate in creating path-dependent decisions, crystallized into designed artifacts par excellence, prototypes, and their conceptual other, provotypes: with both being unfinished and multifaceted, the first ones are effective in reiterating solutions to problems already framed, while the second ones prove to be useful when the goal is to explore and break boundaries, bringing closer preferable futures. By focusing on some provotypes throughout history which challenged markets and, above all, social and cultural structures, the contribution’s final aim is understanding the knowledge produced by provotypes, understood as design spaces where designs’s humanistic side might help developing a deeper sensibility about uncertainty and, most of all, the unfinished feature of societal artifacts, whose experimentation would leave marks and traces to build up f(r)ictions as vital sparks of plurality and collective life.

Keywords: speculative design, provotypes, design knowledge, political theory

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Authors: Rouzbeh Jafari, Joe Nava

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This study includes learnings from an engineering practice normally performed on large scale biohydrogen processes. If properly scale-up is done, biohydrogen can be a reliable pathway for biowaste valorization. Most of the studies on biohydrogen process development have used model feedstock to investigate process key performance indicators (KPIs). This study does not intend to compare different technologies with model feedstock. However, it reports economic drivers and technical challenges which help in developing a road map for expanding biohydrogen economy deployment in Canada. BBA is a consulting firm responsible for the design of hydrogen production projects. Through executing these projects, activity has been performed to identify, register and mitigate technical drawbacks of large-scale hydrogen production. Those learnings, in this study, have been applied to the biohydrogen process. Through data collected by a comprehensive literature review, a base case has been considered as a reference, and several case studies have been performed. Critical parameters of the process were identified and through common engineering practice (process design, simulation, cost estimate, and life cycle assessment) impact of these parameters on the commercialization risk matrix and class 5 cost estimations were reported. The process considered in this study is food waste and woody biomass dark fermentation. To propose a reliable road map to develop a sustainable biohydrogen production process impact of critical parameters was studied on the end-to-end process. These parameters were 1) feedstock composition, 2) feedstock pre-treatment, 3) unit operation selection, and 4) multi-product concept. A couple of emerging technologies also were assessed such as photo-fermentation, integrated dark fermentation, and using ultrasound and microwave to break-down feedstock`s complex matrix and increase overall hydrogen yield. To properly report the impact of each parameter KPIs were identified as 1) Hydrogen yield, 2) energy consumption, 3) secondary waste generated, 4) CO2 footprint, 5) Product profile, 6) $/kg-H2 and 5) environmental impact. The feedstock is the main parameter defining the economic viability of biohydrogen production. Through parametric studies, it was found that biohydrogen production favors feedstock with higher carbohydrates. The feedstock composition was varied, by increasing one critical element (such as carbohydrate) and monitoring KPIs evolution. Different cases were studied with diverse feedstock, such as energy crops, wastewater slug, and lignocellulosic waste. The base case process was applied to have reference KPIs values and modifications such as pretreatment and feedstock mix-and-match were implemented to investigate KPIs changes. The complexity of the feedstock is the main bottleneck in the successful commercial deployment of the biohydrogen process as a reliable pathway for waste valorization. Hydrogen yield, reaction kinetics, and performance of key unit operations highly impacted as feedstock composition fluctuates during the lifetime of the process or from one case to another. In this case, concept of multi-product becomes more reliable. In this concept, the process is not designed to produce only one target product such as biohydrogen but will have two or multiple products (biohydrogen and biomethane or biochemicals). This new approach is being investigated by the BBA team and the results will be shared in another scientific contribution.

Keywords: biohydrogen, process scale-up, economic evaluation, commercialization uncertainties, hydrogen economy

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Authors: Masoume Ehsani, Ning Zhu, Huu Doan, Ali Lohi, Amira Abdelrasoul

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Membrane fouling poses severe challenges in membrane-based wastewater treatment applications. Ultrasound (US) has been considered an effective fouling remediation technique in filtration processes. Bubble cavitation in the liquid medium results from the alternating rarefaction and compression cycles during the US irradiation at sufficiently high acoustic pressure. Cavitation microbubbles generated under US irradiation can cause eddy current and turbulent flow within the medium by either oscillating or discharging energy to the system through microbubble explosion. Turbulent flow regime and shear forces created close to the membrane surface cause disturbing the cake layer and dislodging the foulants, which in turn improve the cleaning efficiency and filtration performance. Therefore, the number, size, velocity, and oscillation pattern of the microbubbles created in the liquid medium play a crucial role in foulant detachment and permeate flux recovery. The goal of the current study is to gain in depth understanding of the influence of the US power intensity and frequency on the microbubble dynamics and its characteristics generated under US irradiation. In comparison with other imaging techniques, the synchrotron in-line Phase Contrast Imaging technique at the Canadian Light Source (CLS) allows in-situ observation and real-time visualization of microbubble dynamics. At CLS biomedical imaging and therapy (BMIT) polychromatic beamline, the effective parameters were optimized to enhance the contrast gas/liquid interface for the accuracy of the qualitative and quantitative analysis of bubble cavitation within the system. With the high flux of photons and the high-speed camera, a typical high projection speed was achieved; and each projection of microbubbles in water was captured in 0.5 ms. ImageJ software was used for post-processing the raw images for the detailed quantitative analyses of microbubbles. The imaging has been performed under the US power intensity levels of 50 W, 60 W, and 100 W, in addition to the US frequency levels of 20 kHz, 28 kHz, and 40 kHz. For the duration of 2 seconds of imaging, the effect of the US power and frequency on the average number, size, and fraction of the area occupied by bubbles were analyzed. Microbubbles’ dynamics in terms of their velocity in water was also investigated. For the US power increase of 50 W to 100 W, the average bubble number and the average bubble diameter were increased from 746 to 880 and from 36.7 µm to 48.4 µm, respectively. In terms of the influence of US frequency, a fewer number of bubbles were created at 20 kHz (average of 176 bubbles rather than 808 bubbles at 40 kHz), while the average bubble size was significantly larger than that of 40 kHz (almost seven times). The majority of bubbles were captured close to the membrane surface in the filtration unit. According to the study observations, membrane cleaning efficiency is expected to be improved at higher US power and lower US frequency due to the higher energy release to the system by increasing the number of bubbles or growing their size during oscillation (optimum condition is expected to be at 20 kHz and 100 W).

Keywords: bubble dynamics, cavitational bubbles, membrane fouling, ultrasonic cleaning

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Authors: Abdul Wohab

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Context: The role of religion in the transformation of Bangladesh society has been significant since 1975. There has been a rise in religious presence, particularly Islam, in both private and public spheres supported by the state apparatuses. In 2009, a 'secular' political party came into power for the second time since independence and initiated the modernization of religious education systems. This research focuses on the transformation observed among the educated middle class who now prefer their children to attend modern, English medium madrasas that offer both religion-based and secular education. Research Aim: This research aims to investigate two main questions: a) what motivates the educated middle class to send their children to madrasa education? b) To what extent can it be argued that Bangladeshi society is transforming from its secular nature to being more religious?Methodology: The research applies a combination of primary and secondary methods. Case studies serve as the primary method, allowing for an in-depth exploration of the motivations of the educated middle class. The secondary method involves analyzing published news articles, op-eds, and websites related to madrasa education, as well as studying the reading syllabus of Aliya and Qwami madrasas in Bangladesh. Findings: Preliminary findings indicate that the educated middle class chooses madrasa education for reasons such as remembering and praying for their departed relatives, keeping their children away from substance abuse, fostering moral and ethical values, and instilling respect for seniors and relatives. The research also reveals that religious education is believed to help children remain morally correct according to the Quran and Hadith. Additionally, the establishment of madrasas in Bangladesh is attributed to economic factors, with demand and supply mechanisms playing a significant role. Furthermore, the findings suggest that government-run primary education institutions in rural areas face more challenges in enrollment compared to religious educational institutions like madrasas. Theoretical Importance: This research contributes to the understanding of societal transformation and the role of religion in this process. By examining the case of Bangladesh, it provides insights into how religion influences education choices and societal values. Data Collection and Analysis Procedures: Data for this research is collected through case studies, including interviews and observations of educated middle-class families who send their children to madrasas. In addition, analysis is conducted on relevant published materials such as news articles, op-eds, and websites. The reading syllabus of Aliya and Qwami madrasas is also analyzed to gain a comprehensive understanding of the education system. Questions Addressed: The research addresses two questions: a) what motivates the educated middle class to choose madrasa education for their children? b) To what extent can it be argued that Bangladeshi society is transforming from its secular nature to being more religious?Conclusion: The preliminary findings of this research highlight the motivations of the educated middle class in opting for madrasa education, including the desire to maintain religious traditions, promote moral values, and provide a strong foundation for their children. It also suggests that Bangladeshi society is experiencing a transformation towards a more religious orientation. This research contributes to the understanding of societal changes and the role of religion within Bangladesh, shedding light on the complex dynamics between religion and education.

Keywords: madrasa education, transformation, Bangladesh, religion and society, education

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Authors: Piotr Jablonski, Krzysztof Mars, Wiktor Niemiec, Agnieszka Kyziol, Marek Hebda, Halina Krawiec, Karol Kyziol

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NiTi alloys, possessing unique mechanical properties such as pseudoelasticity and shape memory effect (SME), are suitable for many applications, including implanthology and biomedical devices. Additionally, these alloys have similar values of elastic modulus to those of human bones, what is very important in orthopedics. Unfortunately, the environment of physiological fluids in vivo causes unfavorable release of Ni ions, which in turn may lead to metalosis as well as allergic reactions and toxic effects in the body. For these reasons, the surface properties of NiTi alloys should be improved to increase corrosion resistance, taking into account biological properties, i.e. excellent biocompatibility. The prospective in this respect are layers based on DLC (Diamond-Like Carbon) structures, which are an attractive solution for many applications in implanthology. These coatings (DLC), usually obtained by PVD (Physical Vapour Deposition) and PA CVD (Plasma Activated Chemical Vapour Deposition) methods, can be also modified by doping with other elements like silicon, nitrogen, oxygen, fluorine, titanium and silver. These methods, in combination with a suitably designed structure of the layers, allow the possibility co-decide about physicochemical and biological properties of modified surfaces. Mentioned techniques provide specific physicochemical properties of substrates surface in a single technological process. In this work, the following types of layers based on DLC structures (incl. Si-DLC or Si/N-DLC) were proposed as prospective and attractive approach in surface functionalization of shape memory alloy. Nitinol substrates were modified in plasma conditions, using RF CVD (Radio Frequency Chemical Vapour Deposition). The influence of plasma treatment on the useful properties of modified substrates after deposition DLC layers doped with silica and/or nitrogen atoms, as well as only pre-treated in O2 NH3 plasma atmosphere in a RF reactor was determined. The microstructure and topography of the modified surfaces were characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM). Furthermore, the atomic structure of coatings was characterized by IR and Raman spectroscopy. The research also included the evaluation of surface wettability, surface energy as well as the characteristics of selected mechanical and biological properties of the layers. In addition, the corrosion properties of alloys after and before modification in the physiological saline were also investigated. In order to determine the corrosion resistance of NiTi in the Ringer solution, the potentiodynamic polarization curves (LSV – Linear Sweep Voltamperometry) were plotted. Furthermore, the evolution of corrosion potential versus immersion time of TiNi alloy in Ringer solution was performed. Based on all carried out research, the usefullness of proposed modifications of nitinol for medical applications was assessed. It was shown, inter alia, that the obtained Si-DLC layers on the surface of NiTi alloy exhibit a characteristic complex microstructure, increased surface development, which is an important aspect in improving the osteointegration of an implant. Furthermore, the modified alloy exhibits biocompatibility, the transfer of the metal (Ni, Ti) to Ringer’s solution is clearly limited.

Keywords: bioactive coatings, corrosion resistance, doped DLC structure, NiTi alloy, RF CVD

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Authors: André Python

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To this day, terrorism persists as a worldwide threat, exemplified by the recent deadly attacks in January 2015 in Paris and the ongoing massacres perpetrated by ISIS in Iraq and Syria. In response to this threat, states deploy various counterterrorism measures, the cost of which could be reduced through effective preventive measures. In order to increase the efficiency of preventive measures, policy-makers may benefit from accurate predictive models that are able to capture the complex spatial dynamics of terrorism occurring at a local scale. Despite empirical research carried out at country-level that has confirmed theories explaining the diffusion processes of terrorism across space and time, scholars have failed to assess diffusion’s theories on a local scale. Moreover, since scholars have not made the most of recent statistical modelling approaches, they have been unable to build up predictive models accurate in both space and time. In an effort to address these shortcomings, this research suggests a novel approach to systematically assess the theories of terrorism’s diffusion on a local scale and provide a predictive model of the local spatial dynamics of terrorism worldwide. With a focus on the lethal terrorist events that occurred after 9/11, this paper addresses the following question: why and how does lethal terrorism diffuse in space and time? Based on geolocalised data on worldwide terrorist attacks and covariates gathered from 2002 to 2013, a binomial spatio-temporal point process is used to model the probability of terrorist attacks on a sphere (the world), the surface of which is discretised in the form of Delaunay triangles and refined in areas of specific interest. Within a Bayesian framework, the model is fitted through an integrated nested Laplace approximation - a recent fitting approach that computes fast and accurate estimates of posterior marginals. Hence, for each location in the world, the model provides a probability of encountering a lethal terrorist attack and measures of volatility, which inform on the model’s predictability. Diffusion processes are visualised through interactive maps that highlight space-time variations in the probability and volatility of encountering a lethal attack from 2002 to 2013. Based on the previous twelve years of observation, the location and lethality of terrorist events in 2014 are statistically accurately predicted. Throughout the global scope of this research, local diffusion processes such as escalation and relocation are systematically examined: the former process describes an expansion from high concentration areas of lethal terrorist events (hotspots) to neighbouring areas, while the latter is characterised by changes in the location of hotspots. By controlling for the effect of geographical, economical and demographic variables, the results of the model suggest that the diffusion processes of lethal terrorism are jointly driven by contagious and non-contagious factors that operate on a local scale – as predicted by theories of diffusion. Moreover, by providing a quantitative measure of predictability, the model prevents policy-makers from making decisions based on highly uncertain predictions. Ultimately, this research may provide important complementary tools to enhance the efficiency of policies that aim to prevent and combat terrorism.

Keywords: diffusion process, terrorism, spatial dynamics, spatio-temporal modeling

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Authors: Yujie Yuan, Yiyang Fan, Hong Fan

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Objective: The RNA methylation recognition protein Aly/REF export factor (ALYREF) is considered one type of “reader” protein acting as a recognition protein of m5C, has been reported involved in several biological progresses including cancer initiation and progression. 5-methylcytosine (m5C) is a conserved and prevalent RNA modification in all species, as accumulating evidence suggests its role in the promotion of tumorigenesis. It has been claimed that ALYREF mediates nuclear export of mRNA with m5C modification and regulates biological effects of cancer cells. However, the systematical regulatory pathways of ALYREF in cancer tissues have not been clarified, yet. Methods: The expression level of ALYREF in pan-cancer and their normal tissues was compared through the data acquired from The Cancer Genome Atlas (TCGA). The University of Alabama at Birmingham Cancer data analysis Portal UALCAN was used to analyze the relationship between ALYREF and clinical pathological features. The relationship between the expression level of ALYREF and prognosis of pan-cancer, and the correlation genes of ALYREF were figured out by using Gene Expression Correlation Analysis database GEPIA. Immune related genes were obtained from TISIDB (an integrated repository portal for tumor-immune system interactions). Immune-related research was conducted by using Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and TIMER. Results: Based on the data acquired from TCGA, ALYREF has an obviously higher-level expression in various types of cancers compared with relevant normal tissues excluding thyroid carcinoma and kidney chromophobe. The immunohistochemical images on The Human Protein Atlas showed that ALYREF can be detected in cytoplasm, membrane, but mainly located in nuclear. In addition, a higher expression level of ALYREF in tumor tissue generates a poor prognosis in majority of cancers. According to the above results, cancers with a higher expression level of ALYREF compared with normal tissues and a significant correlation between ALYREF and prognosis were selected for further analysis. By using TISIDB, we found that portion of ALYREF co-expression genes (such as BIRC5, H2AFZ, CCDC137, TK1, and PPM1G) with high Pearson correlation coefficient (PCC) were involved in anti-tumor immunity or affect resistance or sensitivity to T cell-mediated killing. Furthermore, based on the results acquired from GEPIA, there was significant correlation between ALYREF and PD-L1. It was exposed that there is a negative correlation between the expression level of ALYREF and ESTIMATE score. Conclusion: The present study indicated that ALYREF plays a vital and universal role in cancer initiation and progression of pan-cancer through regulating mitotic progression, DNA synthesis and metabolic process, and RNA processing. The correlation between ALYREF and PD-L1 implied ALYREF may affect the therapeutic effect of immunotherapy of tumor. More evidence revealed that ALYREF may play an important role in tumor immunomodulation. The correlation between ALYREF and immune cell infiltration level indicated that ALYREF can be a potential therapeutic target. Exploring the regulatory mechanism of ALYREF in tumor tissues may expose the reason for poor efficacy of immunotherapy and offer more directions of tumor treatment.

Keywords: ALYREF, pan-cancer, immunotherapy, PD-L1

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Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Alessandra Swiny, Michalis Georgiou, Yiorgos Hadjichristou

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This paper focuses on the questions raised through the work of Unit 5: ‘In/Out of crisis, emergent and adaptive’; an architectural research-based studio at the University of Nicosia. It focusses on sustainable architectural and urban explorations tackling with the ever growing crises in its various types, phases and locations. ‘Great crisis situations’ are seen as ‘great chances’ that trigger investigations for further development and evolution of the built environment in an ultimate sustainable approach. The crisis is taken as an opportunity to rethink the urban and architectural directions as new forces for inventions leading to emergent and adaptive built environments. The Unit 5’s identity and environment facilitates the students to respond optimistically, alternatively and creatively towards the global current crisis. Mark Wigley’s notion that “crises are ultimately productive” and “They force invention” intrigued and defined the premises of the Unit. ‘Weather and nature are coauthors of the built environment’ Jonathan Hill states in his ‘weather architecture’ discourse. The weather is constantly changing and new environments, the subnatures are created which derived from the human activities David Gissen explains. The above set of premises triggered innovative responses by the Unit’s students. They thoroughly investigated the various kinds of crisis and their causes in relation to their various types of Terrains. The tools used for the research and investigation were chosen in contradictive pairs to generate further crisis situations: The re-used/salvaged competed with the new, the handmade rivalling with the fabrication, the analogue juxtaposed with digital. Students were asked to delve into state of art technologies in order to propose sustainable emergent and adaptive architectures and Urbanities, having though always in mind that the human and the social aspects of the community should be the core of the investigation. The resulting unprecedented spatial conditions and atmospheres of the emergent new ways of living are deemed to be the ultimate aim of the investigation. Students explored a variety of sites and crisis conditions such as: The vague terrain of the Green Line in Nicosia, the lost footprints of the sinking Venice, the endangered Australian coral reefs, the earthquake torn town of Crevalcore, and the decaying concrete urbanscape of Athens. Among other projects, ‘the plume project’ proposes a cloud-like, floating and almost dream-like living environment with unprecedented spatial conditions to the inhabitants of the coal mine of Centralia, USA, not just to enable them to survive but even to prosper in this unbearable environment due to the process of the captured plumes of smoke and heat. Existing water wells inspire inversed vertical structures creating a new living underground network, protecting the nomads from catastrophic sand storms in the Araoune of Mali. “Inverted utopia: Lost things in the sand”, weaves a series of tea-houses and a library holding lost artifacts and transcripts into a complex underground labyrinth by the utilization of the sand solidification technology. Within this methodology, crisis is seen as a mechanism for allowing an emergence of new and fascinating ultimate sustainable future cultures and cities.

Keywords: adaptive built environments, crisis as opportunity, emergent urbanities, forces for inventions

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Authors: Mariam Jaber, Abdullah Yahya, Mohammad Alkhedher

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The shift toward sustainable energy solutions increasingly focuses on hydrogen, recognized for its potential as a clean energy carrier. Despite its benefits, hydrogen storage poses significant challenges, primarily due to its low energy density and high volatility. Among the various solutions, pressure vessels designed for hydrogen storage range from Type I to Type V, each tailored for specific needs and benefits. Notably, Type V vessels, with their all-composite, liner-less design, significantly reduce weight and costs while optimizing space and decreasing maintenance demands. This study focuses on optimizing Type V hydrogen storage tanks by examining how different shapes affect performance in drop tests—a crucial aspect of achieving ISO 15869 certification. This certification ensures that if a tank is dropped, it will fail in a controlled manner, ideally by leaking before bursting. While cylindrical vessels are predominant in mobile applications due to their manufacturability and efficient use of space, spherical vessels offer superior stress distribution and require significantly less material thickness for the same pressure tolerance, making them advantageous for high-pressure scenarios. However, spherical tanks are less efficient in terms of packing and more complex to manufacture. Additionally, this study introduces toroidal vessels to assess their performance relative to the more traditional shapes, noting that the toroidal shape offers a more space-efficient option. The research evaluates how different shapes—spherical, cylindrical, and toroidal—affect drop test outcomes when combined with various composite materials and layup configurations. The ultimate goal is to identify optimal vessel geometries that enhance the safety and efficiency of hydrogen storage systems. For our materials, we selected high-performance composites such as Carbon T-700/Epoxy, Kevlar/Epoxy, E-Glass Fiber/Epoxy, and Basalt/Epoxy, configured in various orientations like [0,90]s, [45,-45]s, and [54,-54]. Our tests involved dropping tanks from different angles—horizontal, vertical, and 45 degrees—with an internal pressure of 35 MPa to replicate real-world scenarios as closely as possible. We used finite element analysis and first-order shear deformation theory, conducting tests with the Abaqus Explicit Dynamics software, which is ideal for handling the quick, intense stresses of an impact. The results from these simulations will provide valuable insights into how different designs and materials can enhance the durability and safety of hydrogen storage tanks. Our findings aim to guide future designs, making them more effective at withstanding impacts and safer overall. Ultimately, this research will contribute to the broader field of lightweight composite materials and polymers, advancing more innovative and practical approaches to hydrogen storage. By refining how we design these tanks, we are moving toward more reliable and economically feasible hydrogen storage solutions, further emphasizing hydrogen's role in the landscape of sustainable energy carriers.

Keywords: hydrogen storage, drop test, composite materials, type V tanks, finite element analysis

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Authors: Simrat Kaur, Fatema Diwan, Brad Reddersen

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The unsustainable and injudicious use of natural renewable resources beyond the self-replenishment limits of our planet has proved catastrophic. Most of the Earth’s resources, including land, water, minerals, and biodiversity, have been overexploited. Owing to this, there is a steep rise in the global events of natural calamities of contrasting nature, such as torrential rains, storms, heat waves, rising sea levels, and megadroughts. These are all interconnected through common elements, namely oceanic currents and land’s the green cover. The deforestation fueled by the ‘economic elites’ or the global players have already cleared massive forests and ecological biomes in every region of the globe, including the Amazon. These were the natural carbon sinks prevailing and performing CO2 sequestration for millions of years. The forest biomes have been turned into mono cultivation farms to produce feedstock crops such as soybean, maize, and sugarcane; which are one of the biggest green house gas emitters. Such unsustainable agriculture practices only provide feedstock for livestock and food processing industries with huge carbon and water footprints. These are two main factors that have ‘cause and effect’ relationships in the context of climate change. In contrast to organic and sustainable farming, the mono-cultivation practices to produce food, fuel, and feedstock using chemicals devoid of the soil of its fertility, abstract surface, and ground waters beyond the limits of replenishment, emit green house gases, and destroy biodiversity. There are numerous cases across the planet where due to overuse; the levels of surface water reservoir such as the Lake Mead in Southwestern USA and ground water such as in Punjab, India, have deeply shrunk. Unlike the rain fed food production system on which the poor communities of the world relies; the blue water (surface and ground water) dependent mono-cropping for industrial and processed food create water deficit which put the burden on the domestic users. Excessive abstraction of both surface and ground waters for high water demanding feedstock (soybean, maize, sugarcane), cereal crops (wheat, rice), and cash crops (cotton) have a dual and synergistic impact on the global green house gas emissions and prevalence of megadroughts. Both these factors have elevated global temperatures, which caused cascading events such as soil water deficits, flash fires, and unprecedented burning of the woods, creating megafires in multiple continents, namely USA, South America, Europe, and Australia. Therefore, it is imperative to reduce the green and blue water footprints of agriculture and industrial sectors through recycling of black and gray waters. This paper explores various opportunities for successful implementation of wastewater management for drought preparedness in high risk communities.

Keywords: wastewater, drought, biodiversity, water footprint, nutrient recovery, algae

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Authors: Osman Adiguzel

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Shape memory alloys take place in a class of smart materials by exhibiting a peculiar property called the shape memory effect. This property is characterized by the recoverability of two certain shapes of material at different temperatures. These materials are often called smart materials due to their functionality and their capacity of responding to changes in the environment. Shape memory materials are used as shape memory devices in many interdisciplinary fields such as medicine, bioengineering, metallurgy, building industry and many engineering fields. The shape memory effect is performed thermally by heating and cooling after first cooling and stressing treatments, and this behavior is called thermoelasticity. This effect is based on martensitic transformations characterized by changes in the crystal structure of the material. The shape memory effect is the result of successive thermally and stress-induced martensitic transformations. Shape memory alloys exhibit thermoelasticity and superelasticity by means of deformation in the low-temperature product phase and high-temperature parent phase region, respectively. Superelasticity is performed by stressing and releasing the material in the parent phase region. Loading and unloading paths are different in the stress-strain diagram, and the cycling loop reveals energy dissipation. The strain energy is stored after releasing, and these alloys are mainly used as deformation absorbent materials in control of civil structures subjected to seismic events, due to the absorbance of strain energy during any disaster or earthquake. Thermal-induced martensitic transformation occurs thermally on cooling, along with lattice twinning with cooperative movements of atoms by means of lattice invariant shears, and ordered parent phase structures turn into twinned martensite structures, and twinned structures turn into the detwinned structures by means of stress-induced martensitic transformation by stressing the material in the martensitic condition. Thermal induced transformation occurs with the cooperative movements of atoms in two opposite directions, <110 > -type directions on the {110} - type planes of austenite matrix which is the basal plane of martensite. Copper-based alloys exhibit this property in the metastable β-phase region, which has bcc-based structures at high-temperature parent phase field. Lattice invariant shear and twinning is not uniform in copper-based ternary alloys and gives rise to the formation of complex layered structures, depending on the stacking sequences on the close-packed planes of the ordered parent phase lattice. In the present contribution, x-ray diffraction and transmission electron microscopy (TEM) studies were carried out on two copper-based CuAlMn and CuZnAl alloys. X-ray diffraction profiles and electron diffraction patterns reveal that both alloys exhibit superlattice reflections inherited from the parent phase due to the displacive character of martensitic transformation. X-ray diffractograms taken in a long time interval show that diffraction angles and intensities of diffraction peaks change with the aging duration at room temperature. In particular, some of the successive peak pairs providing a special relation between Miller indices come close to each other. This result refers to the rearrangement of atoms in a diffusive manner.

Keywords: shape memory effect, martensitic transformation, reversibility, superelasticity, twinning, detwinning

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Authors: Ruth Leitch, Joanne Hughes

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This paper presents the findings of a three-year government-funded study (ILiAD) that aimed to understand the reasons for differential educational achievement within and between socially and economically deprived areas in Northern Ireland. Previous international studies have concluded that there is a positive correlation between deprivation and underachievement. Our preliminary secondary data analysis suggested that the factors involved in educational achievement within multiple deprived areas may be more complex than this, with some areas of high multiple deprivation having high levels of student attainment, whereas other less deprived areas demonstrated much lower levels of student attainment, as measured by outcomes on high stakes national tests. The study proposed that no single explanation or disparate set of explanations could easily account for the linkage between levels of deprivation and patterns of educational achievement. Using a social capital perspective that centralizes the connections within and between individuals and social networks in a community as a valuable resource for educational achievement, the ILiAD study involved a multi-level case study analysis of seven community sites in Northern Ireland, selected on the basis of religious composition (housing areas are largely segregated by religious affiliation), measures of multiple deprivation and differentials in educational achievement. The case study approach involved three (interconnecting) levels of qualitative data collection and analysis - what we have termed Micro (or community/grassroots level) understandings, Meso (or school level) explanations and Macro (or policy/structural) factors. The analysis combines a statistical mapping of factors with qualitative, in-depth data interpretation which, together, allow for deeper understandings of the dynamics and contributory factors within and between the case study sites. Thematic analysis of the qualitative data reveals both cross-cutting factors (e.g. demographic shifts and loss of community, place of the school in the community, parental capacity) and analytic case studies of explanatory factors associated with each of the community sites also permit a comparative element. Issues arising from the qualitative analysis are classified either as drivers or inhibitors of educational achievement within and between communities. Key issues that are emerging as inhibitors/drivers to attainment include: the legacy of the community conflict in Northern Ireland, not least in terms of inter-generational stress, related with substance abuse and mental health issues; differing discourses on notions of ‘community’ and ‘achievement’ within/between community sites; inter-agency and intra-agency levels of collaboration and joined-up working; relationship between the home/school/community triad and; school leadership and school ethos. At this stage, the balance of these factors can be conceptualized in terms of bonding social capital (or lack of it) within families, within schools, within each community, within agencies and also bridging social capital between the home/school/community, between different communities and between key statutory and voluntary organisations. The presentation will outline the study rationale, its methodology, present some cross-cutting findings and use an illustrative case study of the findings from a community site to underscore the importance of attending to community differences when trying to engage in research to understand and improve educational attainment for all.

Keywords: educational achievement, multiple deprivation, community case studies, social capital

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Authors: Chris Fersterer, Col Fay, Tobias Danielmeier, Kat Achterberg, Scott Willis

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New Zealand, an island nation, has an extensive coastline peppered with small communities of iconic buildings known as Bachs. Post WWII, these modest buildings were constructed by their owners as retreats and generally were small, low cost, often using recycled material and often they fell below current acceptable building standards. In the latter part of the 20^th century, real estate prices in many of these communities remained low and these areas became permanent residences for people attracted to this affordable lifestyle choice. The Blueskin Resilient Communities Trust (BRCT) is an organisation that recognises the vulnerability of communities in low lying settlements as now being prone to increased flood threat brought about by climate change and sea level rise. Some of the inhabitants of Blueskin Bay, Otago, NZ have already found their properties to be un-insurable because of increased frequency of flood events and property values have slumped accordingly. Territorial authorities also acknowledge this increased risk and have created additional compliance measures for new buildings that are less than 2 m above tidal peaks. Community resilience becomes an additional concern where inhabitants are attracted to a lifestyle associated with a specific location and its people when this lifestyle is unable to be met in a suburban or city context. Traditional models of social housing fail to provide the sense of community connectedness and identity enjoyed by the current residents of Blueskin Bay. BRCT have partnered with the Otago Polytechnic Design School to design a new form of community housing that can react to this environmental change. It is a longitudinal project incorporating participatory approaches as a means of getting people ‘on board’, to understand complex systems and co-develop solutions. In the first period, they are seeking industry support and funding to develop a transportable and fully self-contained housing model that exploits current technologies. BRCT also hope that the building will become an educational tool to highlight climate change issues facing us today. This paper uses the Climate Safe House (CSH) as a case study for education in architectural sustainability through experiential learning offered as part of the Otago Polytechnics Bachelor of Design. Students engage with the project with research methodologies, including site surveys, resident interviews, data sourced from government agencies and physical modelling. The process involves collaboration across design disciplines including product and interior design but also includes connections with industry, both within the education institution and stakeholder industries introduced through BRCT. This project offers a rich learning environment where students become engaged through project based learning within a community of practice, including architecture, construction, energy and other related fields. The design outcomes are expressed in a series of public exhibitions and forums where community input is sought in a truly participatory process.

Keywords: community resilience, problem based learning, project based learning, case study

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Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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Authors: John Doe

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This paper presents the research project “Escape Through Culture”, which is co-funded by the European Union and national resources through the Operational Programme “Competitiveness, Entrepreneurship and Innovation” 2014-2020 and the Single RTDI State Aid Action "RESEARCH - CREATE - INNOVATE". The project implementation is assumed by three partners, (1) the Computer Technology Institute and Press "Diophantus" (CTI), experienced with the design and implementation of serious games, natural language processing and ICT in education, (2) the Laboratory of Environmental Communication and Audiovisual Documentation (LECAD), part of the University of Thessaly, Department of Architecture, which is experienced with the study of creative transformation and reframing of the urban and environmental multimodal experiences through the use of AR and VR technologies, and (3) “Apoplou”, an IT Company with experience in the implementation of interactive digital applications. The research project proposes the design of innovative infrastructure of digital educational escape games for mobile devices and computers, with the use of Virtual Reality and Augmented Reality for the promotion of Greek cultural heritage in Greece and abroad. In particular, the project advocates the combination of Greek cultural heritage and literature, digital technologies advancements and the implementation of innovative gamifying practices. The cultural experience of the players will take place in 3 layers: (1) In space: the digital games produced are going to utilize the dual character of the space as a cultural landscape (the real space - landscape but also the space - landscape as presented with the technologies of augmented reality and virtual reality). (2) In literary texts: the selected texts of Greek writers will support the sense of place and the multi-sensory involvement of the user, through the context of space-time, language and cultural characteristics. (3) In the philosophy of the "escape game" tool: whether played in a computer environment, indoors or outdoors, the spatial experience is one of the key components of escape games. The innovation of the project lies both in the junction of Augmented/Virtual Reality with the promotion of cultural points of interest, as well as in the interactive, gamified practices of literary texts. The digital escape game infrastructure will be highly interactive, integrating the projection of Greek landscape cultural elements and digital literary text analysis, supporting the creation of escape games, establishing and highlighting new playful ways of experiencing iconic cultural places, such as Elefsina, Skiathos etc. The literary texts’ content will relate to specific elements of the Greek cultural heritage depicted by prominent Greek writers and poets. The majority of the texts will originate from Greek educational content available in digital libraries and repositories developed and maintained by CTI. The escape games produced will be available for use during educational field trips, thematic tourism holidays, etc. In this paper, the methodology adopted for infrastructure development will be presented. The research is based on theories of place, gamification, gaming development, making use of corpus linguistics concepts and digital humanities practices for the compilation and the analysis of literary texts.

Keywords: escape games, cultural landscapes, gamification, digital humanities, literature

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Authors: Igor N. Kosenko

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The present contribution is an analysis of more than 300 specimens of Upper Jurassic to Lower Cretaceous oysters collected by V.A. Zakharov during the 1960s and currently stored in the Trofimuk Institute of Geology and Geophysics SB RAS (Novosibirsk, Russia). They were sampled in the northwestern bounder of Western Siberia (Yatriya, Maurynia, Tol’ya and Lopsiya rivers) and the north of Eastern Siberia (Boyarka, Bolshaya Romanikha and Dyabaka-Tari rivers). During the last five years, they were examined with taxonomical and palaeoecological purposes. Based on carbonate material of oyster’s shells were performed isotopic analyses and associated palaeotemperatures. Taxonomical study consists on classical morphofunctional and biometrical analyses. It is completed by another large amount of Cretaceous oysters from Crimea as well as modern Pacific oyster - Crassostrea gigas. Those were studied to understand the range of modification variability between different species. Oysters previously identified as Liostrea are attributed now to four genera: Praeexogyra and Helvetostrea (Flemingostreidae), Pernostrea (Gryphaeidae) and one new genus (Gryphaeidae), including one species “Liostrea” roemeri (Quenstedt). This last is characterized by peculiar ethology, being attached to floating ammonites and morphology, outlined by a beak-shaped umbo on the right (!) valve. Endemic Siberian species from the Pernostrea genus have been included into the subgenus Boreiodeltoideum subgen. nov. Pernostrea and Deltoideum genera have been included into the tribe Pernostreini n. trib. from the Gryphaeinae subfamily. Model of phylogenetic relationships between species of this tribe has been proposed. Siberian oyster complexes were compared with complexes from Western Europe, Poland and East European Platform. In western Boreal and Subboreal Realm (England, northern France and Poland) two stages of oyster’s development were recognized: Jurassic-type and Cretaceous-type. In Siberia, Jurassic and Lower Cretaceous oysters formed a unique complex. It may be due to the isolation of the Siberian Basin toward the West during the Early Cretaceous. Seven oyster’s shells of Pernostrea (Pernostrea) uralensis (Zakharov) from the Jurassic/Cretaceous Boundary Interval (Upper Volgian – Lower Ryazanian) of Maurynia river were used to perform δ13C and δ18O isotopic analyses. The preservation of the carbonate material was controlled by: cathodoluminescence analyses; content of Fe, Mn, Sr; absence of correlation between δ13C and δ18O and content of Fe and Mn. The obtained δ13C and δ18O data were compared with isotopic data based on belemnites from the same stratigraphical interval of the same section and were used to trace palaeotemperatures. A general trend towards negative δ18O values is recorded in the Maurynia section, from the lower part of the Upper Volgian to the middle part of the Ryazanian Chetaites sibiricus ammonite zone. This trend was previously recorded in the Nordvik section. The higher palaeotemperatures (2°C in average) determined from oyster’s shells indicate that belemnites likely migrated laterally and lived part of their lives in cooler waters. This work financially supported by the Russian Foundation for Basic Researches (grant no. 16-35-00003).

Keywords: isotopes, oysters, Siberia, taxonomy

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Authors: Parth Gupta, Ujjawal Singh, Shashank Kumar, Mansi Chandra, Arnab Sarkar

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Microfluidic devices have emerged as indispensable tools across various scientific disciplines, offering precise control and manipulation of fluids at the microscale. Their efficacy in flow-based research, spanning engineering, chemistry, and biology, relies heavily on the geometric design of microfluidic channels. This work introduces a novel approach to optimise these channels through Response Surface Methodology (RSM), departing from the conventional practice of addressing one parameter at a time. Traditionally, optimising microfluidic channels involved isolated adjustments to individual parameters, limiting the comprehensive understanding of their combined effects. In contrast, our approach considers the simultaneous impact of multiple parameters, employing RSM to efficiently explore the complex design space. The outcome is an innovative microfluidic channel that consumes an optimal sample volume and minimises flow time, enhancing overall efficiency. The relevance of geometric parameter optimization in microfluidic channels extends significantly in biomedical engineering. The flow characteristics of porous materials within these channels depend on many factors, including fluid viscosity, environmental conditions (such as temperature and humidity), and specific design parameters like sample volume, channel width, channel length, and substrate porosity. This intricate interplay directly influences the performance and efficacy of microfluidic devices, which, if not optimized, can lead to increased costs and errors in disease testing and analysis. In the context of biomedical applications, the proposed approach addresses the critical need for precision in fluid flow. it mitigate manufacturing costs associated with trial-and-error methodologies by optimising multiple geometric parameters concurrently. The resulting microfluidic channels offer enhanced performance and contribute to a streamlined, cost-effective process for testing and analyzing diseases. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing.

Keywords: microfluidic device, minitab, statistical optimization, response surface methodology

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Authors: Ok-Kyun Im, Kyoung Hee Kim

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We live in an era that faces global challenges of climate changes and resource depletion. With the rapid urbanization and growing energy consumption in the built environment, building facades become ever more important in architectural practice and environmental stewardship. Furthermore, building facade undergoes complex dynamics of social, cultural, environmental and technological changes. Kinetic facades have drawn attention of architects, designers, and engineers in the field of adaptable, responsive and interactive architecture since 1980’s. Materials and building technologies have gradually evolved to address the technical implications of kinetic facades. The kinetic façade is becoming an independent system of the building, transforming the design methodology to sustainable building solutions. Accordingly, there is a need for a new design methodology to guide the design of a kinetic façade and evaluate its sustainable performance. The research objectives are two-fold: First, to establish a new design methodology for kinetic facades and second, to develop a micro-oculi façade system and assess its performance using the established design method. The design approach to the micro-oculi facade is comprised of 1) façade geometry optimization and 2) dynamic building energy simulation. The façade geometry optimization utilizes multi-objective optimization process, aiming to balance the quantitative and qualitative performances to address the sustainability of the built environment. The dynamic building energy simulation was carried out using EnergyPlus and Radiance simulation engines with scripted interfaces. The micro-oculi office was compared with an office tower with a glass façade in accordance with ASHRAE 90.1 2013 to understand its energy efficiency. The micro-oculi facade is constructed with an array of circular frames attached to a pair of micro-shades called a micro-oculus. The micro-oculi are encapsulated between two glass panes to protect kinetic mechanisms with longevity. The micro-oculus incorporates rotating gears that transmit the power to adjacent micro-oculi to minimize the number of mechanical parts. The micro-oculus rotates around its center axis with a step size of 15deg depending on the sun’s position while maximizing daylighting potentials and view-outs. A 2 ft by 2ft prototyping was undertaken to identify operational challenges and material implications of the micro-oculi facade. In this research, a systematic design methodology was proposed, that integrates multi-objectives of kinetic façade design criteria and whole building energy performance simulation within a holistic design process. This design methodology is expected to encourage multidisciplinary collaborations between designers and engineers to collaborate issues of the energy efficiency, daylighting performance and user experience during design phases. The preliminary energy simulation indicated that compared to a glass façade, the micro-oculi façade showed energy savings due to its improved thermal properties, daylighting attributes, and dynamic solar performance across the day and seasons. It is expected that the micro oculi façade provides a cost-effective, environmentally-friendly, sustainable, and aesthetically pleasing alternative to glass facades. Recommendations for future studies include lab testing to validate the simulated data of energy and optical properties of the micro-oculi façade. A 1:1 performance mock-up of the micro-oculi façade can suggest in-depth understanding of long-term operability and new development opportunities applicable for urban façade applications.

Keywords: energy efficiency, kinetic facades, sustainable architecture, urban facades

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Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, new methodologies to analyze investment risk are needed. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. This study modeled the economics and risk strategies of cradle-to-cradle linkages to incorporate the value-chain effects on capital/operational expenditures and investment risk reductions using a proprietary techno-economic model that incorporates investment risk scenarios utilizing the Monte Carlo methodology. The study calculated the sequential increases in profitability for each additional co-host on an operating forestry-based biomass energy plant in West Enfield, Maine. Phase I starts with the base-line of forestry biomass to electricity only and was built up in stages to include co-hosts of a greenhouse and a land-based shrimp farm. Phase I incorporates CO2 and heat waste streams from the operating power plant in an analysis of lowering and stabilizing the operating costs of the agriculture and aquaculture co-hosts. Phase II analysis incorporated a jet-fuel biorefinery and its secondary slip-stream of biochar which would be developed into two additional bio-products: 1) A soil amendment compost for agriculture and 2) A biochar effluent filter for the aquaculture. The second part of the study applied the Monte Carlo risk methodology to illustrate how co-location derisks investment in an integrated Bio-Hub versus individual investments in stand-alone projects of energy, agriculture or aquaculture. The analyzed scenarios compared reductions in both Capital and Operating Expenditures, which stabilizes profits and reduces the investment risk associated with projects in energy, agriculture, and aquaculture. The major findings of this techno-economic modeling using the Monte Carlo technique resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. In 2018, the site was designated as an economic opportunity zone as part of a Federal Program, which allows for Capital Gains tax benefits for investments on the site. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. The Bio-hub Ecosystems techno-economic analysis model is a critical model to expedite new standards for investments in circular zero-waste projects. Profitable projects will expedite adoption and advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable Bio-Economy paradigm that supports local and rural communities.

Keywords: bio-economy, investment risk, circular design, economic modelling

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