Search results for: Francisco J. Real

Authors: Mathieu Hemono, Sophie Puig-Malet, Patrick Zylberman, Avner Bar-Hen, Rainer Sauerborn, Stefanie Schütte, Niamh Herlihi, Antoine Flahault et Anneliese Depoux

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Since the IPCC released its first report in 1990, an increasing number of peer-reviewed publications have reported the health risks associated with climate change. Although there is a large body of evidence supporting the association between climate change and poor health outcomes, the media is inconsistent in the attention it pays to the subject matter. This study aims to analyze the modalities and rhetoric in the media concerning the impact of climate change on health in order to better understand its role in information dissemination. A review was conducted of articles published between 1990 and 2015 in the francophone newspapers Le Monde and Jeune Afrique. A detailed search strategy including specific climate and health terminology was used to search the newspapers’ online databases. 1202 articles were identified as having referenced the terms climate change and health. Inclusion and exclusion criteria were applied to narrow the search to articles referencing the effects of climate change on human health and 160 articles were included in the final analysis. Data was extracted and categorized to create a structured database allowing for further investigation and analysis. The review indicated that although 66% of the selected newspaper articles reference scientific evidence of the impact of climate change on human health, the focus on the topic is limited major political events or is circumstances relating to public health crises. Main findings also include that among the many direct and indirect health outcomes, infectious diseases are the main health outcome highlighted in association with climate change. Lastly, the articles suggest that while developed countries have caused most of the greenhouse effect, the global south is more immediately affected. Overall, the reviewed articles reinforce the need for international cooperation in finding a solution to mitigate the effects of climate change on health. The manner in which scientific results are communicated and disseminated, impact individual and collective perceptions of the topic in the public sphere and affect political will to shape policy. The results of this analysis will underline the modalities of the rhetoric of transparency and provide the basis for a perception study of media discourses. This study is part of an interdisciplinary project called 4CHealth that confronts results of the research done on scientific, political and press literature to better understand how the knowledge on climate changes and health circulates within those different fields and whether and how it is translated to real world change.

Keywords: climate change, health, health impacts, communication, media, rhetoric, awareness, Global South, Africa

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Authors: Franck Acho

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This is a chronic metabolic disorder which is a fast-growing global problem with a huge social, health, and economic consequences. It is estimated that in 2010 there were globally 285 million people (approximately 6.4% of the adult population) suffering from this disease. This number is estimated to increase to 430 million in the absence of better control or cure. An ageing population and obesity are two main reasons for the increase. Diabetes mellitus is a chronic heterogeneous metabolic disorder with a complex pathogenesis. It is characterized by elevated blood glucose levels or hyperglycemia, which results from abnormalities in either insulin secretion or insulin action or both. Hyperglycemia manifests in various forms with a varied presentation and results in carbohydrate, fat, and protein metabolic dysfunctions. Long-term hyperglycemia often leads to various microvascular and macrovascular diabetic complications, which are mainly responsible for diabetes-associated morbidity and mortality. Hyperglycemia serves as the primary biomarker for the diagnosis of diabetes as well. Furthermore, it has been shown that almost 50% of the putative diabetics are not diagnosed until 10 years after onset of the disease, hence the real prevalence of global diabetes must be astronomically high. This study was conducted in a locality to access the level of knowledge, awareness and risk factors associated with people leaving with diabetes mellitus. A month before the screening was to be conducted, a health screening in some selected churches and on the local community radio as well as on relevant WhatsApp groups were advertised. A general health talk was delivered by the head of the screening unit to all attendees who were all educated on the procedure to be carried out with benefits and any possible discomforts after which the attendee’s consent was obtained. Evaluation of the participants for any leads to the diabetes selected for the screening was done by taking adequate history and physical examinations such as excessive thirst, increased urination, tiredness, hunger, unexplained weight loss, feeling irritable or having other mood changes, having blurry vision, having slow-healing sores, getting a lot of infections, such as gum, skin and vaginal infections. Out of the 94 participants the finding show that 78 were females and 16 were males, 70.21% of participants with diabetes were between the ages of 60-69yrs.The study found that only 10.63% of respondents declared a good level of knowledge of diabetes. Out of 3 symptoms of diabetes analyzed in this study, high blood sugar (58.5%) and chronic fatigue (36.17%) were the most recognized. Out of 4 diabetes risk factors analyzed in this study, obesity (21.27%) and unhealthy diet (60.63%) were the most recognized diabetes risk factors, while only 10.6% of respondents indicated tobacco use. The diabetic foot was the most recognized diabetes complication (50.57%), but some the participants indicated vision problems (30.8%),or cardiovascular diseases (20.21%) as diabetes complications.

Keywords: diabetes mellitus, non comunicable disease, general health talk, hyperglycemia

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Authors: Md Kamrul Hassan

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Adaptation interventions are the common response to manage the vulnerabilities of climate change. The nature of adaptation intervention depends on the degree of vulnerability and the capacity of a society. The coping interventions can take the form of hard adaptation – utilising technologies and capital goods like dykes, embankments, seawalls, and/or soft adaptation – engaging knowledge and information sharing, capacity building, policy and strategy development, and innovation. Hard adaptation is quite capital intensive but provides immediate relief from climate change vulnerabilities. This type of adaptation is not real development, as the investment for the adaptation cannot improve the performance – just maintain the status quo of a social or ecological system, and often lead to maladaptation in the long-term. Maladaptation creates a two-way loss for a society – interventions bring further vulnerability on top of the existing vulnerability and investment for getting rid of the consequence of interventions. Hard adaptation is popular to the vulnerable groups, but it focuses so much on the immediate solution and often ignores the environmental issues and future risks of climate change. On the other hand, soft adaptation is education oriented where vulnerable groups learn how to live with climate change impacts. Soft adaptation interventions build the capacity of vulnerable groups through training, innovation, and support, which might enhance the resilience of a system. In consideration of long-term sustainability, soft adaptation can contribute more to resilience than hard adaptation. Taking a developing society as the study context, this study aims to investigate and understand the effectiveness of the adaptation interventions of the coastal community of Sundarbans mangrove forest in Bangladesh. Applying semi-structured interviews with a range of Sundarbans stakeholders including community residents, tourism demand-supply side stakeholders, and conservation and management agencies (e.g., Government, NGOs and international agencies) and document analysis, this paper reports several key insights regarding climate change adaptation. Firstly, while adaptation interventions may offer a short-term to medium-term solution to climate change vulnerabilities, interventions need to be revised for long-term sustainability. Secondly, soft adaptation offers advantages in terms of resilience in a rapidly changing environment, as it is flexible and dynamic. Thirdly, there is a challenge to communicate to educate vulnerable groups to understand more about the future effects of hard adaptation interventions (and the potential for maladaptation). Fourthly, hard adaptation can be used if the interventions do not degrade the environmental balance and if the investment of interventions does not exceed the economic benefit of the interventions. Overall, the goal of an adaptation intervention should be to enhance the resilience of a social or ecological system so that the system can with stand present vulnerabilities and future risks. In order to be sustainable, adaptation interventions should be designed in such way that those can address vulnerabilities and risks of climate change in a long-term timeframe.

Keywords: adaptation, climate change, maladaptation, resilience, Sundarbans, sustainability, vulnerability

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

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Authors: Oliver Fuo

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One of the central features of post-apartheid constitutional reform was the establishment of local government as a distinct sphere of government in the Constitution of the Republic of South Africa, 1996. Local government, constituted by about 279 wall-to-wall municipalities, have legislative and executive powers vested in democratically elected municipal councils to govern areas within their jurisdiction subject only to limits imposed by the Constitution. In addition, unlike the past where municipalities merely played a service delivery role, they are now mandated to realise an expanded developmental mandate – pursue social justice and sustainable development; contribute, together with national and provincial government, to the realisation of socio-economic rights entrenched in the Bill of Rights; and facilitate public participation in local governance. In order to finance their developmental programmes, municipalities receive equitable allocations from national government and have legal powers to generate additional finances by charging rates on property and imposing surcharges on services provided. In addition to its general obligation to foster public participation in local governance, the law requires municipalities to facilitate public participation in their budgeting processes. This requirement is generally consistent with recent trends in local government democratic reforms which call for inclusive budget planning and implementation whereby citizens, civil society and NGOs participate in the allocation of resources. This trend is best captured in the concept of participatory budgeting. This paper specifically analyses the legal and policy framework for participatory budgeting at the local government level in South Africa. Using Borbet South Africa (Pty) Ltd and Others v Nelson Mandela Bay Municipality 2014 (5) SA 256 (ECP) as an example, this paper argues that the legal framework for participatory budgeting creates an illusory right for citizens to participate in municipal budgeting processes. This challenge is further compounded by the barrenness of the jurisprudence of courts that interpret the obligation of municipalities in this regard. It is submitted that the wording of s 27(4) of the Municipal Finance Management Act (MFMA) 53 of 2003 - which expressly stipulates that non-compliance by a municipality with a provision relating to the budget process or a provision in any legislation relating to the approval of a budget-related policy, does not affect the validity of an annual or adjustments budget – is problematic as it seems to trivialise the obligation to facilitate public participation in budgeting processes. It is submitted that where this provision is abused by municipal officials, this could lead to the sidelining of the real interests of communities in local budgets. This research is based on a critical and integrated review of primary and secondary sources of law.

Keywords: courts and jurisprudence, local government law, participatory budgeting, South Africa

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Authors: Noga Bregman

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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

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Authors: Jian Wu

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Since a few years, some French companies have integrated CRS (corporate social responsibility) criteria in their variable remuneration plans to ‘restore a good working atmosphere’ and ‘preserve the natural environment’. These CSR criteria are based on concerns on environment protection, social aspects, and corporate governance. In June 2012, a report on this practice has been made jointly by ORSE (which means Observatory on CSR in French) and PricewaterhouseCoopers. Facing this initiative from the business world, we need to examine whether it has a real economic utility. We adopt a theoretical approach for our study. First, we examine the debate between the ‘orthodox’ point of view in economics and the CSR school of thought. The classical economic model asserts that in a capitalist economy, exists a certain ‘invisible hand’ which helps to resolve all problems. When companies seek to maximize their profits, they are also fulfilling, de facto, their duties towards society. As a result, the only social responsibility that firms should have is profit-searching while respecting the minimum legal requirement. However, the CSR school considers that, as long as the economy system is not perfect, there is no ‘invisible hand’ which can arrange all in a good order. This means that we cannot count on any ‘divine force’ which makes corporations responsible regarding to society. Something more needs to be done in addition to firms’ economic and legal obligations. Then, we reply on some financial theories and empirical evident to examine the sound foundation of CSR. Three theories developed in corporate governance can be used. Stakeholder theory tells us that corporations owe a duty to all of their stakeholders including stockholders, employees, clients, suppliers, government, environment, and society. Social contract theory tells us that there are some tacit ‘social contracts’ between a company and society itself. A firm has to respect these contracts if it does not want to be punished in the form of fine, resource constraints, or bad reputation. Legitime theory tells us that corporations have to ‘legitimize’ their actions toward society if they want to continue to operate in good conditions. As regards empirical results, we present a literature review on the relationship between the CSR performance and the financial performance of a firm. We note that, due to difficulties in defining these performances, this relationship remains still ambiguous despite numerous research works realized in the field. Finally, we are curious to know whether the integration of CSR criteria in variable remuneration plans – which is practiced so far in big companies – should be extended to other ones. After investigation, we note that two groups of firms have the greatest need. The first one involves industrial sectors whose activities have a direct impact on the environment, such as petroleum and transport companies. The second one involves companies which are under pressures in terms of return to deal with international competition.

Keywords: corporate social responsibility, corporate governance, variable remuneration, stakeholder theory

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Authors: Indujeeva Keerthila Peiris

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The secular view of mindfulness has some connotation to the original meaning of mindfulness mentioned in the Theravada Buddhist texts (Pāli Canon), but there is a substantial difference in the meaning of the two. Secular Mindfulness Based Interventions (MBI) focus on stilling the mind, which may provide short-term benefits and help individuals to deal with physical pain, grief, and distress. However, as with many popular educational innovations, the foundational values of mindfulness strategies have been distorted and subverted in a number of instances in which ‘McMindfulness’ programmes have been implemented with a view to reducing mindfulness mediation as a self-help technique that is easily misappropriated for the exclusive pursuit of corporate objectives, employee pacification, and commercial profit. The intention of this paper is not to critique the misappropriations of mindfulness. Instead, to go back to the root source and bring insights from the Buddhist Pāli Canon and its associated teachings on mindfulness in its own terms. In the Buddha’s discourses, as preserved in the Pāli Canon, there is nothing more significant than the understanding and practice of ‘Satipatthãna’. The Satipatthāna Sutta , the ‘Discourse on the Establishment of Mindfulness,’ opens with a proclamation highlighting both the purpose of this training and its methodology. The right practice of mindfulness is the gateway to understanding the Buddha’s teaching. However, although this concept is widely discussed among the Dhamma practitioners, it is the least understood one of them all. The purpose of this paper is to understand deeper meaning of mindfulness as it was originally intended by the Teacher. The natural state of mind is that it wanders. It wanders into the past, the present, and the future. One’s ability to hold attention to a mind object (emotion, thought, feeling, sensation, sense impression) called ‘concentration’. The intentional concentration process does not lead to wisdom. However, the development of wisdom starts when the mind is calm, concentrated, and unified. The practice of insight contemplation aims at gaining a direct understanding of the real nature of phenomena. According to the Buddha’s teaching, there are three basic facts of all existence: 1) impermanence (anicca in Pāli) ; 2) fabrication (also commonly known as suffering, unsatisfactoriness, sankhara or dukka in Pāli); 3) not-self (insubstantiality or impersonality, annatta in Pāli ). The entire Buddhist doctrine is based on these three facts. The problem is our ignorance covers reality. It is not that a person sees the emptiness of them or that we try to see the emptiness of our experience by conceptually thinking that they are empty. It is an experiential outcome that happens when the cause-and- effect overrides the self-view (sakkaya dhitti), and ignorance is known as ignorance and eradicated once and for all. Therefore, the right view (samma dhitti) is the starting point of the path, not ethical conduct (sila) or samadhi (jhana). In order to develop the right view, we need to first listen to the correct Dhamma and possess Yoniso manasikara (right comprehension) to know the five aggregates as five aggregates.

Keywords: mindfulness, spirituality, buddhism, pali canon

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Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

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Authors: Peter Baji

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In recent years, a growing body of literature emphasizes the increasingly negative impacts of urban road congestion in the everyday life of citizens. Although there are different responses from the public sector to decrease traffic congestion in urban regions, the most effective public intervention is using congestion charges. Because travel is an economic asset, its consumption can be controlled by extra taxes or prices effectively, but this demand-side intervention is often unpopular. Measuring traffic flows with the help of different methods has a long history in transport sciences, but until recently, there was not enough sufficient data for evaluating road traffic flow patterns on the scale of an entire road system of a larger urban area. European cities (e.g., London, Stockholm, Milan), in which congestion charges have already been introduced, designated a particular zone in their downtown for paying, but it protects only the users and inhabitants of the CBD (Central Business District) area. Through the use of Google Maps data as a resource for revealing urban road traffic flow patterns, this paper aims to provide a solution for a fairer and smarter congestion pricing method in cities. The case study area of the research contains three bordering districts of Budapest which are linked by one main road. The first district (5th) is the original downtown that is affected by the congestion charge plans of the city. The second district (13th) lies in the transition zone, and it has recently been transformed into a new CBD containing the biggest office zone in Budapest. The third district (4th) is a mainly residential type of area on the outskirts of the city. The raw data of the research was collected with the help of Google’s Distance Matrix API (Application Programming Interface) which provides future estimated traffic data via travel times between freely fixed coordinate pairs. From the difference of free flow and congested travel time data, the daily congestion patterns and hot spots are detectable in all measured roads within the area. The results suggest that the distribution of congestion peak times and hot spots are uneven in the examined area; however, there are frequently congested areas which lie outside the downtown and their inhabitants also need some protection. The conclusion of this case study is that cities can develop a real-time and place-based congestion charge system that forces car users to avoid frequently congested roads by changing their routes or travel modes. This would be a fairer solution for decreasing the negative environmental effects of the urban road transportation instead of protecting a very limited downtown area.

Keywords: Budapest, congestion charge, distance matrix API, application programming interface, pilot study

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Authors: Mustafa İlhan Akbaş, Özlem Garibay, Ivan Garibay

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The economic entities in innovation ecosystems form various industry clusters, in which they compete and cooperate to survive and grow. Within a successful and stable industry cluster, the entities acquire different roles that complement each other in the system. The universities and research centers have been accepted to have a critical role in these systems for the creation and development of innovations. However, the real effect of research institutions on regional economic growth is difficult to assess. In this paper, we present our approach for the identification of the impact of research activities on the regional entrepreneurship for a specific high-tech industry: optics and photonics. The optics and photonics has been defined as an enabling industry, which combines the high-tech photonics technology with the developing optics industry. The recent literature suggests that the growth of optics and photonics firms depends on three important factors: the embedded regional specializations in the labor market, the research and development infrastructure, and a dynamic small firm network capable of absorbing new technologies, products and processes. Therefore, the role of each factor and the dynamics among them must be understood to identify the requirements of the entrepreneurship activities in optics and photonics industry. There are three main contributions of our approach. The recent studies show that the innovation in optics and photonics industry is mostly located around metropolitan areas. There are also studies mentioning the importance of research center locations and universities in the regional development of optics and photonics industry. These studies are mostly limited with the number of patents received within a short period of time or some limited survey results. Therefore the first contribution of our approach is conducting a comprehensive analysis for the state and recent history of the photonics and optics research in the US. For this purpose, both the research centers specialized in optics and photonics and the related research groups in various departments of institutions (e.g. Electrical Engineering, Materials Science) are identified and a geographical study of their locations is presented. The second contribution of the paper is the analysis of regional entrepreneurship activities in optics and photonics in recent years. We use the membership data of the International Society for Optics and Photonics (SPIE) and the regional photonics clusters to identify the optics and photonics companies in the US. Then the profiles and activities of these companies are gathered by extracting and integrating the related data from the National Establishment Time Series (NETS) database, ES-202 database and the data sets from the regional photonics clusters. The number of start-ups, their employee numbers and sales are some examples of the extracted data for the industry. Our third contribution is the utilization of collected data to investigate the impact of research institutions on the regional optics and photonics industry growth and entrepreneurship. In this analysis, the regional and periodical conditions of the overall market are taken into consideration while discovering and quantifying the statistical correlations.

Keywords: entrepreneurship, industrial clusters, optics, photonics, emerging industries, research centers

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Authors: Dalia Hanna, Alexander Ferworn

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This research provides detailed proposed training modules for the public safety teams and, specifically, SAR teams responsible for search and rescue operations related to finding lost persons with dementia. Finding a lost person alive is the goal of this training. Time matters if a lost person is to be found alive. Finding lost people living with dementia is quite challenging, as they are unaware they are lost and will not seek help. Even a small contribution to SAR operations could contribute to saving a life. SAR operations will always require expert professional and human volunteers. However, we can reduce their time, save lives, and reduce costs by providing practical training that is based on real-life scenarios. The content for the proposed training is based on the research work done by the researcher in this area. This research has demonstrated that, based on utilizing drones, the algorithmic approach could support a successful search outcome. Understanding the behavior of the lost person, learning where they may be found, predicting their survivability, and automating the search are all contributions of this work, founded in theory and demonstrated in practice. In crisis management, human behavior constitutes a vital aspect in responding to the crisis; the speed and efficiency of the response often get affected by the difficulty of the context of the operation. Therefore, training in this area plays a significant role in preparing the crisis manager to manage the emotional aspects that lead to decision-making in these critical situations. Since it is crucial to gain high-level strategic choices and the ability to apply crisis management procedures, simulation exercises become central in training crisis managers to gain the needed skills to respond critically to these events. The training will enhance the responders’ ability to make decisions and anticipate possible consequences of their actions through flexible and revolutionary reasoning in responding to the crisis efficiently and quickly. As adult learners, search and rescue teams will be approaching training and learning by taking responsibility of the learning process, appreciate flexible learning and as contributors to the teaching and learning happening during that training. These are all characteristics of adult learning theories. The learner self-reflects, gathers information, collaborates with others and is self-directed. One of the learning strategies associated with adult learning is effective elaboration. It helps learners to remember information in the long term and use it in situations where it might be appropriate. It is also a strategy that can be taught easily and used with learners of different ages. Designers must design reflective activities to improve the student’s intrapersonal awareness.

Keywords: training, OER, dementia, drones, search and rescue, adult learning, UDL, instructional design

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Authors: Sudipta Garai

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Films as a cultural, social practice remains a dominant space for creation and destruction of ideologies and practices which make the sociological viewing, analysis, and interpretation of the same a complex affair. It remains the doorway between the interpretations and understanding of the writer/director and the reader/viewer. India, being a multi-linguistic culture, the media plays a much intriguing role than that of newspaper, books, stories, novels or any other medium of expression. Known to be the largest democracy, the State seem to guarantee and safeguard people’s choices and life of dignity through its Fundamental Rights and Directives. However, the laws contradict themselves when it comes to IPC 377 criminalizing anything except penovaginal sexual intercourse restricting alternative sexual preferences and practices questioning its sense of ‘democracy.' In this context, the issue of homosexuality came up in bits and pieces through various representations in ‘popular’ cinema mostly with sudden references of mockery and laughter where the explicit narratives of ‘queer’ seemed missing. Rituparno Ghosh, an eminent film maker of Bengal, came up as the ‘queer’ face in Kolkata specifically through his ‘queer’ trilogy (Memories in March, 2010; Arekti Premer Golpo, 2010; Chitrangada: A Crowning Wish, 2012) coming out of his own closet and speaking about his own sexual choices not only through the explicit narratives in films but also in person which made these films an important point of departure in Bengali film history. A sociological reading of these films through a discourse analysis is being done with the critical questions of ‘choice,' ’freedom,' ‘love and marriage’ and most importantly the ‘change.' This study not only focuses on the films and its analysis of content but also to engage with its audience, queer and not in order to extend beyond the art form into the actual vulnerabilities of life and experiences through informal interviews, focused group discussions and engaging with the real life narratives. A research of this kind is always looked upon as a medium of change hoping for a better world wiping away the discrimination and ‘shame’ the ‘queer’ faces in their everyday life, but a social science research is limited but its ‘time’ and academic boundary where the hope of change might be initiated but not fulfilled. The experiences and reflections of the ‘queer’ not only redefined the narratives of the films but also me as a researcher. The perspectives of the ‘hetero-normative’ informants gave a broader picture of the study and the socio-cultural complications that are intrigued with the ideas of resistance and change. The issues on subjectivity, power, and position couldn’t be wiped out in a study of this kind as both politics and aesthetics become integrated with each other in the creation of any art form be it films or a study of research.

Keywords: cinema, alternative sexualities, narratives, sexual choices, state and society

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Authors: Giada Feletti, Daniela Tedesco, Paolo Trucco

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The present study aims to develop a dashboard of Key Performance Indicators (KPI) to enhance information and predictive capabilities in Emergency Medical Services (EMS) systems, supporting both operational and strategic decisions of different actors. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning the indicators currently used for the performance measurement of EMS systems. From this literature analysis, it emerged that current studies focus on two distinct perspectives: the ambulance service, a fundamental component of pre-hospital health treatment, and the patient care in the Emergency Department (ED). The perspective proposed by this study is to consider an integrated view of the ambulance service process and the ED process, both essential to ensure high quality of care and patient safety. Thus, the proposal focuses on the entire healthcare service process and, as such, allows considering the interconnection between the two EMS processes, the pre-hospital and hospital ones, connected by the assignment of the patient to a specific ED. In this way, it is possible to optimize the entire patient management. Therefore, attention is paid to the dependency of decisions that in current EMS management models tend to be neglected or underestimated. In particular, the integration of the two processes enables the evaluation of the advantage of an ED selection decision having visibility on EDs’ saturation status and therefore considering the distance, the available resources and the expected waiting times. Starting from a critical review of the KPIs proposed in the extant literature, the design of the dashboard was carried out: the high number of analyzed KPIs was reduced by eliminating the ones firstly not in line with the aim of the study and then the ones supporting a similar functionality. The KPIs finally selected were tested on a realistic dataset, which draws us to exclude additional indicators due to the unavailability of data required for their computation. The final dashboard, which was discussed and validated by experts in the field, includes a variety of KPIs able to support operational and planning decisions, early warning, and citizens’ awareness of EDs accessibility in real-time. By associating each KPI to the EMS phase it refers to, it was also possible to design a well-balanced dashboard covering both efficiency and effective performance of the entire EMS process. Indeed, just the initial phases related to the interconnection between ambulance service and patient’s care are covered by traditional KPIs compared to the subsequent phases taking place in the hospital ED. This could be taken into consideration for the potential future development of the dashboard. Moreover, the research could proceed by building a multi-layer dashboard composed of the first level with a minimal set of KPIs to measure the basic performance of the EMS system at an aggregate level and further levels with KPIs that can bring additional and more detailed information.

Keywords: dashboard, decision support, emergency medical services, key performance indicators

Procedia PDF Downloads 113

Authors: Peter Modregger, Özgül Öztürk

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Glass fabric reinforced thermoplastic (GFRT) are composite materials, which combine low weight and resilient mechanical properties rendering them especially suitable for automobile construction. However, defects in the glass fabric as well as in the polymer matrix can occur during manufacturing, which may compromise component lifetime or even safety. One type of these defects is local fiber shifts, which can be difficult to detect. Recently, we have experimentally demonstrated the reliable detection of local fiber shifts by X-ray scattering based on the edge-illumination (EI) principle. EI constitutes a novel X-ray imaging technique that utilizes two slit masks, one in front of the sample and one in front of the detector, in order to simultaneously provide absorption, phase, and scattering contrast. The principle of contrast formation is as follows. The incident X-ray beam is split into smaller beamlets by the sample mask, resulting in small beamlets. These are distorted by the interaction with the sample, and the distortions are scaled up by the detector masks, rendering them visible to a pixelated detector. In the experiment, the sample mask is laterally scanned, resulting in Gaussian-like intensity distributions in each pixel. The area under the curves represents absorption, the peak offset refraction, and the width of the curve represents the scattering occurring in the sample. Here, scattering is caused by the numerous glass fiber/polymer matrix interfaces. In our recent publication, we have shown that the standard deviation of the absorption and scattering values over a selected field of view can be used to distinguish between intact samples and samples with local fiber shift defects. The quantification of defect detection performance was done by using p-values (p=0.002 for absorption and p=0.009 for scattering) and contrast-to-noise ratios (CNR=3.0 for absorption and CNR=2.1 for scattering) between the two groups of samples. This was further improved for the scattering contrast to p=0.0004 and CNR=4.2 by utilizing a harmonic decomposition analysis of the images. Thus, we concluded that local fiber shifts can be reliably detected by the X-ray scattering contrasts provided by EI. However, a potential application in, for example, production monitoring requires fast data acquisition times. For the results above, the scanning of the sample masks was performed over 50 individual steps, which resulted in long total scan times. In this paper, we will demonstrate that reliable detection of local fiber shift defects is also possible by using single images, which implies a speed up of total scan time by a factor of 50. Additional performance improvements will also be discussed, which opens the possibility for real-time acquisition. This contributes a vital step for the translation of EI to industrial applications for a wide variety of materials consisting of numerous interfaces on the micrometer scale.

Keywords: defects in composites, X-ray scattering, local fiber shifts, X-ray edge Illumination

Procedia PDF Downloads 63

Authors: Lombuso P. Shabalala

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This research paper investigates the importance of community involvement in tourism development activities from the initial stage. Community is defined as a group of people living in the same area and practicing common ownership and practices or with a commonality such as norms, religion, values, customs, or identity. Globalisation has restructured economic, political, and social relationships at the local level, which impacts community involvement in activities taking place in their own space. Although social relationships and interests are no longer limited to local communities, the power of place remains. Whereas, tourism is considered as an activity essential to the life of nations because of its direct effects on the social, cultural, educational, and economic sectors of national societies and their international relations. The existing literature has indicated that the four types of motivation in community involvement are best differentiated by identifying the unique ultimate goal for each motivation. In a nutshell, the ultimate goal for egoism is to increase one's own welfare; altruism is to increase the welfare of another individual or individuals; collectivism is aimed at increasing the welfare of a group, and the principlism is to uphold one or more moral principles. As a base of community involvement, each of these four forms of motivation exhibits its own strengths and weaknesses to be acknowledged. Purposive sampling was suitable to select the fourteen descendant group representatives. The representatives included chief/s, headman, senior descendants’ member, and members of the traditional council who descends from MWCHS. The qualitative research design was adopted for the study in the form of semi-structured interviews. Community development is a social process involving residents in activities designed to improve their quality of life. The key finding of the research is the importance of involving communities, in particular, the immediate community members from the initial stage of any proposed tourism development activity. Without a doubt, the immediate communities are well informed about the dynamics of the area (economically, politically, and socially). Therefore, the finding suggests that communities are in a better position to advise project managers on possible potential tourism developments activities that can address the real needs and benefit the community, instead of investing resources in a development that will not benefit or add any value in the lives of the targeted communities. It must be noted that the power of the place where the development will be implemented remains with the community. Furthermore, community support and buy-in are crucial to the success of prospective tourism development. In conclusion, it cannot be denied that community involvement comes with its own challenges, contrary to greater sustainable benefits that can be realized prior to articulation. The study suggests for project managers to ensure a fair and transparent community involvement process. Fair distribution of meaningful roles could secure trust and result in these communities to view the proposed development as their own.

Keywords: communities, development, involvement, tourism

Procedia PDF Downloads 191

Authors: Jakub Berčík, Elena Horská, Ľudmila Nagyová

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Nowadays, the point of sale remains one of the few channels of communication which is not oversaturated yet and has great potential for the future. The fact that purchasing decisions are significantly affected by emotions, while up to 75 % of them are implemented at the point of sale, only demonstrates its importance. The share of impulsive purchases is about 60-75 %, depending on the particular product category. Nevertheless, habits predetermine the content of the shopping cart above all and hence in this regard the role of in-store communication is to disrupt the routine and compel the customer to try something new. This is the reason why it is essential to know how to work with this relatively young branch of marketing communication as efficiently as possible. New global trend in this discipline is evaluating the effectiveness of particular tools in the in-store communication. To increase the efficiency it is necessary to become familiar with the factors affecting the customer both consciously and unconsciously, and that is a task for neuromarketing and sensory marketing. It is generally known that the customer remembers the negative experience much longer and more intensely than the positive ones, therefore it is essential for marketers to avoid this negative experience. The final effect of POP (Point of Purchase) or POS (Point of Sale) tools is conditional not only on their quality and design, but also on the location at the point of sale which contributes to the overall positive atmosphere in the store. Therefore, in-store advertising is increasingly in the center of attention and companies are willing to spend even a third of their marketing communication budget on it. The paper deals with a comprehensive, interdisciplinary research of the impact of traditional as well as innovative tools of in-store communication on the attention and emotional state (valence and arousal) of consumers on the food market. The research integrates measurements with eye camera (Eye tracker) and electroencephalograph (EEG) in real grocery stores as well as in laboratory conditions with the purpose of recognizing attention and emotional response among respondents under the influence of selected tools of in-store communication. The object of the research includes traditional (e.g. wobblers, stoppers, floor graphics) and innovative (e.g. displays, wobblers with LED elements, interactive floor graphics) tools of in-store communication in the fresh unpackaged food segment. By using a mobile 16-channel electroencephalograph (EEG equipment) from the company EPOC, a mobile eye camera (Eye tracker) from the company Tobii and a stationary eye camera (Eye tracker) from the company Gazepoint, we observe the attention and emotional state (valence and arousal) to reveal true consumer preferences using traditional and new unusual communication tools at the point of sale of the selected foodstuffs. The paper concludes with suggesting possibilities for rational, effective and energy-efficient combination of in-store communication tools, by which the retailer can accomplish not only captivating and attractive presentation of displayed goods, but ultimately also an increase in retail sales of the store.

Keywords: electroencephalograph (EEG), emotion, eye tracker, in-store communication

Procedia PDF Downloads 392

Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

Procedia PDF Downloads 139

Authors: Lukasz Grabowski, Marcin Szlachetka, Tytus Tulwin

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The main task of the engine cooling system is to maintain its average operating temperatures within strictly defined limits. Too high or too low average temperatures result in accelerated wear or even damage to the engine or its individual components. In order to avoid local overheating or significant temperature gradients, leading to high stresses in the component, the aim is to ensure an even flow of air. In the case of analyses related to heat exchange, one of the main problems is the comparison of temperature fields because standard measuring instruments such as thermocouples or thermistors only provide information about the course of temperature at a given point. Thermal imaging tests can be helpful in this case. With appropriate camera settings and taking into account environmental conditions, we are able to obtain accurate temperature fields in the form of thermograms. Emission of heat from the engine to the engine compartment is an important issue when designing a cooling system. Also, in the case of liquid cooling, the main sources of heat in the form of emissions from the engine block, cylinders, etc. should be identified. It is important to redesign the engine compartment ventilation system. Ensuring proper cooling of aircraft reciprocating engine is difficult not only because of variable operating range but mainly because of different cooling conditions related to the change of speed or altitude of flight. Engine temperature also has a direct and significant impact on the properties of engine oil, which under the influence of this parameter changes, in particular, its viscosity. Too low or too high, its value can be a result of fast wear of engine parts. One of the ways to determine the temperatures occurring on individual parts of the engine is the use of thermal imaging measurements. The article presents the results of preliminary thermal imaging tests of aircraft piston diesel engine with a maximum power of about 100 HP. In order to perform the heat emission tests of the tested engine, the ThermaCAM S65 thermovision monitoring system from FLIR (Forward-Looking Infrared) together with the ThermaCAM Researcher Professional software was used. The measurements were carried out after the engine warm up. The engine speed was 5300 rpm The measurements were taken for the following environmental parameters: air temperature: 17 °C, ambient pressure: 1004 hPa, relative humidity: 38%. The temperatures distribution on the engine cylinder and on the exhaust manifold were analysed. Thermal imaging tests made it possible to relate the results of simulation tests to the real object by measuring the rib temperature of the cylinders. The results obtained are necessary to develop a CFD (Computational Fluid Dynamics) model of heat emission from the engine bay. The project/research was financed in the framework of the project Lublin University of Technology-Regional Excellence Initiative, funded by the Polish Ministry of Science and Higher Education (contract no. 030/RID/2018/19).

Keywords: aircraft, piston engine, heat, emission

Procedia PDF Downloads 119

Authors: Josef Uher, Jana Boháčová, Richard Kadeřábek

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In this paper, we present a multi-robot imaging and irradiation research platform referred to as Irradion, with full capabilities of portable arbitrary path computed tomography (CT). Irradion is an imaging and irradiation unit entirely based on robotic arms for research on cancer treatment with ion beams on small animals (mice or rats). The platform comprises two subsystems that combine several imaging modalities, such as 2D X-ray imaging, CT, and particle tracking, with precise positioning of a small animal for imaging and irradiation. Computed Tomography: The CT subsystem of the Irradion platform is equipped with two 6-joint robotic arms that position a photon counting detector and an X-ray tube independently and freely around the scanned specimen and allow image acquisition utilizing computed tomography. Irradiation measures nearly all conventional 2D and 3D trajectories of X-ray imaging with precisely calibrated and repeatable geometrical accuracy leading to a spatial resolution of up to 50 µm. In addition, the photon counting detectors allow X-ray photon energy discrimination, which can suppress scattered radiation, thus improving image contrast. It can also measure absorption spectra and recognize different materials (tissue) types. X-ray video recording and real-time imaging options can be applied for studies of dynamic processes, including in vivo specimens. Moreover, Irradion opens the door to exploring new 2D and 3D X-ray imaging approaches. We demonstrate in this publication various novel scan trajectories and their benefits. Proton Imaging and Particle Tracking: The Irradion platform allows combining several imaging modules with any required number of robots. The proton tracking module comprises another two robots, each holding particle tracking detectors with position, energy, and time-sensitive sensors Timepix3. Timepix3 detectors can track particles entering and exiting the specimen and allow accurate guiding of photon/ion beams for irradiation. In addition, quantifying the energy losses before and after the specimen brings essential information for precise irradiation planning and verification. Work on the small animal research platform Irradion involved advanced software and hardware development that will offer researchers a novel way to investigate new approaches in (i) radiotherapy, (ii) spectral CT, (iii) arbitrary path CT, (iv) particle tracking. The robotic platform for imaging and radiation research developed for the project is an entirely new product on the market. Preclinical research systems with precision robotic irradiation with photon/ion beams combined with multimodality high-resolution imaging do not exist currently. The researched technology can potentially cause a significant leap forward compared to the current, first-generation primary devices.

Keywords: arbitrary path CT, robotic CT, modular, multi-robot, small animal imaging

Procedia PDF Downloads 91

Authors: Arin Salamah Qudsi

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Female piety and the roles that female mystics played in Muslim landscapes of the period between the ninth and thirteenth centuries are topics that attracted many scholarly endeavors. However, personal aspects of both male and female Sufis were not thoroughly investigated. It would be of a great significance to examine the different roles of Sufi women as spouses, household supporters, and, mothers based on Sufi and non Sufi sources. Sisters and mothers, rather than wives and daughters, are viewed in anthropological studies of different cultures as women who could enjoy a high social status and thus play influential roles. Sufi hagiographies, which are our main sources, have long been regarded in a negative light, and their value for our understanding of the early history of Sufism is held in doubt. More recently, however, a new scholarly voice has begun to reclaim the historical value of hagiographies. We need to approach the narrative structures and styles of the anecdotal segments, which are the building blocks of the hagiographical body of writing. The image of a particular Sufi figure as portrayed by his near-contemporaries can provide a more useful means to sketch the components of his unique piety than his real life. However, in certain cases, whenever singular and unique appearances of particular stories occur, certain historical and individual conclusions could be sought. As for women in Sufi hagiographies, we know about sisters who acted as a solid support for their renowned Sufi brothers. Some of those sisters preferred not to be married until a late age in order to "serve" their brothers, while others supported their brothers while pursuing their own spiritual careers. Data of this type should be carefully considered and its historical context should be thoroughly investigated. The reference here is to women, mostly married women, who offered to maintain their brothers or male relatives despite social norms or generic prohibitions, which undoubtedly gave them strong authority over them. As for mothers, we should differentiate between mothers who were Sufis themselves, and those who were the mothers of Sufi figures. It seems most likely that in both types, mothers were not always unquestionably the effective lightening trigger. Mothers of certain Sufi figures denied their sons free mobility, taking advantage of the highly esteemed principle of gratifying the wishes of one's mother and the seminal ideal of ḥaqq al-wālida (lit. mother's right). Drawing on the anecdotes provided by a few sources leads to the suggestion that many Sufis actually strove to reduce their mothers' authority in order to establish their independent careers. In light of women's authority over their brothers and sons in Sufi spheres, maternal uncles could enjoy a crucial position of influence over their nephews. The roles of Sufi mothers and of Sufi maternal uncles in the lives of early Sufi figures are topics that have not yet been dealt with in modern scholarship on classical Sufism.

Keywords: female Sufis, hagiographies, maternal uncles, mother's right

Procedia PDF Downloads 334

Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

Procedia PDF Downloads 464

Authors: Antonio Ruiz Gonzalez, Kwang-Leong Choy

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The measurement of electrolytes has a high value in the clinical routine. Ions are present in all body fluids with variable concentrations and are involved in multiple pathologies such as heart failures and chronic kidney disease. In the case of dissolved potassium, although a high concentration in the blood (hyperkalemia) is relatively uncommon in the general population, it is one of the most frequent acute electrolyte abnormalities. In recent years, the integration of thin films technologies in this field has allowed the development of highly sensitive biosensors with ultra-low limits of detection for the assessment of metals in liquid samples. However, despite the current efforts in the miniaturization of sensitive devices and their integration into portable systems, only a limited number of successful examples used commercially can be found. This fact can be attributed to a high cost involved in their production and the sustained degradation of the electrodes over time, which causes a signal drift in the measurements. Thus, there is an unmet necessity for the development of low-cost and robust sensors for the real-time monitoring of analyte concentrations in patients to allow the early detection and diagnosis of diseases. This paper reports a thin film ion-selective sensor for the evaluation of potassium ions in aqueous samples. As an alternative for this fabrication method, aerosol assisted chemical vapor deposition (AACVD), was applied due to cost-effectivity and fine control over the film deposition. Such a technique does not require vacuum and is suitable for the coating of large surface areas and structures with complex geometries. This approach allowed the fabrication of highly homogeneous surfaces with well-defined microstructures onto 50 nm thin gold layers. The degradative processes of the ubiquitously employed poly (vinyl chloride) membranes in contact with an electrolyte solution were studied, including the polymer leaching process, mechanical desorption of nanoparticles and chemical degradation over time. Rational design of a protective coating based on an organosilicon material in combination with cellulose to improve the long-term stability of the sensors was then carried out, showing an improvement in the performance after 5 weeks. The antifouling properties of such coating were assessed using a cutting-edge quartz microbalance sensor, allowing the quantification of the adsorbed proteins in the nanogram range. A correlation between the microstructural properties of the films with the surface energy and biomolecules adhesion was then found and used to optimize the protective film.

Keywords: hyperkalemia, drift, AACVD, organosilicon

Procedia PDF Downloads 124

Authors: Eva Filová, Jana Daňková, Věra Sovková, Matej Daniel

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Titanium alloys are biocompatible metals that are widely used in clinical practice as load bearing implants. The chemical modification may influence cell adhesion, proliferation, and differentiation as well as stiffness of the material. The aim of the study was to evaluate the adhesion, growth and differentiation of pig mesenchymal stem cells on the novel beta titanium alloy Ti36Nb6Ta compared to standard medical titanium alloy Ti6Al4V. Discs of Ti36Nb6Ta and Ti6Al4V alloy were sterilized by ethanol, put in 48-well plates, and seeded by pig mesenchymal stem cells at the density of 60×103/cm2 and cultured in Minimum essential medium (Sigma) supplemented with 10% fetal bovine serum and penicillin/streptomycin. Cell viability was evaluated using MTS assay (CellTiter 96® AQueous One Solution Cell Proliferation Assay;Promega), cell proliferation using Quant-iT™ ds DNA Assay Kit (Life Technologies). Cells were stained immunohistochemically using monoclonal antibody beta-actin, and secondary antibody conjugated with AlexaFluor®488 and subsequently the spread area of cells was measured. Cell differentiation was evaluated by alkaline phosphatase assay using p-nitrophenyl phosphate (pNPP) as a substrate; the reaction was stopped by NaOH, and the absorbance was measured at 405 nm. Osteocalcin, specific bone marker was stained immunohistochemically and subsequently visualized using confocal microscopy; the fluorescence intensity was analyzed and quantified. Moreover, gene expression of osteogenic markers osteocalcin and type I collagen was evaluated by real-time reverse transcription-PCR (qRT-PCR). For statistical evaluation, One-way ANOVA followed by Student-Newman-Keuls Method was used. For qRT-PCR, the nonparametric Kruskal-Wallis Test and Dunn's Multiple Comparison Test were used. The absorbance in MTS assay was significantly higher on titanium alloy Ti6Al4V compared to beta titanium alloy Ti36Nb6Ta on days 7 and 14. Mesenchymal stem cells were well spread on both alloys, but no difference in spread area was found. No differences in alkaline phosphatase assay, fluorescence intensity of osteocalcin as well as the expression of type I collagen, and osteocalcin genes were observed. Higher expression of type I collagen compared to osteocalcin was observed for cells on both alloys. Both beta titanium alloy Ti36Nb6Ta and titanium alloy Ti6Al4V Ti36Nb6Ta supported mesenchymal stem cellsˈ adhesion, proliferation and osteogenic differentiation. Novel beta titanium alloys Ti36Nb6Ta is a promising material for bone implantation. The project was supported by the Czech Science Foundation: grant No. 16-14758S, the Grant Agency of the Charles University, grant No. 1246314 and by the Ministry of Education, Youth and Sports NPU I: LO1309.

Keywords: beta titanium, cell growth, mesenchymal stem cells, titanium alloy, implant

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Authors: Mohammadreza Bakhtiari, Mehrdad Maghsoudi, Hamidreza Bakhtiari

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The widespread adoption of laptops has become essential to modern lifestyles, supporting work, education, and entertainment. Social media platforms have emerged as key spaces where users share real-time feedback on laptop performance, providing a valuable source of data for understanding consumer preferences. This study leverages aspect-based sentiment analysis (ABSA) on 1.5 million tweets to examine how users from developed and developing countries perceive and prioritize 16 key laptop features. The analysis reveals that consumers in developing countries express higher satisfaction overall, emphasizing affordability, durability, and reliability. Conversely, users in developed countries demonstrate more critical attitudes, especially toward performance-related aspects such as cooling systems, battery life, and chargers. The study employs a mixed-methods approach, combining ABSA using the PyABSA framework with expert insights gathered through a Delphi panel of ten industry professionals. Data preprocessing included cleaning, filtering, and aspect extraction from tweets. Universal issues such as battery efficiency and fan performance were identified, reflecting shared challenges across markets. However, priorities diverge between regions, while users in developed countries demand high-performance models with advanced features, those in developing countries seek products that offer strong value for money and long-term durability. The findings suggest that laptop manufacturers should adopt a market-specific strategy by developing differentiated product lines. For developed markets, the focus should be on cutting-edge technologies, enhanced cooling solutions, and comprehensive warranty services. In developing markets, emphasis should be placed on affordability, versatile port options, and robust designs. Additionally, the study highlights the importance of universal charging solutions and continuous sentiment monitoring to adapt to evolving consumer needs. This research offers practical insights for manufacturers seeking to optimize product development and marketing strategies for global markets, ensuring enhanced user satisfaction and long-term competitiveness. Future studies could explore multi-source data integration and conduct longitudinal analyses to capture changing trends over time.

Keywords: consumer behavior, durability, laptop industry, sentiment analysis, social media analytics

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

Procedia PDF Downloads 120

Authors: Hengameh Hosseini

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Design of large healthcare facilities – such as hospitals, multi-service line clinics, and nursing facilities - that can accommodate patients with wide-ranging disabilities is a challenging endeavor and one that is poorly understood among healthcare facility managers, administrators, and executives. An even less-understood extension of this problem is the implications of weakly or insufficiently accommodative design of facilities for healthcare workers in physically-intensive jobs who may also suffer from a range of disabilities and who are therefore at increased risk of workplace accident and injury. Combine this reality with the vast range of facility types, ages, and designs, and the problem of universal accommodation becomes even more daunting and complex. In this study, we focus on the implication of facility design for healthcare workers suffering with low vision who also have physically active jobs. The points of difficulty are myriad and could span health service infrastructure, the equipment used in health facilities, and transport to and from appointments and other services can all pose a barrier to health care if they are inaccessible, less accessible, or even simply less comfortable for people with various disabilities. We conduct a series of surveys and interviews with employees and administrators of 7 facilities of a range of sizes and ownership models in the Northeastern United States and combine that corpus with in-facility observations and data collection to identify five major points of failure common to all the facilities that we concluded could pose safety threats to employees with vision impairments, ranging from very minor to severe. We determine that lack of design empathy is a major commonality among facility management and ownership. We subsequently propose three methods for remedying this lack of empathy-informed design, to remedy the dangers posed to employees: the use of an existing open-sourced Augmented Reality application to simulate the low-vision experience for designers and managers; the use of a machine learning model we develop to automatically infer facility shortcomings from large datasets of recorded patient and employee reviews and feedback; and the use of a computer vision model fine tuned on images of each facility to infer and predict facility features, locations, and workflows, that could again pose meaningful dangers to visually impaired employees of each facility. After conducting a series of real-world comparative experiments with each of these approaches, we conclude that each of these are viable solutions under particular sets of conditions, and finally characterize the range of facility types, workforce composition profiles, and work conditions under which each of these methods would be most apt and successful.

Keywords: artificial intelligence, healthcare workers, facility design, disability, visually impaired, workplace safety

Procedia PDF Downloads 117

Authors: Marco Sewald

Abstract:

Due to the current enforcement of exterritorial U.S. legislation, up to 9 million U.S. (dual) citizens residing abroad are subject to U.S. double and surcharge taxation and at risk of losing access to otherwise basic financial services and investment opportunities abroad. The United States is the only OECD country that taxes non-resident citizens, lawful permanent residents and other non-resident aliens on their worldwide income, based on local U.S. tax laws. To enforce these policies the U.S. has implemented ‘saving clauses’ in all tax treaties and implemented several compliance provisions, including the Foreign Account Tax Compliance Act (FATCA), Qualified Intermediaries Agreements (QI) and Intergovernmental Agreements (IGA) addressing Foreign Financial Institutions (FFIs) to implement these provisions in foreign jurisdictions. This policy creates systematic cases of double and surcharge taxation. The increased enforcement of compliance rules is creating additional report burdens for U.S. persons abroad and FFIs accepting such U.S. persons as customers. FFIs in Europe react with a growing denial of specific financial services to this population. The numbers of U.S. citizens renouncing has dramatically increased in the last years. A case study is chosen as an appropriate methodology and research method, as being an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used. This evaluative approach is testing whether the combination of policies works in practice, or whether they are in accordance with desirable moral, political, economical aims, or may serve other causes. The research critically evaluates the financial and non-financial consequences and develops sufficient strategies. It further discusses these strategies to avoid the undesired consequences of exterritorial U.S. legislation. Three possible strategies are resulting from the use cases: (1) Duck and cover, (2) Pay U.S. double/surcharge taxes, tax preparing fees and accept imposed product limitations and (3) Renounce U.S. citizenship and pay possible exit taxes, tax preparing fees and the requested $2,350 fee to renounce. While the first strategy is unlawful and therefore unsuitable, the second strategy is only suitable if the U.S. citizen residing abroad is planning to move to the U.S. in the future. The last strategy is the only reasonable and lawful way provided by the U.S. to limit the exposure to U.S. double and surcharge taxation and the limitations on financial products. The results are believed to add a perspective to the current academic discourse regarding U.S. citizenship based taxation, currently dominated by U.S. scholars, while providing sufficient strategies for the affected population at the same time.

Keywords: citizenship based taxation, FATCA, FBAR, qualified intermediaries agreements, renounce U.S. citizenship

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Authors: Regis Pochon, Nicolas Stefaniak, Veronique Baltazart, Pamela Gobin

Abstract:

Anxiety is known to have an impact on working memory. In reasoning or memory tasks, individuals with anxiety tend to show longer response times and poorer performance. Furthermore, there is a memory bias for negative information in anxiety. Given the crucial role of working memory in lexical learning, anxious students may encounter more difficulties in learning to read and spell. Anxiety could even affect an earlier learning, that is the activation of phonological representations, which are decisive for the learning of reading and writing. The aim of this study is to compare the access to phonological representations of beginning readers and writers according to their level of anxiety, using an auditory lexical decision task. Eighty students of 6- to 9-years-old completed the French version of the Revised Children's Manifest Anxiety Scale and were then divided into four anxiety groups according to their total score (Low, Median-Low, Median-High and High). Two set of eighty-one stimuli (words and non-words) have been auditory presented to these students by means of a laptop computer. Stimuli words were selected according to their emotional valence (positive, negative, neutral). Students had to decide as quickly and accurately as possible whether the presented stimulus was a real word or not (lexical decision). Response times and accuracy were recorded automatically on each trial. It was anticipated a) longer response times for the Median-High and High anxiety groups in comparison with the two others groups, b) faster response times for negative-valence words in comparison with positive and neutral-valence words only for the Median-High and High anxiety groups, c) lower response accuracy for Median-High and High anxiety groups in comparison with the two others groups, d) better response accuracy for negative-valence words in comparison with positive and neutral-valence words only for the Median-High and High anxiety groups. Concerning the response times, our results showed no difference between the four groups. Furthermore, inside each group, the average response times was very close regardless the emotional valence. Otherwise, group differences appear when considering the error rates. Median-High and High anxiety groups made significantly more errors in lexical decision than Median-Low and Low groups. Better response accuracy, however, is not found for negative-valence words in comparison with positive and neutral-valence words in the Median-High and High anxiety groups. Thus, these results showed a lower response accuracy for above-median anxiety groups than below-median groups but without specificity for the negative-valence words. This study suggests that anxiety can negatively impact the lexical processing in young students. Although the lexical processing speed seems preserved, the accuracy of this processing may be altered in students with moderate or high level of anxiety. This finding has important implication for the prevention of reading and spelling difficulties. Indeed, during these learnings, if anxiety affects the access to phonological representations, anxious students could be disturbed when they have to match phonological representations with new orthographic representations, because of less efficient lexical representations. This study should be continued in order to precise the impact of anxiety on basic school learning.

Keywords: anxiety, emotional valence, childhood, lexical access

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Authors: Amine Alaoui Sanae, Tagjdid Reda, Loutfi Chafiqa, Melloul Merouane, Laloui Aziz, Touil Nadia, El Fahim, E. Mostafa

Abstract:

Background: Rotavirus group A (RVA) strains with G8P[14] specificities are usually detected in calves and goats. However, these strains have been reported globally in humans and have often been characterized as originating from zoonotic transmissions, particularly in area where ruminants and humans live side-by-side. Whether human P[14] genotypes are two-way and can be transmitted to animal species remains to be established. Here we describe VP4 deduced amino-acid relationships of three Moroccan P[14] genotypes originating from different species and the receptiveness of an alpine goat to a human G8P[14] through an experimental infection. Material/methods: the human MA31 RVA strain was originally identified in a four years old girl presenting an acute gastroenteritis hospitalized at the pediatric care unit in Rabat Hospital in 2011. The virus was isolated and propagated in MA104 cells in the presence of trypsin. Ch_10S and 8045_S animal RVA strains were identified in fecal samples of a 2-week-old native goat and 3-week-old calf with diarrhea in 2011 in Bouaarfa and My Bousselham respectively. Genomic RNAs of all strains were subjected to a two-step RT-PCR and sequenced using the consensus primers VP4. The phylogenetic tree for MA31, Ch_10S and 8045_S VP4 and a set of published P[14] genotypes was constructed using MEGA6 software. The receptivity of MA31 strain by an eight month-old alpine goat was assayed. The animal was orally and intraperitonally inoculated with a dose of 8.5 TCID50 of virus stock at passage level 3. The shedding of the virus was tested by a real time RT-PCR assay. Results: The phylogenetic tree showed that the three Moroccan strains MA31, Ch_10S and 8045_S VP4 were highly related to each other (100% similar at the nucleotide level). They were clustered together with the B10925, Sp813, PA77 and P169 strains isolated in Belgium, Spain and Italy respectively. The Belgian strain B10925 was the most closely related to the Moroccan strains. In contrast, the 8045_S and Ch_10S strains were clustered distantly from the Tunisian calf strain B137 and the goat strain cap455 isolated in South Africa respectively. The human MA31 RVA strain was able to induce bloody diarrhea at 2 days post infection (dpi) in the alpine goat kid. RVA virus shedding started by 2 dpi (Ct value of 28) and continued until 5 dpi (Ct value of 25) with a concomitant elevation in the body temperature. Conclusions: Our study while limited to one animal, is the first study proving experimentally that a human P[14] genotype causes diarrhea and virus shedding in the goat. This result reinforce the potential role of inter- species transmission in generating novel and rare rotavirus strains such G8P[14] which infect humans.

Keywords: interspecies transmission, rotavirus, goat, human

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