Search results for: ordinary differential equation networks

Authors: Sara Saboonian, Pierre Filion

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There are two distinct planning approaches attempting to transform the North American suburb so as to reduce its adverse environmental impacts. The first one, the recentralization approach, proposes intensification, multi-functionality and more reliance on public transit and walking. It thus offers an alternative to the prevailing low-density, spatial specialization and automobile dependence of the North American suburb. The second approach concentrates instead on the provision of green infrastructure, which rely on natural systems rather than on highly engineered solutions to deal with the infrastructure needs of suburban areas. There are tensions between these two approaches as recentralization generally overlooks green infrastructure, which can be space consuming (as in the case of water retention systems), and thus conflicts with the intensification goals of recentralization. The research investigates three Canadian planned suburban centres in the Greater Toronto Area, where recentralization is the current planning practice, despite rising awareness of the benefits of green infrastructure. Methods include reviewing the literature on green infrastructure planning, a critical analysis of the Ontario provincial plans for recentralization, surveying residents’ preferences regarding alternative suburban development models, and interviewing officials who deal with the local planning of the three centres. The case studies expose the difficulties in creating planned suburban centres that accommodate green infrastructure while adhering to recentralization principles. Until now, planners have been mostly focussed on recentralization at the expense of green infrastructure. In this context, the frequent lack of compatibility between recentralization and the space requirements of green infrastructure explains the limited presence of such infrastructures in planned suburban centres. Finally, while much attention has been given in the planning discourse to the economic and lifestyle benefits of recentralization, much less has been made of the wide range of advantages of green infrastructure, which explains limited public mobilization over the development of green infrastructure networks. The paper will concentrate on ways of combining recentralization with green infrastructure strategies and identify the aspects of the two approaches that are most compatible with each other. The outcome of such blending will marry high density, public-transit oriented developments, which generate walkability and street-level animation, with the presence of green space, naturalized settings and reliance on renewable energy. The paper will advance a planning framework that will fuse green infrastructure with recentralization, thus ensuring the achievement of higher density and reduced reliance on the car along with the provision of critical ecosystem services throughout cities. This will support and enhance the objectives of both green infrastructure and recentralization.

Keywords: environmental-based planning, green infrastructure, multi-functionality, recentralization

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Authors: Waleed Al-Nuaimy, Luke Anastassiou, Manjinder Kainth

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As the process of teaching has evolved with the advent of new technologies over the ages, so has the process of learning. Educators have perpetually found themselves on the lookout for new technology-enhanced methods of teaching in order to increase learning efficiency and decrease ever expanding workloads. Shortly after the invention of the internet, web-based learning started to pick up in the late 1990s and educators quickly found that the process of providing learning material and marking assignments could change thanks to the connectivity offered by the internet. With the creation of early web-based virtual learning environments (VLEs) such as SPIDER and Blackboard, it soon became apparent that VLEs resulted in higher reported computer self-efficacy among students, but at the cost of students being less satisfied with the learning process . It may be argued that the impersonal nature of VLEs, and their limited functionality may have been the leading factors contributing to this reported dissatisfaction. To this day, often faced with the prospects of assigning colossal engineering cohorts their homework and assessments, educators may frequently choose optimally curated assessment formats, such as multiple-choice quizzes and numerical answer input boxes, so that automated grading software embedded in the VLEs can save time and mark student submissions instantaneously. A crucial skill that is meant to be learnt during most science and engineering undergraduate degrees is gaining the confidence in using, solving and deriving mathematical equations. Equations underpin a significant portion of the topics taught in many STEM subjects, and it is in homework assignments and assessments that this understanding is tested. It is not hard to see that this can become challenging if the majority of assignment formats students are engaging with are multiple-choice questions, and educators end up with a reduced perspective of their students’ ability to manipulate equations. Artificial intelligence (AI) has in recent times been shown to be an important consideration for many technologies. In our paper, we explore the use of new AI based software designed to work in conjunction with current VLEs. Using our experience with the software, we discuss its potential to solve a selection of problems ranging from impersonality to the reduction of educator workloads by speeding up the marking process. We examine the software’s potential to increase learning efficiency through its features which claim to allow more customized and higher-quality feedback. We investigate the usability of features allowing students to input equation derivations in a range of different forms, and discuss relevant observations associated with these input methods. Furthermore, we make ethical considerations and discuss potential drawbacks to the software, including the extent to which optical character recognition (OCR) could play a part in the perpetuation of errors and create disagreements between student intent and their submitted assignment answers. It is the intention of the authors that this study will be useful as an example of the implementation of AI in a practical assessment scenario insofar as serving as a springboard for further considerations and studies that utilise AI in the setting and marking of science and engineering assignments.

Keywords: engineering education, assessment, artificial intelligence, optical character recognition (OCR)

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Authors: Annis Lai Chu Fung

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While aggression had high stability throughout developmental stages and across generations, it should be the top priority of researchers and frontline helping professionals to develop prevention and intervention programme for aggressive children and children at risk of developing aggressive behaviours. Although there is a substantial amount of anti-bullying programmes, they gave disappointingly small effect sizes. The neglectful practical significance could be attributed to the overly simplistic categorisation of individuals involved as bullies or victims. In the past three decades, the distinction between reactive and proactive aggression has been well-proved. As children displaying reactively aggressive behaviours have distinct social-information processing pattern with those showing proactively aggressive behaviours, it is critical to identify the unique needs of the two subtypes accordingly when designing an intervention. The onset of reactive aggression and proactive aggression was observed at earliest in 4.4 and 6.8 years old respectively. Such findings called for a differential early intervention targeting these high-risk children. However, to the best of the author’s knowledge, the author was the first to establish an evidence-based intervention programme against reactive and proactive aggression. With the largest samples in the world, the author, in the past 10 years, explored three different approaches and their effectiveness against aggression quantitatively and qualitatively with longitudinal design. The three approaches presented are (a) cognitive-behavioral approach, (b) moral education, with Chinese marital arts and ethics as the medium, and (c) bioneurological measures (omega-3 supplementation). The studies adopted a multi-informant approach with repeated measures before and after the intervention, and follow-up assessment. Participants were recruited from primary and secondary schools in Hong Kong. In the cognitive-behavioral approach, 66 reactive aggressors and 63 proactive aggressors, aged from 11 to 17, were identified from 10,096 secondary-school children with questionnaire and subsequent structured interview. Participants underwent 10 group sessions specifically designed for each subtype of aggressor. Results revealed significant declines in aggression levels from the baseline to the follow-up assessment after 1 year. In moral education through the Chinese martial arts, 315 high-risk aggressive children, aged 6 to 12 years, were selected from 3,511 primary-school children and randomly assigned into four types of 10-session intervention group, namely martial-skills-only, martial-ethics-only, both martial-skills-and-ethics, and physical fitness (placebo). Results showed only the martial-skills-and-ethics group had a significant reduction in aggression after treatment and 6 months after treatment comparing with the placebo group. In the bioneurological approach, 218 children, aged from 8 to 17, were randomly assigned to the omega-3 supplement group and the placebo group. Results revealed that compared with the placebo group, the omega-3 supplement group had significant declines in aggression levels at the 6-month follow-up assessment. All three approaches were effective in reducing proactive and reactive aggression. Traditionally, intervention programmes against aggressive behaviour often adapted the cognitive and/or behavioural approach. However, cognitive-behavioural approach for children was recently challenged by its demanding requirement of cognitive ability. Traditional cognitive interventions may not be as beneficial to an older population as in young children. The present study offered an insightful perspective in aggression reduction measures.

Keywords: intervention, outcome effectiveness, proactive aggression, reactive aggression

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Authors: Bijit Kalita, K. V. N. Surendra

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The pulley works under both compressive loading due to contacting belt in tension and central torque due to cause rotation. In a power transmission system, the belt pulley assemblies offer a contact problem in the form of two mating cylindrical parts. In this work, we modeled a pulley as a heavy two-dimensional circular disk. Stress analysis due to contact loading in the pulley mechanism is performed. Finite element analysis (FEA) is conducted for a pulley to investigate the stresses experienced on its inner and outer periphery. In most of the heavy-duty applications, most frequently used mechanisms to transmit power in applications such as automotive engines, industrial machines, etc. is Belt Drive. Usually, very heavy circular disks are used as pulleys. A pulley could be entitled as a drum and may have a groove between two flanges around the circumference. A rope, belt, cable or chain can be the driving element of a pulley system that runs over the pulley inside the groove. A pulley is experienced by normal and shear tractions on its contact region in the process of motion transmission. The region may be belt-pulley contact surface or pulley-shaft contact surface. In 1895, Hertz solved the elastic contact problem for point contact and line contact of an ideal smooth object. Afterward, this hypothesis is generally utilized for computing the actual contact zone. Detailed stress analysis in such contact region of such pulleys is quite necessary to prevent early failure. In this paper, the results of the finite element analyses carried out on the compressed disk of a belt pulley arrangement using fracture mechanics concepts are shown. Based on the literature on contact stress problem induced in the wide field of applications, generated stress distribution on the shaft-pulley and belt-pulley interfaces due to the application of high-tension and torque was evaluated in this study using FEA concepts. Finally, the results obtained from ANSYS (APDL) were compared with the Hertzian contact theory. The study is mainly focused on the fatigue life estimation of a rotating part as a component of an engine assembly using the most famous Paris equation. Digital Image Correlation (DIC) analyses have been performed using the open-source software. From the displacement computed using the images acquired at a minimum and maximum force, displacement field amplitude is computed. From these fields, the crack path is defined and stress intensity factors and crack tip position are extracted. A non-linear least-squares projection is used for the purpose of the estimation of fatigue crack growth. Further study will be extended for the various application of rotating machinery such as rotating flywheel disk, jet engine, compressor disk, roller disk cutter etc., where Stress Intensity Factor (SIF) calculation plays a significant role on the accuracy and reliability of a safe design. Additionally, this study will be progressed to predict crack propagation in the pulley using maximum tangential stress (MTS) criteria for mixed mode fracture.

Keywords: crack-tip deformations, contact stress, stress concentration, stress intensity factor

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Authors: Rocío González-Sánchez, Sara Alonso-Muñoz

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Food waste implies an inefficient management of the final stages in the food supply chain. Referring to Sustainable Development Goals (SDGs) by United Nations, the SDG 12.3 proposes to halve per capita food waste at the retail and consumer level and to reduce food losses. In the linear system, food waste is disposed and, to a lesser extent, recovery or reused after consumption. With the negative effect on stocks, the current food consumption system is based on ‘produce, take and dispose’ which put huge pressure on raw materials and energy resources. Therefore, greater focus on the circular management of food waste will mitigate the environmental, economic, and social impact, following a Triple Bottom Line (TBL) approach and consequently the SDGs fulfilment. A mixed methodology is used. A total sample of 311 publications from Web of Science database were retrieved. Firstly, it is performed a bibliometric analysis by SciMat and VOSviewer software to visualise scientific maps about co-occurrence analysis of keywords and co-citation analysis of journals. This allows for the understanding of the knowledge structure about this field, and to detect research issues. Secondly, a systematic literature review is conducted regarding the most influential articles in years 2020 and 2021, coinciding with the most representative period under study. Thirdly, to support the development of this field it is proposed an agenda according to the research gaps identified about circular economy and food waste management. Results reveal that the main topics are related to waste valorisation, the application of waste-to-energy circular model and the anaerobic digestion process towards fossil fuels replacement. It is underlined that the use of food as a source of clean energy is receiving greater attention in the literature. There is a lack of studies about stakeholders’ awareness and training. In addition, available data would facilitate the implementation of circular principles for food waste recovery, management, and valorisation. The research agenda suggests that circularity networks with suppliers and customers need to be deepened. Technological tools for the implementation of sustainable business models, and greater emphasis on social aspects through educational campaigns are also required. This paper contributes on the application of circularity to food waste management by abandoning inefficient linear models. Shedding light about trending topics in the field guiding to scholars for future research opportunities.

Keywords: bibliometric analysis, circular economy, food waste management, future research lines

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Authors: Esna B. Buğday, Niray Tunçel

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Spirituality has a motivational influence on consumers' psychological states, lifestyles, and behavioral intentions. Spirituality refers to the feeling that there is a divine power greater than ourselves and a connection among oneself, others, nature, and the sacred. In addition, spirituality concerns the human soul and spirit against the material and physical world and consists of three dimensions: self-discovery, relationships, and belief in a higher power. Of them, self-discovery is to explore the meaning and the purpose of life. Relationships refer to the awareness of the connection between human beings and nature as well as respect for them. In addition, higher power represents the transcendent aspect of spirituality, which means to believe in a holy power that creates all the systems in the universe. Furthermore, a voluntary simplicity lifestyle is (1) to adopt a simple lifestyle by minimizing the attachment to and the consumption of material things and possessions, (2) to have an ecological awareness respecting all living creatures, and (3) to express the desire for exploring and developing the inner life. Voluntary simplicity is a multi-dimensional construct that consists of a desire for a voluntarily simple life (e.g., avoiding excessive consumption), cautious attitudes in shopping (e.g., not buying unnecessary products), acceptance of self-sufficiency (e.g., being self-sufficient individual), and rejection of highly developed functions of products (e.g., preference for simple functioned products). One of the main reasons for living simply is to sustain a spiritual life, as voluntary simplicity provides the space for achieving psychological and spiritual growth, cultivating self-reliance since voluntary simplifier frees themselves from the overwhelming externals and takes control of their daily lives. From this point of view, it is expected that people with a strong sense of spirituality will be likely to adopt a simple lifestyle. In this respect, the study aims to examine the impact of spirituality on consumers' voluntary simple lifestyle tendencies. As consumers' consumption attitudes and behaviors depend on their lifestyles, exploring the factors that lead them to embrace voluntary simplicity significantly predicts their purchase behavior. In this respect, this study presents empirical research based on a data set collected from 478 Turkish consumers through an online survey. First, exploratory factor analysis is applied to the data to reveal the dimensions of spirituality and voluntary simplicity scales. Second, confirmatory factor analysis is conducted to assess the measurement model. Last, the hypotheses are analyzed using partial least square structural equation modeling (PLS-SEM). The results confirm that spirituality's self-discovery and relationships dimensions positively impact both cautious attitudes in shopping and acceptance of self-sufficiency dimensions of voluntary simplicity. In contrast, belief in a higher power does not significantly influence consumers' voluntary simplicity tendencies. Even though there has been theoretical support drawing a positive relationship between spirituality and voluntary simplicity, to the best of the authors' knowledge, this has not been empirically tested in the literature before. Hence, this study contributes to the current knowledge by analyzing the direct influence of spirituality on consumers' voluntary simplicity tendencies. Additionally, analyzing this impact on the consumers of an emerging market is another contribution to the literature.

Keywords: spirituality, voluntary simplicity, self-sufficiency, conscious shopping, Turkish consumers

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Authors: E. Gaury, P. Mandausch, O. Picot, A. R. Thomas, L. Veisblat, L. Ralambozanany, C. Delsart

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In Dakar, demographic and spatial growth was accompanied by a 50% increase in household waste between 1988 and 2008 in the city. In addition, a change in the nature of household waste was observed between 1990 and 2007. The share of plastic increased by 15% between 2004 and 2007 in Dakar. Plastics represent the seventh category of household waste, the most produced per year in Senegal. The share of plastic in household and similar waste is 9% in Senegal. Waste management in the city of Dakar is a complex process involving a multitude of formal and informal actors with different perceptions and objectives. The objective of this study was to understand the motivations that could lead to sorting action, as well as the perception of plastic waste sorting within the Dakar population (households and institutions). The problematic of this study was as follows: what may be the factors playing a role in the sorting action? In an attempt to answer this, two approaches have been developed: (1) An exploratory qualitative study by semi-structured interviews with two groups of individuals concerned by the sorting of plastic waste: on the one hand, the experts in charge of waste management and on the other the households-producers of waste plastics. This study served as the basis for formulating the hypotheses and thus for the quantitative analysis. (2) A quantitative study using a questionnaire survey method among households producing plastic waste in order to test the previously formulated hypotheses. The objective was to have quantitative results representative of the population of Dakar in relation to the behavior and the process inherent in the adoption of the plastic waste sorting action. The exploratory study shows that the perception of state responsibility varies between institutions and households. Public institutions perceive this as a shared responsibility because the problem of plastic waste affects many sectors (health, environmental education, etc.). Their involvement is geared more towards raising awareness and educating young people. As state action is limited, the emergence of private companies in this sector seems logical as they are setting up collection networks to develop a recycling activity. The state plays a moral support role in these activities and encourages companies to do more. The study of the understanding of the action of sorting plastic waste by the population of Dakar through a quantitative analysis was able to demonstrate the attitudes and constraints inherent in the adoption of plastic waste sorting.Cognitive attitude, knowledge, and visible consequences have been shown to correlate positively with sorting behavior. Thus, it would seem that the population of Dakar is more sensitive to what they see and what they know to adopt sorting behavior.It has also been shown that the strongest constraints that could slow down sorting behavior were the complexity of the process, too much time and the lack of infrastructure in which to deposit plastic waste.

Keywords: behavior, Dakar, plastic waste, waste management

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Authors: Katharina Eberhardt, Florian Klaus Kaiser, Frank Schultmann

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Last-mile distribution is one of the most critical parts of a disaster relief operation. Various uncertainties, such as infrastructure conditions, resource availability, and fluctuating beneficiary demand, render last-mile distribution challenging in disaster relief operations. The need to balance critical performance criteria like response time, meeting demand and cost-effectiveness further complicates the task. The occurrence of disasters cannot be controlled, and the magnitude is often challenging to assess. In summary, these uncertainties create a need for additional flexibility, agility, and preparedness in logistics operations. As a result, strategic planning and efficient network design are critical for an effective and efficient response. Furthermore, the increasing frequency of disasters and the rising cost of logistical operations amplify the need to provide robust and resilient solutions in this area. Therefore, we formulate a scenario-based bi-objective optimization model that integrates pre-positioning, allocation, and distribution of relief supplies extending the general form of a covering location problem. The proposed model aims to minimize underlying logistics costs while maximizing demand coverage. Using a set of disruption scenarios, the model allows decision-makers to identify optimal network solutions to address the risk of disruptions. We provide an empirical case study of the public authorities’ emergency food storage strategy in Germany to illustrate the potential applicability of the model and provide implications for decision-makers in a real-world setting. Also, we conduct a sensitivity analysis focusing on the impact of varying stockpile capacities, single-site outages, and limited transportation capacities on the objective value. The results show that the stockpiling strategy needs to be consistent with the optimal number of depots and inventory based on minimizing costs and maximizing demand satisfaction. The strategy has the potential for optimization, as network coverage is insufficient and relies on very high transportation and personnel capacity levels. As such, the model provides decision support for public authorities to determine an efficient stockpiling strategy and distribution network and provides recommendations for increased resilience. However, certain factors have yet to be considered in this study and should be addressed in future works, such as additional network constraints and heuristic algorithms.

Keywords: humanitarian logistics, bi-objective optimization, pre-positioning, last mile distribution, decision support, disaster relief networks

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Authors: A. M. Byrne, E. Bonfiglio, C. Rigby, N. Edelstyn

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Introduction: Neuromarketing employs numerous methodologies when investigating products and advertisement effectiveness. Electroencephalography (EEG), a non-invasive measure of electrical activity from the brain, is commonly used in neuromarketing. EEG data can be considered using time-frequency (TF) analysis, where changes in the frequency of brainwaves are calculated to infer participant’s mental states, or event-related potential (ERP) analysis, where changes in amplitude are observed in direct response to a stimulus. This presentation discusses the findings of a systematic review of EEG measures in neuromarketing. A systematic review summarises evidence on a research question, using explicit measures to identify, select, and critically appraise relevant research papers. Thissystematic review identifies which EEG measures are the most robust predictor of customer preference and purchase intention. Methods: Search terms identified174 papers that used EEG in combination with marketing-related stimuli. Publications were excluded if they were written in a language other than English or were not published as journal articles (e.g., book chapters). The review investigated which TF effect (e.g., theta-band power) and ERP component (e.g., N400) most consistently reflected preference and purchase intention. Machine-learning prediction was also investigated, along with the use of EEG combined with physiological measures such as eye-tracking. Results: Frontal alpha asymmetry was the most reliable TF signal, where an increase in activity over the left side of the frontal lobe indexed a positive response to marketing stimuli, while an increase in activity over the right side indexed a negative response. The late positive potential, a positive amplitude increase around 600 ms after stimulus presentation, was the most reliable ERP component, reflecting the conscious emotional evaluation of marketing stimuli. However, each measure showed mixed results when related to preference and purchase behaviour. Predictive accuracy was greatly improved through machine-learning algorithms such as deep neural networks, especially when combined with eye-tracking or facial expression analyses. Discussion: This systematic review provides a novel catalogue of the most effective use of each EEG measure commonly used in neuromarketing. Exciting findings to emerge are the identification of the frontal alpha asymmetry and late positive potential as markers of preferential responses to marketing stimuli. Predictive accuracy using machine-learning algorithms achieved predictive accuracies as high as 97%, and future research should therefore focus on machine-learning prediction when using EEG measures in neuromarketing.

Keywords: EEG, ERP, neuromarketing, machine-learning, systematic review, time-frequency

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: Aidan N. Smallwood, Celestine R. Weegenaar, Jack N. Evans

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The intensive care unit (ICU) is a particularly resource heavy environment, in terms of staff, drugs and equipment required. Whilst many areas of the hospital are attempting to cut down on plastic use and minimise their impact on the environment, this has proven challenging within the confines of intensive care. Concurrently, as globalization has progressed over recent decades, there has been a tendency towards centralised manufacturing with international distribution networks for products, often covering large distances. In this study, we have modelled the standard consumption of plastic single-use items over the course of the first 24-hours of an average individual patient’s stay in a 12 bed ICU in the United Kingdom (UK). We have identified the country of manufacture and calculated the minimum possible distance travelled by each item from factory to patient. We have assumed direct transport via the shortest possible straight line from country of origin to the UK and have not accounted for transport within either country. Assuming an intubated patient with invasive haemodynamic monitoring and central venous access, there are a total of 52 distincts, largely plastic, disposable products which would reasonably be required in the first 24-hours after admission. Each product type has only been counted once to account for multiple items being shipped as one package. Travel distances from origin were summed to give the total distance combined for all 52 products. The minimum possible total distance travelled from country of origin to the UK for all types of product was 273,353 km, equivalent to 6.82 circumnavigations of the globe, or 71% of the way to the moon. The mean distance travelled was 5,256 km, approximately the distance from London to Mecca. With individual packaging for each item, the total weight of consumed products was 4.121 kg. The CO2 produced shipping these items by air freight would equate to 30.1 kg, however doing the same by sea would produce 0.2 kg CO2. Extrapolating these results to the 211,932 UK annual ICU admissions (2018-2019), even with the underestimates of distance and weight of our assumptions, air freight would account for 6586 tons CO2 emitted annually, approximately 130 times that of sea freight. Given the drive towards cost saving within the UK health service, and the decline of the local manufacturing industry, buying from intercontinental manufacturers is inevitable However, transporting all consumables by sea where feasible would be environmentally beneficial, as well as being less costly than air freight. At present, the NHS supply chain purchases from medical device companies, and there is no freely available information as to the transport mode used to deliver the product to the UK. This must be made available to purchasers in order to give a fuller picture of life cycle impact and allow for informed decision making in this regard.

Keywords: CO2, intensive care, plastic, transport

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Authors: Hind Alshoubaki

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The world is now confronting a widespread urban phenomenon: refugee camps, which have mostly been established in ‘rushing mode,’ pointing toward affording temporary settlements for refugees that provide them with minimum levels of safety, security and protection from harsh weather conditions within a very short time period. In fact, those emergency settlements are transforming into permanent ones since time is a decisive factor in terms of construction and camps’ age. These play an essential role in transforming their temporary character into a permanent one that generates deep modifications to the city’s territorial structure, shaping a new identity and creating a contentious change in the city’s form and history. To achieve a better understanding for the transformation of refugee camps, this study is based on a mixed-methods approach: the qualitative approach explores different refugee camps and analyzes their transformation process in terms of population density and the changes to the city’s territorial structure and urban features. The quantitative approach employs a statistical regression analysis as a reliable prediction of refugees’ satisfaction within the Zaatari camp in order to predict its future transformation. Obviously, refugees’ perceptions of their current conditions will affect their satisfaction, which plays an essential role in transforming emergency settlements into permanent cities over time. The test basically discusses five main themes: the access and readiness of schools, the dispersion of clinics and shopping centers; the camp infrastructure, the construction materials, and the street networks. The statistical analysis showed that Syrian refugees were not satisfied with their current conditions inside the Zaatari refugee camp and that they had started implementing changes according to their needs, desires, and aspirations because they are conscious about the fact of their prolonged stay in this settlement. Also, the case study analyses showed that neglecting the fact that construction takes time leads settlements being created with below-minimum standards that are deteriorating and creating ‘slums,’ which lead to increased crime rates, suicide, drug use and diseases and deeply affect cities’ urban tissues. For this reason, recognizing the ‘temporary-eternal’ character of those settlements is the fundamental concept to consider refugee camps from the beginning as definite permanent cities. This is the key factor to minimize the trauma of displacement on both refugees and the hosting countries. Since providing emergency settlements within a short time period does not mean using temporary materials, having a provisional character or creating ‘makeshift cities.’

Keywords: refugee, refugee camp, temporary, Zaatari

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Authors: Lei Ye, Min Liu, Yong-Li Gao, Jun Zhang

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Purpose: The aims of the study are to investigate the status of health-promoting lifestyle and to compare the healthy lifestyle of emergency nurses in different levels of hospitals in Sichuan province, China. The investigation is mainly about the health-promoting lifestyle, including spiritual growth, health responsibility, physical activity, nutrition, interpersonal relations, stress management. Then the factors were analyzed influencing the health-promoting lifestyle of emergency nurses in hospitals of Sichuan province in order to find the relevant models to provide reference evidence for intervention. Study Design: A cross-sectional research method was adopted. Stratified cluster sampling, based on geographical location, was used to select the health facilities of 1389 emergency nurses in 54 hospitals from Sichuan province in China. Method: The 52-item, six-factor structure Health-Promoting Lifestyle Profile II (HPLP- II) instrument was used to explore participants’ self-reported health-promoting behaviors and measure the dimensions of health responsibility, physical activity, nutrition, interpersonal relations, spiritual growth, and stress management. Demographic characteristics, education, work duration, emergency nursing work duration and self-rated health status were documented. Analysis: Data were analyzed through SPSS software ver. 17.0. Frequency, percentage, mean ± standard deviation were used to describe the general information, while the Nonparametric Test was used to compare the constituent ratio of general data of different hospitals. One-way ANOVA was used to compare the scores of health-promoting lifestyle in different levels hospital. A multiple linear regression model was established. P values which were less than 0.05 determined statistical significance in all analyses. Result: The survey showed that the total score of health-promoting lifestyle of nurses at emergency departments in Sichuan Province was 120.49 ± 21.280. The relevant dimensions are ranked by scores in descending order: interpersonal relations, nutrition, health responsibility, physical activity, stress management, spiritual growth. The total scores of the three-A hospital were the highest (121.63 ± 0.724), followed by the senior class hospital (119.7 ± 1.362) and three-B hospital (117.80 ± 1.255). The difference was statistically significant (P=0.024). The general data of nurses was used as the independent variable which includes age, gender, marital status, living conditions, nursing income, hospital level, Length of Service in nursing, Length of Service in emergency, Professional Title, education background, and the average number of night shifts. The total score of health-promoting lifestyle was used as dependent variable; Multiple linear regression analysis method was adopted to establish the regression model. The regression equation F = 20.728, R2 = 0.061, P < 0.05, the age, gender, nursing income, turnover intention and status of coping stress affect the health-promoting lifestyle of nurses in emergency department, the result was statistically significant (P < 0.05 ). Conclusion: The results of the investigation indicate that it will help to develop health promoting interventions for emergency nurses in all levels of hospital in Sichuan Province through further research. Managers need to pay more attention to emergency nurses’ exercise, stress management, self-realization, and conduct intervention in nurse training programs.

Keywords: emergency nurse, health-promoting lifestyle profile II, health behaviors, lifestyle

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Authors: Aisha Siddiqa

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The knowledge of pragmatic practices in a particular language is considered key to effective communication. Unlike one’s native language where this knowledge is acquired spontaneously, more conscious attention is required to learn second language pragmatics. Traditional foreign language (FL) classrooms generally focus on the acquisition of vocabulary and lexico-grammatical structures, neglecting pragmatic functions that are essential for effective communication in the multilingual networks of the modern world. In terms of effective communication, of particular importance is knowledge of what is perceived as polite or impolite in a certain language, an aspect of pragmatics which is not perceived as obligatory but is nonetheless indispensable for successful intercultural communication and integration. While learning a second language, the acquisition of politeness assumes more prominence as the politeness norms and practices vary according to language and culture. Therefore, along with focusing on the ‘use’ of politeness strategies, it is crucial to examine the ‘acquisition’ and the ‘acquisitional development’ of politeness strategies by second language learners, particularly, by lower proficiency leaners as the norms of politeness are usually focused in lower levels. Hence, there is an obvious need for a study that not only investigates the acquisition of pragmatics by young FL learners using innovative multiple methods; but also identifies the potential causes of the gaps in their development. The present research employs a cross sectional design to explore the acquisition of politeness by young English as a foreign language learners (EFL) in France; at three levels of secondary school learning. The methodology involves two phases. In the first phase a cartoon oral production task (COPT) is used to elicit samples of requests from young EFL learners in French schools. These data are then supplemented by a) role plays, b) an analysis of textbooks, and c) video recordings of classroom activities. This mixed method approach allows us to explore the repertoire of politeness strategies the learners possess and delve deeper into the opportunities available to learners in classrooms to learn politeness strategies in requests. The paper will provide the results of the analysis of COPT data for 250 learners at three different stages of English as foreign language development. Data analysis is based on categorization of requests developed in CCSARP project. The preliminary analysis of the COPT data shows that there is substantial evidence of pragmalinguistic development across all levels but the developmental process seems to gain momentum in the second half of the secondary school period as compared to the early period at school. However, there is very little evidence of sociopragmatic development. The study aims to document the current classroom practices in France by looking at the development of young EFL learner’s politeness strategies across three levels of secondary schools.

Keywords: acquisition, English, France, interlanguage pragmatics, politeness

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Authors: Katerina Krizova, Inigo Molina

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The ongoing climate change affects various natural processes resulting in significant changes in human life. Since there is still a growing human population on the planet with more or less limited resources, agricultural production became an issue and a satisfactory amount of food has to be reassured. To achieve this, agriculture is being studied in a very wide context. The main aim here is to increase primary production on a spatial unit while consuming as low amounts of resources as possible. In Europe, nowadays, the staple issue comes from significantly changing the spatial and temporal distribution of precipitation. Recent growing seasons have been considerably affected by long drought periods that have led to quantitative as well as qualitative yield losses. To cope with such kind of conditions, new techniques and technologies are being implemented in current practices. However, behind assessing the right management, there is always a set of the necessary information about plot properties that need to be acquired. Remotely sensed data had gained attention in recent decades since they provide spatial information about the studied surface based on its spectral behavior. A number of space platforms have been launched carrying various types of sensors. Spectral indices based on calculations with reflectance in visible and NIR bands are nowadays quite commonly used to describe the crop status. However, there is still the staple limit by this kind of data - cloudiness. Relatively frequent revisit of modern satellites cannot be fully utilized since the information is hidden under the clouds. Therefore, microwave remote sensing, which can penetrate the atmosphere, is on its rise today. The scientific literature describes the potential of radar data to estimate staple soil (roughness, moisture) and vegetation (LAI, biomass, height) properties. Although all of these are highly demanded in terms of agricultural monitoring, the crop moisture content is the utmost important parameter in terms of agricultural drought monitoring. The idea behind this study was to exploit the unique combination of SAR (Sentinel-1) and optical (Sentinel-2) data from one provider (ESA) to describe potential crop water stress during dry cropping season of 2019 at six winter wheat plots in the central Czech Republic. For the period of January to August, Sentinel-1 and Sentinel-2 images were obtained and processed. Sentinel-1 imagery carries information about C-band backscatter in two polarisations (VV, VH). Sentinel-2 was used to derive vegetation properties (LAI, FCV, NDWI, and SAVI) as support for Sentinel-1 results. For each term and plot, summary statistics were performed, including precipitation data and soil moisture content obtained through data loggers. Results were presented as summary layouts of VV and VH polarisations and related plots describing other properties. All plots performed along with the principle of the basic SAR backscatter equation. Considering the needs of practical applications, the vegetation moisture content may be assessed using SAR data to predict the drought impact on the final product quality and yields independently of cloud cover over the studied scene.

Keywords: precision agriculture, remote sensing, Sentinel-1, SAR, water content

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Authors: Mohamed Gaafar, Evan Davies

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Many municipalities within Canada and abroad use chloramination to disinfect drinking water so as to avert the production of the disinfection by-products (DBPs) that result from conventional chlorination processes and their consequential public health risks. However, the long-lasting monochloramine disinfectant (NH2Cl) can pose a significant risk to the environment. As, it can be introduced into stormwater sewers, from different water uses, and thus freshwater sources. Little research has been undertaken to monitor and characterize the decay of NH2Cl and to study the parameters affecting its decomposition in stormwater networks. Therefore, the current study was intended to investigate this decay starting by building a stormwater model and validating its hydraulic and hydrologic computations, and then modelling water quality in the storm sewers and examining the effects of different parameters on chloramine decay. The presented work here is only the first stage of this study. The 30th Avenue basin in Southern Edmonton was chosen as a case study, because the well-developed basin has various land-use types including commercial, industrial, residential, parks and recreational. The City of Edmonton has already built a MIKE-URBAN stormwater model for modelling floods. Nevertheless, this model was built to the trunk level which means that only the main drainage features were presented. Additionally, this model was not calibrated and known to consistently compute pipe flows higher than the observed values; not to the benefit of studying water quality. So the first goal was to complete modelling and updating all stormwater network components. Then, available GIS Data was used to calculate different catchment properties such as slope, length and imperviousness. In order to calibrate and validate this model, data of two temporary pipe flow monitoring stations, collected during last summer, was used along with records of two other permanent stations available for eight consecutive summer seasons. The effect of various hydrological parameters on model results was investigated. It was found that model results were affected by the ratio of impervious areas. The catchment length was tested, however calculated, because it is approximate representation of the catchment shape. Surface roughness coefficients were calibrated using. Consequently, computed flows at the two temporary locations had correlation coefficients of values 0.846 and 0.815, where the lower value pertained to the larger attached catchment area. Other statistical measures, such as peak error of 0.65%, volume error of 5.6%, maximum positive and negative differences of 2.17 and -1.63 respectively, were all found in acceptable ranges.

Keywords: stormwater, urban drainage, simulation, validation, MIKE URBAN

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Rasha Elsawy

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Aside from the rapid growth of global information technology and the Internet, another key trend is the swift proliferation of wearable technologies. The future of wearable technologies is very bright as an emerging revolution in this technological world. Beyond this, individual continuance intention toward IT is an important area that drew academics' and practitioners' attention. The literature review exhibits that continuance usage is an important concern that needs to be addressed for any technology to be advantageous and for consumers to succeed. However, consumers noticeably abandon their wearable devices soon after purchase, losing all subsequent benefits that can only be achieved through continued usage. Purpose-This thesis aims to develop an integrated model designed to explain and predict consumers' behavioural intention(BI) and continued use (CU) of wearable fitness technology (WFT) to identify the determinants of the CU of technology. Because of this, the question arises as to whether there are differences between technology adoption and post-adoption (CU) factors. Design/methodology/approach- The study employs the unified theory of acceptance and use of technology2 (UTAUT2), which has the best explanatory power, as an underpinning framework—extending it with further factors, along with user-specific personal characteristics as moderators. All items will be adapted from previous literature and slightly modified according to the WFT/SW context. A longitudinal investigation will be carried out to examine the research model, wherein a survey will include these constructs involved in the conceptual model. A quantitative approach based on a questionnaire survey will collect data from existing wearable technology users. Data will be analysed using the structural equation modelling (SEM) method based on IBM SPSS statistics and AMOS 28.0. Findings- The research findings will provide unique perspectives on user behaviour, intention, and actual continuance usage when accepting WFT. Originality/value- Unlike previous works, the current thesis comprehensively explores factors that affect consumers' decisions to continue using wearable technology. That is influenced by technological/utilitarian, affective, emotional, psychological, and social factors, along with the role of proposed moderators. That novel research framework is proposed by extending the UTAUT2 model with additional contextual variables classified into Performance Expectancy, Effort Expectancy, Social Influence (societal pressure regarding body image), Facilitating Conditions, Hedonic Motivation (to be split up into two concepts: perceived enjoyment and perceived device annoyance), Price value, and Habit-forming techniques; adding technology upgradability as determinants of consumers' behavioural intention and continuance usage of Information Technology (IT). Further, using personality traits theory and proposing relevant user-specific personal characteristics (openness to technological innovativeness, conscientiousness in health, extraversion, neuroticism, and agreeableness) to moderate the research model. Thus, the present thesis obtains a more convincing explanation expected to provide theoretical foundations for future emerging IT (such as wearable fitness devices) research from a behavioural perspective.

Keywords: wearable technology, wearable fitness devices/smartwatches, continuance use, behavioural intention, upgradability, longitudinal study

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Authors: Tunde Ope-Davies

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Transmediality and platformization as online content-sharing protocols have continued to accentuate the growing impact of the unprecedented digital revolution across the world. The rapid transformation across all sectors as a result of this revolution has continued to spotlight the increasing importance of new media technologies in redefining and reshaping the rhythm and dynamics of our private and public discursive practices. Equally, social and political activities are being impacted daily through the creation and transmission of political discourse content through multi-channel platforms such as mobile telephone communication, social media networks and the internet. It has been observed that digital platforms have become central to the production, processing, and distribution of multimodal social data and cultural content. The platformization paradigm thus underpins our understanding of how digital platforms enhance the production and heterogenous distribution of media and cultural content through these platforms and how this process facilitates socioeconomic and political activities. The use of multiple digital platforms to share and transmit political discourse material synchronously and asynchronously has gained some exciting momentum in the last few years. Nigeria’s 2023 general elections amplified the usage of social media and other online platforms as tools for electioneering campaigns, socio-political mobilizations and civic engagement. The study, therefore, focuses on transmedia and platformed political discourse as a new strategy to promote political candidates and their manifesto in order to mobilize support and woo voters. This innovative transmedia digital discourse model involves a constellation of online texts and images transmitted through different online platforms almost simultaneously. The data for the study was extracted from the 2023 general elections campaigns in Nigeria between January- March 2023 through media monitoring, manual download and the use of software to harvest the online electioneering campaign material. I adopted a discursive-analytic qualitative technique with toolkits drawn from a computer-mediated multimodal discourse paradigm. The study maps the progressive development of digital political discourse in this young democracy. The findings also demonstrate the inevitable transformation of modern democratic practice through platform-dependent and transmedia political discourse. Political actors and media practitioners now deploy layers of social media network platforms to convey messages and mobilize supporters in order to aggregate and maximize the impact of their media campaign projects and audience reach.

Keywords: social media, digital humanities, political discourse, platformized discourse, multimodal discourse

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Authors: J. Van Engeland, C. Lavigne, S. De Jaeger

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In the light of the transition towards a more circular economy, recovery of products, parts or materials will gain in importance. Additionally, the EU proximity principle related to waste management and emissions generated by transporting large amounts of end-of-life products, shift attention to local recovery networks. The Flemish inter-communal cooperation for municipal solid waste management Meetjesland (IVM) is currently investigating the set-up of such a network. More specifically, the network encompasses the recycling of polyvinyl chloride (PVC), which is collected in separate containers. When these containers are full, a truck should transport them to the processor which can recycle the PVC into new products. This paper proposes a model to optimize the container collection. The containers are located at different Civic Amenity sites (CA sites) in a certain region. Since people can drop off their waste at these CA sites, the containers will gradually fill up during a planning horizon. If a certain container is full, it has to be collected and replaced by an empty container. The collected waste is then transported to a single processor. To perform this collection and transportation of containers, the responsible firm has a set of vehicles stationed at a single depot and different personnel crews. A vehicle can load exactly one container. If a trailer is attached to the vehicle, it can load an additional container. Each day of the planning horizon, the different crews and vehicles leave the depot to collect containers at the different sites. After loading one or two containers, the crew has to drive to the processor for unloading the waste and to pick up empty containers. Afterwards, the crew can again visit sites or it can return to the depot to end its collection work for that day. All along the collection process, the crew has to respect the opening hours of the sites. In order to allow for some flexibility, a crew is allowed to wait a certain amount of time at the gate of a site until it opens. The problem described can be modelled as a variant to the PVRP-TW (Periodic Vehicle Routing Problem with Time Windows). However, a vehicle can at maximum load two containers, hence only two subsequent site visits are possible. For that reason, we will refer to the model as a model for building tactical waste collection schemes. The goal is to a find a schedule describing which crew should visit which CA site on which day to minimize the number of trucks and the routing costs. The model was coded in IBM CPLEX Optimization studio and applied to a number of test instances. Good results were obtained, and specific suggestions concerning route and truck costs could be made. For a large range of input parameters, collection schemes using two trucks are obtained.

Keywords: container collection, crew scheduling, mixed integer linear programming, waste management

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Authors: Nick Woodier, Iain Moppett

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Background: It is estimated that one in ten patients admitted to hospital will suffer an adverse event in their care. While the majority of these will result in low harm, patients are being significantly harmed by the processes meant to help them. Healthcare, therefore, seeks to make improvements in patient safety by taking learning from other industries that are perceived to be more mature in their management of safety events. Of particular interest to healthcare are ‘near misses,’ those events that almost happened but for an intervention. Healthcare does not have any guidance as to how best to manage and learn from near misses to reduce the chances of harm to patients. The authors, as part of a larger study of near-miss management in healthcare, sought to learn from the UK nuclear sector to develop principles for how healthcare can identify, report, and learn from near misses to improve patient safety. The nuclear sector was chosen as an exemplar due to its status as an ultra-safe industry. Methods: A Grounded Theory (GT) methodology, augmented by a scoping review, was used. Data collection included interviews, scenario discussion, field notes, and the literature. The review protocol is accessible online. The GT aimed to develop theories about how nuclear manages near misses with a focus on defining them and clarifying how best to support reporting and analysis to extract learning. Near misses related to radiation release or exposure were focused on. Results: Eightnuclear interviews contributed to the GT across nuclear power, decommissioning, weapons, and propulsion. The scoping review identified 83 articles across a range of safety-critical industries, with only six focused on nuclear. The GT identified that nuclear has a particular focus on precursors and low-level events, with regulation supporting their management. Exploration of definitions led to the recognition of the importance of several interventions in a sequence of events, but that do not solely rely on humans as these cannot be assumed to be robust barriers. Regarding reporting and analysis, no consistent methods were identified, but for learning, the role of operating experience learning groups was identified as an exemplar. The safety culture across nuclear, however, was heard to vary, which undermined reporting of near misses and other safety events. Some parts of the industry described that their focus on near misses is new and that despite potential risks existing, progress to mitigate hazards is slow. Conclusions: Healthcare often sees ‘nuclear,’ as well as other ultra-safe industries such as ‘aviation,’ as homogenous. However, the findings here suggest significant differences in safety culture and maturity across various parts of the nuclear sector. Healthcare can take learning from some aspects of management of near misses in nuclear, such as how they are defined and how learning is shared through operating experience networks. However, healthcare also needs to recognise that variability exists across industries, and comparably, it may be more mature in some areas of safety.

Keywords: culture, definitions, near miss, nuclear safety, patient safety

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Authors: Wellemans Isabelle, Remmelink Myriam, Foucart Annick, Rusu Stefan, Compère Christophe

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Primary pulmonary meningioma (PPM) is a very rare tumor, and its occurrence has been reported only sporadically. Multiple PPMs are even more exceptional, and herein, we report, to the best of our knowledge, the fourth case, focusing on the clinicopathological features of the tumor. Moreover, the possible relationship between the use of progesterone–only contraceptives and the development of these neoplasms will be discussed. Case Report: We report a case of a 51-year-old female presenting three solid pulmonary nodules, with the following localizations: right upper lobe, middle lobe, and left lower lobe, described as incidental findings on computed tomography (CT) during a pre-bariatric surgery check-up. The patient revealed no drinking or smoking history. The physical exam was unremarkable except for the obesity. The lesions ranged in size between 6 and 24 mm and presented as solid nodules with lobulated contours. The largest lesion situated in the middle lobe had mild fluorodeoxyglucose (FDG) uptake on F-18 FDG positron emission tomography (PET)/CT, highly suggestive of primary lung neoplasm. For pathological assessment, video-assisted thoracoscopic middle lobectomy and wedge resection of the right upper nodule was performed. Histological examination revealed relatively well-circumscribed solid proliferation of bland meningothelial cells growing in whorls and lobular nests, presenting intranuclear pseudo-inclusions and psammoma bodies. No signs of anaplasia were observed. The meningothelial cells expressed diffusely Vimentin, focally Progesterone receptors and were negative for epithelial (cytokeratin (CK) AE1/AE3, CK7, CK20, Epithelial Membrane Antigen (EMA)), neuroendocrine markers (Synaptophysin, Chromogranin, CD56) and Estrogenic receptors. The proliferation labelling index Ki-67 was low (<5%). Metastatic meningioma was ruled out by brain and spine magnetic resonance imaging (MRI) scans. The third lesion localized in the left lower lobe was followed-up and resected three years later because of its slow but significant growth (14 mm to 16 mm), alongside two new infra centimetric lesions. Those three lesions showed a morphological and immunohistochemical profile similar to previously resected lesions. The patient was disease-free one year post-last surgery. Discussion: Although PPMs are mostly benign and slow-growing tumors with an excellent prognosis, they do not present specific radiological characteristics, and it is difficult to differentiate it from other lung tumors, histopathologic examination being essential. Aggressive behavior is associated with atypical or anaplastic features (WHO grades II–III) The etiology is still uncertain and different mechanisms have been proposed. A causal connection between sexual hormones and meningothelial proliferation has long been suspected and few studies examining progesterone only contraception and meningioma risk have all suggested an association. In line with this, our patient was treated with Levonorgestrel, a progesterone agonist, intra-uterine device (IUD). Conclusions: PPM, defined by the typical histological and immunohistochemical features of meningioma in the lungs and the absence of central nervous system lesions, is an extremely rare neoplasm, mainly solitary and associating, and indolent growth. Because of the unspecific radiologic findings, it should always be considered in the differential diagnosis of lung neoplasms. Regarding multiple PPM, only three cases are reported in the literature, and this is the first described in a woman treated by a progesterone-only IUD to the best of our knowledge.

Keywords: pulmonary meningioma, multiple meningioma, meningioma, pulmonary nodules

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Authors: David Tennison

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In the wake of the Covid-19 pandemic, a new chronic illness emerged onto the global stage: Long Covid. Long Covid presents with several symptoms commonly seen in other poorly-understood illnesses, such as fibromyalgia (FM) and myalgic encephalomyelitis/ chronic fatigue syndrome (ME/CFS). However, while Long Covid has swiftly become a recognised illness, FM and ME/CFS are still seen as contested, which impacts patient care and healthcare experiences. This study aims to examine what the differences are between Long Covid and FM; and if the Long Covid case can provide guidance for how to address the healthcare challenge of contested illnesses. To address this question, this study performed comprehensive research into the history of FM; our current biomedical understanding of it; and available healthcare interventions (within the context of the UK NHS). Analysis was undertaken of the stigma and stereotypes around FM, and a comparison made between FM and the emerging Long Covid literature, along with the healthcare response to Long Covid. This study finds that healthcare for chronic contested illnesses in the UK is vastly insufficient - in terms of pharmaceutical and holistic interventions, and the provision of secondary care options. Interestingly, for Long Covid, many of the treatment suggestions are pulled directly from those used for contested illnesses. The key difference is in terms of funding and momentum – Long Covid has generated exponentially more interest and research in a short time than there has been in the last few decades of contested illness research. This stands to help people with FM and ME/CFS – for example, research has recently been funded into “brain fog”, a previously elusive and misunderstood symptom. FM is culturally regarded as a “women’s disease” and FM stigma stems from notions of “hysteria”. A key finding is that the idea of FM affecting women disproportionally is not reflected in modern population studies. Emerging data on Long Covid also suggests a slight leaning towards more female patients, however it is less feminised, potentially due to it emerging in the global historical moment of the pandemic. Another key difference is that FM is rated as an extremely low-prestige illness by healthcare professionals, while it was in large part due to the advocacy of affected healthcare professionals that Long Covid was so quickly recognised by science and medicine. In conclusion, Long Covid (and the risk of future pandemics and post-viral illnesses) highlight a crucial need for implementing new, and reinforcing existing, care networks for chronic illnesses. The difference in how contested illnesses like FM, and new ones like Long Covid are treated have a lot to do with the historical moment in which they emerge – but cultural stereotypes, from within and without medicine, need updating. Particularly as they contribute to disease stigma that causes genuine harm to patients. However, widespread understanding and acceptance of Long Covid could help fight contested illness stigma, and the attention, funding and research into Long Covid may actually help raise the profile of contested illnesses and uncover answers about their symptomatology.

Keywords: long COVID, fibromyalgia, myalgic encephalomyelitis, chronic fatigue syndrome, NHS, healthcare, contested illnesses, chronic illnesses, COVID-19 pandemic

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Authors: Rommila Chandra, Harshika Choudhary

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The value of integrated, participatory, and community based sustainable development strategies is eminent, but in practice, it still remains fragmentary and often leads to short-lived results. Despite the global presence of climate change, its impacts are felt differently by different communities based on their vulnerability. The developing countries have the low adaptive capacity and high dependence on environmental variables, making them highly susceptible to outmigration and poverty. We need to understand how to enable these approaches, taking into account the various governmental and non-governmental stakeholders functioning at different levels, to deliver long-term socio-economic and environmental well-being of local communities. The research assessed the financial and natural vulnerability of Himalayan networks, focusing on their potential to adapt to various changes, through accessing their perceived reactions and local knowledge. The evaluation was conducted by testing indices for vulnerability, with a major focus on indicators for adaptive capacity. Data for the analysis were collected from the villages around Govind National Park and Wildlife Sanctuary, located in the Indian Himalayan Region. The villages were stratified on the basis of connectivity via road, thus giving two kinds of human settlements connected and isolated. The study focused on understanding the complex relationship between outmigration and the socio-cultural sentiments of local people to not abandon their land, assessing their adaptive capacity for livelihood opportunities, and exploring their contribution that integrated participatory methodologies can play in delivering sustainable development. The result showed that the villages having better road connectivity, access to market, and basic amenities like health and education have a better understanding about the climatic shift, natural hazards, and a higher adaptive capacity for income generation in comparison to the isolated settlements in the hills. The participatory approach towards environmental conservation and sustainable use of natural resources were seen more towards the far-flung villages. The study helped to reduce the gap between local understanding and government policies by highlighting the ongoing adaptive practices and suggesting precautionary strategies for the community studied based on their local conditions, which differ on the basis of connectivity and state of development. Adaptive capacity in this study has been taken as the externally driven potential of different parameters, leading to a decrease in outmigration and upliftment of the human environment that could lead to sustainable livelihood development in the rural areas of Himalayas.

Keywords: adaptive capacity, Indian Himalayan region, participatory, sustainable livelihood development

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Authors: Martin Pellon Consunji

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Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

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Authors: Majid Farsadrouh Rashti, Alireza Mohammadinejad, Amir Shafiee Kisomi

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Lead (Pb²⁺), a cation, is a prime constituent of the majority of the industrial effluents such as mining, smelting and coal combustion, Pb-based painting and Pb containing pipes in water supply systems, paper and pulp refineries, printing, paints and pigments, explosive manufacturing, storage batteries, alloy and steel industries. The maximum permissible limit of lead in the water used for drinking and domesticating purpose is 0.01 mg/L as advised by Bureau of Indian Standards, BIS. This becomes the acceptable 'safe' level of lead(II) ions in water beyond which, the water becomes unfit for human use and consumption, and is potential enough to lead health problems and epidemics leading to kidney failure, neuronal disorders, and reproductive infertility. Superabsorbent hydrogels are loosely crosslinked hydrophilic polymers that in contact with aqueous solution can easily water and swell to several times to their initial volume without dissolving in aqueous medium. Superabsorbents are kind of hydrogels capable to swell and absorb a large amount of water in their three-dimensional networks. While the shapes of hydrogels do not change extensively during swelling, because of tremendously swelling capacity of superabsorbent, their shape will broadly change.Because of their superb response to changing environmental conditions including temperature pH, and solvent composition, superabsorbents have been attracting in numerous industrial applications. For instance, water retention property and subsequently. Natural-based superabsorbent hydrogels have attracted much attention in medical pharmaceutical, baby diapers, agriculture, and horticulture because of their non-toxicity, biocompatibility, and biodegradability. Novel superabsorbent hydrogel nanocomposites were prepared by graft copolymerization of acrylamide and itaconic acid in the presence of nanoclay (laponite), using methylene bisacrylamide (MBA) and potassium persulfate, former as a crosslinking agent and the second as an initiator. The superabsorbent hydrogel nanocomposites structure was characterized by FTIR spectroscopy, SEM and TGA Spectroscopy adsorption of metal ions on poly (AAm-co-IA). The equilibrium swelling values of copolymer was determined by gravimetric method. During the adsorption of metal ions on polymer, residual metal ion concentration in the solution and the solution pH were measured. The effects of the clay content of the hydrogel on its metal ions uptake behavior were studied. The NC hydrogels may be considered as a good candidate for environmental applications to retain more water and to remove heavy metals.

Keywords: adsorption, hydrogel, nanocomposite, super adsorbent

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Authors: Surupa Shaw, Debjyoti Banerjee

Abstract:

Enhancing heat transfer in compact volumes is a challenge when constrained by cost issues, especially those associated with requirements for minimizing pumping power consumption. This is particularly acute for electronic chip cooling applications. Technological advancements in microelectronics have led to development of chip architectures that involve increased power consumption. As a consequence packaging, technologies are saddled with needs for higher rates of power dissipation in smaller form factors. The increasing circuit density, higher heat flux values for dissipation and the significant decrease in the size of the electronic devices are posing thermal management challenges that need to be addressed with a better design of the cooling system. Maximizing surface area for heat exchanging surfaces (e.g., extended surfaces or “fins”) can enable dissipation of higher levels of heat flux. Fractal structures have been shown to maximize surface area in compact volumes. Self-replicating structures at multiple length scales are called “Fractals” (i.e., objects with fractional dimensions; unlike regular geometric objects, such as spheres or cubes whose volumes and surface area values scale as integer values of the length scale dimensions). Fractal structures are expected to provide an appropriate technology solution to meet these challenges for enhanced heat transfer in the microelectronic devices by maximizing surface area available for heat exchanging fluids within compact volumes. In this study, the effect of different fractal micro-channel architectures and flow structures on the enhancement of transport phenomena in heat exchangers is explored by parametric variation of fractal dimension. This study proposes a model that would enable cost-effective solutions for thermal-fluid transport for energy applications. The objective of this study is to ascertain the sensitivity of various parameters (such as heat flux and pressure gradient as well as pumping power) to variation in fractal dimension. The role of the fractal parameters will be instrumental in establishing the most effective design for the optimum cooling of microelectronic devices. This can help establish the requirement of minimal pumping power for enhancement of heat transfer during cooling. Results obtained in this study show that the proposed models for fractal architectures of microchannels significantly enhanced heat transfer due to augmentation of surface area in the branching networks of varying length-scales.

Keywords: fractals, microelectronics, constructal theory, heat transfer enhancement, pumping power enhancement

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Authors: Fouad Mrad, Viviane Zaccour

Abstract:

The accelerated developments in the political, economic, environmental, security, health, and social folders are exhausting planners across the world, especially in Arab countries. The impact of the tension is multifaceted and has resulted in conflicts, wars, migration, and human insecurity. The potential cross-cutting role that science, innovation and technology can play in supporting Arab societies to address these pressing challenges is a serious, unique chance for the people of the region. This opportunity is based on the existing capacity of educated youth and inaccessible talents in the local universities and research centers. It has been accepted that Arab countries have achieved major advancements in the economy, education and social wellbeing since the 70s of the 20th Century. Mainly direct outcome of the oil and other natural resources. The UN Secretary-General, during the Education Summit in Sep 2022, stressed that “Learning continues to underplay skills, including problem-solving, critical thinking and empathy.” Stars of Science by Qatar Foundation was launched in 2009 and has been sustained through 2023. Consistent mission from the start: To mobilize a new generation of Pan-Arab innovators and problem solvers by encouraging youth participation and interest in Science, Technology and Entrepreneurship throughout the Arab world via the program and its social media activities. To make science accessible and attractive to mass audiences by de-mystifying the process of innovation. Harnessing best practices within reality TV to show that science, engineering, and innovation are important in everyday life and can be fun.” Thousands of Participants learned unforgettable lessons; winners changed their lives forever as they learned and earned seed capital; they became drivers of change in their countries and families; millions of viewers were exposed to an innovative experimental process, and culturally, several relevant national institutions adopted the SOS track in their national initiatives. The program exhibited experientially youth self-efficacy as the most distinct core property of human agency, which is an individual's belief in his or her capacity to execute behaviors necessary to produce specific performance attainments. In addition, the program proved that innovations are performed by networks of people with different sets of technological, useful knowledge, skills and competencies introduced by socially shared technological knowledge as a main determinant of economic activities in any economy.

Keywords: science, invention, innovation, Qatar foundation, QSTP, prototyping

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Authors: Alba Ballester Ciuró, Marc Pares Franzi

Abstract:

While coming decades are likely to see a higher flood risk in Europe and greater socio-economic damages, traditional flood risk management has become inefficient. In response to that, new approaches such as capacity building and public participation have recently been incorporated in natural hazards mitigation policy (i.e. Sendai Framework for Action, Intergovernmental Panel on Climate Change reports and EU Floods Directive). By integrating capacity building and public participation, we present a research concerning the promotion of participatory social capacity building actions for flood risk mitigation at the local level. Social capacities have been defined as the resources and abilities available at individual and collective level that can be used to anticipate, respond to, cope with, recover from and adapt to external stressors. Social capacity building is understood as a process of identifying communities’ social capacities and of applying collaborative strategies to improve them. This paper presents a proposal of systematization of participatory social capacity building process for flood risk mitigation, and its implementation in a high risk of flooding area in the Ebro river basin: Ribera Alta del Ebro. To develop this process, we designed and tested a tool that allows measuring and building five types of social capacities: knowledge, motivation, networks, participation and finance. The tool implementation has allowed us to assess social capacities in the area. Upon the results of the assessment we have developed a co-decision process with stakeholders and flood risk management authorities on which participatory activities could be employed to improve social capacities for flood risk mitigation. Based on the results of this process, and focused on the weaker social capacities, we developed a set of participatory actions in the area oriented to general public and stakeholders: informative sessions on flood risk management plan and flood insurances, interpretative river descents on flood risk management (with journalists, teachers, and general public), interpretative visit to the floodplain, workshop on agricultural insurance, deliberative workshop on project funding, deliberative workshops in schools on flood risk management (playing with a flood risk model). The combination of obtaining data through a mixed-methods approach of qualitative inquiry and quantitative surveys, as well as action research through co-decision processes and pilot participatory activities, show us the significant impact of public participation on social capacity building for flood risk mitigation and contributes to the understanding of which main factors intervene in this process.

Keywords: flood risk management, public participation, risk reduction, social capacities, vulnerability assessment

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Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

Abstract:

This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

Procedia PDF Downloads 149