Search results for: architecture complexity

Authors: Ilaria Coppola, Davide Lacqua, Nadia Ranìa

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Over the past two decades, migration has gained central importance in the global landscape. Europe hosts the largest number of migrants, totaling 92.9 million people, approximately 37.4 million of whom are regular residents within the European Union's borders. Reception services and different modes of management have received increasing attention precisely because of the complexity of the phenomenon, which necessarily impacts the wider community. Indeed, opening a reception center in an area entails major challenges for that context, for the community that inhabits it, and for the people who use that service. Questioning the strategies needed to offer a functional reception service means listening to the different actors involved who daily face the difficulties involved in working in the field. Recognizing the importance of the professional figures who work closely with migrant people, each with their own specific experiences has led researchers to study and analyze the different types of reception centers and their management. This has led to the development of intervention models and best practices in various countries. However, research from this perspective is still limited, especially in Italy. From this theoretical framework, this study aims to bring out an innovative qualitative tool, such as the world café, the work experiences of 29 social workers working in shelters in the Italian context. Most of the participants were female and lived in the Northwest regions of Italy. Through this tool, the aim was to bring out and share reflections on the critical issues encountered in working in reception centers, with a view to identifying possible solutions for better management of services. The World café represents a tool used in participatory action research that promotes dialogue among participants through the sharing of reflections and ideas. In fact, from critical reflections, participants are invited to identify and share possible solutions to provide a more functional service with benefits to the entire community. Therefore, this research, through the innovative technique of the World café, aims to promote critical thinking processes that can help participants find solutions that can be introduced into their work contexts or proposed to decision-makers. Specifically, the findings shed light on several issues, including complex bureaucratic procedures, insufficient project planning, and inefficiencies in the services provided to migrants. These concerns collectively contribute to what participants perceive as a disorganized and uncoordinated system. In addition, the study explores potential solutions that promote more efficient networking practices, coordinated project management, and a more positive approach to cultural diversity. The main results obtained will be discussed with a focus on critical reflections and possible solutions identified.

Keywords: participatory action research, world café method, reception services, migration contexts, social workers, Italy

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Authors: Mohamed Malek Khenissi, Mohamed Montassar Ben Slama, Anis Belhaj Mohamed, Moncef Saidi

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Northern Tunisia is well known by its different and complex structural and geological zones that have been the result of a geodynamic history that extends from the early Mesozoic era to the actual period. One of these zones is the salt province, where the Halokinesis process is manifested by a number of NE/SW salt structures such as Jebel Ech-Cheid which represents masses of materials characterized by a high plasticity and low density. The salt masses extrusions that have been developed due to an extension that started from the late Triassic to late Cretaceous. The evolution of salt bodies within sedimentary basins have not only contributed to modify the architecture of the basin, but it also has certain geochemical effects which touch mainly source rocks that surround it. It has been demonstrated that the presence of salt structures within sedimentary basins can influence its temperature distribution and thermal history. Moreover, it has been creating heat flux anomalies that may affect the maturity of organic matter and the timing of hydrocarbon generation. Field samples of the Bahloul source rock (Cenomanan-Tunonian) were collected from different sights from all around Ech Cheid salt structure and evaluated using Rock-eval pyrolysis and GC/MS techniques in order to assess the degree of maturity evolution and the heat flux anomalies in the different zones analyze. The Total organic Carbon (TOC) values range between 1 to 9% and the (Tmax) ranges between 424 and 445°C, also the distribution of the source rock biomarkers both saturated and aromatic changes in a regular fashions with increasing maturity and this are shown in the chromatography results such as Ts/(Ts+Tm) ratios, 22S/(22S+22R) values for C31 homohopanes, ββ/(ββ+αα)20R and 20S/(20S+20R) ratios for C29 steranes which gives a consistent maturity indications and assessment of the field samples. These analyses are carried to interpret the maturity evolution and the heat flux around Ech Cheid salt structure through the geological history. These analyses also aim to demonstrate that the salt structure can have a direct effect on the geothermal gradient of the basin and on the maturity of the Bahloul Formation source rock. The organic matter has reached different stages of thermal maturity, but delineate a general increasing maturity trend. Our study confirms that the J. Ech Cheid salt body have on the first hand: a huge influence on the local distribution of anoxic depocentre at least within Cenomanian-Turonian time. In the second hand, the thermal anomaly near the salt mass has affected the maturity of Bahloul Formation.

Keywords: Bahloul formation, depocentre, GC/MS, rock-eval

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Authors: Jessica Raven Gates, Gemma Wilson-Menzfeld, Professor Alison Steven

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In 2019, the Primary Care system in the UK National Health Service (NHS) was subject to reform and restructuring. Primary Care Networks (PCNs) were established, which aligned with a trend towards integrated care both within the NHS and internationally. The introduction of PCNs brought groups of GP practices in a locality together, to operate as a network, build on existing services and collaborate at a larger scale. PCNs were expected to bring a range of benefits to patients and address some of the workforce pressures in the NHS, through an expanded and collaborative workforce. The early establishment of PCNs was disrupted by the emerging COVID-19 pandemic. This study, set in the context of the pandemic, aimed to explore experiences of the PCN workforce, and their perceptions of the establishment of PCNs. Specific objectives focussed on examining factors perceived as enabling or hindering the success of a PCN, the impact on day-to-day work, the approach to implementing change, and the influence of the COVID-19 pandemic upon PCN development. This study is part of a three-phase PhD project that utilized qualitative approaches and was underpinned by social constructionist philosophy. Phase 1: a systematic narrative review explored the provision of preventative healthcare services in UK primary settings and examined facilitators and barriers to delivery as experienced by the workforce. Phase 2: informed by the findings of phase 1, semi-structured interviews were conducted with fifteen participants (PCN workforce). Phase 3: follow-up interviews were conducted with original participants to examine any changes to their experiences and perceptions of PCNs. Three main themes span across phases 2 and 3 and were generated through a Framework Analysis approach: 1) working together at scale, 2) network infrastructure, and 3) PCN leadership. Findings suggest that through efforts to work together at scale and collaborate as a network, participants have broadly accepted the concept of PCNs. However, the workforce has been hampered by system design and system complexity. Operating against such barriers has led to a negative psychological impact on some PCN leaders and others in the PCN workforce. While the pandemic undeniably increased pressure on healthcare systems around the world, it also acted as a disruptor, offering a glimpse into how collaboration in primary care can work well. Through the integration of findings from all phases, a new theoretical model has been developed, which conceptualises the findings from this Ph.D. study and demonstrates how the workforce has experienced change associated with the establishment of PCNs. The model includes a contextual component of the COVID-19 pandemic and has been informed by concepts from Complex Adaptive Systems theory. This model is the original contribution to knowledge of the PhD project, alongside recommendations for practice, policy and future research. This study is significant in the realm of health services research, and while the setting for this study is the UK NHS, the findings will be of interest to an international audience as the research provides insight into how the healthcare workforce may experience imposed policy and service changes.

Keywords: health services research, qualitative research, NHS workforce, primary care

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Authors: Dianelys Vega, Carlos Magluta, Ney Roitman

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The simulation of loads induced by walking people in civil engineering structures is still challenging It has been the focus of considerable research worldwide in the recent decades due to increasing number of reported vibration problems in pedestrian structures. One of the most important key in the designing of slender structures is the Human-Structure Interaction (HSI). How moving people interact with structures and the effect it has on their dynamic responses is still not well understood. To rely on calibrated pedestrian models that accurately estimate the structural response becomes extremely important. However, because of the complexity of the pedestrian mechanisms, there are still some gaps in knowledge and more reliable models need to be investigated. On this topic several authors have proposed biodynamic models to represent the pedestrian, whether these models provide a consistent approximation to physical reality still needs to be studied. Therefore, this work comes to contribute to a better understanding of this phenomenon bringing an experimental validation of a pedestrian walking model and a Human-Structure Interaction model. In this study, a bi-dimensional bipedal walking model was used to represent the pedestrians along with an interaction model which was applied to a prototype footbridge. Numerical models were implemented in MATLAB. In parallel, experimental tests were conducted in the Structures Laboratory of COPPE (LabEst), at Federal University of Rio de Janeiro. Different test subjects were asked to walk at different walking speeds over instrumented force platforms to measure the walking force and an accelerometer was placed at the waist of each subject to measure the acceleration of the center of mass at the same time. By fitting the step force and the center of mass acceleration through successive numerical simulations, the model parameters are estimated. In addition, experimental data of a walking pedestrian on a flexible structure was used to validate the interaction model presented, through the comparison of the measured and simulated structural response at mid span. It was found that the pedestrian model was able to adequately reproduce the ground reaction force and the center of mass acceleration for normal and slow walking speeds, being less efficient for faster speeds. Numerical simulations showed that biomechanical parameters such as leg stiffness and damping affect the ground reaction force, and the higher the walking speed the greater the leg length of the model. Besides, the interaction model was also capable to estimate with good approximation the structural response, that remained in the same order of magnitude as the measured response. Some differences in frequency spectra were observed, which are presumed to be due to the perfectly periodic loading representation, neglecting intra-subject variabilities. In conclusion, this work showed that the bipedal walking model could be used to represent walking pedestrians since it was efficient to reproduce the center of mass movement and ground reaction forces produced by humans. Furthermore, although more experimental validations are required, the interaction model also seems to be a useful framework to estimate the dynamic response of structures under loads induced by walking pedestrians.

Keywords: biodynamic models, bipedal walking models, human induced loads, human structure interaction

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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: Ercan Kızılay, Mustafa Demi̇rel, Selçuk Coşkun

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Railway signaling systems consist of vital products that regulate railway traffic and provide safe route arrangements and maneuvers of trains. SIL 4 signal lamps are produced by many manufacturers today. There is a need for systems that enable these signal lamps to be controlled by commands from the interlocking. These systems should act as fail-safe and give error indications to the interlocking system when an unexpected situation occurs for the safe operation of railway systems from the RAMS perspective. In the past, driving and proving the lamp in relay-based systems was typically done via signaling relays. Today, the proving of lamps is done by comparing the current values read over the return circuit, the lower and upper threshold values. The purpose is an analog electronic object controller with the possibility of easy integration with vital systems and the signal lamp itself. During the study, the EN50126 standard approach was considered, and the concept, definition, risk analysis, requirements, architecture, design, and prototyping were performed throughout this study. FMEA (Failure Modes and Effects Analysis) and FTA (Fault Tree) Analysis) have been used for safety analysis in accordance with EN 50129. Concerning these analyzes, the 1oo2D reactive fail-safe hardware design of a controller has been researched. Electromagnetic compatibility (EMC) effects on the functional safety of equipment, insulation coordination, and over-voltage protection were discussed during hardware design according to EN 50124 and EN 50122 standards. As vital equipment for railway signaling, railway signal object controllers should be developed according to EN 50126 and EN 50129 standards which identify the steps and requirements of the development in accordance with the SIL 4(Safety Integrity Level) target. In conclusion of this study, an analog railway signal object controller, which takes command from the interlocking system, is processed in driver cards. Driver cards arrange the voltage level according to desired visibility by means of semiconductors. Additionally, prover cards evaluate the current upper and lower thresholds. Evaluated values are processed via logic gates which are composed as 1oo2D by means of analog electronic technologies. This logic evaluates the voltage level of the lamp and mitigates the risks of undue dimming.

Keywords: object controller, railway electronic, analog electronic, safety, railway signal

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Authors: S. Arias

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New housing developments and the technological changes that this implies, adapt the styles of living of its residents, as well as new family structures and forms of work due to the particular needs of a specific group of people which involves different techniques of dealing with, organize, equip and use a particular territory. Currently, own their own space is increasingly important and the cities are faced with the challenge of providing the opportunity for such demands, as well as energy, water and waste removal necessary in the process of construction and occupation of new human settlements. Until the day of today, not has failed to give full response to these demands and needs, resulting in cities that grow without control, badly used land, avenues and congested streets. Buildings and dwellings have an important impact on the environment and on the health of the people, therefore environmental quality associated with the comfort of humans to the sustainable development of natural resources. Applied to architecture, this concept involves the incorporation of new technologies in all the constructive process of a dwelling, changing customs of developers and users, what must be a greater effort in planning energy savings and thus reducing the emissions Greenhouse Gases (GHG) depending on the geographical location where it is planned to develop. Since the techniques of occupation of the territory are not the same everywhere, must take into account that these depend on the geographical, social, political, economic and climatic-environmental circumstances of place, which in modified according to the degree of development reached. In the analysis that must be undertaken to check the degree of sustainability of the place, it is necessary to make estimates of the energy used in artificial air conditioning and lighting. In the same way is required to diagnose the availability and distribution of the water resources used for hygiene and for the cooling of artificially air-conditioned spaces, as well as the waste resulting from these technological processes. Based on the results obtained through the different stages of the analysis, it is possible to perform an energy audit in the process of proposing recommendations of sustainability in architectural spaces in search of energy saving, rational use of water and natural resources optimization. The above can be carried out through the development of a sustainable building code in develop technical recommendations to the regional characteristics of each study site. These codes would seek to build bases to promote a building regulations applicable to new human settlements looking for is generated at the same time quality, protection and safety in them. This building regulation must be consistent with other regulations both national and municipal and State, such as the laws of human settlements, urban development and zoning regulations.

Keywords: building regulations, housing, sustainability, technology

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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: Gilberto Goracci, Fabio Curti

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This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.

Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field

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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: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

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Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: Marta Kaprzyk

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The cinema of Alejandro González Iñárritu hasn’t been subjected to a lot of detailed analysis yet, what makes it an exceptionally interesting research material. The purpose of this presentation is to discuss the significance of urban space in three films of this Mexican director, that forms Death Trilogy: ‘Amores Perros’ (2000), ‘21 Grams’ (2003) and ‘Babel’ (2006). The fact that in the aforementioned movies the urban space itself becomes an additional protagonist with its own identity, psychology and the ability to transform and affect other characters, in itself warrants for independent research and analysis. Independently, such mode of presenting urban space has another function; it enables the director to complement the rest of characters. The basis for methodology of this description of cinematographic space is to treat its visual layer as a point of departure for a detailed analysis. At the same time, the analysis itself will be supported by recognised academic theories concerning special issues, which are transformed here into essential tools necessary to describe the world (mise-en-scène) created by González Iñárritu. In ‘Amores perros’ the Mexico City serves as a scenery – a place full of contradictions- in the movie depicted as a modern conglomerate and an urban jungle, as well as a labyrinth of poverty and violence. In this work stylistic tropes can be found in an intertextual dialogue of the director with photographies of Nan Goldin and Mary Ellen Mark. The story recounted in ‘21 Grams’, the most tragic piece in the trilogy, is characterised by almost hyperrealistic sadism. It takes place in Memphis, which on the screen turns into an impersonal formation full of heterotopias described by Michel Foucault and non-places, as defined by Marc Augé in his essay. By contrast, the main urban space in ‘Babel’ is Tokio, which seems to perfectly correspond with the image of places discussed by Juhani Pallasmaa in his works concerning the reception of the architecture by ‘pathological senses’ in the modern (or, even more adequately, postmodern) world. It’s portrayed as a city full of buildings that look so surreal, that they seem to be completely unsuitable for the humans to move between them. Ultimately, the aim of this paper is to demonstrate the coherence of the manner in which González Iñárritu designs urban spaces in his Death Trilogy. In particular, the author attempts to examine the imperative role of the cities that form three specific microcosms in which the protagonists of the Mexican director live their overwhelming tragedies.

Keywords: cinematographic space, Death Trilogy, film Studies, González Iñárritu Alejandro, urban space

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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: Ke-Jing Lee, Cheng-Jung Lee, Yu-Chi Chang, Li-Wen Wang, Yeong-Her Wang

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To avoid the cross-talk issue of only resistive random access memory (RRAM) cell, one transistor and one resistor (1T1R) architecture with a TiO₂-based RRAM cell connected with solution barium zirconate nickelate (BZN) organic thin film transistor (OTFT) device is successfully demonstrated. The OTFT were fabricated on a glass substrate. Aluminum (Al) as the gate electrode was deposited via a radio-frequency (RF) magnetron sputtering system. The barium acetate, zirconium n-propoxide, and nickel II acetylacetone were synthesized by using the sol-gel method. After the BZN solution was completely prepared using the sol-gel process, it was spin-coated onto the Al/glass substrate as the gate dielectric. The BZN layer was baked at 100 °C for 10 minutes under ambient air conditions. The pentacene thin film was thermally evaporated on the BZN layer at a deposition rate of 0.08 to 0.15 nm/s. Finally, gold (Au) electrode was deposited using an RF magnetron sputtering system and defined through shadow masks as both the source and drain. The channel length and width of the transistors were 150 and 1500 μm, respectively. As for the manufacture of 1T1R configuration, the RRAM device was fabricated directly on drain electrodes of TFT device. A simple metal/insulator/metal structure, which consisting of Al/TiO₂/Au structures, was fabricated. First, Au was deposited to be a bottom electrode of RRAM device by RF magnetron sputtering system. Then, the TiO₂ layer was deposited on Au electrode by sputtering. Finally, Al was deposited as the top electrode. The electrical performance of the BZN OTFT was studied, showing superior transfer characteristics with the low threshold voltage of −1.1 V, good saturation mobility of 5 cm²/V s, and low subthreshold swing of 400 mV/decade. The integration of the BZN OTFT and TiO₂ RRAM devices was finally completed to form 1T1R configuration with low power consumption of 1.3 μW, the low operation current of 0.5 μA, and reliable data retention. Based on the I-V characteristics, the different polarities of bipolar switching are found to be determined by the compliance current with the different distribution of the internal oxygen vacancies used in the RRAM and 1T1R devices. Also, this phenomenon can be well explained by the proposed mechanism model. It is promising to make the 1T1R possible for practical applications of low-power active matrix flat-panel displays.

Keywords: one transistor and one resistor (1T1R), organic thin-film transistor (OTFT), resistive random access memory (RRAM), sol-gel

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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: Despoina Mouratidis, Katia Lida Kermanidis

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Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

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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

Procedia PDF Downloads 104