Search results for: feature points

Authors: Natalia Zhabo, Sergey Nikitin, Marina Avdonina, Mariya Nikitina

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The analysis of the activities of one of the events of the international educational and entertainment project Velonotte is provided: an evening bicycle tour with children around Florence. The aim of the project is to develop methods and techniques for increasing the sensitivity of the cycling participants and listeners of the radio broadcasts to the treasures of the national heritage, in this case, to the historical layers of the city and the ecology of the Renaissance epoch. The block of educational tasks is considered, and the issues of preserving the identity of the city are discussed. Methods. The Florentine event was prepared during more than a year. First of all the creative team selected such events of the history of the city which seem to be important for revealing the specifics of the city, its spirit - from antiquity to our days – including the forums of Internet with broad public opinion. Then a route (seven kilometers) was developed, which was proposed to the authorities and organizations of the city. The selection of speakers was conducted according to several criteria: they should be authors of books, famous scientists, connoisseurs in a certain sphere (toponymy, history of urban gardens, art history), capable and willing to talk with participants directly at the points of stops, in order to make a dialogue and so that performances could be organized with their participation. The music was chosen for each part of the itinerary to prepare the audience emotionally. Cards for coloring with images of the main content of each stop were created for children. A site was done to inform the participants and to keep photos, videos and the audio files with speakers’ speech afterward. Results: Held in April 2017, the event was dedicated to the 640th Anniversary of the Filippo Brunelleschi, Florentine architect, and to the 190th anniversary of the publication of Florence guide by Stendhal. It was supported by City of Florence and Florence Bike Festival. Florence was explored to transfer traditional elements of culture, sometimes unfairly forgotten from ancient times to Brunelleschi and Michelangelo and Tschaikovsky and David Bowie with lectures by professors of Universities. Memorable art boards were installed in public spaces. Elements of the cultural code are deeply internalized in the minds of the townspeople, the perception of the city in everyday life and human communication is comparable to such fundamental concepts of the self-awareness of the townspeople as mental comfort and the level of happiness. The format of a fun and playful walk with the ICT support gives new opportunities for enriching the city's cultural code of each citizen with new components, associations, connotations.

Keywords: edutainment, cultural code, cycling, sensitization Florence

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Authors: Mark Opmeer

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The fruitful relationship between cultural heritage and digital technology is evident. Due to the development of user-friendly software, an increasing amount of heritage scholars use ict for their research activities. As a result, the implementation of information technology for heritage planning has become a research objective in itself. During the last decades, we have witnessed a growing debate and literature about the importance of computer technologies for the field of cultural heritage and ecotourism. Indeed, implementing digital technology in support of these domains can be very fruitful for one’s research practice. However, due to the rapid development of new software scholars may find it challenging to use these innovations in an appropriate way. As such, this contribution seeks to explore the interplay between geospatial technologies (geo-ict), civic engagement and cultural heritage and tourism. In this article, we discuss our findings on the use of geo-ict in support of civic participation, cultural heritage and sustainable tourism development in the southern Italian district of Brindisi. In the city of Latiano, three workshops were organized that involved local members of the community to distinguish and discuss interesting points of interests (POI’s) which represent the cultural significance and identity of the area. During the first workshop, a so called mappa della comunità was created on a touch table with collaborative mapping software, that allowed the participators to highlight potential destinations for tourist purposes. Furthermore, two heritage-based itineraries along a selection of identified POI’s was created to make the region attractive for recreants and tourists. These heritage-based itineraries reflect the communities’ ideas about the cultural identity of the region. Both trails were subsequently implemented in a dedicated mobile application (app) and was evaluated using a mixed-method approach with the members of the community during the second workshop. In the final workshop, the findings of the collaboration, the heritage trails and the app was evaluated with all participants. Based on our conclusions, we argue that geospatial technologies have a significant potential for involving local communities in heritage planning and tourism development. The participants of the workshops found it increasingly engaging to share their ideas and knowledge using the digital map of the touch table. Secondly, the use of a mobile application as instrument to test the heritage-based itineraries in the field was broadly considered as fun and beneficial for enhancing community awareness and participation in local heritage. The app furthermore stimulated the communities’ awareness of the added value of geospatial technologies for sustainable tourism development in the area. We conclude this article with a number of recommendations in order to provide a best practice for organizing heritage workshops with similar objectives.

Keywords: civic engagement, geospatial technologies, tourism development, cultural heritage

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Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

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Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

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Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

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Authors: Shilpi Bora, Abhirup Chatterjee, Debkumar Chakrabarti

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Organizations of all the sectors around the world are increasingly revisiting their workplace strategies with due concern for women working therein. Limited office space and rigid work arrangements contribute to lesser job satisfaction and greater work impoundments for any organization. Flexible workspace strategies are indispensable to accommodate the progressive rise of modular workstations and involvement of women. Today’s generation of employees deserves malleable office environments with employee-friendly job conditions and strategies. The workplace nowadays stands on rapid organizational changes in progressive and flexible work culture. Occupational well-being practices need to keep pace with the rapid changes in office-based work. Working at the office (workspace) with awkward postures or for long periods can cause pain, discomfort, and injury. The world is stirring towards the era of globalization and progress. The 4000 women police personnel constitute less than one per cent of the total police strength of India. Lots of innovative fields are growing fast, and it is important that we should accommodate women in those arenas. The timeworn trends should be set apart to set out for fresh opportunities and possibilities of development and success through more involvement of women in the workplace. The notion of women policing is gaining position throughout the world, and various countries are putting solemn efforts to mainstream women in policing. As the role of women policing in a society is budding, and thus it is also notable that the accessibility of women at general police stations should be considered. Accordingly, the impact of workspace at police station on the employee productivity has been widely deliberated as a crucial contributor to employee satisfaction leading to better functional motivation. Thus the present research aimed to look into the office workstation design of police station with reference to womanhood specific issues to uplift occupational wellbeing of the policewomen. Personal interview and individual responses collected through administering to a subjective assessment questionnaire on thirty women police as well as to have their views on these issues by purposive non-probability sampling of women police personnel of different ranks posted in Guwahati, Assam, India. Scrutiny of the collected data revealed that office design has a substantial impact on the policewomen job satisfaction in the police station. In this study, the workspace was designed in such a way that the set of factors would impact on the individual to ensure increased productivity. Office design such as furniture, noise, temperature, lighting and spatial arrangement were considered. The primary feature which affected the productivity of policewomen was the furniture used in the workspace, which was found to disturb the everyday and overall productivity of policewomen. Therefore, it was recommended to have proper and adequate ergonomics design intervention to improve the office design for better performance. This type of study is today’s need-of-the-hour to empower women and facilitate their inner talent to come up in service of the nation. The office workspace design also finds critical importance at several other occupations also – where office workstation needs further improvement.

Keywords: office workspace design, policewomen, womanhood concerns at workspace, occupational wellbeing

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Authors: Sukran Karatas

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Authentic energy network interrelations between the Creator and the creations as well as from creations to creations are the most important points for the worlds of physics and metaphysic to unite together and work in harmony, both within human beings, on the other hand, have the ability to choose their own life style voluntarily. However, it includes the automated involuntary spirit, soul and body working systems together with the voluntary actions, which involve personal, cultural and universal, rational or irrational variable values. Therefore, it is necessary for human beings to know the methods of existing authentic energy network connections to be able to communicate correlate and accommodate the physical and metaphysical entities as a proper functioning unity; this is essential for complete human psychological, biological and social well-being. Authentic knowledge is necessary for human beings to verify the position of self within self and with others to regulate conscious and voluntary actions accordingly in order to prevent oppressions and frictions within self and between self and others. Unfortunately, the absence of genuine individual and universal basic knowledge about how to establish an authentic energy network connection within self, with the deity and the environment is the most problematic issue even in the twenty-first century. The second most problematic issue is how to maintain freedom, equality and justice among human beings during these strictly interwoven network connections, which naturally involve physical, metaphysical and behavioral actions of the self and the others. The third and probably the most complicated problem is the scientific identification and the authentication of the deity. This not only provides the whole power and control over the choosers to set their life orders but also to establish perfect physical and metaphysical links as fully coordinated functional energy network. This thus indicates that choosing an authentic deity is the key-point that influences automated, emotional, and behavioral actions altogether, which shapes human perception, personal actions, and life orders. Therefore, we will be considering the existing ‘four types of energy wave end boundary behaviors’, comprising, free end, fixed end boundary behaviors, as well as boundary behaviors from denser medium to less dense medium and from less dense medium to denser medium. Consequently, this article aims to demonstrate that the authentication and the choice of deity has an important effect on individual psychological, biological and social health. It is hoped that it will encourage new researches in the field of authentic energy network connections to establish the best position and the most correct interrelation connections with self and others without violating the authorized orders and the borders of one another to live happier and healthier lives together. In addition, the book ‘Deity and Freedom, Equality, Justice in History, Philosophy, Science’ has more detailed information for those interested in this subject.

Keywords: deity, energy network, power, freedom, equality, justice, happiness, sadness, hope, fear, psychology, biology, sociology

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Authors: Mariia Karizhenskaia, Tanvi Nandani, Ali Tafazoli Moghadam

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

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

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Authors: Anne M. Denton, Rahul Gomes, David W. Franzen

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High-resolution elevation data are becoming increasingly available, but typical approaches for computing topographic features, like slope and curvature, still assume small sliding windows, for example, of size 3x3. That means that the digital elevation model (DEM) has to be resampled to the scale of the landform features that are of interest. Any higher resolution is lost in this resampling. When the topographic features are computed through regression that is performed at the resolution of the original data, the accuracy can be much higher, and the reported result can be adjusted to the length scale that is relevant locally. Slope and variance are calculated for overlapping windows, meaning that one regression result is computed per raster point. The number of window centers per area is the same for the output as for the original DEM. Slope and variance are computed by performing regression on the points in the surrounding window. Such an approach is computationally feasible because of the additive nature of regression parameters and variance. Any doubling of window size in each direction only takes a single pass over the data, corresponding to a logarithmic scaling of the resulting algorithm as a function of the window size. Slope and variance are stored for each aggregation step, allowing the reported slope to be selected to minimize variance. The approach thereby adjusts the effective window size to the landform features that are characteristic to the area within the DEM. Starting with a window size of 2x2, each iteration aggregates 2x2 non-overlapping windows from the previous iteration. Regression results are stored for each iteration, and the slope at minimal variance is reported in the final result. As such, the reported slope is adjusted to the length scale that is characteristic of the landform locally. The length scale itself and the variance at that length scale are also visualized to aid in interpreting the results for slope. The relevant length scale is taken to be half of the window size of the window over which the minimum variance was achieved. The resulting process was evaluated for 1-meter DEM data and for artificial data that was constructed to have defined length scales and added noise. A comparison with ESRI ArcMap was performed and showed the potential of the proposed algorithm. The resolution of the resulting output is much higher and the slope and aspect much less affected by noise. Additionally, the algorithm adjusts to the scale of interest within the region of the image. These benefits are gained without additional computational cost in comparison with resampling the DEM and computing the slope over 3x3 images in ESRI ArcMap for each resolution. In summary, the proposed approach extracts slope and aspect of DEMs at the lengths scales that are characteristic locally. The result is of higher resolution and less affected by noise than existing techniques.

Keywords: high resolution digital elevation models, multi-scale analysis, slope calculation, window-based regression

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Francesca Fermi, Paola Astegiano, Angelo Martino, Stephanie Heitel, Michael Krail

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In order to achieve the targeted emission reductions for the decarbonisation of the European economy by 2050, fundamental contributions are required from both energy and transport sectors. The objective of this paper is to analyse the impacts of a largescale diffusion of e-vehicles, either battery-based or fuel cells, together with the implementation of transport policies aiming at decreasing the use of motorised private modes in order to achieve greenhouse gas emission reduction goals, in the context of a future high share of renewable energy. The analysis of the impacts and challenges of future scenarios on transport sector is performed with the ASTRA (ASsessment of TRAnsport Strategies) model. ASTRA is a strategic system-dynamic model at European scale (EU28 countries, Switzerland and Norway), consisting of different sub-modules related to specific aspects: the transport system (e.g. passenger trips, tonnes moved), the vehicle fleet (composition and evolution of technologies), the demographic system, the economic system, the environmental system (energy consumption, emissions). A key feature of ASTRA is that the modules are linked together: changes in one system are transmitted to other systems and can feed-back to the original source of variation. Thanks to its multidimensional structure, ASTRA is capable to simulate a wide range of impacts stemming from the application of transport policy measures: the model addresses direct impacts as well as second-level and third-level impacts. The simulation of the different scenarios is performed within the REFLEX project, where the ASTRA model is employed in combination with several energy models in a comprehensive Modelling System. From the transport sector perspective, some of the impacts are driven by the trend of electricity price estimated from the energy modelling system. Nevertheless, the major drivers to a low carbon transport sector are policies related to increased fuel efficiency of conventional drivetrain technologies, improvement of demand management (e.g. increase of public transport and car sharing services/usage) and diffusion of environmentally friendly vehicles (e.g. electric vehicles). The final modelling results of the REFLEX project will be available from October 2018. The analysis of the impacts and challenges of future scenarios is performed in terms of transport, environmental and social indicators. The diffusion of e-vehicles produces a consistent reduction of future greenhouse gas emissions, although the decarbonisation target can be achieved only with the contribution of complementary transport policies on demand management and supporting the deployment of low-emission alternative energy for non-road transport modes. The paper explores the implications through time of transport policy measures on mobility and environment, underlying to what extent they can contribute to a decarbonisation of the transport sector. Acknowledgements: The results refer to the REFLEX project which has received grants from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 691685.

Keywords: decarbonisation, greenhouse gas emissions, e-mobility, transport policies, energy

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Authors: Susanna Graziano, Lydia Krstic Ward

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The purpose of this presentation is to demonstrate the steps of using multimedia and collaborative platforms in project-based learning. The presentation will demonstrate the stages of the learning project with various components of independent and collaborative learning, where students research the topic, share information, prepare a survey, use social media (Facebook, Instagram, WhasApp) and collaborative platforms (wikispaces.com and Google docs) to collect, analyze and process data, then produce reports and logos to be displayed as a final product. At the beginning of the presentation participants will answer a questionnaire about project based learning and share their experience on using social media, real–world project work and collaborative learning. Using a PPP, the presentation will walk participants through the steps of a completed project where tertiary education students are involved in putting together a multimedia campaign for safe driving in Kuwait. The research component of the project entails taking a holistic view on the problem of the high death rate in traffic accidents. The final goal of the project is to lead students to raise public awareness about the importance of safe driving. The project steps involve using the social media and collaborative platforms for collecting data and sharing the required materials to be used in the final product – a display of written reports, slogans and videos, as well as oral presentations. The same structure can be used to organize a multimedia campaign focusing on other issues, whilst scaffolding on students’ ability to brainstorm, retrieve information, organize it and engage in collaborative/ cooperative learning whilst being immersed in content-based learning as well as in authentic tasks. More specifically, the project we carried out at Box Hill College was a real-world one and involved a multimedia Campaign for Safe Driving since reckless driving is one of the major problems in the country. The idea for the whole project started by a presentation given by a board member of the Kuwaiti Society for Traffic Safety who was invited to college and spoke about: • Driving laws in the country, • What causes car accidents, • Driving safety tips. The principal goal of this project was to let students consider problems of traffic in Kuwait from different points of view. They also had to address the number and causes of accidents, evaluate the effectiveness of the local traffic law in order to send a warning about the importance of safe driving and, finally, suggest ways of its improvement. Benefits included: • Engagement, • Autonomy, • Motivation, • Content knowledge, • Language mastery, • Enhanced critical thinking, • Increased metacognitive awareness, • Improved social skills, • Authentic experience.

Keywords: social media, online learning platforms, collaborative platforms, project based learning

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

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

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

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Authors: Ali Mohammed Ali Lmbash

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The global refugee crisis points to the vital need for sustainable and resistant solutions to different kinds of problems for displaced persons all over the world. Among the myriads of sustainable concerns, however, there are diverse considerations including energy consumption, waste management, water access, and resiliency of structures. Our research aims to develop distinct ideas for sustainable architecture given the exigent problems in disaster-threatened areas starting with the Hatay Refugee camp in Turkey where the majority of the camp dwellers are Syrian refugees. Commencing community-based participatory research which focuses on the socio-environmental issues of displaced populations, this study will apply two approaches with a specific focus on the Hatay region. The initial experiment uses Richter's predictive model and simulations to forecast earthquake outcomes in refugee campers. The result could be useful in implementing architectural design tactics that enhance structural reliability and ensure the security and safety of shelters through earthquakes. In the second experiment a model is generated which helps us in predicting the quality of the existing water sources and since we understand how greatly water is vital for the well-being of humans, we do it. This research aims to enable camp administrators to employ forward-looking practices while managing water resources and thus minimizing health risks as well as building resilience of the refugees in the Hatay area. On the other side, this research assesses other sustainability problems of Hatay Refugee Camp as well. As energy consumption becomes the major issue, housing developers are required to consider energy-efficient designs as well as feasible integration of renewable energy technologies to minimize the environmental impact and improve the long-term sustainability of housing projects. Waste management is given special attention in this case by imposing recycling initiatives and waste reduction measures to reduce the pace of environmental degradation in the camp's land area. As well, study gives an insight into the social and economic reality of the camp, investigating the contribution of initiatives such as urban agriculture or vocational training to the enhancement of livelihood and community empowerment. In a similar fashion, this study combines the latest research with practical experience in order to contribute to the continuing discussion on sustainable architecture during disaster relief, providing recommendations and info that can be adapted on every scale worldwide. Through collaborative efforts and a dedicated sustainability approach, we can jointly get to the root of the cause and work towards a far more robust and equitable society.

Keywords: smart architecture, Hatay Camp, sustainability, machine learning.

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Authors: Anna V. Zaporozhchenko, Dmytro Kutnyakhov, Katherina Medjanik, Christian Tusche, Hans-Joachim Elmers, Olena Fedchenko, Sergey Chernov, Martin Ellguth, Sergej A. Nepijko, Gerd Schoenhense

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Graphene reveals a unique electronic structure that predetermines many intriguing properties such as massless charge carriers, optical transparency and high velocity of fermions at the Fermi level, opening a wide horizon of future applications. Hence, a detailed investigation of the electronic structure of graphene is crucial. The method of choice is angular resolved photoelectron spectroscopy ARPES. Here we present experiments using time-of-flight (ToF) momentum microscopy, being an alternative way of ARPES using full-field imaging of the whole Brillouin zone (BZ) and simultaneous acquisition of up to several 100 energy slices. Unlike conventional ARPES, k-microscopy is not limited in simultaneous k-space access. We have recorded the whole first BZ of graphene on Ir(111) including all six Dirac cones. As excitation source we used synchrotron radiation from BESSY II (Berlin) at the U125-2 NIM, providing linearly polarized (both polarizations p- and s-) VUV radiation. The instrument uses a delay-line detector for single-particle detection up the 5 Mcps range and parallel energy detection via ToF recording. In this way, we gather a 3D data stack I(E,kx,ky) of the full valence electronic structure in approx. 20 mins. Band dispersion stacks were measured in the energy range of 14 eV up to 23 eV with steps of 1 eV. The linearly-dispersing graphene bands for all six K and K’ points were simultaneously recorded. We find clear features of hybridization with the substrate, in particular in the linear dichroism in the angular distribution (LDAD). Recording of the whole Brillouin zone of graphene/Ir(111) revealed new features. First, the intensity differences (i.e. the LDAD) are very sensitive to the interaction of graphene bands with substrate bands. Second, the dark corridors are investigated in detail for both, p- and s- polarized radiation. They appear as local distortions of photoelectron current distribution and are induced by quantum mechanical interference of graphene sublattices. The dark corridors are located in different areas of the 6 Dirac cones and show chirality behaviour with a mirror plane along vertical axis. Moreover, two out of six show an oval shape while the rest are more circular. It clearly indicates orientation dependence with respect to E vector of incident light. Third, a pattern of faint but very sharp lines is visible at energies around 22eV that strongly remind on Kikuchi lines in diffraction. In conclusion, the simultaneous study of all six Dirac cones is crucial for a complete understanding of dichroism phenomena and the dark corridor.

Keywords: band structure, graphene, momentum microscopy, LDAD

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Authors: Anand R. Nair, Markus Trenker

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

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

Procedia PDF Downloads 235

Authors: Tshephang Bright Molale

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Much is written on the importance of participatory communication and its role in uplifting indigent communities. As the closest government sphere to communities, local government is charged with directly improving the lives of the poor and is required by legislation to conduct Integrated Development Planning (IDP). This requires a municipality to utilise participatory communication aspects including dialogue, empowerment, and planning. These are most important pillars of community development. However, many studies have warned that elements such as modernisation, dependency and bureaucracy need to be observed with caution since they have the potential to impede and limit the extent of participatory communication in community development. These concepts serve as the basic points of departure and theoretical background underpinning this study, which is tasked with exploring the extent of participatory communication in the IDP context of Jouberton Township in the Matlosana Local Municipality, South Africa. In her public address on challenges facing South Africa’s local municipalities in January 2014, former premier, Thandi Modise, emphasised the need for communities to attend municipal IDP meetings, approve earmarked IDP projects, and learn about municipal budget spending. It is evident from theory and higher echelon of government that participatory communication is seen as cardinal to the existence of municipal government. From this background, this study was carried out under the assumption that the practice of participatory communication in contemporary local government only exists on paper; while in reality the public does not enjoy active participation in municipal IDP consultative frameworks. This is despite much discourse being available in government and in academia around the importance of participatory communication in community development. The study espoused a qualitative research approach to gather data and purposive sampling was used to select respondents linked to two IDP projects in Jouberton Township from the 2012/13 financial year. Its purpose was to explore perceptions among municipal representatives and community members in Jouberton Township on the extent of participatory communication in the IDP context. The empirical part of the study comprised of focus group, unstructured interviews, and participant observation. The study revealed that Jouberton communities are passive participators in municipal IDP consultative frameworks where they participate by just being informed about what is going to happen or has already happened and feedback is minimal. This is opposed to a desired form of empowered participation which is recommended by scholars in development communication where stakeholders granted space to participate in joint analysis and joint decision-making about what should be achieved and how. It has been discovered that there is a lack of active participation in community development in the IDP context of Matlosana Municipality and the study makes recommendations on how transformative participatory communication can be applied to improve current norms and standards in local government.

Keywords: development communication, government communication, integrated development plan, participatory communication

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Authors: Kaitlyn O'Mara, Michele Burford

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Estuaries and coastal bays can receive large quantities of sediment from surrounding catchments during flooding or high flow periods. Large river systems that feed freshwater into estuaries can flow through several catchments of varying geology. Human modification of catchments for agriculture, industry and urban use can contaminate soils with excess nutrients, trace metals and other pollutants. Land clearing, especially clearing of riparian vegetation, can accelerate erosion, mobilising, transporting and depositing soil particles into rivers, estuaries and coastal bays. In this study, a flood simulation experiment was used to study the flux of nutrients between soil particles and water during this erosion, transport and deposition process. Granite, sedimentary and basalt surface soils (as well as sub-soils of granite and sedimentary) were collected from eroding areas surrounding the Brisbane River, Australia. The <63 µm size fraction of each soil type was tumbled in freshwater for 3 days, to simulation flood erosion and transport, followed by stationary exposure to seawater for 4 weeks, to simulate deposition into estuaries. Filtered water samples were taken at multiple time points throughout the experiment and analysed for water nutrient concentrations. The highest rates of nutrient release occurred during the first hour of exposure to freshwater and seawater, indicating a chemical reaction with seawater that may act to release some nutrient particles that remain bound to the soil during turbulent freshwater transport. Although released at a slower rate than the first hour, all of the surface soil types showed continual ammonia, nitrite and nitrate release over the 4-week seawater exposure, suggesting that these soils may provide ongoing supply of these nutrients to estuarine waters after deposition. Basalt surface soil released the highest concentrations of phosphates and dissolved organic phosphorus. Basalt soils are found in much of the agricultural land surrounding the Brisbane River and contributed largely to the 2011 Brisbane River flood plume deposit in Moreton Bay, suggesting these soils may be a source of phosphate enrichment in the bay. The results of this study suggest that erosion of catchment soils during storm and flood events may be a source of nutrient supply in receiving waterways, both freshwater and marine, and that the amount of nutrient release following these events may be affected by the type of soil deposited. For example, flooding in different catchments of a river system over time may result in different algal and food web responses in receiving estuaries.

Keywords: flood, nitrogen, nutrient, phosphorus, sediment, soil

Procedia PDF Downloads 181

Authors: Mehak Burza

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As we pause to observe the Holocaust Remembrance Day each year on 27 January, it becomes important to consider how the Holocaust is witnessed, and its education is perceived across the globe. The dissemination of knowledge of the Holocaust becomes more pertinent in the countries that were not directly affected by it. The Holocaust education is not widespread in Asian countries and is thus not mandatory as an academic discipline for school and university students. One such Asian country that often considers Holocaust as an isolated event is India. Though the struggle for freedom began with the 1857 mutiny (the first war of Indian independence) but the freedom revolts gained momentum specifically during the years 1944-1947, when India was steeped in a battery of rebellions. However, freedom for the Indian subcontinent from the domination of British Raj came at the cost of partition of India that resulted in widespread bloodshed and immigration. For India, it is this backdrop of her freedom struggle that always outweighs the incidents of the Second World War, including the catastrophic event of the Holocaust. As a result, the knowledge about the Holocaust is available through secondary sources such as Holocaust documentaries and movies. Besides Anne Frank’s diary, the knowledge about the Holocaust is disseminated through the course readings in the universities. The most common literary acquaintances with the Jewish faith for university students are when they come across the Jewish characters in their course readings. The Prioress’s Tale in Geoffrey Chaucer’s Canterbury Tales, the character of Shylock in William Shakespeare’s The Merchant of Venice, and the Jewish protagonist, Barabas, in Christopher Marlow’s Jew of Malta. Apart from this, the school textbooks mention a detailed chapter on Holocaust and Hitler, which is an encouraging turn. However, there still exists a yawning gap between dissemination and sensitization of Holocaust education owing to different geographical locales. My paper presentation aims to trace the intersectional elements between India and the Holocaust that can serve as the required pivotal stand-board to foster sensitization towards Holocaust education in the Indian subcontinent. For instance, Maharaja Jam SahebDigvijaysinhjiRanjitsinhji, the ruler of Nawanagar, a princely state in British India, helped save thousand Polish Jewish children in 1945 at the time when India herself was steeped in its struggle for freedom. Famously known as the ‘Indian Oskar Schindler’ Polish government has named a street after him in Krakow, Poland. Another example that deserves mention is the spy princess, Noor Inayat Khan, a descendent of Tipu Sultan, who became the most celebrated British spyand fought against the Nazis. Additionally, by offering refuge to Jews, India has proved to be a distant haven for them. Researching further the domain of Jewish refugees in India will not only illuminate a dull/gray zone of investigation but also enable the educators to provide appropriate entry points for introducing the subject of Shoah/Holocaust in India, a subject which unfortunately hitherto is either seldom discussed or is equated with the Partition of India.

Keywords: awareness, dissemination, holocaust, India

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Authors: Petnamnueng Dettipponpong, Shuen E. Chen

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Heat stress is known to have negative effects on reproductive functions, such as follicular development and ovulation. This study aimed to investigate the specific effects of heat stress on steroid hormone secretion of ovarian follicle cells, particularly in relation to the expression of Apolipoprotein B (ApoB) and microsomal triglyceride transfer protein (MTP). The aim of the study was to understand the impact of heat stress on steroid hormone secretion in ovarian follicle cells and to explore the role of ApoB and MTP in this process. Primary granulosa and theca cells were collected from follicles and cultured under heat stress conditions (42 °C) for various time periods. Controls were maintained under normal conditions (37.5 °C ). The culture medium was collected at different time points to measure levels of progesterone and estradiol using ELISA kits. ApoB and MTP expression levels were analyzed using homemade antibodies and western blot. Data were assessed by a one-way ANOVA comparison test with Duncan’s new multiple-range test. Results were expressed as mean±S.E. Difference was considered significant at P<0.05. The results showed that heat stress significantly increased progesterone secretion in granulosa cells, with the peak observed after 13 hours of recovery under thermoneutral conditions. Estradiol secretion by theca cells was not affected. Heat stress also had a significant negative effect on granulosa cell viability. Additionally, the expression of ApoB and MTP was found to be differentially regulated by heat stress. ApoB expression in theca cells was transiently promoted, while ApoB expression in granulosa cells was consistently suppressed. MTP expression increased after 5 hours of recovery in both cell types. These findings suggest a mechanism by which chicken follicle cells export cellular lipids as very low-density lipoprotein (VLDL) in response to thermal stress. These contribute to our understanding of the role of ApoB and MTP steroidogenesis and lipid metabolism under heat stress conditions. The study involved the collection of primary granulosa and theca cells, culture under different temperature conditions, and analysis of the culture medium for hormone levels using ELISA kits. ApoB and MTP expression levels were assessed using homemade antibodies and western blot. This study aimed to address the effects of heat stress on steroid hormone secretion in ovarian follicle cells, as well as the role of ApoB and MTP in this process. The study demonstrates that heat stress stimulates steroidogenesis in granulosa cells, affecting progesterone secretion. ApoB and MTP expression were found to be differentially regulated by heat stress, indicating a potential mechanism for the export of cellular lipids in response to thermal stress.

Keywords: heat stress, granulosa cells, theca cells, steroidogenesis, chicken, apolipoprotein B, microsomal triglyceride transfer protein

Procedia PDF Downloads 66

Authors: Teresita Lopez Joy, Jose A. Acevedo Suarez, Martha I. Gomez Acosta, Ana Julia Acevedo Urquiaga

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Current trends in business competitiveness indicate the need to manage businesses as supply chains and not in isolation. The use of strategies aimed at maximum satisfaction of customers in a network and based on inter-company cooperation; contribute to obtaining successful joint results. In the Cuban economic context, the development of productive linkages to achieve integrated management of supply chains is considering a key aspect. In order to achieve this jump, it is necessary to develop acting capabilities in the entities that make up the chains through a systematic procedure that allows arriving at a management model in consonance with the environment. The objective of the research focuses on: designing a model and procedure for the development of integrated management of supply chains in economic entities. The results obtained are: the Model and the Procedure for the Development of the Supply Chains Integrated Management (MP-SCIM). The Model is based on the development of logistics in the network actors, the joint work between companies, collaborative planning and the monitoring of a main indicator according to the end customers. The application Procedure starts from the well-founded need for development in a supply chain and focuses on training entrepreneurs as doers. The characterization and diagnosis is done to later define the design of the network and the relationships between the companies. It takes into account the feedback as a method of updating the conditions and way to focus the objectives according to the final customers. The MP-SCIM is the result of systematic work with a supply chain approach in companies that have consolidated as coordinators of their network. The cases of the edible oil chain and explosives for construction sector reflect results of more remarkable advances since they have applied this approach for more than 5 years and maintain it as a general strategy of successful development. The edible oil trading company experienced a jump in sales. In 2006, the company started the analysis in order to define the supply chain, apply diagnosis techniques, define problems and implement solutions. The involvement of the management and the progressive formation of performance capacities in the personnel allowed the application of tools according to the context. The company that coordinates the explosives chain for construction sector shows adequate training with independence and opportunity in the face of different situations and variations of their business environment. The appropriation of tools and techniques for the analysis and implementation of proposals is a characteristic feature of this case. The coordinating entity applies integrated supply chain management to its decisions based on the timely training of the necessary action capabilities for each situation. Other cases of study and application that validate these tools are also detailed in this paper, and they highlight the results of generalization in the quantitative and qualitative improvement according to the final clients. These cases are: teaching literature in universities, agricultural products of local scope and medicine supply chains.

Keywords: integrated management, logistic system, supply chain management, tactical-operative planning

Procedia PDF Downloads 151

Authors: Shiao-Wei Chu

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In order to enhance the ability of their graduates to compete in an increasingly globalized economy, the majority of universities in Taiwan require students to pass Freshman English in order to earn a bachelor's degree. However, many college students show low motivation in English class for several important reasons, including exam-oriented lessons, unengaging classroom activities, a lack of opportunities to use English in authentic contexts, and low levels of confidence in using English. Students’ lack of motivation in English classes is evidenced when students doze off, work on assignments from other classes, or use their phones to chat with others, play video games or watch online shows. Cooperative learning aims to address these problems by encouraging language learners to use the target language to share individual experiences, cooperatively complete tasks, and to build a supportive classroom learning community whereby students take responsibility for one another’s learning. This study includes approximately 50 student participants in a low-proficiency Freshman English class. Each week, participants will work together in groups of between 3 and 4 students to complete various in-class interactive tasks. The instructor will employ a reward system that incentivizes students to be responsible for their own as well as their group mates’ learning. The rewards will be based on points that team members earn through formal assessment scores as well as assessment of their participation in weekly in-class discussions. The instructor will record each team’s week-by-week improvement. Once a team meets or exceeds its own earlier performance, the team’s members will each receive a reward from the instructor. This cooperative learning approach aims to stimulate EFL freshmen’s learning motivation by creating a supportive, low-pressure learning environment that is meant to build learners’ self-confidence. Students will practice all four language skills; however, the present study focuses primarily on the learners’ reading comprehension. Data sources include in-class discussion notes, instructor field notes, one-on-one interviews, students’ midterm and final written reflections, and reading scores. Triangulation is used to determine themes and concerns, and an instructor-colleague analyzes the qualitative data to build interrater reliability. Findings are presented through the researcher’s detailed description. The instructor-researcher has developed this approach in the classroom over several terms, and its apparent success at motivating students inspires this research. The aims of this study are twofold: first, to examine the possible benefits of this cooperative approach in terms of students’ learning outcomes; and second, to help other educators to adapt a more cooperative approach to their classrooms.

Keywords: freshman English, cooperative language learning, EFL learners, learning motivation, zone of proximal development

Procedia PDF Downloads 141

Authors: Palak Sadhwani, Susie Pryor

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This paper investigates interprofessional collaboration (IPC) in the context of entrepreneurship education. Collaboration has been found to enhance problem solving, leverage expertise, improve resource allocation, and create organizational efficiencies. However, research suggests that successful collaboration is hampered by individual and organizational characteristics. IPC occurs when two or more professionals work together to solve a problem or achieve a common objective. The necessity for this form of collaboration is particularly prevalent in cross-disciplinary fields. In this study, we utilize social exchange theory (SET) to examine IPC in the context of an entrepreneurship living learning community (LLC) at a large university in the Western United States. Specifically, we explore these research questions: How are rules or norms established that govern the collaboration process? How are resources valued and distributed? How are relationships developed and managed among and between parties? LLCs are defined as groups of students who live together in on-campus housing and share similar academic or special interests. In 2007, the Association of American Colleges and Universities named living communities a high impact practice (HIP) because of their capacity to enhance and give coherence to undergraduate education. The entrepreneurship LLC in this study was designed to offer first year college students the opportunity to live and learn with like-minded students from diverse backgrounds. While the university offers other LLC environments, the target residents for this LLC are less easily identified and are less apparently homogenous than residents of other LLCs on campus (e.g., Black Scholars, LatinX, Women in Science and Education), creating unique challenges. The LLC is a collaboration between the university’s College of Business & Public Administration and the Department of Housing and Residential Education (DHRE). Both parties are contributing staff, technology, living and learning spaces, and other student resources. This paper reports the results an ethnographic case study which chronicles the start-up challenges associated with the co-creation of the LLC. SET provides a general framework for examining how resources are valued and exchanged. In this study, SET offers insights into the processes through which parties negotiate tensions resulting from approaching this shared project from very different perspectives and cultures in a novel project environment. These tensions occur due to a variety of factors, including team formation and management, allocation of resources, and differing output expectations. The results are useful to both scholars and practitioners of entrepreneurship education and organizational management. They suggest probably points of conflict and potential paths towards reconciliation.

Keywords: case study, ethnography, interprofessional collaboration, social exchange theory

Procedia PDF Downloads 136

Authors: Akmez Nabeerasool, Michaelis Massaros, Nigel Brown, David Sanderson, David Parocki, Charlotte Thompson, Mike Lodge, Mikael Khan

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The provision of clean and safe drinking water is of paramount importance and is a basic human need. Water scarcity coupled with tightening of regulations and the inability of current treatment technologies to deal with emerging contaminants and Pharmaceuticals and personal care products means that alternative treatment technologies that are viable and cost effective are required in order to meet demand and regulations for clean water supplies. Logistically, the application of water treatment in rural areas presents unique challenges due to the decentralisation of abstraction points arising from low population density and the resultant lack of infrastructure as well as the need to treat water at the site of use. This makes it costly to centralise treatment facilities and hence provide potable water direct to the consumer. Furthermore, across the UK there are segments of the population that rely on a private water supply which means that the owner or user(s) of these supplies, which can serve one household to hundreds, are responsible for the maintenance. The treatment of these private water supply falls on the private owners, and it is imperative that a chemical free technological solution that can operate unattended and does not produce any waste is employed. Arvia’s patented advanced oxidation technology combines the advantages of adsorption and electrochemical regeneration within a single unit; the Organics Destruction Cell (ODC). The ODC uniquely uses a combination of adsorption and electrochemical regeneration to destroy organics. Key to this innovative process is an alternative approach to adsorption. The conventional approach is to use high capacity adsorbents (e.g. activated carbons with high porosities and surface areas) that are excellent adsorbents, but require complex and costly regeneration. Arvia’s technology uses a patent protected adsorbent, Nyex™, which is a non-porous, highly conductive, graphite based adsorbent material that enables it to act as both the adsorbent and as a 3D electrode. Adsorbed organics are oxidised and the surface of the Nyex™ is regenerated in-situ for further adsorption without interruption or replacement. Treated water flows from the bottom of the cell where it can either be re-used or safely discharged. Arvia™ Technology Ltd. has trialled the application of its tertiary water treatment technology in treating reservoir water abstracted near Glasgow, Scotland, with promising results. Several other pilot plants have also been successfully deployed at various locations in the UK showing the suitability and effectiveness of the technology in removing recalcitrant organics (including pharmaceuticals, steroids and hormones), COD and colour.

Keywords: Arvia™ process, adsorption, water treatment, electrochemical oxidation

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Authors: E. Fabre, C. Vale, E. Pereira, C. M. Silva

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Introduction: Mercury is one of the most troublesome toxic metals responsible for the contamination of the aquatic systems due to its accumulation and bioamplification along the food chain. The 2030 agenda for sustainable development of United Nations promotes the improving of water quality by reducing water pollution and foments an enhance in wastewater treatment, encouraging their recycling and safe water reuse globally. Sorption processes are widely used in wastewater treatments due to their many advantages such as high efficiency and low operational costs. In these processes the target contaminant is removed from the solution by a solid sorbent. The more selective and low cost is the biosorbent the more attractive becomes the process. Agricultural wastes are especially attractive approaches for sorption. They are largely available, have no commercial value and require little or no processing. In this work, banana peels were tested for mercury removal from low concentrated solutions. In order to investigate the applicability of this solid, six water matrices were used increasing the complexity from natural waters to a real wastewater. Studies of kinetics and equilibrium were also performed using the most known models to evaluate the viability of the process In line with the concept of circular economy, this study adds value to this by-product as well as contributes to liquid waste management. Experimental: The solutions were prepared with Hg(II) initial concentration of 50 µg L-1 in natural waters, at 22 ± 1 ºC, pH 6, magnetically stirring at 650 rpm and biosorbent mass of 0.5 g L-1. NaCl was added to obtain the salt solutions, seawater was collected from the Portuguese coast and the real wastewater was kindly provided by ISQ - Instituto de Soldadura e qualidade (Welding and Quality Institute) and diluted until the same concentration of 50 µg L-1. Banana peels were previously freeze-drying, milled, sieved and the particles < 1 mm were used. Results: Banana peels removed more than 90% of Hg(II) from all the synthetic solutions studied. In these cases, the enhance in the complexity of the water type promoted a higher mercury removal. In salt waters, the biosorbent showed removals of 96%, 95% and 98 % for 3, 15 and 30 g L-1 of NaCl, respectively. The residual concentration of Hg(II) in solution achieved the level of drinking water regulation (1 µg L-1). For real matrices, the lower Hg(II) elimination (93 % for seawater and 81 % for the real wastewaters), can be explained by the competition between the Hg(II) ions and the other elements present in these solutions for the sorption sites. Regarding the equilibrium study, the experimental data are better described by the Freundlich isotherm (R ^ 2=0.991). The Elovich equation provided the best fit to the kinetic points. Conclusions: The results exhibited the great ability of the banana peels to remove mercury. The environmental realist conditions studied in this work, highlight their potential usage as biosorbents in water remediation processes.

Keywords: banana peels, mercury removal, sorption, water treatment

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Authors: Marzieh Ahmadi, Ruhullah Alikhan Gorgani

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The usual methods of measuring regional inequalities can not reflect the internal changes of the country in terms of their displacement in different development groups, and the indicators of inequalities are not effective in demonstrating the dynamics of the distribution of inequality. For this purpose, this paper examines the dynamics of the urban inertial transport in the country during the period of 2006-2016 using the CIRD multidimensional index and stochastic kernel density method. it firstly selects 25 indicators in five dimensions including macroeconomic conditions, science and innovation, environmental sustainability, human capital and public facilities, and two-stage Principal Component Analysis methodology are developed to create a composite index of inequality. Then, in the second stage, using a nonparametric analytical approach to internal distribution dynamics and a stochastic kernel density method, the convergence hypothesis of the CIRD index of the Iranian provinces center is tested, and then, based on the ergodic density, long-run equilibrium is shown. Also, at this stage, for the purpose of adopting accurate regional policies, the distribution dynamics and process of convergence or divergence of the Iranian provinces for each of the five. According to the results of the first Stage, in 2006 & 2016, the highest level of development is related to Tehran and zahedan is at the lowest level of development. The results show that the central cities of the country are at the highest level of development due to the effects of Tehran's knowledge spillover and the country's lower cities are at the lowest level of development. The main reason for this may be the lack of access to markets in the border provinces. Based on the results of the second stage, which examines the dynamics of regional inequality transmission in the country during 2006-2016, the first year (2006) is not multifaceted and according to the kernel density graph, the CIRD index of about 70% of the cities. The value is between -1.1 and -0.1. The rest of the sequence on the right is distributed at a level higher than -0.1. In the kernel distribution, a convergence process is observed and the graph points to a single peak. Tends to be a small peak at about 3 but the main peak at about-0.6. According to the chart in the final year (2016), the multidimensional pattern remains and there is no mobility in the lower level groups, but at the higher level, the CIRD index accounts for about 45% of the provinces at about -0.4 Take it. That this year clearly faces the twin density pattern, which indicates that the cities tend to be closely related to each other in terms of development, so that the cities are low in terms of development. Also, according to the distribution dynamics results, the provinces of Iran follow the single-density density pattern in 2006 and the double-peak density pattern in 2016 at low and moderate inequality index levels and also in the development index. The country diverges during the years 2006 to 2016.

Keywords: Urban Disparity, CIRD Index, Convergence, Distribution Dynamics, Random Kernel Density

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Authors: Nadia Belu, Laurenţiu Mihai Ionescu, Agnieszka Misztal

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The automotive industry is one of the most important industries in the world that concerns not only the economy, but also the world culture. In the present financial and economic context, this field faces new challenges posed by the current crisis, companies must maintain product quality, deliver on time and at a competitive price in order to achieve customer satisfaction. Two of the most recommended techniques of quality management by specific standards of the automotive industry, in the product development, are Failure Mode and Effects Analysis (FMEA) and Control Plan. FMEA is a methodology for risk management and quality improvement aimed at identifying potential causes of failure of products and processes, their quantification by risk assessment, ranking of the problems identified according to their importance, to the determination and implementation of corrective actions related. The companies use Control Plans realized using the results from FMEA to evaluate a process or product for strengths and weaknesses and to prevent problems before they occur. The Control Plans represent written descriptions of the systems used to control and minimize product and process variation. In addition Control Plans specify the process monitoring and control methods (for example Special Controls) used to control Special Characteristics. In this paper we propose a computer-aided solution with Genetic Algorithms in order to reduce the drafting of reports: FMEA analysis and Control Plan required in the manufacture of the product launch and improved knowledge development teams for future projects. The solution allows to the design team to introduce data entry required to FMEA. The actual analysis is performed using Genetic Algorithms to find optimum between RPN risk factor and cost of production. A feature of Genetic Algorithms is that they are used as a means of finding solutions for multi criteria optimization problems. In our case, along with three specific FMEA risk factors is considered and reduce production cost. Analysis tool will generate final reports for all FMEA processes. The data obtained in FMEA reports are automatically integrated with other entered parameters in Control Plan. Implementation of the solution is in the form of an application running in an intranet on two servers: one containing analysis and plan generation engine and the other containing the database where the initial parameters and results are stored. The results can then be used as starting solutions in the synthesis of other projects. The solution was applied to welding processes, laser cutting and bending to manufacture chassis for buses. Advantages of the solution are efficient elaboration of documents in the current project by automatically generating reports FMEA and Control Plan using multiple criteria optimization of production and build a solid knowledge base for future projects. The solution which we propose is a cheap alternative to other solutions on the market using Open Source tools in implementation.

Keywords: automotive industry, FMEA, control plan, automotive technology

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Authors: Tal Braverman Uriel, Tal Litvak Hirsch

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Background and Objectives: Little or only partial emphasis has been placed on exploring the complexity of consensual non-monogamous relationships. The term "polyamory" refers to consensual non-monogamy, and it is defined as having emotional and/or sexual relations simultaneously with two or more people, the consent and knowledge of all the partners concerned. Managing multiple romantic relationships with different people evokes more emotions, leads to more emotional conflicts arising from different interests, and demands practical strategies. An individual's transition from a monogamous lifestyle to a consensual non-monogamous lifestyle yields new challenges, accompanied by stress, uncertainty, and question marks, as do other life-changing events, such as divorce or transition to parenthood. The study examines both the process of transition and adaptation to a consensually non-monogamous relationship, as well as the coping mechanism involved in the daily conduct of this lifestyle. The research focuses on understanding the consequences, challenges, and coping methods from a personal, marital, and familial point of view and focuses on 40 middle-aged individuals (20 men and 20 women ages 40-60). The research sheds light on a way of life that has not been previously studied in Israel and is still considered unacceptable. Theories of crisis (e.g., as Folkman and Lazarus) were applied, and as a result, a deeper understanding of the subject was reached, all while focusing on multiple aspects of dealing with stress. The basic research question examines the consequences of entering a polyamorous life from a personal point of view as an individual, partner, and parent and the ways of coping with these consequences. Method: The research is conducted with a narrative qualitative approach in the interpretive paradigm, including semi-structured in-depth interviews. The method of analysis is thematic. Results: The findings indicate that in most cases, an individual's motivation to open the relationship is mainly a longing for better sexuality and for an added layer of excitement to their lives. Most of the interviewees were assisted by their spouses in the process, as well as by social networks and podcasts on the subject. Some of them therapeutic professionals from the field are helpful. It also clearly emerged that among those who experienced acute emotional crises with the primary partner or painful separations from secondary partners, all believed polyamory to be the adequate way of life for them. Finally, a key resource for managing tension and stress is the ability to share and communicate with the primary partner. Conclusions: The study points to the challenges and benefits of a non-monogamous lifestyle as well as the use of coping mechanisms and resources that are consistent with the existing theory and research in the field in the context of life changes. The study indicates the need to expand the research canvas in the future in the context of parenting and the consequences for children.

Keywords: a-monogamy, consent, family, stress, tension

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Binbin Chen, Dennis Y. C. Leung

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Aluminium (Al) -air cell holds a high volumetric capacity density of 8.05 Ah cm-3, benefit from the trivalence of Al ions. Additional benefits of Al-air cell are low price and environmental friendliness. Furthermore, the Al energy conversion process is characterized of 100% recyclability in theory. Along with a large base of raw material reserve, Al attracts considerable attentions as a promising material to be integrated within the global energy system. However, despite the early successful applications in military services, several problems exist that prevent the Al-air cells from widely civilian use. The most serious issue is the parasitic corrosion of Al when contacts with electrolyte. To overcome this problem, super-pure Al alloyed with various traces of metal elements are used to increase the corrosion resistance. Nevertheless, high-purity Al alloys are costly and require high energy consumption during production process. An alternative approach is to add inexpensive inhibitors directly into the electrolyte. However, such additives would increase the internal ohmic resistance and hamper the cell performance. So far these methods have not provided satisfactory solutions for the problem within Al-air cells. For the operation of alkaline Al-air cell, there are still other minor problems. One of them is the formation of aluminium hydroxide in the electrolyte. This process decreases ionic conductivity of electrolyte. Another one is the carbonation process within the gas diffusion layer of cathode, blocking the porosity of gas diffusion. Both these would hinder the performance of cells. The present work optimizes the above problems by building an Al-air cell operation system, consisting of four components. A top electrolyte tank containing fresh electrolyte is located at a high level, so that it can drive the electrolyte flow by gravity force. A mechanical rechargeable Al-air cell is fabricated with low-cost materials including low grade Al, carbon paper, and PMMA plates. An electrolyte waste tank with elaborate channel is designed to separate the hydrogen generated from the corrosion, which would be collected by gas collection device. In the first section of the research work, we investigated the performance of the mechanical rechargeable Al-air cell with a constant flow rate of electrolyte, to ensure the repeatability experiments. Then the whole system was assembled together and the feasibility of operating was demonstrated. During experiment, pure hydrogen is collected by collection device, which holds potential for various applications. By collecting this by-product, high utilization efficiency of aluminum is achieved. Considering both electricity and hydrogen generated, an overall utilization efficiency of around 90 % or even higher under different working voltages are achieved. Fluidic electrolyte could remove aluminum hydroxide precipitate and solve the electrolyte deterioration problem. This operation system provides a low-cost strategy for harvesting energy from the abundant secondary Al. The system could also be applied into other metal-air cells and is suitable for emergency power supply, power plant and other applications. The low cost feature implies great potential for commercialization. Further optimization, such as scaling up and optimization of fabrication, will help to refine the technology into practical market offerings.

Keywords: aluminium-air cell, high efficiency, hydrogen, mechanical recharge

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