Search results for: adaptable business models

Authors: Keith Diamond, Tracy Collier, Ciara Sterling, Ben Kraal

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The increased frequency and intensity of disaster events in the Asia-Pacific region is likely to require organisations to better understand how their initiatives, and the support they provide to their customers, intersect with other organisations aiming to support communities in achieving disaster resilience. While there is a growing awareness that disaster response and recovery rebuild programmes need to adapt to more integrated, community-led approaches, there is often a discrepancy between how programmes intend to work and how they are collectively experienced in the community, creating undesired effects on community resilience. Following Australia’s North Queensland Monsoon Disaster of 2019, this research set out to understand and evaluate how the service and support ecosystem impacted on the local community’s experience and influenced their ability to respond and recover. The purpose of this initiative was to identify actionable, cross-sector, people-centered improvements that support communities to recover and thrive when faced with disaster. The challenge arose as a group of organisations, including utility providers, banks, insurers, and community organisations, acknowledged that improving their own services would have limited impact on community wellbeing unless the other services people need are also improved and aligned. The research applied human-centred service design methods, typically applied to single products or services, to design a new way to understand a whole-of-community journey. Phase 1 of the research conducted deep contextual interviews with residents and small business owners impacted by the North Queensland Monsoon and qualitative data was analysed to produce community journey maps that detailed how individuals navigated essential services, such as accommodation, finance, health, and community. Phase 2 conducted interviews and focus groups with frontline workers who represented industries that provided essential services to assist the community. Data from Phase 1 and Phase 2 of the research was analysed and combined to generate a systems map that visualised the positive and negative impacts that occurred across the disaster response and recovery service ecosystem. Insights gained from the research has catalysed collective action to address future Australian disaster events. The case study outlines a transformative way for sectors and industries to rethink their corporate social responsibility activities towards a cross-sector partnership model that shares responsibility and approaches disaster response and recovery as a single service that can be designed to meet the needs of communities.

Keywords: corporate social responsibility, cross sector partnerships, disaster resilience, human-centred design, service design, systems change

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Authors: B. Sudhakara Reddy

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In modern economy, energy is fundamental to virtually every product and service in use. It has been developed on the dependence of abundant and easy-to-transform polluting fossil fuels. On one hand, increase in population and income levels combined with increased per capita energy consumption requires energy production to keep pace with economic growth, and on the other, the impact of fossil fuel use on environmental degradation is enormous. The conflicting policy objectives of protecting the environment while increasing economic growth and employment has resulted in this paradox. Hence, it is important to decouple economic growth from environmental degeneration. Hence, the search for green energy involving affordable, low-carbon, and renewable energies has become global priority. This paper explores a transition to a sustainable energy system using the socio-economic-technical scenario method. This approach takes into account the multifaceted nature of transitions which not only require the development and use of new technologies, but also of changes in user behaviour, policy and regulation. The scenarios that are developed are: baseline business as usual (BAU) as well as green energy (GE). The baseline scenario assumes that the current trends (energy use, efficiency levels, etc.) will continue in future. India’s population is projected to grow by 23% during 2010 –2030, reaching 1.47 billion. The real GDP, as per the model, is projected to grow by 6.5% per year on average between 2010 and 2030 reaching US$5.1 trillion or $3,586 per capita (base year 2010). Due to increase in population and GDP, the primary energy demand will double in two decades reaching 1,397 MTOE in 2030 with the share of fossil fuels remaining around 80%. The increase in energy use corresponds to an increase in energy intensity (TOE/US $ of GDP) from 0.019 to 0.036. The carbon emissions are projected to increase by 2.5 times from 2010 reaching 3,440 million tonnes with per capita emissions of 2.2 tons/annum. However, the carbon intensity (tons per US$ of GDP) decreases from 0.96 to 0.67. As per GE scenario, energy use will reach 1079 MTOE by 2030, a saving of about 30% over BAU. The penetration rate of renewable energy resources will reduce the total primary energy demand by 23% under GE. The reduction in fossil fuel demand and focus on clean energy will reduce the energy intensity to 0.21 (TOE/US$ of GDP) and carbon intensity to 0.42 (ton/US$ of GDP) under the GE scenario. The study develops new ‘pathways out of poverty’ by creating more than 10 million jobs and thus raise the standard of living of low-income people. Our scenarios are, to a great extent, based on the existing technologies. The challenges to this path lie in socio-economic-political domains. However, to attain a green economy the appropriate policy package should be in place which will be critical in determining the kind of investments that will be needed and the incidence of costs and benefits. These results provide a basis for policy discussions on investments, policies and incentives to be put in place by national and local governments.

Keywords: energy, renewables, green technology, scenario

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Authors: Najibullah M, Soumendra Nath Kuiry

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Dams and reservoirs are perceived for their estimable alms to irrigation, water supply, flood control, electricity generation, etc. which civilize the prosperity and wealth of society across the world. Meantime the dam breach could cause devastating flood that can threat to the human lives and properties. Failures of large dams remain fortunately very seldom events. Nevertheless, a number of occurrences have been recorded in the world, corresponding in an average to one to two failures worldwide every year. Some of those accidents have caused catastrophic consequences. So it is decisive to predict the dam break flow for emergency planning and preparedness, as it poses high risk to life and property. To mitigate the adverse impact of dam break, modeling is necessary to gain a good understanding of the temporal and spatial evolution of the dam-break floods. This study will mainly deal with one-dimensional (1D) dam break modeling. Less commonly used in the hydraulic research community, another possible option for modeling the rapidly varied dam-break flows is the extended Boussinesq equations (BEs), which can describe the dynamics of short waves with a reasonable accuracy. Unlike the Shallow Water Equations (SWEs), the BEs taken into account the wave dispersion and non-hydrostatic pressure distribution. To capture the dam-break oscillations accurately it is very much needed of at least fourth-order accurate numerical scheme to discretize the third-order dispersion terms present in the extended BEs. The scope of this work is therefore to develop an 1D fourth-order accurate in both space and time Boussinesq model for dam-break flow analysis by using finite-volume / finite difference scheme. The spatial discretization of the flux and dispersion terms achieved through a combination of finite-volume and finite difference approximations. The flux term, was solved using a finite-volume discretization whereas the bed source and dispersion term, were discretized using centered finite-difference scheme. Time integration achieved in two stages, namely the third-order Adams Basforth predictor stage and the fourth-order Adams Moulton corrector stage. Implementation of the 1D Boussinesq model done using PYTHON 2.7.5. Evaluation of the performance of the developed model predicted as compared with the volume of fluid (VOF) based commercial model ANSYS-CFX. The developed model is used to analyze the risk of cascading dam failures similar to the Panshet dam failure in 1961 that took place in Pune, India. Nevertheless, this model can be used to predict wave overtopping accurately compared to shallow water models for designing coastal protection structures.

Keywords: Boussinesq equation, Coastal protection, Dam-break flow, One-dimensional model

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Authors: Taha Anjamrooz, Sareh Rajabi, Ayman Alzaatreh

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Smart cities are playing important roles in real life. Integration and automation between different features of modern cities and information technologies improve smart city efficiency, energy management, human and equipment resource management, life quality and better utilization of resources for the customers. One of difficulties in this path, is use, interface and link between software, hardware, and other IT technologies to develop and optimize processes in various business fields such as construction, supply chain management and transportation in parallel to cost-effective and resource reduction impacts. Also, Smart cities are certainly intended to demonstrate a vital role in offering a sustainable and efficient model for smart houses while mitigating environmental and ecological matters. Energy management is one of the most important matters within smart houses in the smart cities and communities, because of the sensitivity of energy systems, reduction in energy wastage and maximization in utilizing the required energy. Specially, the consumption of energy in the smart houses is important and considerable in the economic balance and energy management in smart city as it causes significant increment in energy-saving and energy-wastage reduction. This research paper develops features and concept of smart city in term of overall efficiency through various effective variables. The selected variables and observations are analyzed through data analysis processes to demonstrate the efficiency of smart city and compare the effectiveness of each variable. There are ten chosen variables in this study to improve overall efficiency of smart city through increasing effectiveness of smart houses using an automated solar photovoltaic system, RFID System, smart meter and other major elements by interfacing between software and hardware devices as well as IT technologies. Secondly to enhance aspect of energy management by energy-saving within smart house through efficient variables. The main objective of smart city and smart houses is to reproduce energy and increase its efficiency through selected variables with a comfortable and harmless atmosphere for the customers within a smart city in combination of control over the energy consumption in smart house using developed IT technologies. Initially the comparison between traditional housing and smart city samples is conducted to indicate more efficient system. Moreover, the main variables involved in measuring overall efficiency of system are analyzed through various processes to identify and prioritize the variables in accordance to their influence over the model. The result analysis of this model can be used as comparison and benchmarking with traditional life style to demonstrate the privileges of smart cities. Furthermore, due to expensive and expected shortage of natural resources in near future, insufficient and developed research study in the region, and available potential due to climate and governmental vision, the result and analysis of this study can be used as key indicator to select most effective variables or devices during construction phase and design

Keywords: smart city, traditional housing, RFID, photovoltaic system, energy efficiency, energy saving

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Authors: Roberto Feltrero, Sara Osuna-Acedo

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Responsible Research and Innovation have to accomplish one fundamental aim: everybody has to participate in the benefits of innovation, but also innovation has to be democratic; that is to say, everybody may have the possibility to participate in the decisions in the innovation process. Particularly, a democratic and inclusive model of social participation and innovation includes persons with disabilities and people at risk of discrimination. Innovations on Artificial Intelligence for social development have to accomplish the same dual goal: improving equality for accessing fields of public interest like education, training and public services, as well as improving civic and democratic participation in the process of developing such innovations for all. This research aims to develop innovations, policies and policy recommendations to apply and disseminate such artificial intelligence and social model for making educational and administrative processes more accessible. First, designing a citizen participation process to engage citizens in the designing and use of artificial intelligence tools for public services. This will result in improving trust in democratic institutions contributing to enhancing the transparency, effectiveness, accountability and legitimacy of public policy-making and allowing people to participate in the development of ethical standards for the use of such technologies. Second, improving educational tools for lifelong learning with AI models to improve accountability and educational data management. Dissemination, education and social participation will be integrated, measured and evaluated in innovative educational processes to make accessible all the educational technologies and content developed on AI about responsible and social innovation. A particular case will be presented regarding access for all to educational tools and public services. This accessibility requires cognitive adaptability because, many times, legal or administrative language is very complex. Not only for people with cognitive disabilities but also for old people or citizens at risk of educational or social discrimination. Artificial Intelligence natural language processing technologies can provide tools to translate legal, administrative, or educational texts to a more simple language that can be accessible to everybody. Despite technological advances in language processing and machine learning, this becomes a huge project if we really want to respect ethical and legal consequences because that kinds of consequences can only be achieved with civil and democratic engagement in two realms: 1) to democratically select texts that need and can be translated and 2) to involved citizens, experts and nonexperts, to produce and validate real examples of legal texts with cognitive adaptations to feed artificial intelligence algorithms for learning how to translate those texts to a more simple and accessible language, adapted to any kind of population.

Keywords: responsible research and innovation, AI social innovations, cognitive accessibility, public participation

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Authors: Moien Mojabi, Aurelien Hospital, Daniel Potts, Chris Young, Albert Leung

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The wave analysis is an integral part of the hydrotechnical assessment carried out during the permitting and design phases for coastal structures, such as marinas. This analysis aims in quantifying: i) the Suitability of the coastal structure design against Small Craft Harbour wave tranquility safety criterion; ii) Potential environmental impacts of the structure (e.g., effect on wave, flow, and sediment transport); iii) Mooring and dock design and iv) Requirements set by regulatory agency’s (e.g., WSA section 11 application). While a complex three-dimensional hydrodynamic modelling approach can be applied on large-scale projects, the need for an efficient and reliable wave analysis method suitable for smaller scale marina projects was identified. As a result, Tetra Tech has developed and applied an integrated analysis framework (hereafter TT approach), which takes the advantage of the state-of-the-art numerical models while preserving the level of simplicity that fits smaller scale projects. The present paper aims to describe the TT approach and highlight the key advantages of using this integrated framework in lake marina projects. The core of this methodology is made by integrating wind, water level, bathymetry, and structure geometry data. To respond to the needs of specific projects, several add-on modules have been added to the core of the TT approach. The main advantages of this method over the simplified analytical approaches are i) Accounting for the proper physics of the lake through the modelling of the entire lake (capturing real lake geometry) instead of a simplified fetch approach; ii) Providing a more realistic representation of the waves by modelling random waves instead of monochromatic waves; iii) Modelling wave-structure interaction (e.g. wave transmission/reflection application for floating structures and piles amongst others); iv) Accounting for wave interaction with the lakebed (e.g. bottom friction, refraction, and breaking); v) Providing the inputs for flow and sediment transport assessment at the project site; vi) Taking in consideration historical and geographical variations of the wind field; and vii) Independence of the scale of the reservoir under study. Overall, in comparison with simplified analytical approaches, this integrated framework provides a more realistic and reliable estimation of wave parameters (and its spatial distribution) in lake marinas, leading to a realistic hydrotechnical assessment accessible to any project size, from the development of a new marina to marina expansion and pile replacement. Tetra Tech has successfully utilized this approach since many years in the Okanagan area.

Keywords: wave modelling, wind-wave, extreme value analysis, marina

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Authors: Amany Abdelrazek

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Fashion is considered the main feature of modern and postmodern capitalist and consumerist society. Consumer historians maintain that fashion, namely, a sector of people embracing a prevailing clothing style for a short period, started during the Middle Ages but gained popularity later. It symbolised the transition from a medieval society with its solid fixed religious values into a modern society with its secular consumer dynamic culture. Renaissance society was a modern secular society concerning its preoccupation with daily life and changing circumstances. Yet, the late 18th-century industrial revolution revolutionised thought and ideology in Europe. The Industrial Revolution reinforced the Western belief in rationality and strengthened the position of science. In such a rational Western society, modernity, with its new ideas, came to challenge the whole idea of old fixed norms, reflecting the modern secular, rational culture and renouncing the medieval pious consumer. In modern society, supported by the industrial revolution and mass production, fashion encouraged broader sectors of society to integrate into fashion reserved for the aristocracy and royal courts. Moreover, the fashion project emphasizes the human body and its beauty, contradicting Judeo-Christian culture, which tends to abhor and criticize interest in sensuality and hedonism. In mainstream Western discourse, fashionable dress differentiates between emancipated stylish consumerist secular modern female and the assumed oppressed traditional modest religious female. Opposing this discourse, I look at the controversy over what has been called "Islamic fashion" that started during the 1980s and continued to gain popularity in contemporary Egyptian society. I discuss the challenges of being a fashionable and Muslim practicing female in light of two prominent models for female "Islamic fashion" in postcolonial Egypt; Jasmin Mohshen, the first hijabi model in Egypt and Manal Rostom, the first Muslim woman to represent the Nike campaign in the Middle East. The research employs fashion and postcolonial theories to rethink current Muslim women's position on women's emancipation, Western modernity and practising faith in postcolonial Egypt. The paper argues that Muslim women's current innovative and fashionable dress can work as a counter-discourse to the Orientalist and exclusive representation of non-Western Muslim culture as an inherently inert timeless culture. Furthermore, "Islamic" fashionable dress as an aesthetic medium for expressing ideas and convictions in contemporary Egypt interrogates the claim of universal secular modernity and Western fashion theorists' reluctance to consider Islamic fashion as fashion.

Keywords: fashion, muslim women, modernity, secularism

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Authors: Walter Vera-Ortega, Idoia Busnadiego, Sam J. Wilson

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Introduction: Human Immunodeficiency Virus type 1 (HIV-1) is responsible for the acquired immunodeficiency syndrome (AIDS), a leading cause of death worldwide infecting millions of people each year. Despite intensive research in vaccine development, therapies against HIV-1 infection are not curative, and the huge genetic variability of HIV-1 challenges to drug development. Current animal models for HIV-1 research present important limitations, impairing the progress of in vivo approaches. Macaques require a CD8+ depletion to progress to AIDS, and the maintenance cost is high. Mice are a cheaper alternative but need to be 'humanized,' and breeding is not possible. The development of an HIV-1 clone able to replicate in mice is a challenging proposal. The lack of human co-factors in mice impedes the function of the HIV-1 accessory proteins, Tat and Rev, hampering HIV-1 replication. However, Tat and Rev function can be replaced by constitutive/chimeric promoters, codon-optimized proteins and the constitutive transport element (CTE), generating a novel HIV-1 clone able to replicate in mice without disrupting the amino acid sequence of the virus. By minimally manipulating the genomic 'identity' of the virus, we propose the generation of an HIV-1 clone able to replicate in mice to assist in antiviral drug development. Methods: i) Plasmid construction: The chimeric promoters and CTE copies were cloned by PCR using lentiviral vectors as templates (pCGSW and pSIV-MPCG). Tat mutants were generated from replication competent HIV-1 plasmids (NHG and NL4-3). ii) Infectivity assays: Retroviral vectors were generated by transfection of human 293T cells and murine NIH 3T3 cells. Virus titre was determined by flow cytometry measuring GFP expression. Human B-cells (AA-2) and Hela cells (TZMbl) were used for infectivity assays. iii) Protein analysis: Tat protein expression was determined by TZMbl assay and HIV-1 capsid by western blot. Results: We have determined that NIH 3T3 cells are able to generate HIV-1 particles. However, they are not infectious, and further analysis needs to be performed. Codon-optimized HIV-1 constructs are efficiently made in 293T cells in a Tat and Rev independent manner and capable of packaging a competent genome in trans. CSGW is capable of generating infectious particles in the absence of Tat and Rev in human cells when 4 copies of the CTE are placed preceding the 3’LTR. HIV-1 Tat mutant clones encoding different promoters are functional during the first cycle of replication when Tat is added in trans. Conclusion: Our findings suggest that the development of an HIV-1 Tat-Rev independent clone is challenging but achievable aim. However, further investigations need to be developed prior presenting our HIV-1 clone as a candidate model for research.

Keywords: codon-optimized, constitutive transport element, HIV-1, long terminal repeats, research model

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Authors: Kibrom Hadush

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Countries like Ethiopia, whose economy is mainly rain-fed dependent agriculture, are highly vulnerable to climate variability and weather extremes. Sub-seasonal (monthly) and dekadal forecasts are hence critical for crop production and water resource management. Therefore, this paper was conducted to study the predictability and variability of Kiremt rainfall over the northern half of Ethiopia on monthly and dekadal time scales in association with global Sea Surface Temperature (SST) at different lag time. Trends in rainfall have been analyzed on annual, seasonal (Kiremt), monthly, and dekadal (June–September) time scales based on rainfall records of 36 meteorological stations distributed across four homogenous zones of the northern half of Ethiopia for the period 1992–2017. The results from the progressive Mann–Kendall trend test and the Sen’s slope method shows that there is no significant trend in the annual, Kiremt, monthly and dekadal rainfall total at most of the station's studies. Moreover, the rainfall in the study area varies spatially and temporally, and the distribution of the rainfall pattern increases from the northeast rift valley to northwest highlands. Methods of analysis include graphical correlation and multiple linear regression model are employed to investigate the association between the global SSTs and Kiremt rainfall over the homogeneous rainfall zones and to predict monthly and dekadal (June-September) rainfall using SST predictors. The results of this study show that in general, SST in the equatorial Pacific Ocean is the main source of the predictive skill of the Kiremt rainfall variability over the northern half of Ethiopia. The regional SSTs in the Atlantic and the Indian Ocean as well contribute to the Kiremt rainfall variability over the study area. Moreover, the result of the correlation analysis showed that the decline of monthly and dekadal Kiremt rainfall over most of the homogeneous zones of the study area are caused by the corresponding persistent warming of the SST in the eastern and central equatorial Pacific Ocean during the period 1992 - 2017. It is also found that the monthly and dekadal Kiremt rainfall over the northern, northwestern highlands and northeastern lowlands of Ethiopia are positively correlated with the SST in the western equatorial Pacific, eastern and tropical northern the Atlantic Ocean. Furthermore, the SSTs in the western equatorial Pacific and Indian Oceans are positively correlated to the Kiremt season rainfall in the northeastern highlands. Overall, the results showed that the prediction models using combined SSTs at various ocean regions (equatorial and tropical) performed reasonably well in the prediction (With R2 ranging from 30% to 65%) of monthly and dekadal rainfall and recommends it can be used for efficient prediction of Kiremt rainfall over the study area to aid with systematic and informed decision making within the agricultural sector.

Keywords: dekadal, Kiremt rainfall, monthly, Northern Ethiopia, sea surface temperature

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Authors: Sherif Fakher

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Hydrogen has been gaining a lot of global attention as an uprising contributor in the energy sector. Labeled as an energy carrier, hydrogen is used in many industries and can be used to generate electricity via fuel cells. Blue hydrogen involves the production of hydrogen from hydrocarbons using different processes that emit CO₂. However, the CO₂ is captured and stored. Hence, very little environmental damage occurs during the hydrogen production process. This research investigates the ability to use different catalysts for the production of hydrogen from different hydrocarbon sources, including coal, oil, and gas, using a two-step Aquathermolysis reaction. The research presents the results of experiments conducted to evaluate different catalysts and also highlights the main advantages of this process over other blue hydrogen production methods, including methane steam reforming, autothermal reforming, and oxidation. Two methods of hydrogen generation were investigated including partial oxidation and aquathermolysis. For those two reactions, the reaction kinetics, thermodynamics, and medium were all investigated. Following this, experiments were conducted to test the hydrogen generation potential from both methods. The porous media tested were sandstone, ash, and prozzolanic material. The spent oils used were spent motor oil and spent vegetable oil from cooking. Experiments were conducted at temperatures up to 250 C and pressures up to 3000 psi. Based on the experimental results, mathematical models were developed to predict the hydrogen generation potential at higher thermodynamic conditions. Since both partial oxidation and aquathermolysis require relatively high temperatures to undergo, it was important to devise a method by which these high temperatures can be generated at a low cost. This was done by investigating two factors, including the porous media used and the reliance on the spent oil. Of all the porous media used, the ash had the highest thermal conductivity. The second step was the partial combustion of part of the spent oil to generate the heat needed to reach the high temperatures. This reduced the cost of the heat generation significantly. For the partial oxidation reaction, the spent oil was burned in the presence of a limited oxygen concentration to generate carbon monoxide. The main drawback of this process was the need for burning. This resulted in the generation of other harmful and environmentally damaging gases. Aquathermolysis does not rely on burning, which makes it the cleaner alternative. However, it needs much higher temperatures to run the reaction. When comparing the hydrogen generation potential for both using gas chromatography, aquathermolysis generated 23% more hydrogen using the same volume of spent oil compared to partial oxidation. This research introduces the concept of using spent oil for hydrogen production. This can be a very promising method to produce a clean source of energy using a waste product. This can also help reduce the reliance on freshwater for hydrogen generation which can divert the usage of freshwater to other more important applications.

Keywords: blue hydrogen production, catalytic aquathermolysis, direct carbon dioxide capture, CCUS

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Authors: Laura Isabel Guarin, Juliana Vargas, Philippe Chang

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The analysis and study of Open Channel flow dynamics for River applications has been based on flow modelling using discreet numerical models based on hydrodynamic equations. The overall spatial characteristics of rivers, i.e. its length to depth to width ratio generally allows one to correctly disregard processes occurring in the vertical or transverse dimensions thus imposing hydrostatic pressure conditions and considering solely a 1D flow model along the river length. Through a calibration process an accurate flow model may thus be developed allowing for channel study and extrapolation of various scenarios. The Magdalena River in Colombia is a large river basin draining the country from South to North with 1550 km with 0.0024 average slope and 275 average width across. The river displays high water level fluctuation and is characterized by a series of meanders. The city of La Dorada has been affected over the years by serious flooding in the rainy and dry seasons. As the meander is evolving at a steady pace repeated flooding has endangered a number of neighborhoods. This study has been undertaken in pro of correctly model flow characteristics of the river in this region in order to evaluate various scenarios and provide decision makers with erosion control measures options and a forecasting tool. Two field campaigns have been completed over the dry and rainy seasons including extensive topographical and channel survey using Topcon GR5 DGPS and River Surveyor ADCP. Also in order to characterize the erosion process occurring through the meander, extensive suspended and river bed samples were retrieved as well as soil perforation over the banks. Hence based on DEM ground digital mapping survey and field data a 2DH flow model was prepared using the Iber freeware based on the finite volume method in a non-structured mesh environment. The calibration process was carried out comparing available historical data of nearby hydrologic gauging station. Although the model was able to effectively predict overall flow processes in the region, its spatial characteristics and limitations related to pressure conditions did not allow for an accurate representation of erosion processes occurring over specific bank areas and dwellings. As such a significant helical flow has been observed through the meander. Furthermore, the rapidly changing channel cross section as a consequence of severe erosion has hindered the model’s ability to provide decision makers with a valid up to date planning tool.

Keywords: erosion, finite volume method, flow dynamics, flow modelling, meander

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Authors: Kirsi Snellman, Johannes Gartner, , Katja Upadaya

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A transition towards a future where the economy serves society so that it evolves within the safe operating space of the planet calls for fundamental changes in the way managers think, feel and act, and make decisions that relate to social and environmental issues. Sustainable decision-making in organizations are often challenging tasks characterized by trade-offs between environmental, social and financial aspects, thus often bringing forth ethical concerns. Although there have been significant developments in incorporating uncertainty into environmental decision-making and measuring constructs and dimensions in ethical behavior in organizations, the majority of sustainable decision-making models are rationalist-based. Moreover, research in psychology indicates that one’s readiness to make a decision depends on the individual’s state of mind, the feasibility of the implied change, and the compatibility of strategies and tactics of implementation. Although very informative, most of this extant research is limited in the sense that it often directs attention towards the rational instead of the emotional. Hence, little is known about the role of emotions in sustainable decision making, especially in situations where decision-makers evaluate a variety of options and use their feelings as a source of information in tackling the uncertainty. To fill this lacuna, and to embrace the uncertainty and perceived risk involved in decisions that touch upon social and environmental aspects, it is important to add emotion to the evaluation when aiming to reach the one right and good ethical decision outcome. This analysis builds on recent findings in moral psychology that associate feelings and intuitions with ethical decisions and suggests that emotions can sensitize the manager to evaluate the rightness or wrongness of alternatives if ethical concerns are present in sustainable decision making. Capturing such sensitive evaluation as triggered by intuitions, we suggest that rational justification can be complemented by using emotions as a tool to tune in to what feels right in making sustainable decisions. This analysis integrates ethical decision-making theories with recent advancements in emotion theories. It determines the conditions under which emotions play a role in sustainability decisions by contributing to a personal equilibrium in which intuition and rationality are both activated and in accord. It complements the rationalist ethics view according to which nothing fogs the mind in decision making so thoroughly as emotion, and the concept of cheater’s high that links unethical behavior with positive affect. This analysis contributes to theory with a novel theoretical model that specifies when and why managers, who are more emotional, are, in fact, more likely to make ethical decisions than those managers who are more rational. It also proposes practical advice on how emotions can convert the manager’s preferences into choices that benefit both common good and one’s own good throughout the transition towards a more sustainable future.

Keywords: emotion, ethical decision making, intuition, sustainability

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Authors: Juan C. Pérez-Mesa, Emilio Galdeano-Gómez, Jerónimo De Burgos-Jiménez, José F. Bienvenido-Bárcena, José F. Jiménez-Guerrero

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Environmental cost and transport congestion on roads resulting from product distribution in Europe have to lead to the creation of various programs and studies seeking to reduce these negative impacts. In this regard, apart from other institutions, the European Commission (EC) has designed plans in recent years promoting a more sustainable transportation model in an attempt to ultimately shift traffic from the road to the sea by using intermodality to achieve a model rebalancing. This issue proves especially relevant in supply chains from peripheral areas of the continent, where the supply of certain agrifood products is high. In such cases, the most difficult challenge is managing perishable goods. This study focuses on new approaches that strengthen the modal shift, as well as the reduction of externalities. This problem is analyzed by attempting to promote intermodal system (truck and short sea shipping) for transport, taking as point of reference highly perishable products (vegetables) exported from southeast Spain, which is the leading supplier to Europe. Methodologically, this paper seeks to contribute to the literature by proposing a different and complementary approach to establish a comparison between intermodal and the “only road” alternative. For this purpose, the multicriteria decision is utilized in a p-median model (P-M) adapted to the transport of perishables and to a means of shipping selection problem, which must consider different variables: transit cost, including externalities, time, and frequency (including agile response time). This scheme avoids bias in decision-making processes. By observing the results, it can be seen that the influence of the externalities as drivers of the modal shift is reduced when transit time is introduced as a decision variable. These findings confirm that the general strategies, those of the EC, based on environmental benefits lose their capacity for implementation when they are applied to complex circumstances. In general, the different estimations reveal that, in the case of perishables, intermodality would be a secondary and viable option only for very specific destinations (for example, Hamburg and nearby locations, the area of influence of London, Paris, and the Netherlands). Based on this framework, the general outlook on this subject should be modified. Perhaps the government should promote specific business strategies based on new trends in the supply chain, not only on the reduction of externalities, and find new approaches that strengthen the modal shift. A possible option is to redefine ports, conceptualizing them as digitalized redistribution and coordination centers and not only as areas of cargo exchange.

Keywords: environmental externalities, intermodal transport, perishable food, transit time

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Authors: El Ghazi Safae, Cherkaoui Mounia

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Within companies, emotions have been forgotten as key elements of successful management systems. Seen as factors which disturb judgment, make reckless acts or affect negatively decision-making. Since management systems were influenced by the Taylorist worker image, that made the work regular and plain, and considered employees as executing machines. However, recently, in globalized economy characterized by a variety of uncertainties, emotions are proved as useful elements, even necessary, to attend high-level management. The work of Elton Mayo and Kurt Lewin reveals the importance of emotions. Since then emotions start to attract considerable attention. These studies have shown that emotions influence, directly or indirectly, many organization processes. For example, the quality of interpersonal relationships, job satisfaction, absenteeism, stress, leadership, performance and team commitment. Emotions became fundamental and indispensable to individual yield and so on to management efficiency. The idea that a person potential is associated to Intellectual Intelligence, measured by the IQ as the main factor of social, professional and even sentimental success, was the main problematic that need to be questioned. The literature on emotional intelligence has made clear that success at work does not only depend on intellectual intelligence but also other factors. Several researches investigating emotional intelligence impact on performance showed that emotionally intelligent managers perform more, attain remarkable results, able to achieve organizational objectives, impact the mood of their subordinates and create a friendly work environment. An improvement in the emotional intelligence of managers is therefore linked to the professional development of the organization and not only to the personal development of the manager. In this context, it would be interesting to question the importance of emotional intelligence. Does it impact organizational performance? What is the importance of emotional intelligence and how it impacts organizational performance? The literature highlighted that measurement and conceptualization of emotional intelligence are difficult to define. Efforts to measure emotional intelligence have identified three models that are more prominent: the mixed model, the ability model, and the trait model. The first is considered as cognitive skill, the second relates to the mixing of emotional skills with personality-related aspects and the latter is intertwined with personality traits. But, despite strong claims about the importance of emotional intelligence in the workplace, few studies have empirically examined the impact of emotional intelligence on organizational performance, because even though the concept of performance is at the heart of all evaluation processes of companies and organizations, we observe that performance remains a multidimensional concept and many authors insist about the vagueness that surrounds the concept. Given the above, this article provides an overview of the researches related to emotional intelligence, particularly focusing on studies that investigated the impact of emotional intelligence on organizational performance to contribute to the emotional intelligence literature and highlight its importance and show how it impacts companies’ performance.

Keywords: emotions, performance, intelligence, firms

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Authors: James G. Matthew, Seonmin Huh, Frank X. Bennett

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English for Specific Purposes, ESP, aims to equip learners with necessary English language skills. Many ESP programs address language skills for job performance, including reading job related documents and oral proficiency. Within ESP is English for occupational purposes, EOP, which centers around developing communicative competence for the globalized workplace. Many ESP and EOP courses lack the content needed to assist students to progress at work, resulting in the need to create lexical compilation for different professions. It is important to teach communicative competence and soft skills for real job-related problem situations and address the complexities of the real world to help students to be successful in their professions. ESP and EOP research is therefore trying to balance both profession-specific educational contents as well as international multi-disciplinary language skills for the globalized workforce. The current study will build upon the existing discussion by developing pedagogy to assist students in their career through developing a strong practical command of relevant English vocabulary. Our research question focuses on the pedagogy two professors incorporated in their English for employment courses. The current study is a qualitative case study on the modes of teaching delivery for EOP in South Korea. Two foreign professors teaching at two different universities in South Korea volunteered for the study to explore their teaching practices. Both professors’ curriculums included the components of employment-related concept vocabulary, business presentations, CV/resume and cover letter preparation, and job interview preparation. All the pre-made recorded video lectures, live online class sessions with students, teachers’ lesson plans, teachers’ class materials, students’ assignments, and midterm and finals video conferences were collected for data analysis. The study then focused on unpacking representative patterns in their teaching methods. The professors used their strengths as native speakers to extend the class discussion from narrow and restricted conversations to giving students broader opportunities to practice authentic English conversation. The methods of teaching utilized three main steps to extend the conversation. Firstly, students were taught concept vocabulary. Secondly, the vocabulary was then combined in speaking activities where students had to solve scenarios, and the students were required to expand on the given forms of words and language expressions. Lastly, the students had conversations in English, using the language learnt. The conversations observed in both classes were those of authentic, expanded English communication and this way of expanding concept vocabulary lessons into extended conversation is one representative pedagogical approach that both professors took. Extended English conversation, therefore, is crucial for EOP education.

Keywords: concept vocabulary, english as a foreign language, english for employment, extended conversation

Procedia PDF Downloads 88

Authors: Prateek Goyal, Archini Paruthi, Superb K. Misra

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Contamination of water resources has been a major concern, which has drawn attention to the need to develop new material models for treatment of effluents. Existing conventional waste water treatment methods remain ineffective sometimes and uneconomical in terms of remediating contaminants like heavy metal ions (mercury, arsenic, lead, cadmium and chromium); organic matter (dyes, chlorinated solvents) and high salt concentration, which makes water unfit for consumption. We believe that nanotechnology based strategy, where we use nanoparticles as a tool to remediate a class of pollutants would prove to be effective due to its property of high surface area to volume ratio, higher selectivity, sensitivity and affinity. In recent years, scientific advancement has been made to study the application of photocatalytic (ZnO, TiO2 etc.) nanomaterials and magnetic nanomaterials in remediating contaminants (like heavy metals and organic dyes) from water/wastewater. Our study focuses on the synthesis and monitoring remediation efficiency of ZnO, Fe3O4 and Fe3O4 coated ZnO nanoparticulate system for the removal of heavy metals and dyes simultaneously. Multitude of ZnO nanostructures (spheres, rods and flowers) using multiple routes (microwave & hydrothermal approach) offers a wide range of light active photo catalytic property. The phase purity, morphology, size distribution, zeta potential, surface area and porosity in addition to the magnetic susceptibility of the particles were characterized by XRD, TEM, CPS, DLS, BET and VSM measurements respectively. Further on, the introduction of crystalline defects into ZnO nanostructures can also assist in light activation for improved dye degradation. Band gap of a material and its absorbance is a concrete indicator for photocatalytic activity of the material. Due to high surface area, high porosity and affinity towards metal ions and availability of active surface sites, iron oxide nanoparticles show promising application in adsorption of heavy metal ions. An additional advantage of having magnetic based nanocomposite is, it offers magnetic field responsive separation and recovery of the catalyst. Therefore, we believe that ZnO linked Fe3O4 nanosystem would be efficient and reusable. Improved photocatalytic efficiency in addition to adsorption for environmental remediation has been a long standing challenge, and the nano-composite system offers the best of features which the two individual metal oxides provide for nanoremediation.

Keywords: adsorption, nanocomposite, nanoremediation, photocatalysis

Procedia PDF Downloads 233

Authors: N. Garrós, P. Bustos, N. Beirampour, R. Mohammadi, M. Mallandrich, A.C. Calpena, H. Colom

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Atopic dermatitis (AD) is a persistent skin condition characterized by chronic inflammation caused by an autoimmune response. It is a prevalent clinical issue that requires continual treatment to enhance the patient's quality of life. Systemic therapy often involves the use of glucocorticoids or immunosuppressants to manage symptoms. Our objective was to create and assess topical liposomal formulations containing Baricitinib (BNB), a reversible inhibitor of Janus-associated kinase (JAK), which is involved in various immune responses. These formulations were intended to address flare-ups and improve treatment outcomes for AD. We created three distinct liposomal formulations by combining different amounts of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC), cholesterol (CHOL), and ceramide (CER): (i) pure POPC, (ii) POPC mixed with CHOL (at a ratio of 8:2, mol/mol), and (iii) POPC mixed with CHOL and CER (at a ratio of 3.6:2.4:4.0 mol/mol/mol). We conducted various tests to determine the formulations' skin tolerance, irritancy capacity, and their ability to cause erythema and edema on altered skin. We also assessed the transepidermal water loss (TEWL) and skin hydration of rabbits to evaluate the efficacy of the formulations. Histological analysis, the HET-CAM test, and the modified Draize test were all used in the evaluation process. The histological analysis revealed that liposome POPC and POPC:CHOL avoided any damage to the tissues structures. The HET-CAM test showed no irritation effect caused by any of the three liposomes, and the modified Draize test showed a good Draize score for erythema and edema. Liposome POPC effectively counteracted the impact of xylol on the skin, and no erythema or edema was observed during the study. TEWL values were constant for all the liposomes with similar values to the negative control (within the range 8 - 15 g/h·m2, which means a healthy value for rabbits), whereas the positive control showed a significant increase. The skin hydration values were constant and followed the trend of the negative control, while the positive control showed a steady increase during the tolerance study. In conclusion, the developed formulations containing BNB exhibited no harmful or irritating effects, they did not demonstrate any irritant potential in the HET-CAM test and liposomes POPC and POPC:CHOL did not cause any structural alteration according to the histological analysis. These positive findings suggest that additional research is necessary to evaluate the efficacy of these liposomal formulations in animal models of the disease, including mutant animals. Furthermore, before proceeding to clinical trials, biochemical investigations should be conducted to better understand the mechanisms of action involved in these formulations.

Keywords: baricitinib, HET-CAM test, histological study, JAK inhibitor, liposomes, modified draize test

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Authors: Biao Sun, Tejas Bhatelia, Vishnu Pareek, Ranjeet Utikar, Moses Tadé

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Additive manufacturing (AM), commonly known as 3D printing, with the continuing advances in parallel processing and computational modeling, has created a paradigm shift (with significant radical thinking) in the design and operation of chemical processing plants, especially LNG plants. With the rising energy demands, environmental pressures, and economic challenges, there is a continuing industrial need for disruptive technologies such as AM, which possess capabilities that can drastically reduce the cost of manufacturing and operations of chemical processing plants in the future. However, the continuing challenge for 3D printing is its lack of adaptability in re-designing the process plant equipment coupled with the non-existent theory or models that could assist in selecting the optimal candidates out of the countless potential fabrications that are possible using AM. One of the most common packings used in the LNG process is structured packing in the packed column (which is a unit operation) in the process. In this work, we present an example of an optimum strategy for the application of AM to this important unit operation. Packed columns use a packing material through which the gas phase passes and comes into contact with the liquid phase flowing over the packing, typically performing the necessary mass transfer to enrich the products, etc. Structured packing consists of stacks of corrugated sheets, typically inclined between 40-70° from the plane. Computational Fluid Dynamics (CFD) was used to test and model various geometries to study the governing hydrodynamic characteristics. The results demonstrate that the costly iterative experimental process can be minimized. Furthermore, they also improve the understanding of the fundamental physics of the system at the multiscale level. SpiroPak, patented by Curtin University, represents an innovative structured packing solution currently at a technology readiness level (TRL) of 5~6. This packing exhibits remarkable characteristics, offering a substantial increase in surface area while significantly enhancing hydrodynamic and mass transfer performance. Recent studies have revealed that SpiroPak can reduce pressure drop by 50~70% compared to commonly used commercial packings, and it can achieve 20~50% greater mass transfer efficiency (particularly in CO2 absorption applications). The implementation of SpiroPak has the potential to reduce the overall size of columns and decrease power consumption, resulting in cost savings for both capital expenditure (CAPEX) and operational expenditure (OPEX) when applied to retrofitting existing systems or incorporated into new processes. Furthermore, pilot to large-scale tests is currently underway to further advance and refine this technology.

Keywords: Additive Manufacturing (AM), 3D printing, Computational Fluid Dynamics (CFD, structured packing (SpiroPak)

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Authors: Sudikshya Bhandari, Jonathan K. London

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The earthquake of April 2015 was one of the biggest disasters in the history of Nepal. The epicenter was located near Barpak, north of the Gorkha district. Before the disaster, this settlement was a compact and homogeneous settlement manifesting its uniqueness through the social and cultural activities, and a distinct vernacular architecture. Narrow alleys with stone paved streets, buildings with slate roofs, and common spaces between the houses made this settlement socially, culturally, and environmentally cohesive. With the presence of micro hydro power plants, local economic activities enabled the local community to exist and thrive. Agriculture and animal rearing are the sources of livelihood for the majority of families, along with the booming homestays (where local people welcome guests to their home, as a business) and local shops. Most of these activities are difficult to find as the houses have been destroyed with the earthquake and the process of reconstruction has been transforming the outlook of the settlement. This study characterized the drastic transformation in Barpak post-earthquake, and analyzed the consequences of the reconstruction process. In addition, it contributes to comprehending a broader representation about unsustainability created by the lack of contextual post-disaster development. Since the research is based in a specific area, a case study approach was used. Sample houses were selected on the basis of ethnicity and house typology. Mixed methods such as key informant and semi structured interviews, focus groups, observations and photographs are used for the collection of data. The research focus is predominantly on the physical change of the house typology from vernacular to externally adopted designs. This transformation of the house entails socio-cultural changes such as social fragmentation with differences among the rich and the poor and decreases in the social connectivity within families and neighborhood. Families have found that new houses require more maintenance and resources that have increased their economic expenses. The study also found that the reconstructed houses are not thermally comfortable in the cold climate of Barpak, leading to the increased use of different sources of heating like electric heaters and more firewood. Lack of storage spaces for crops and livestock have discouraged them to pursue traditional means of livelihood and depend more on buying food from stores, ultimately making it less economical for most of the families. The transformation of space leading to the economic, social and cultural changes demonstrates the unsustainability of Barpak. Conclusions from the study suggest place based and inclusive planning and policy formations that include locals as partners, identifying the possible ways to minimize the impact and implement these recommendations into the future policy and planning scenarios.

Keywords: earthquake, Nepal, reconstruction, settlement, transformation

Procedia PDF Downloads 105

Authors: V. K. Rajaletchumy, S. L. Chia, M. I. Setyawati, M. S. Muthu, S. S. Feng, D. T. Leong

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Triple negative breast cancers (TNBC) can be classified as one of the most aggressive with a high rate of local recurrences and systematic metastases. TNBCs are insensitive to existing hormonal therapy or targeted therapies such as the use of monoclonal antibodies, due to the lack of oestrogen receptor (ER) and progesterone receptor (PR) and the absence of overexpression of human epidermal growth factor receptor 2 (HER2) compared with other types of breast cancers. The absence of targeted therapies for selective delivery of therapeutic agents into tumours, led to the search for druggable targets in TNBC. In this study, we developed a targeted micellar system of cetuximab-conjugated micelles of D-α-tocopheryl polyethylene glycol succinate (vitamin E TPGS) for targeted delivery of docetaxel as a model anticancer drug for the treatment of TNBCs. We examined the efficacy of our micellar system in xenograft models of triple negative breast cancers and explored the effect of the micelles on post-treatment tumours in order to elucidate the mechanism underlying the nanomedicine treatment in oncology. The targeting micelles were found preferentially accumulated in tumours immediately after the administration of the micelles compare to normal tissue. The fluorescence signal gradually increased up to 12 h at the tumour site and sustained for up to 24 h, reflecting the increases in targeted micelles (TPFC) micelles in MDA-MB-231/Luc cells. In comparison, for the non-targeting micelles (TPF), the fluorescence signal was evenly distributed all over the body of the mice. Only a slight increase in fluorescence at the chest area was observed after 24 h post-injection, reflecting the moderate uptake of micelles by the tumour. The successful delivery of docetaxel into tumour by the targeted micelles (TPDC) exhibited a greater degree of tumour growth inhibition than Taxotere® after 15 days of treatment. The ex vivo study has demonstrated that tumours treated with targeting micelles exhibit enhanced cell cycle arrest and attenuated proliferation compared with the control and with those treated non-targeting micelles. Furthermore, the ex vivo investigation revealed that both the targeting and non-targeting micellar formulations shows significant inhibition of cell migration with migration indices reduced by 0.098- and 0.28-fold, respectively, relative to the control. Overall, both the in vivo and ex vivo data increased the confidence that our micellar formulations effectively targeted and inhibited EGF-overexpressing MDA-MB-231 tumours.

Keywords: biodegradable polymers, cancer nanotechnology, drug targeting, molecular biomaterials, nanomedicine

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Authors: Henry Lau, Dilupa Nakandala, Li Zhao

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In today’s business, it is well-recognized that risk is an important factor that needs to be taken into consideration before a decision is made. Studies indicate that both the number of risks faced by organizations and their potential consequences are growing. Supply chain risk management has become one of the major concerns for practitioners and researchers. Supply chain leaders and scholars are now focusing on the importance of managing supply chain risk. In order to meet the challenge of managing and mitigating supply chain risk (SCR), we must first identify the different dimensions of SCR and assess its relevant probability and severity. SCR has been classified in many different ways, and there are no consistently accepted dimensions of SCRs and several different classifications are reported in the literature. Basically, supply chain risks can be classified into two dimensions namely disruption risk and operational risk. Disruption risks are those caused by events such as bankruptcy, natural disasters and terrorist attack. Operational risks are related to supply and demand coordination and uncertainty, such as uncertain demand and uncertain supply. Disruption risks are rare but severe and hard to manage, while operational risk can be reduced through effective SCM activities. Other SCRs include supply risk, process risk, demand risk and technology risk. In fact, the disorganized classification of SCR has created confusion for SCR scholars. Moreover, practitioners need to identify and assess SCR. As such, it is important to have an overarching framework tying all these SCR dimensions together for two reasons. First, it helps researchers use these terms for communication of ideas based on the same concept. Second, a shared understanding of the SCR dimensions will support the researchers to focus on the more important research objective: operationalization of SCR, which is very important for assessing SCR. In general, fresh food supply chain is subject to certain level of risks, such as supply risk (low quality, delivery failure, hot weather etc.) and demand risk (season food imbalance, new competitors). Effective strategies to mitigate fresh food supply chain risk are required to enhance operations. Before implementing effective mitigation strategies, we need to identify the risk sources and evaluate the risk level. However, assessing the supply chain risk is not an easy matter, and existing research mainly use qualitative method, such as risk assessment matrix. To address the relevant issues, this paper aims to analyze the risk factor of the fresh food supply chain using an approach comprising both fuzzy logic and hierarchical holographic modeling techniques. This novel approach is able to take advantage the benefits of both of these well-known techniques and at the same time offset their drawbacks in certain aspects. In order to develop this integrated approach, substantial research work is needed to effectively combine these two techniques in a seamless way, To validate the proposed integrated approach, a case study in a fresh food supply chain company was conducted to verify the feasibility of its functionality in a real environment.

Keywords: fresh food supply chain, fuzzy logic, hierarchical holographic modelling, operationalization, supply chain risk

Procedia PDF Downloads 231

Authors: A. G. Akhundov

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Issues of obtaining unbiased data on the status of pipeline systems of oil- and oil product transportation become especially important when laying and operating pipelines under severe nature and climatic conditions. The essential attention is paid here to researching exogenous processes and their impact on linear facilities of the pipeline system. Reliable operation of pipelines under severe nature and climatic conditions, timely planning and implementation of compensating measures are only possible if operation conditions of pipeline systems are regularly monitored, and changes of permafrost soil and hydrological operation conditions are accounted for. One of the main reasons for emergency situations to appear is the geodynamic factor. Emergency situations are proved by the experience to occur within areas characterized by certain conditions of the environment and to develop according to similar scenarios depending on active processes. The analysis of natural and technical systems of main pipelines at different stages of monitoring gives a possibility of making a forecast of the change dynamics. The integration of GIS technologies, traditional means of geotechnical monitoring (in-line inspection, geodetic methods, field observations), and remote methods (aero-visual inspection, aero photo shooting, air and ground laser scanning) provides the most efficient solution of the problem. The united environment of geo information system (GIS) is a comfortable way to implement the monitoring system on the main pipelines since it provides means to describe a complex natural and technical system and every element thereof with any set of parameters. Such GIS enables a comfortable simulation of main pipelines (both in 2D and 3D), the analysis of situations and selection of recommendations to prevent negative natural or man-made processes and to mitigate their consequences. The specifics of such systems include: a multi-dimensions simulation of facilities in the pipeline system, math modelling of the processes to be observed, and the use of efficient numeric algorithms and software packets for forecasting and analyzing. We see one of the most interesting possibilities of using the monitoring results as generating of up-to-date 3D models of a facility and the surrounding area on the basis of aero laser scanning, data of aerophotoshooting, and data of in-line inspection and instrument measurements. The resulting 3D model shall be the basis of the information system providing means to store and process data of geotechnical observations with references to the facilities of the main pipeline; to plan compensating measures, and to control their implementation. The use of GISs for geotechnical monitoring of pipeline systems is aimed at improving the reliability of their operation, reducing the probability of negative events (accidents and disasters), and at mitigation of consequences thereof if they still are to occur.

Keywords: databases, 3D GIS, geotechnical monitoring, pipelines, laser scaning

Procedia PDF Downloads 185

Authors: Ahmad S. Darwish, Tarek Lemaoui, Hanifa Taher, Inas M. AlNashef, Fawzi Banat

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This research reports a systematic top-down approach for designing neoteric hydrophobic solvents –particularly, deep eutectic solvents (DES) and ionic liquids (IL)– as furfural extractants from aqueous media for the application of sustainable biomass conversion. The first stage of the framework entailed screening 32 neoteric solvents to determine their efficacy against toluene as the application’s conventional benchmark for comparison. The selection criteria for the best solvents encompassed not only their efficiency in extracting furfural but also low viscosity and minimal toxicity levels. Additionally, for the DESs, their natural origins, availability, and biodegradability were also taken into account. From the screening pool, two neoteric solvents were selected: thymol:decanoic acid 1:1 (Thy:DecA) and trihexyltetradecyl phosphonium bis(trifluoromethylsulfonyl) imide [P₁₄,₆,₆,₆][NTf₂]. These solvents outperformed the toluene benchmark, achieving efficiencies of 94.1% and 97.1% respectively, compared to toluene’s 81.2%, while also possessing the desired properties. These solvents were then characterized thoroughly in terms of their physical properties, thermal properties, critical properties, and cross-contamination solubilities. The selected neoteric solvents were then extensively tested under various operating conditions, and an exceptional stable performance was exhibited, maintaining high efficiency across a broad range of temperatures (15–100 °C), pH levels (1–13), and furfural concentrations (0.1–2.0 wt%) with a remarkable equilibrium time of only 2 minutes, and most notably, demonstrated high efficiencies even at low solvent-to-feed ratios. The durability of the neoteric solvents was also validated to be stable over multiple extraction-regeneration cycles, with limited leachability to the aqueous phase (≈0.1%). Moreover, the extraction performance of the solvents was then modeled through machine learning, specifically multiple non-linear regression (MNLR) and artificial neural networks (ANN). The models demonstrated high accuracy, indicated by their low absolute average relative deviations with values of 2.74% and 2.28% for Thy:DecA and [P₁₄,₆,₆,₆][NTf₂], respectively, using MNLR, and 0.10% for Thy:DecA and 0.41% for [P₁₄,₆,₆,₆][NTf₂] using ANN, highlighting the significantly enhanced predictive accuracy of the ANN. The neoteric solvents presented herein offer noteworthy advantages over traditional organic solvents, including their high efficiency in both extraction and regeneration processes, their stability and minimal leachability, making them particularly suitable for applications involving aqueous media. Moreover, these solvents are more environmentally friendly, incorporating renewable and sustainable components like thymol and decanoic acid. This exceptional efficacy of the newly developed neoteric solvents signifies a significant advancement, providing a green and sustainable alternative for furfural production from biowaste.

Keywords: sustainable biomass conversion, furfural extraction, ionic liquids, deep eutectic solvents

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Authors: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Maryam Ziaee, Himanshu Shee, Amrik Sohal

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Big Data Analytics (BDA) in supply chain management has recently drawn the attention of academics and practitioners. Big data refers to a massive amount of data from different sources, in different formats, generated at high speed through transactions in business environments and supply chain networks. Traditional statistical tools and techniques find it difficult to analyse this massive data. BDA can assist organisations to capture, store, and analyse data specifically in the field of supply chain. Currently, there is a paucity of research on BDA in the pharmaceutical supply chain context. In this research, the Australian pharmaceutical supply chain was selected as the case study. This industry is highly significant since the right medicine must reach the right patients, at the right time, in right quantity, in good condition, and at the right price to save lives. However, drug shortages remain a substantial problem for hospitals across Australia with implications on patient care, staff resourcing, and expenditure. Furthermore, a massive volume and variety of data is generated at fast speed from multiple sources in pharmaceutical supply chain, which needs to be captured and analysed to benefit operational decisions at every stage of supply chain processes. As the pharmaceutical industry lags behind other industries in using BDA, it raises the question of whether the use of BDA can improve transparency among pharmaceutical supply chain by enabling the partners to make informed-decisions across their operational activities. This presentation explores the impacts of BDA on supply chain management. An exploratory qualitative approach was adopted to analyse data collected through interviews. This study also explores the BDA potential in the whole pharmaceutical supply chain rather than focusing on a single entity. Twenty semi-structured interviews were undertaken with top managers in fifteen organisations (five pharmaceutical manufacturers, five wholesalers/distributors, and five public hospital pharmacies) to investigate their views on the use of BDA. The findings revealed that BDA can enable pharmaceutical entities to have improved visibility over the whole supply chain and also the market; it enables entities, especially manufacturers, to monitor consumption and the demand rate in real-time and make accurate demand forecasts which reduce drug shortages. Timely and precise decision-making can allow the entities to source and manage their stocks more effectively. This can likely address the drug demand at hospitals and respond to unanticipated issues such as drug shortages. Earlier studies explore BDA in the context of clinical healthcare; however, this presentation investigates the benefits of BDA in the Australian pharmaceutical supply chain. Furthermore, this research enhances managers’ insight into the potentials of BDA at every stage of supply chain processes and helps to improve decision-making in their supply chain operations. The findings will turn the rhetoric of data-driven decision into a reality where the managers may opt for analytics for improved decision-making in the supply chain processes.

Keywords: big data analytics, data-driven decision, pharmaceutical industry, supply chain management

Procedia PDF Downloads 98

Authors: William Kerua

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The PNG University of Technology (Unitech) has mandatory access to teaching, research and extension education. Given such function, the Agriculture Department has established the ‘South Pacific Institute of Sustainable Agriculture and Rural Development (SPISARD)’ in 2004. SPISARD is established as a vehicle to improve farming systems practiced in selected villages by undertaking pluralistic extension method through ‘Educational Institutional Approach’. Unlike other models, SPISARD’s educational institutional approach stresses on improving the whole farming systems practiced in a holistic manner and has a two-fold focus. The first is to understand the farming communities and improve the productivity of the farming systems in a sustainable way to increase income, improve nutrition and food security as well as livelihood enhancement trainings. The second is to enrich the Department’s curriculum through teaching, research, extension and getting inputs from farming community. SPISARD has established number of model villages in various provinces in Papua New Guinea (PNG) and with many positive outcome and success stories. Adaption of ‘educational institutional approach’ thus binds research, extension and training into one package with the use of students and academic staff through model village establishment in delivering development and extension to communities. This centre (SPISARD) coordinates the activities of the model village programs and linkages. The key to the development of the farming systems is establishing and coordinating linkages, collaboration, and developing partnerships both within and external institutions, organizations and agencies. SPISARD has a six-point step strategy for the development of sustainable agriculture and rural development. These steps are (i) establish contact and identify model villages, (ii) development of model village resource centres for research and trainings, (iii) conduct baseline surveys to identify problems/needs of model villages, (iv) development of solution strategies, (v) implementation and (vi) evaluation of impact of solution programs. SPISARD envisages that the farming systems practiced being improved if the villages can be made the centre of SPISARD activities. Therefore, SPISARD has developed a model village approach to channel rural development. The model village when established become the conduit points where teaching, training, research, and technology transfer takes place. This approach is again different and unique to the existing ones, in that, the development process take place in the farmers’ environment with immediate ‘real time’ feedback mechanisms based on the farmers’ perspective and satisfaction. So far, we have developed 14 model villages and have conducted 75 trainings in 21 different areas/topics in 8 provinces to a total of 2,832 participants of both sex. The aim of these trainings is to directly participate with farmers in the pursuit to improving their farming systems to increase productivity, income and to secure food security and nutrition, thus to improve their livelihood.

Keywords: development, educational institutional approach, livelihood improvement, sustainable agriculture

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Authors: Mas Pertiwi I. G. AG Istri, Sri Kristinayanti Wayan, Oka Aryawan I. Gede Made

Abstract:

Ability of government to meet the needs of infrastructure investment constrained by the size of the budget commitments for other sectors. Another barrier is the complexity of the process of land acquisition. Public Private Partnership can help bridge the investment gap by including the amount of funding from the private sector, shifted the responsibility of financing, construction of the asset, and the operation and post-project design and care to them. In principle, a construction project implementation always requires the investor as a party to provide resources in the form of funding which it must be contained in a successor agreement in the form of a contract. In general, construction contracts consist of contracts which passed in Indonesia and contract International. One source of funding used in the implementation of construction projects comes from funding that comes from the collaboration between the government and the private sector, for example with the system: BLT (Build Lease Transfer), BOT (Build Operate Transfer), BTO (Build Transfer Operate) and BOO (Build Operate Own). And form of payment under a construction contract can be distinguished several ways: monthly payment, payments based on progress and payment after completed projects (Turn Key). One of the tools used to analyze the feasibility of the investment is to use financial models. The financial model describes the relationship between different variables and assumptions used. From a financial model will be known how the cash flow structure of the project, which includes revenues, expenses, liabilities to creditors and the payment of taxes to the government. Net cash flow generated from the project will be used as a basis for analyzing the feasibility of investment source of project financing Public Private Partnership could come from equity or debt. The proportion of funding according to its source is a comparison of a number of investment funds originating from each source of financing for a total investment cost during the construction period by selected the contract system and several alternative financing percentage ratio determined according to sources will generate cash flow structure that is different. Of the various possibilities for the structure of the cash flow generated will be analyzed by software is to test T Paired to compared the contract system used by various alternatives comparison of financing to determine the effect of the contract system and the comparison of such financing for the feasibility of investment toll road construction project for the economic life of 20 (twenty) years. In this use case studies of toll road contruction project Bali Mandara. And in this analysis only covered two systems contracts, namely Build Operate Transfer and Turn Key. Based on the results obtained by analysis of the variable investment feasibility of the NPV, BCR and IRR between the contract system Build Operate Transfer and contract system Turn Key on the interest rate of 9%, 12% and 15%.

Keywords: contract system, financing, internal rate of return, net present value

Procedia PDF Downloads 219

Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

Abstract:

The U.S. Federal Emergency Management Agency (FEMA) developed flood maps based on experts’ experience and estimates of the probability of flooding. Current flood-risk models evaluate flood risk with regional and subjective measures without impact from torrential rain and nuisance flooding at the neighborhood level. Nuisance flooding occurs in small areas in the community, where a few streets or blocks are routinely impacted. This type of flooding event occurs when torrential rainstorm combined with high tide and sea level rise temporarily exceeds a given threshold. In South Florida, this threshold is 1.7 ft above Mean Higher High Water (MHHW). The National Weather Service defines torrential rain as rain deposition at a rate greater than 0.3-inches per hour or three inches in a single day. Data from the Florida Climate Center, 1970 to 2020, shows 371 events with more than 3-inches of rain in a day in 612 months. The purpose of this research is to develop a data-driven method to determine comprehensive analytical damage-avoidance criteria that account for nuisance flood events at the single-family home level. The method developed uses the Failure Mode and Effect Analysis (FMEA) method from the American Society of Quality (ASQ) to estimate the Damage Avoidance (DA) preparation for a 1-day 100-year storm. The Consequence of Nuisance Flooding (CoNF) is estimated from community mitigation efforts to prevent nuisance flooding damage. The Probability of Nuisance Flooding (PoNF) is derived from the frequency and duration of torrential rainfall causing delays and community disruptions to daily transportation, human illnesses, and property damage. Urbanization and population changes are related to the U.S. Census Bureau's annual population estimates. Data collected by the United States Department of Agriculture (USDA) Natural Resources Conservation Service’s National Resources Inventory (NRI) and locally by the South Florida Water Management District (SFWMD) track the development and land use/land cover changes with time. The intent is to include temporal trends in population density growth and the impact on land development. Results from this investigation provide the risk of nuisance flooding as a function of CoNF and PoNF for coastal areas of South Florida. The data-based criterion provides awareness to local municipalities on their flood-risk assessment and gives insight into flood management actions and watershed development.

Keywords: flood risk, nuisance flooding, urban flooding, FMEA

Procedia PDF Downloads 81

Authors: Gautier Girard, Marion Martiny, Sebastien Mercier, Mohamad Jrad, Mohamed-Slim Bahi, Laurent Bodin, Francois Lechleiter, David Nevo, Sophie Dareys

Abstract:

Reliability of electronic devices has always been of highest interest for Aero-MIL and space applications. In any electronic device, Printed Circuit Board (PCB), providing interconnection between components, is a key for reliability. During the last decades, PCB technologies evolved to sustain and/or fulfill increased original equipment manufacturers requirements and specifications, higher densities and better performances, faster time to market and longer lifetime, newer material and mixed buildups. From the very beginning of the PCB industry up to recently, qualification, experiments and trials, and errors were the most popular methods to assess system (PCB) reliability. Nowadays OEM, PCB manufacturers and scientists are working together in a close relationship in order to develop predictive models for PCB reliability and lifetime. To achieve that goal, it is fundamental to characterize precisely base materials (laminates, electrolytic copper, …), in order to understand failure mechanisms and simulate PCB aging under environmental constraints by means of finite element method for example. The laminates are woven composites and have thus an orthotropic behaviour. The in-plane properties can be measured by combining classical uniaxial testing and digital image correlation. Nevertheless, the out-of-plane properties cannot be evaluated due to the thickness of the laminate (a few hundred of microns). It has to be noted that the knowledge of the out-of-plane properties is fundamental to investigate the lifetime of high density printed circuit boards. A homogenization method combining analytical and numerical approaches has been developed in order to obtain the complete elastic orthotropic behaviour of a woven composite from its precise 3D internal structure and its experimentally measured in-plane elastic properties. Since the mechanical properties of the resin surrounding the fibres are unknown, an inverse method is proposed to estimate it. The methodology has been applied to one laminate used in hyperfrequency spatial applications in order to get its elastic orthotropic behaviour at different temperatures in the range [-55°C; +125°C]. Next; numerical simulations of a plated through hole in a double sided PCB are performed. Results show the major importance of the out-of-plane properties and the temperature dependency of these properties on the lifetime of a printed circuit board. Acknowledgements—The support of the French ANR agency through the Labcom program ANR-14-LAB7-0003-01, support of CNES, Thales Alenia Space and Cimulec is acknowledged.

Keywords: homogenization, orthotropic behaviour, printed circuit board, woven composites

Procedia PDF Downloads 194