Search results for: soetal complexity

Authors: Ngoc Thao Linh Dang

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Urban waterfront redevelopment is a global phenomenon, and thousands of schemes are being carried out in large metropoles, medium-sized cities, and even small towns all over the world. This opportunity brings the city back to the river and rediscovers waterfront revitalization as a unique opportunity for cities to reconnect with their unique historical and cultural image. The redevelopment can encourage economic investments, serve as a social platform for public interactions, and allow dwellers to express their rights to the city. Many coastal cities have effectively transformed the perception of their waterfront area through years of redevelopment initiatives, having been neglected for over a century. However, this process has never been easy due to the particular complexity of the space: local culture, history, and market-led development. Moreover, municipal governments work out the balance of diverse stakeholder interests, especially when repurposing high-profile and redundant spaces that form the core of urban economic investment while also accommodating the present and future generations in sustainable environments. Urban critics consistently grapple with the effectiveness of the planning process on the new waterfront, where public spaces are criticized for presenting a lack of opportunities for actual public participation due to privatization and authoritarian governance while no longer doing what they are ‘meant to’: all arise in reaction to the perceived failure of these places to meet expectations. The planning culture and the decision-making context determine the level of public involvement in the planning process; however, in the context of competing market forces and commercial interests dominating cities’ planning agendas, planning for public space in urban waterfronts tends to be for economic gain rather than supporting residents' social needs. These newly pleasing settings satisfied the cluster of middle-class individuals, new communities living along the waterfront, and tourists. A trend of public participatory exclusion is primarily determined by the nature of the planning being undertaken and the decision-making context in which it is embedded. Starting from this context, the research investigates the influence of planning on waterfront regeneration and the role of participation in this process. The research aims to look specifically at the characteristics of the planning process of the waterfront in Da Nang and its impact on the regeneration of the place to regain the city’s historical value and enhance local cultural identity and images. Vietnam runs a top-down planning system where municipal governments have control or power over what happens in their city following the approved planning from the national government. The community has never been excluded from development; however, their participation is still marginalized. In order to ensure social equality, a proposed approach called "bottom-up" should be considered and implemented alongside the traditional "top-down" process and provide a balance of perspectives, as it allows for the voices of the most underprivileged social group involved in a planning project to be heard, rather than ignored. The research provides new insights into the influence of the planning process on the waterfront regeneration in the context of Da Nang.

Keywords: planning process, public participation, top-down planning, waterfront regeneration

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Authors: Rafael Alexandre Dos Reis

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Research has shown a substantial increase in the participation of Conventionally Fuelled Vehicles (CFVs) in the urban transport modal split. The reasons for this unsustainable reality are multiple, from economic interventions to individual behaviour. The development and delivery of positive incentives for the adoption of more environmental-friendly modes of transport is an emerging strategy to help in tackling the problem of excessive use of conventionally fuelled vehicles. The efficiency of this approach, like other information-based schemes, can benefit from the knowledge of their potential impacts in theoretical constructs of multiple behaviour change theories. The goal of this research is to critically analyse theories of behaviour that are relevant to transport research and the impacts of positive incentives on the theoretical determinants of behaviour, strengthening the current body of evidence about the benefits of this approach. The main method to investigate this will involve a literature review on two main topics: the current theories of behaviour that have empirical support in transport research and the past or ongoing positive incentives programs that had an impact on car use reduction. The reviewed programs of positive incentives were the following: The TravelSmart®; Spitsmijden®; Incentives for Singapore Commuters® (INSINC); COMMUTEGREENER®; MOVESMARTER®; STREETLIFE®; SUPERHUB®; SUNSET® and the EMPOWER® project. The theories analysed were the heory of Planned Behaviour (TPB); The Norm Activation Theory (NAM); Social Learning Theory (SLT); The Theory of Interpersonal Behaviour (TIB); The Goal-Setting Theory (GST) and The Value-Belief-Norm Theory (VBN). After the revisions of the theoretical constructs of each of the theories and their influence on car use, it can be concluded that positive incentives schemes impact on behaviour change in the following manners: -Changing individual’s attitudes through informational incentives; -Increasing feelings of moral obligations to reduce the use of CFVs; -Increase the perceived social pressure to engage in more sustainable mobility behaviours through the use of comparison mechanisms in social media, for example; -Increase the perceived control of behaviour through informational incentives and training incentives; -Increasing personal norms with reinforcing information; -Providing tools for self-monitoring and self-evaluation; -Providing real experiences in alternative modes to the car; -Making the observation of others’ car use reduction possible; -Informing about consequences of behaviour and emphasizing the individual’s responsibility with society and the environment; -Increasing the perception of the consequences of car use to an individual’s valued objects; -Increasing the perceived ability to reduce threats to environment; -Help establishing goals to reduce car use; - iving personalized feedback on the goal; -Increase feelings of commitment to the goal; -Reducing the perceived complexity of the use of alternatives to the car. It is notable that the emerging technique of delivering positive incentives are systematically connected to causal determinants of travel behaviour. The preliminary results of the reviewed programs evidence how positive incentives might strengthen these determinants and help in the process of behaviour change.

Keywords: positive incentives, private car use reduction, sustainable behaviour, voluntary travel behaviour change

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Authors: Mirele Plenishti

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Revisionist powers are sometimes associated to revolutionary and status quo powers, this because along the line representing the level of satisfaction–dissatisfaction with the system, revisionist powers are located in between status quo and revolutionary powers. In particular, the case of revisionist powers seeking for social status adjustments (while having status quo intentions) can, in the first option, be refuted due to the disbelief that dissatisfaction could coexist with status quo intentions – this entailing the possibility to trigger a spiral effect by over-counter-reacting. In the second option, revisionist powers can be underestimated as a real threat, this entailing a potential inadequate reaction. The necessity to well manage international change entails the need to understand better how revisionist powers seek for changes in status, within the system. The complexity of this case is heightened by the propensity of both IR scholars and practitioners to infer states' aims and intentions – towards the system – by looking at their behaviours. This has resulted in the tendency to consider cooperative international behaviours as symptomatic of status quo intentions, and vice versa: status quo intentions as manifested through positive/cooperative behaviours. Similarly, assertive/competitive international behaviours are considered as symptomatic (and vice versa, as manifestations) of revolutionary intentions. Therefore, within complex and composite foreign policies, scholars who disbelieve the existence of revisionist powers with status quo intentions, tend to highlight the negative/competitive elements; while more optimist scholars tend to focus on conforming/cooperative behaviours. Both perspectives, while understanding relevant components of the complex international interaction, still miss a composite overview. In order to closely investigate the strategies adopted by (status quo aiming) revisionist states, and by drawing on sociological studies on peer relations, focused on children's behaviour, one could expect that the compresence of both positive (compliant/cooperative) and negative (competitive/assertive) behaviours, is deliberate, and functional to seeking social status adjustments. Indeed, at the end of 90s, peer relation studies focused on children's behaviour, discerned between the concept of social acceptance (that refers to the degree of social preference assigned to the child– how much is s/he liked) and popularity (which refers to the social status assigned to the child within the group). By building on this distinction, it was possible to identify a link relating social acceptance to prosocial (compliant/cooperative) behaviours and strategies, and popularity to both prosocial and antisocial (aggressive/assertive) behaviours and strategies. Since then, antisocial behaviours ceased to be considered as a proof of social maladjustment and were finally identified as socially recognized strategies adopted in function of the achievement of popularity. Drawing on these results, one can hypothesize that also international status seekers perform both positive (conforming/compliant/cooperative) and negative (assertive/aggressive/competitive) behaviours. Therefore, the link between aims and behaviours loses its strength, since cooperative and competitive behaviours are both means for status seeking strategies that aim at status quo intentions. By carrying out a historical investigation of Italy's foreign policy during fascism, the intent is to closely look at this compresence of behaviours, in order to better qualify its components and their relations.

Keywords: compresence of cooperative and competitive behaviours and strategies, revisionist powers, status quo intentions, status seeking

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Authors: M. Bukowski, K. Kreissl

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Social and environmental pressures in our times bear threats that often cross-border in scale, such as climate change, poverty-driven migration, demographic change as well as socio-economic developments. One of the hot topics is prevailing in many societies across Europe and worldwide, concerns 'affordable housing' and poverty-driven international and domestic migration (including displacements through gentrification processes), focusing here on the urban and regional context. The right to adequate housing and shelter is one of the recognized in the Universal Declaration of Human rights and International Covenant on Economic, Social and Cultural Rights, and as such considered as a human right of the second generation. The decreasing supply of affordable housing, especially in urban areas, has reached dimensions that have led to an increasing 'housing crisis'. This crisis, which has even reached middle-income homes, has an even more devastating impact on low income and poor households raising poverty levels. Therefore, the understanding of the connection between housing and poverty is vital to integrate and support the different stakeholders in order to tackle poverty. When it comes to issues of inequalities and poverty within the SDG framework, multi-faceted stakeholders with different claims, distribution of resources and interactions with other development goals (spill-over and trade-offs) account for a highly complex context. To contribute to a sustainable and fair society and hence to support the UN Sustainable Development Goals, the University of Salzburg participates in the Austrian-wide universities' network 'UniNEtZ'. Our joint target is to develop an options report for the Austrian Government regarding the seventeen SDGs, so far hosted by 18 Austrian universities. In this vein, the University of Salzburg; i.e., the Centre for Ethics and Poverty Research, the departments of Geography and Geology and the Department of Sociology and Political Science are focusing on the SDG 1 (No Poverty) and SDG 10 (Reduced Inequalities). Our target and research focus is to assess and evaluate the status of SDG 1 and 10 in Austria, to find possible solutions and to support stakeholders' integration. We aim at generating and deducing appropriate options as scientific support, from interdisciplinary research studies to 'Sustainability Developing Goals and their Targets' in action. For this reason, and to deal with the complexity of the Agenda 2030, we have developed a special Model for Inequalities and Poverty Assessment (IPAM). Through the example of 'affordable housing' we provide insight into the situation focusing on sustainable outcomes, including ethical and justice perceptions. The IPAM has proven to be a helpful tool in detecting the different imponderables on the Agenda 2030, assessing the situation, showing gaps and options for ethical SDG actions combining different SDG targets. Supported by expert and expert group interviews, this assessment allows different stakeholders to overview a complex and dynamic SDG challenge (here housing) which is necessary to be involved in an action finding process.

Keywords: affordable housing, inequality, poverty, sustainable development goals

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Authors: Michael Wendland

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This paper presents a framework to teach a methodical design approach by the help of using a mixture of game-based learning, design challenges and competitions as forms of direct assessment. In today’s world, developing products is more complex than ever. Conflicting goals of product cost and quality with limited time as well as post-pandemic part shortages increase the difficulty. Common design approaches for mechatronic products mitigate some of these effects by helping the users with their methodical framework. Due to the inherent complexity of these products, the number of involved resources and the comprehensive design processes, students very rarely have enough time or motivation to experience a complete approach in one semester course. But, for students to be successful in the industrial world, it is crucial to know these methodical frameworks and to gain first-hand experience. Therefore, it is necessary to teach these design approaches in a real-world setting and keep the motivation high as well as learning to manage upcoming problems. This is achieved by using a game-based approach and a set of design challenges that are given to the students. In order to mimic industrial collaboration, they work in teams of up to six participants and are given the main development target to design a remote-controlled robot that can manipulate a specified object. By setting this clear goal without a given solution path, a constricted time-frame and limited maximal cost, the students are subjected to similar boundary conditions as in the real world. They must follow the methodical approach steps by specifying requirements, conceptualizing their ideas, drafting, designing, manufacturing and building a prototype using rapid prototyping. At the end of the course, the prototypes will be entered into a contest against the other teams. The complete design process is accompanied by theoretical input via lectures which is immediately transferred by the students to their own design problem in practical sessions. To increase motivation in these sessions, a playful learning approach has been chosen, i.e. designing the first concepts is supported by using lego construction kits. After each challenge, mandatory online quizzes help to deepen the acquired knowledge of the students and badges are awarded to those who complete a quiz, resulting in higher motivation and a level-up on a fictional leaderboard. The final contest is held in presence and involves all teams with their functional prototypes that now need to contest against each other. Prices for the best mechanical design, the most innovative approach and for the winner of the robotic contest are awarded. Each robot design gets evaluated with regards to the specified requirements and partial grades are derived from the results. This paper concludes with a critical review of the proposed framework, the game-based approach for the designed prototypes, the reality of the boundary conditions, the problems that occurred during the design and manufacturing process, the experiences and feedback of the students and the effectiveness of their collaboration as well as a discussion of the potential transfer to other educational areas.

Keywords: design challenges, game-based learning, playful learning, methodical framework, mechatronics, student assessment, constructive alignment

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Authors: Ashish Thakur

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This technical paper was written in view of focusing the biomaterials and its various applications in modern industries. Author tires to elaborate not only the medical, infect plenty of application in other industries. The scope of the research area covers the wide range of physical, biological and chemical sciences that underpin the design of biomaterials and the clinical disciplines in which they are used. A biomaterial is now defined as a substance that has been engineered to take a form which, alone or as part of a complex system, is used to direct, by control of interactions with components of living systems, the course of any therapeutic or diagnostic procedure. Biomaterials are invariably in contact with living tissues. Thus, interactions between the surface of a synthetic material and biological environment must be well understood. This paper reviews the benefits and challenges associated with surface modification of the metals in biomedical applications. The paper also elaborates how the surface characteristics of metallic biomaterials, such as surface chemistry, topography, surface charge, and wettability, influence the protein adsorption and subsequent cell behavior in terms of adhesion, proliferation, and differentiation at the biomaterial–tissue interface. The chapter also highlights various techniques required for surface modification and coating of metallic biomaterials, including physicochemical and biochemical surface treatments and calcium phosphate and oxide coatings. In this review, the attention is focused on the biomaterial-associated infections, from which the need for anti-infective biomaterials originates. Biomaterial-associated infections differ markedly for epidemiology, aetiology and severity, depending mainly on the anatomic site, on the time of biomaterial application, and on the depth of the tissues harbouring the prosthesis. Here, the diversity and complexity of the different scenarios where medical devices are currently utilised are explored, providing an overview of the emblematic applicative fields and of the requirements for anti-infective biomaterials. In addition to this, chapter introduces nanomedicine and the use of both natural and synthetic polymeric biomaterials, focuses on specific current polymeric nanomedicine applications and research, and concludes with the challenges of nanomedicine research. Infection is currently regarded as the most severe and devastating complication associated to the use of biomaterials. Osteoporosis is a worldwide disease with a very high prevalence in humans older than 50. The main clinical consequences are bone fractures, which often lead to patient disability or even death. A number of commercial biomaterials are currently used to treat osteoporotic bone fractures, but most of these have not been specifically designed for that purpose. Many drug- or cell-loaded biomaterials have been proposed in research laboratories, but very few have received approval for commercial use. Polymeric nanomaterial-based therapeutics plays a key role in the field of medicine in treatment areas such as drug delivery, tissue engineering, cancer, diabetes, and neurodegenerative diseases. Advantages in the use of polymers over other materials for nanomedicine include increased functionality, design flexibility, improved processability, and, in some cases, biocompatibility.

Keywords: nanomedicine, tissue, infections, biomaterials

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Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: Çağrı Bekir Baysal, Göktuğ Burak Çalık

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Armored vehicles may have different traction layouts as a result of terrain capabilities and mobility needs. Two main categories of layouts can be separated as wheeled and tracked. Tracked vehicles have superior off-road capabilities but what they gain on terrain performance they lose on mobility front. Wheeled vehicles on the other hand do not have as good terrain capabilities as tracked vehicles but they have superior mobility capabilities such as top speed, range and agility with respect to tracked vehicles. Conventional armored vehicles employ a diesel ICE as main power source. In these vehicles ICE is mechanically connected to the powertrain. This determines the ICE rpm as a result of speed and torque requested by the driver. ICE efficiency changes drastically with torque and speed required and conventional vehicles suffer in terms of fuel consumption because of this. Hybrid electric vehicles employ at least one electric motor in order to improve fuel efficiency. There are different types of hybrid vehicles but main types are Series Hybrid, Parallel Hybrid and Series-Parallel Hybrid. These vehicles introduce an electric motor for traction and also can have a generator electric motor for range extending purposes. Having an electric motor as the traction power source brings the flexibility of either using the ICE as an alternative traction source while it is in efficient range or completely separating the ICE from traction and using it solely considering efficiency. Hybrid configurations have additional advantages for armored vehicles in addition to fuel efficiency. Heat signature, silent operation and prolonged stationary missions can be possible with the help of the high-power battery pack that will be present in the vehicle for hybrid drivetrain. Because of the reasons explained, hybrid armored vehicles are becoming a target area for military and also for vehicle suppliers. In order to have a better idea and starting point when starting a hybrid armored vehicle design, hybrid drivetrain configuration has to be selected after performing a trade-off study. This study has to include vehicle mobility simulations, integration level, vehicle level and performance level criteria. In this study different hybrid traction configurations possible for an 8x8 vehicle is compared using above mentioned criteria set. In order to compare hybrid traction configurations ease of application, cost, weight advantage, reliability, maintainability, redundancy and performance criteria have been used. Performance criteria points have been defined with the help of vehicle simulations and tests. Results of these simulations and tests also help determining required tractive power for an armored vehicle including conditions like trench and obstacle crossing, gradient climb. With the method explained in this study, each configuration is assigned a point for each criterion. This way, correct configuration can be selected objectively for every application. Also, key aspects of armored vehicles, mine protection and ballistic protection will be considered for hybrid configurations. Results are expected to vary for different types of vehicles but it is observed that having longitudinal differential locking capability improves mobility and having high motor count increases complexity in general.

Keywords: armored vehicles, electric drivetrain, electric mobility, hybrid vehicles

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Authors: Shyamani Hettiarachchi, Thilini Lokubalasuriya, Shakeela Saleem, Dinusha Nonis, Isuru Dharmaratne, Lakshika Udugama

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Introduction: Late identification of language difficulties in children could result in long-term negative consequences for communication, literacy and self-esteem. This highlights the need for early identification and intervention for speech, language and communication difficulties. Speech and language therapy is a relatively new profession in Sri Lanka and at present, there are no formal standardized screening tools to assess language skills in Sinhala-speaking children. The development and validation of a short, accurate screening tool to enable the identification of children with syntactic difficulties in Sinhala is a current need. Aims: 1) To develop test items for a Sinhala Syntactic Structures (S3 Short Form) test on children aged between 3;0 to 5;0 years 2) To validate the test of Sinhala Syntactic Structures (S3 Short Form) on children aged between 3; 0 to 5; 0 years Methods: The Sinhala Syntactic Structures (S3 Short Form) was devised based on the Renfrew Action Picture Test. As Sinhala contains post-positions in contrast to English, the principles of the Renfrew Action Picture Test were followed to gain an information score and a grammar score but the test devised reflected the linguistic-specificity and complexity of Sinhala and the pictures were in keeping with the culture of the country. This included the dative case marker ‘to give something to her’ (/ejɑ:ʈə/ meaning ‘to her’), the instrumental case marker ‘to get something from’ (/ejɑ:gən/ meaning ‘from him’ or /gɑhən/ meaning ‘from the tree’), possessive noun (/ɑmmɑge:/ meaning ‘mother’s’ or /gɑhe:/ meaning ‘of the tree’ or /male:/ meaning ‘of the flower’) and plural markers (/bɑllɑ:/ bɑllo:/ meaning ‘dog/dogs’, /mɑlə/mɑl/ meaning ‘flower/flowers’, /gɑsə/gɑs/ meaning ‘tree/trees’ and /wɑlɑ:kulə/wɑlɑ:kulu/ meaning ‘cloud/clouds’). The picture targets included socio-culturally appropriate scenes of the Sri Lankan New Year celebration, elephant procession and the Buddhist ‘Wesak’ ceremony. The test was piloted with a group of 60 participants and necessary changes made. In phase 1, the test was administered to 100 Sinhala-speaking children aged between 3; 0 and 5; 0 years in one district. In this presentation on phase 2, the test was administered to another 100 Sinhala-speaking children aged between 3; 0 to 5; 0 in three districts. In phase 2, the selection of the test items was assessed via measures of content validity, test-retest reliability and inter-rater reliability. The age of acquisition of each syntactic structure was determined using content and grammar scores which were statistically analysed using t-tests and one-way ANOVAs. Results: High percentage agreement was found on test-retest reliability on content validity and Pearson correlation measures and on inter-rater reliability. As predicted, there was a statistically significant influence of age on the production of syntactic structures at p<0.05. Conclusions: As the target test items included generated the information and the syntactic structures expected, the test could be used as a quick syntactic screening tool with preschool children.

Keywords: Sinhala, screening, syntax, language

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Authors: Laura Alvarez-Alonso, Francisco Garcia-Carro, Jorge Loredo

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Population growth and industrial development imply an increase in the energy demands and the problems caused by emissions of greenhouse effect gases, which has inspired the search for clean sources of energy. Hydrogen (H₂) is expected to play a key role in the world’s energy future by replacing fossil fuels. The properties of H₂ make it a green fuel that does not generate pollutants and supplies sufficient energy for power generation, transportation, and other applications. Supercritical Water Gasification (SCWG) represents an attractive alternative for the recovery of energy from wastes. SCWG allows conversion of a wide range of raw materials into a fuel gas with a high content of hydrogen and light hydrocarbons through their treatment at conditions higher than those that define the critical point of water (temperature of 374°C and pressure of 221 bar). Methane used as a transport fuel is another important gasification product. The number of different uses of gas and energy forms that can be produced depending on the kind of material gasified and type of technology used to process it, shows the flexibility of SCWG. This feature allows it to be integrated with several industrial processes, as well as power generation systems or waste-to-energy production systems. The final aim of this work is to study which conditions and equipment are the most efficient and advantageous to explore the possibilities to obtain streams rich in H₂ from oily wastes, which represent a major problem both for the environment and human health throughout the world. In this paper, the relative complexity of technology needed for feasible gasification process cycles is discussed with particular reference to the different feedstocks that can be used as raw material, different reactors, and energy recovery systems. For this purpose, a review of the current status of SCWG technologies has been carried out, by means of different classifications based on key features as the feed treated or the type of reactor and other apparatus. This analysis allows to improve the technology efficiency through the study of model calculations and its comparison with experimental data, the establishment of kinetics for chemical reactions, the analysis of how the main reaction parameters affect the yield and composition of products, or the determination of the most common problems and risks that can occur. The results of this work show that SCWG is a promising method for the production of both hydrogen and methane. The most significant choices of design are the reactor type and process cycle, which can be conveniently adopted according to waste characteristics. Regarding the future of the technology, the design of SCWG plants is still to be optimized to include energy recovery systems in order to reduce costs of equipment and operation derived from the high temperature and pressure conditions that are necessary to convert water to the SC state, as well as to find solutions to remove corrosion and clogging of components of the reactor.

Keywords: hydrogen production, organic wastes, supercritical water gasification, system integration, waste-to-energy

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Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

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Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

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Authors: Sebastian Hiergeist

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It is a common view that Unmanned Aerial Vehicles (UAV) tend to migrate into the civil airspace. This trend is challenging UAV manufacturer in plenty ways, as there come up a lot of new requirements and functional aspects. On the higher application levels, this might be collision detection and avoidance and similar features, whereas all these functions only act as input for the flight control components of the aircraft. The flight control computer (FCC) is the central component when it comes up to ensure a continuous safe flight and landing. As these systems are flight critical, they have to be built up redundantly to be able to provide a Fail-Operational behavior. Recent architectural approaches of FCCs used in UAV systems are often based on very simple microprocessors in combination with proprietary Application-Specific Integrated Circuit (ASIC) or Field Programmable Gate Array (FPGA) extensions implementing the whole redundancy functionality. In the future, such simple microprocessors may not be available anymore as they are more and more replaced by higher sophisticated System on Chip (SoC). As the avionic industry cannot provide enough market power to significantly influence the development of new semiconductor products, the use of solutions from foreign markets is almost inevitable. Products stemming from the industrial market developed according to IEC 61508, or automotive SoCs, according to ISO 26262, can be seen as candidates as they have been developed for similar environments. Current available SoC from the industrial or automotive sector provides quite a broad selection of interfaces like, i.e., Ethernet, SPI or FlexRay, that might come into account for the implementation of a redundancy network. In this context, possible network architectures shall be investigated which could be established by using the interfaces stated above. Of importance here is the avoidance of any single point of failures, as well as a proper segregation in distinct fault containment regions. The performed analysis is supported by the use of guidelines, published by the aviation authorities (FAA and EASA), on the reliability of data networks. The main focus clearly lies on the reachable level of safety, but also other aspects like performance and determinism play an important role and are considered in the research. Due to the further increase in design complexity of recent and future SoCs, also the risk of design errors, which might lead to common mode faults, increases. Thus in the context of this work also the aspect of dissimilarity will be considered to limit the effect of design errors. To achieve this, the work is limited to broadly available interfaces available in products from the most common silicon manufacturer. The resulting work shall support the design of future UAV FCCs by giving a guideline on building up a redundancy network between SoCs, solely using on board interfaces. Therefore the author will provide a detailed usability analysis on available interfaces provided by recent SoC solutions, suggestions on possible redundancy architectures based on these interfaces and an assessment of the most relevant characteristics of the suggested network architectures, like e.g. safety or performance.

Keywords: redundancy, System-on-Chip, UAV, flight control computer (FCC)

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: Tomaz Oliveira, Rui Medeiros, André Lacerda

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Introduction: Cleft lip and/or palate are the most frequent forms of congenital craniofacial anomalies, affecting mainly the middle third of the face and manifesting by functional and aesthetic changes. Bilateral cleft lip represents a reconstructive surgical challenge, not only for the labial component but also for the associated nasal deformation. Recently, the paradigm of the approach to this pathology has changed, placing the focus on muscle reconstruction and anatomical repositioning of the nasal cartilages in order to obtain the best aesthetic and functional results. The aim of this study is to carry out a systematic review of the surgical approach to bilateral cleft lip, retrospectively analyzing the case series of Plastic Surgery Service at Hospital Santa Maria (Lisbon, Portugal) regarding this pathology, the global assessment of the characteristics of the operated patients and the study of the different surgical approaches and their complications in the last 20 years. Methods: The present work demonstrates a retrospective and descriptive study of patients who underwent at least one reconstructive surgery for cleft lip and/or palate, in the CPRE service of the HSM, in the period between January 1 of 1997 and December 31 of 2017, in which the data relating to 361 individuals were analyzed who, after applying the exclusion criteria, constituted a sample of 212 participants. The variables analyzed were the year of the first surgery, gender, age, type of orofacial cleft, surgical approach, and its complications. Results: There was a higher overall prevalence in males, with cleft lip and cleft palate occurring in greater proportion in males, with the cleft palate being more common in females. The most frequently recorded malformation was cleft lip and palate, which is complete in most cases. Regarding laterality, alterations with a unilateral labial component were the most commonly observed, with the left lip being described as the most affected. It was found that the vast majority of patients underwent primary intervention up to 12 months of age. The surgical techniques used in the approach to this pathology showed an important chronological variation over the years. Discussion: Cleft lip and/or palate is a medical condition associated with high aesthetic and functional morbidity, which requires early treatment in order to optimize the long-term outcome. The existence of a nasolabial component and its respective surgical correction plays a central role in the treatment of this pathology. The high rates of post-surgical complications and unconvincing aesthetic results have motivated an evolution of the surgical technique, increasingly evident in recent years, allowing today to achieve satisfactory aesthetic results, even in bilateral cleft lip with high deformation complexity. The introduction of techniques that favor nasolabial reconstruction based on anatomical principles has been producing increasingly convincing results. The analyzed sample shows that most of the results obtained in this study are, in general, compatible with the results published in the literature. Conclusion: This work showed that the existence of small variations in the surgical technique can bring significant improvements in the functional and aesthetic results in the treatment of bilateral cleft lip.

Keywords: cleft lip, palate lip, congenital abnormalities, cranofacial malformations

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Authors: Linmin Zhang

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Entrained-flow gasification technology is considered the most promising gasification technology because of its clean and efficient utilization characteristics. The stable fluidity of slag at high temperatures is the key to affecting the long-period operation of the gasifier. The diversity and differences of coal ash-slag systems make it difficult to meet the requirements for stable slagging in entrained-flow gasifiers. Therefore, coal blending or adding fluxes has been used in industry for a long time to improve the flow behavior of coal ash. As a by-product of the indirect coal liquefaction process, indirect coal liquefaction residue (ICLR) is a kind of industrial solid waste that is usually disposed of by stacking or landfilling. However, this disposal method will not only occupy land resources but also cause serious pollution to soil and water bodies by leachate containing toxic and harmful metals. As a carbon-containing matrix, ICLR is not only a kind of waste but also a kind of energy substance. Utilizing existing industrial gasifiers to blend combustion ICLR can not only transform industrial solid waste into fuel but also save coal resources. Moreover, the ICLR usually contains a unique ash chemical composition different from coal, which will affect the slagging performance of the gasifier. Therefore, exploring the effect of the ash addition in ICLR on the coal ash flow behavior can not only improve the slagging performance and gasification efficiency of entrained-flow gasifier by using the unique ash chemical composition of ICLR but also provide some theoretical support for the large-scale consumption of industrial solid waste. Combining molecular dynamics simulation with Raman spectroscopy experiment, the effect of ICLR addition on slag structure and fluidity was explained, and the relationship between the evolution law of slag short/medium range microstructure and macroscopic flow behavior was discussed. The research found that the high silicon and aluminum content in coal ash led to the formation of complex [SiO₄]⁴- tetrahedron and [AlO₄]⁵- tetrahedron structures at high temperature, and the [SiO₄]⁴- tetrahedron and [AlO₄]⁵- tetrahedron were connected by oxygen atoms to form a multi-membered ring structure with high polymerization degree. Due to the action of the multi-membered ring structure, the internal friction in the slag increased, and the viscosity value was higher on the macro-level. As a network-modified ion, Fe2+ could replace Si4+ and Al3+ in the multi-membered ring structure and combine with O2-, which will destroy the bridge oxygen (BO) structure and transform more complex tri cluster oxygen (TO) and bridge oxygen (BO) into simple non-bridge oxygen (NBO) structure. As a result, a large number of multi-membered rings with high polymerization degrees were depolymerized into low-membered rings with low polymerization degrees. The evolution of oxygen types and ring structures in slag reduced the structure complexity and polymerization degree of coal ash slag, resulting in a decrease in the viscosity of coal ash slag.

Keywords: ash slag, coal gasification, fluidity, industrial solid waste, slag structure

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Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Sunil Chandra, Himanshu Rawat, Vikas Gusain, Triparna Barman

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Forest fires are a recurrent phenomenon in the Himalayan region owing to the presence of vulnerable forest types, topographical gradients, climatic weather conditions, and anthropogenic pressure. The present study focuses on the identification of forest fire-affected areas in a small part of the West Himalayan region using a differential normalized burnt ratio method and spectral unmixing methods. The study area has a rugged terrain with the presence of sub-tropical pine forest, montane temperate forest, and sub-alpine forest and scrub. The major reason for fires in this region is anthropogenic in nature, with the practice of human-induced fires for getting fresh leaves, scaring wild animals to protect agricultural crops, grazing practices within reserved forests, and igniting fires for cooking and other reasons. The fires caused by the above reasons affect a large area on the ground, necessitating its precise estimation for further management and policy making. In the present study, two approaches have been used for carrying out a burnt area analysis. The first approach followed for burnt area analysis uses a differenced normalized burnt ratio (dNBR) index approach that uses the burnt ratio values generated using the Short-Wave Infrared (SWIR) band and Near Infrared (NIR) bands of the Sentinel-2 image. The results of the dNBR have been compared with the outputs of the spectral mixing methods. It has been found that the dNBR is able to create good results in fire-affected areas having homogenous forest stratum and with slope degree <5 degrees. However, in a rugged terrain where the landscape is largely influenced by the topographical variations, vegetation types, tree density, the results may be largely influenced by the effects of topography, complexity in tree composition, fuel load composition, and soil moisture. Hence, such variations in the factors influencing burnt area assessment may not be effectively carried out using a dNBR approach which is commonly followed for burnt area assessment over a large area. Hence, another approach that has been attempted in the present study utilizes a spectral mixing method where the individual pixel is tested before assigning an information class to it. The method uses a neural network approach utilizing Sentinel-2 bands. The training and testing data are generated from the Sentinel-2 data and the national field inventory, which is further used for generating outputs using ML tools. The analysis of the results indicates that the fire-affected regions and their severity can be better estimated using spectral unmixing methods, which have the capability to resolve the noise in the data and can classify the individual pixel to the precise burnt/unburnt class.

Keywords: categorical data, log linear modeling, neural network, shifting cultivation

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Authors: Nynne Nørup, Julie Helles Eriksen, Rikke M. Moalem, Else Skjold

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Despite a growing focus on the high environmental impact of textiles, textile waste is only recently considered as part of the waste field. Consequently, there is a general lack of knowledge and data within this field. Particularly the lack of a common perception of textiles generates several problems e.g., to recognize the full material potential the fraction contains, which is cruel if the textile must enter the circular economy. This study aims to qualify a method to make the resources in textile waste visible in a way that makes it possible to move them as high up in the waste hierarchy as possible. Textiles are complex and cover many different types of products, fibers and combinations of fibers and production methods. In garments alone, there is a great variety, even when narrowing it to only undergarments. However, textile waste is often reduced to one fraction, assessed solely by quantity, and compared to quantities of other waste fractions. Disregarding the complexity and reducing textiles to a single fraction that covers everything made of textiles increase the risk of neglecting the value of the materials, both with regards to their properties and economical. Instead of trying to fit textile waste into the current primarily linear waste system where volume is a key part of the business models, this study focused on integrating textile waste as a resource in the design and production phase. The study combined interdisciplinary methods for determining replacement rates used in Life Cycle Assessments and Mass Flow Analysis methods with the designer’s toolbox to hereby activate the properties of textile waste in a way that can unleash its potential optimally. It was hypothesized that by activating Denmark's tradition for design and high level of craftsmanship, it is possible to find solutions that can be used today and create circular resource models that reduce the use of virgin fibers. Through waste samples, case studies, and testing of various design approaches, this study explored how to functionalize the method so that the product after the end-use is kept as a material and only then processed at fiber level to obtain the best environmental utilization. The study showed that the designers' ability to decode the properties of the materials and understanding of craftsmanship were decisive for how well the materials could be utilized today. The later in the life cycle the textiles appeared as waste, the more demanding the description of the materials to be sufficient, especially if to achieve the best possible use of the resources and thus a higher replacement rate. In addition, it also required adaptation in relation to the current production because the materials often varied more. The study found good indications that part of the solution is to use geodata i.e., where in the life cycle the materials were discarded. An important conclusion is that a fully developed method can help support better utilization of textile resources. However, it stills requires a better understanding of materials by the designers, as well as structural changes in business and society.

Keywords: circular economy, development of sustainable processes, environmental impacts, environmental management of textiles, environmental sustainability through textile recycling, interdisciplinary method development, resource optimization, recycled textile materials and the evaluation of recycling, sustainability and recycling opportunities in the textile and apparel sector

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Authors: Pia Ulvenblad, Henrik Barth, Jennie Cederholm BjöRklund, Maya Hoveskog, Per-Ola Ulvenblad

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The importance of business model innovation (BMI) is widely recognized. This is also valid for firms in the agri-food industry, closely connected to global challenges. Worldwide food production will have to increase 70% by 2050 and the United Nations’ sustainable development goals prioritize research and innovation on food security and sustainable agriculture. The firms of the agri-food industry have opportunities to increase their competitive advantage through BMI. However, the process of BMI is complex and the implementation of new business models is associated with high degree of risk and failure. Thus, managers from all industries and scholars need to better understand how to address this complexity. Therefore, the research presented in this paper (i) explores different categories of barriers in research literature on business models in the agri-food industry, and (ii) illustrates categories of barriers with empirical cases. This study is addressing the rather limited understanding on barriers for BMI in the agri-food industry, through a systematic literature review (SLR) of 570 peer-reviewed journal articles that contained a combination of ‘BM’ or ‘BMI’ with agriculture-related and food-related terms (e.g. ‘agri-food sector’) published in the period 1990-2014. The study classifies the barriers in several categories and illustrates the identified barriers with ten empirical cases. Findings from the literature review show that barriers are mainly identified as outcomes. It can be assumed that a perceived barrier to growth can often be initially exaggerated or underestimated before being challenged by appropriate measures or courses of action. What may be considered by the public mind to be a barrier could in reality be very different from an actual barrier that needs to be challenged. One way of addressing barriers to growth is to define barriers according to their origin (internal/external) and nature (tangible/intangible). The framework encompasses barriers related to the firm (internal addressing in-house conditions) or to the industrial or national levels (external addressing environmental conditions). Tangible barriers can include asset shortages in the area of equipment or facilities, while human resources deficiencies or negative willingness towards growth are examples of intangible barriers. Our findings are consistent with previous research on barriers for BMI that has identified human factors barriers (individuals’ attitudes, histories, etc.); contextual barriers related to company and industry settings; and more abstract barriers (government regulations, value chain position, and weather). However, human factor barriers – and opportunities - related to family-owned businesses with idealistic values and attitudes and owning the real estate where the business is situated, are more frequent in the agri-food industry than other industries. This paper contributes by generating a classification of the barriers for BMI as well as illustrating them with empirical cases. We argue that internal barriers such as human factors barriers; values and attitudes are crucial to overcome in order to develop BMI. However, they can be as hard to overcome as for example institutional barriers such as governments’ regulations. Implications for research and practice are to focus on cognitive barriers and to develop the BMI capability of the owners and managers of agri-industry firms.

Keywords: agri-food, barriers, business model, innovation

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: Maria De Los Angeles Rodriguez Cadena

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This paper discusses how the fictional versions of women of the past contribute to advance today’s ideas of social justice, personal freedom and emancipation as well as to highlight the creative challenge of constructing people and events on fictional narratives on television that incorporate multiple and simultaneous layers of meaning and complexity. This project builds on existing scholarship on audiovisual texts by exploring an influential but under-studied director. In two Mexican television series, Patricia Arriaga Jordan, an award-winning television producer, scriptwriter and director, constructs the life of two outstanding women that have played an influential role in national history and captured Mexican’s popular imagination for generations: Sor Juana Inés de la Cruz, and Malinche. Malinche (2018) tells the story of an extraordinary indigenous woman, Malintzin, during the Spanish Conquest (1511-1550) that is considered to have played a key role in the fall of the Aztec empire by acting as translator, negotiator and cultural mediator for the Spanish conquerors. Juana Ines (2016) portrays Sor Juana, a poet, essayist, playwright, theologian, philosopher, nun, of XVII century colonial Mexico, one of the brightest minds of her time, and now recognized as the first feminist of the Americas who wrote on the rights of women to an education, religious authority and feminist advocacy. Both series, as fictional narratives that recreate defining historical periods, specific events and relevant characters in the History of Mexico can be read as an example of what is called texts of cultural memory. A cultural memory text is a narrative that bonds the concepts of history, identity and belonging, and that is realized and disseminated through symbolic systems such as written documents, visual images, and dramatic representation. Cultural memory, through its narratives of historical fiction, emphasizes memory processes (historiography) and its implications and artifacts (cultural memory) mainly through the medial frameworks of remembering, which are the medial process by which memories (narratives, documents) participate in public knowledge and become collective memory. Historical fiction on television not only creates a portrayal of the past related to the real lives of protagonists, but it also significantly contributes to understand the past as an ever-evolving entity that highlights both, the necessary connection with the present as part of a developing sense of collective identity and belonging, as well as the relevance of the medium in which the past is represented and that ultimately supports the process of historical awareness. Through the emblematic recreation of national heroines and historical events in the unique context of historical drama on television, those texts constitute a venue where concepts of the past and the traditionally established ideas about history and heroines are highlighted, questioned and transformed.

Keywords: cultural memory, historical fiction, Mexico, television, women directors

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Authors: Nilam Bano, Uzma Iram

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Globally, the dilemma of undernutrition has become a notable concern for the researchers, academicians, and policymakers because of its severe consequences for many centuries. The nutritional deficiencies create hurdles for the people to achieve goals related to live a better lifestyle. Not only at micro level but also at the macro level, the consequences of undernutrition affect the economic progress of the country. The initial five years of a child’s life are considered critical for the physical growth and brain development. In this regard, children require special care and good quality food (nutrient intake) to fulfill their nutritional demand of the growing body. Having the sensitive stature and health, children specially under the age of 5 years are more vulnerable to the poor economic, housing, environmental and other social conditions. Beside confronting economic challenges and political upheavals, Pakistan is also going through from a rough patch in the context of social development. Majority of the children are facing serious health problems in the absence of required nutrition. The complexity of this issue is getting severe day by day and specially children are left behind with different type of immune problems and vitamins and mineral deficiencies. It is noted that children from the well-off background are less likely affected by the undernutrition. In order to underline this issue, the present study aims to highlight the existing nutritional inequalities among the children of under five years in Pakistan. Moreover, this study strives to decompose those factors that severely affect the existing nutritional inequality and standing in the queue to capture the consideration of concerned authorities. Pakistan Demographic and Health Survey 2012-13 was employed to assess the relevant indicators of undernutrition such as stunting, wasting, underweight and associated socioeconomic factors. The objectives were executed through the utilization of the relevant empirical techniques. Concentration indices were constructed to measure the nutritional inequalities by utilizing three measures of undernutrition; stunting, wasting and underweight. In addition to it, the decomposition analysis following the logistic regression was made to unfold the determinants that severely affect the nutritional inequalities. The negative values of concentration indices illustrate that children from the marginalized background are affected by the undernutrition more than their counterparts who belong from rich households. Furthermore, the result of decomposition analysis indicates that child age, size of a child at birth, wealth index, household size, parents’ education, mother’s health and place of residence are the most contributing factors in the prevalence of existing nutritional inequalities. Considering the result of the study, it is suggested to the policymakers to design policies in a way so that the health sector of Pakistan can stimulate in a productive manner. Increasing the number of effective health awareness programs for mothers would create a notable difference. Moreover, the education of the parents must be concerned by the policymakers as it has a significant association with the present research in terms of eradicating the nutritional inequalities among children.

Keywords: concentration index, decomposition analysis, inequalities, undernutrition, Pakistan

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Authors: Mariia Karizhenskaia, Tanvi Nandani, Ali Tafazoli Moghadam

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Hospice palliative care (HPC) is one of the most complicated philosophies of care in which physical, social/cultural, and spiritual aspects of human life are intermingled with an undeniably significant role in every aspect. Among these dimensions of care, culture possesses an outstanding position in the process and goal determination of HPC. This study shows the importance of cultural elements in the establishment of effective and optimized structures of HPC in the Canadian healthcare environment. Our systematic search included Medline, Google Scholar, and St. Lawrence College Library, considering original, peer-reviewed research papers published from 1998 to 2023 to identify recent national literature connecting culture and palliative care delivery. The most frequently presented feature among the articles is the role of culture in the efficiency of the HPC. It has been shown frequently that including the culturespecific parameters of each nation in this system of care is vital for its success. On the other hand, ignorance about the exclusive cultural trends in a specific location has been accompanied by significant failure rates. Accordingly, implementing a culture-wise adaptable approach is mandatory for multicultural societies. The following outcome of research studies in this field underscores the importance of culture-oriented education for healthcare staff. Thus, all the practitioners involved in HPC will recognize the importance of traditions, religions, and social habits for processing the care requirements. Cultural competency training is a telling sample of the establishment of this strategy in health care that has come to the aid of HPC in recent years. Another complexity of the culturized HPC nowadays is the long-standing issue of racialization. Systematic and subconscious deprivation of minorities has always been an adversity of advanced levels of care. The last part of the constellation of our research outcomes is comprised of the ethical considerations of culturally driven HPC. This part is the most sophisticated aspect of our topic because almost all the analyses, arguments, and justifications are subjective. While there was no standard measure for ethical elements in clinical studies with palliative interventions, many research teams endorsed applying ethical principles for all the involved patients. Notably, interpretations and projections of ethics differ in varying cultural backgrounds. Therefore, healthcare providers should always be aware of the most respectable methodologies of HPC on a case-by-case basis. Cultural training programs have been utilized as one of the main tactics to improve the ability of healthcare providers to address the cultural needs and preferences of diverse patients and families. In this way, most of the involved health care practitioners will be equipped with cultural competence. Considerations for ethical and racial specifications of the clients of this service will boost the effectiveness and fruitfulness of the HPC. Canadian society is a colorful compilation of multiple nationalities; accordingly, healthcare clients are diverse, and this divergence is also translated into HPC patients. This fact justifies the importance of studying all the cultural aspects of HPC to provide optimal care on this enormous land.

Keywords: cultural competence, end-of-life care, hospice, palliative care

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Authors: Aditya Purohit, Neha Bansal

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Unplanned urbanization and multidirectional sprawl of the cities have resulted in increased motorization and deteriorating transport conditions like traffic congestion, longer commuting, pollution, increased carbon footprint, and above all increased fatalities. In order to overcome these problems, various practices have been adopted including– promoting and implementing mass transport; traffic junction channelization; smart transport etc. However, these methods are found to be primarily focusing on vehicular mobility rather than people accessibility. With this research gap, this paper tries to resolve the mobility issues for Ahmedabad city in India, which being the economic capital Gujarat state has a huge commuter and visitor inflow. This research aims to resolve the traffic congestion and urban mobility issues focusing on Gujarat State Regional Transport Corporation (GSRTC) for the city of Ahmadabad by analyzing the existing operations and network structure of GSRTC followed by finding possibilities of integrating it with other modes of urban transport. The network restructuring (NR) methodology is used with appropriate variations, based on commuter demand and growth pattern of the city. To do these ‘scenarios’ based on priority issues (using 12 parameters) and their best possible solution, are established after route network analysis for 2700 population sample of 20 traffic junctions/nodes across the city. Approximately 5% sample (of passenger inflow) at each node is considered using random stratified sampling technique two scenarios are – Scenario 1: Resolving mobility issues by use of Special Purpose Vehicle (SPV) in joint venture to GSRTC and Private Operators for establishing feeder service, which shall provide a transfer service for passenger for movement from inner city area to identified peripheral terminals; and Scenario 2: Augmenting existing mass transport services such as BRTS and AMTS for using them as feeder service to the identified peripheral terminals. Each of these has now been analyzed for the best suitability/feasibility in network restructuring. A desire-line diagram is constructed using this analysis which indicated that on an average 62% of designated GSRTC routes are overlapping with mass transportation service routes of BRTS and AMTS in the city. This has resulted in duplication of bus services causing traffic congestion especially in the Central Bus Station (CBS). Terminating GSRTC services on the periphery of the city is found to be the best restructuring network proposal. This limits the GSRTC buses at city fringe area and prevents them from entering into the city core areas. These end-terminals of GSRTC are integrated with BRTS and AMTS services which help in segregating intra-state and inter-state bus services. The research concludes that absence of integrated multimodal transport network resulted in complexity of transport access to the commuters. As a further scope of research comparing and understanding of value of access time in total travel time and its implication on generalized cost on trip and how it varies city wise may be taken up.

Keywords: mass transportation, multi-modal integration, network restructuring, travel behavior, urban transport

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Authors: Sthanu Mahadev, Wen Chan, Melanie Lim

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Anisotropy dominated continuous-fiber composite materials have garnered attention in numerous mechanical and aerospace structural applications. Tailored mechanical properties in advanced composites can exhibit superiority in terms of stiffness-to-weight ratio, strength-to-weight ratio, low-density characteristics, coupled with significant improvements in fatigue resistance as opposed to metal structure counterparts. Extensive research has demonstrated their core potential as more than just mere lightweight substitutes to conventional materials. Prior work done by Mahadev and Chan focused on formulating a modified composite shell theory based prognosis methodology for investigating the structural response of thin-walled circular cylindrical shell type composite configurations under in-plane mechanical loads respectively. The prime motivation to develop this theory stemmed from its capability to generate simple yet accurate closed-form analytical results that can efficiently characterize circular composite shell construction. It showcased the development of a novel mathematical framework to analytically identify the location of the centroid for thin-walled, open cross-section, curved composite shells that were characterized by circumferential arc angle, thickness-to-mean radius ratio, and total laminate thickness. Ply stress variations for curved cylindrical shells were analytically examined under the application of centric tensile and bending loading. This work presents a cost-effective, small-platform experimental methodology by taking advantage of the full-field measurement capability of digital image correlation (DIC) for an accurate assessment of key mechanical parameters such as in-plane mechanical stresses and strains, centroid location etc. Mechanical property measurement of advanced composite materials can become challenging due to their anisotropy and complex failure mechanisms. Full-field displacement measurements are well suited for characterizing the mechanical properties of composite materials because of the complexity of their deformation. This work encompasses the fabrication of a set of curved cylindrical shell coupons, the design and development of a novel test-fixture design and an innovative experimental methodology that demonstrates the capability to very accurately predict the location of centroid in such curved composite cylindrical strips via employing a DIC based strain measurement technique. Error percentage difference between experimental centroid measurements and previously estimated analytical centroid results are observed to be in good agreement. The developed analytical modified-shell theory provides the capability to understand the fundamental behavior of thin-walled cylindrical shells and offers the potential to generate novel avenues to understand the physics of such structures at a laminate level.

Keywords: anisotropy, composites, curved cylindrical shells, digital image correlation

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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Authors: M. Shiva Prasad, S. R. Atchuta, T. Vijayaraghavan, S. Sakthivel

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The world is in need of efficient energy conversion technologies which are affordable, accessible, and sustainable with eco-friendly nature. Solar energy is one of the cornerstones for the world’s economic growth because of its abundancy with zero carbon pollution. Among the various solar energy conversion technologies, solar thermal technology has attracted a substantial renewed interest due to its diversity and compatibility in various applications. Solar thermal systems employ concentrators, tracking systems and heat engines for electricity generation which lead to high cost and complexity in comparison with photovoltaics; however, it is compatible with distinct thermal energy storage capability and dispatchable electricity which creates a tremendous attraction. Apart from that, employing cost-effective solar selective receiver tube in a concentrating solar thermal (CST) system improves the energy conversion efficiency and directly reduces the cost of technology. In addition, the development of solar receiver tubes by low cost methods which can offer high optical properties and corrosion resistance in an open-air atmosphere would be beneficial for low and medium temperature applications. In this regard, our work opens up an approach which has the potential to achieve cost-effective energy conversion. We have developed a highly selective tandem absorber coating through a facile wet chemical route by a combination of chemical oxidation, sol-gel, and nanoparticle coating methods. The developed tandem absorber coating has gradient refractive index nature on stainless steel (SS 304) and exhibited high optical properties (α ≤ 0.95 & ε ≤ 0.14). The first absorber layer (Cr-Mn-Fe oxides) developed by controlled oxidation of SS 304 in a chemical bath reactor. A second composite layer of ZrO₂-SiO₂ has been applied on the chemically oxidized substrate by So-gel dip coating method to serve as optical enhancing and corrosion resistant layer. Finally, an antireflective layer (MgF₂) has been deposited on the second layer, to achieve > 95% of absorption. The developed tandem layer exhibited good thermal stability up to 250 °C in open air atmospheric condition and superior corrosion resistance (withstands for > 200h in salt spray test (ASTM B117)). After the successful development of a coating with targeted properties at a laboratory scale, a prototype of the 1 m tube has been demonstrated with excellent uniformity and reproducibility. Moreover, it has been validated under standard laboratory test condition as well as in field condition with a comparison of the commercial receiver tube. The presented strategy can be widely adapted to develop highly selective coatings for a variety of CST applications ranging from hot water, solar desalination, and industrial process heat and power generation. The high-performance, cost-effective medium temperature receiver tube technology has attracted many industries, and recently the technology has been transferred to Indian industry.

Keywords: concentrated solar thermal system, solar selective coating, tandem absorber, ultralow refractive index

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Authors: Estela Díaz

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This article aims to make three contributions. First, build on the literature on ethical decision-making literature by exploring factors that influence the intention of adopting veganism. Second, study the superiority of extended models of the Theory of Planned Behavior (TPB) for understanding the process involved in forming the intention of adopting veganism. Third, analyze the moderating effect of gender on TPB given that attitudes and behavior towards animals are gender-sensitive. No study, to our knowledge, has examined these questions. Veganism is not a diet but a political and moral stand that exclude, for moral reasons, the use of animals. Although there is a growing interest in studying veganism, it continues being overlooked in empirical research, especially within the domain of social psychology. TPB has been widely used to study a broad range of human behaviors, including moral issues. Nonetheless, TPB has rarely been applied to examine ethical decisions about animals and, even less, to veganism. Hence, the validity of TPB in predicting the intention of adopting veganism remains unanswered. A total of 476 non-vegan Spanish university students (55.6% female; the mean age was 23.26 years, SD= 6.1) responded to online and pencil-and-paper self-reported questionnaire based on previous studies. TPB extended models incorporated two background factors: ‘general attitudes towards humanlike-attributes ascribed to animals’ (AHA) (capacity for reason/emotions/suffer, moral consideration, and affect-towards-animals); and ‘general attitudes towards 11 uses of animals’ (AUA). SPSS 22 and SmartPLS 3.0 were used for statistical analyses. This study constructed a second-order reflective-formative model and took the multi-group analysis (MGA) approach to study gender effects. Six models of TPB (the standard and five competing) were tested. No a priori hypotheses were formulated. The results gave partial support to TPB. Attitudes (ATTV) (β = .207, p < .001), subjective norms (SNV) (β = .323, p < .001), and perceived control behavior (PCB) (β = .149, p < .001) had a significant direct effect on intentions (INTV). This model accounted for 27,9% of the variance in intention (R2Adj = .275) and had a small predictive relevance (Q2 = .261). However, findings from this study reveal that contrary to what TPB generally proposes, the effect of the background factors on intentions was not fully mediated by the proximal constructs of intentions. For instance, in the final model (Model#6), both factors had significant multiple indirect effect on INTV (β = .074, 95% C = .030, .126 [AHA:INTV]; β = .101, 95% C = .055, .155 [AUA:INTV]) and significant direct effect on INTV (β = .175, p < .001 [AHA:INTV]; β = .100, p = .003 [AUA:INTV]). Furthermore, the addition of direct paths from background factors to intentions improved the explained variance in intention (R2 = .324; R2Adj = .317) and the predictive relevance (Q2 = .300) over the base-model. This supports existing literature on the superiority of enhanced TPB models to predict ethical issues; which suggests that moral behavior may add additional complexity to decision-making. Regarding gender effect, MGA showed that gender only moderated the influence of AHA on ATTV (e.g., βWomen−βMen = .296, p < .001 [Model #6]). However, other observed gender differences (e.g. the explained variance of the model for intentions were always higher for men that for women, for instance, R2Women = .298; R2Men = .394 [Model #6]) deserve further considerations, especially for developing more effective communication strategies.

Keywords: veganism, Theory of Planned Behavior, background factors, gender moderation

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Authors: Lara Bettinelli, Bernhard Glatz, Josef Fink

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Planning engineers and researchers use various calculation models with different levels of complexity, calculation efficiency and accuracy in dynamic calculations of railway bridges under high-speed traffic. When choosing a vehicle model to depict the dynamic loading on the bridge structure caused by passing high-speed trains, different goals are pursued: On the one hand, the selected vehicle models should allow the calculation of a bridge’s vibrations as realistic as possible. On the other hand, the computational efficiency and manageability of the models should be preferably high to enable a wide range of applications. The commonly adopted and straightforward vehicle model is the moving load model (MLM), which simplifies the train to a sequence of static axle loads moving at a constant speed over the structure. However, the MLM can significantly overestimate the structure vibrations, especially when resonance events occur. More complex vehicle models, which depict the train as a system of oscillating and coupled masses, can reproduce the interaction dynamics between the vehicle and the bridge superstructure to some extent and enable the calculation of more realistic bridge accelerations. At the same time, such multi-body models require significantly greater processing capacities and precise knowledge of various vehicle properties. The European standards allow for applying the so-called additional damping method when simple load models, such as the MLM, are used in dynamic calculations. An additional damping factor depending on the bridge span, which should take into account the vibration-reducing benefits of the vehicle-bridge interaction, is assigned to the supporting structure in the calculations. However, numerous studies show that when the current standard specifications are applied, the calculation results for the bridge accelerations are in many cases still too high compared to the measured bridge accelerations, while in other cases, they are not on the safe side. A proposal to calculate the additional damping based on extensive dynamic calculations for a parametric field of simply supported bridges with a ballasted track was developed to address this issue. In this contribution, several different approaches to determine the additional damping of the supporting structure considering the vehicle-bridge interaction when using the MLM are compared with one another. Besides the standard specifications, this includes the approach mentioned above and two additional recently published alternative formulations derived from analytical approaches. For a bridge catalogue of 65 existing bridges in Austria in steel, concrete or composite construction, calculations are carried out with the MLM for two different high-speed trains and the different approaches for additional damping. The results are compared with the calculation results obtained by applying a more sophisticated multi-body model of the trains used. The evaluation and comparison of the results allow assessing the benefits of different calculation concepts for the additional damping regarding their accuracy and possible applications. The evaluation shows that by applying one of the recently published redesigned additional damping methods, the calculation results can reflect the influence of the vehicle-bridge interaction on the design-relevant structural accelerations considerably more reliable than by using normative specifications.

Keywords: Additional Damping Method, Bridge Dynamics, High-Speed Railway Traffic, Vehicle-Bridge-Interaction

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Authors: Anand R. Nair, Markus Trenker

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Lifting body concepts were conceived as early as 1917 and patented by Roy Scroggs. It was an idea of using the fuselage as a lift producing body with no or small wings. Many of these designs were developed and even flight tested between 1920’s to 1970’s, but it was not pursued further for commercial flight as at lower airspeeds, such a configuration was incapable to produce sufficient lift for the entire aircraft. The concept presented in this contribution is combining the lifting body design along with a fixed wing to maximise the lift produced by the aircraft. Conventional aircraft fuselages are designed to be aerodynamically efficient, which is to minimise the drag; however, these fuselages produce very minimal or negligible lift. For the design of an unmanned fixed wing transport aircraft, many of the restrictions which are present for commercial aircraft in terms of fuselage design can be excluded, such as windows for the passengers/pilots, cabin-environment systems, emergency exits, and pressurization systems. This gives new flexibility to design fuselages which are unconventionally shaped to contribute to the lift of the aircraft. The two lifting body concepts presented in this contribution are targeting different applications: For a fast cargo delivery drone, the fuselage is based on a scaled airfoil shape with a cargo capacity of 500 kg for euro pallets. The aircraft has a span of 14 m and reaches 1500 km at a cruising speed of 90 m/s. The aircraft could also easily be adapted to accommodate pilot and passengers with modifications to the internal structures, but pressurization is not included as the service ceiling envisioned for this type of aircraft is limited to 10,000 ft. The next concept to be investigated is called a multi-purpose drone, which incorporates a different type of lifting body and is a much more versatile aircraft as it will have a VTOL capability. The aircraft will have a wingspan of approximately 6 m and flight speeds of 60 m/s within the same service ceiling as the fast cargo delivery drone. The multi-purpose drone can be easily adapted for various applications such as firefighting, agricultural purposes, surveillance, and even passenger transport. Lifting body designs are not a new concept, but their effectiveness in terms of cargo transportation has not been widely investigated. Due to their enhanced lift producing capability, lifting body designs enable the reduction of the wing area and the overall weight of the aircraft. This will, in turn, reduce the thrust requirement and ultimately the fuel consumption. The various designs proposed in this contribution will be based on the general aviation category of aircrafts and will be focussed on unmanned methods of operation. These unmanned fixed-wing transport drones will feature appropriate cargo loading/unloading concepts which can accommodate large size cargo for efficient time management and ease of operation. The various designs will be compared in performance to their conventional counterpart to understand their benefits/shortcomings in terms of design, performance, complexity, and ease of operation. The majority of the performance analysis will be carried out using industry relevant standards in computational fluid dynamics software packages.

Keywords: lifting body concept, computational fluid dynamics, unmanned fixed-wing aircraft, cargo drone

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