Search results for: adaptive architecture

Authors: Jared Beard, Ali Baheri

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As autonomous systems become more prominent in society, ensuring their safe application becomes increasingly important. This is clearly demonstrated with autonomous cars traveling through a crowded city or robots traversing a warehouse with heavy equipment. Human environments can be complex, having high dimensional state and action spaces. This gives rise to two problems. One being that analytic solutions may not be possible. The other is that in simulation based approaches, searching the entirety of the problem space could be computationally intractable, ruling out formal methods. To overcome this, approximate solutions may seek to find failures or estimate their likelihood of occurrence. One such approach is adaptive stress testing (AST) which uses reinforcement learning to induce failures in the system. The premise of which is that a learned model can be used to help find new failure scenarios, making better use of simulations. In spite of these failures AST fails to find particularly sparse failures and can be inclined to find similar solutions to those found previously. To help overcome this, multi-fidelity learning can be used to alleviate this overuse of information. That is, information in lower fidelity can simulations can be used to build up samples less expensively, and more effectively cover the solution space to find a broader set of failures. Recent work in multi-fidelity learning has passed information bidirectionally using “knows what it knows” (KWIK) reinforcement learners to minimize the number of samples in high fidelity simulators (thereby reducing computation time and load). The contribution of this work, then, is development of the bidirectional multi-fidelity AST framework. Such an algorithm, uses multi-fidelity KWIK learners in an adversarial context to find failure modes. Thus far, a KWIK learner has been used to train an adversary in a grid world to prevent an agent from reaching its goal; thus demonstrating the utility of KWIK learners in an AST framework. The next step is implementation of the bidirectional multi-fidelity AST framework described. Testing will be conducted in a grid world containing an agent attempting to reach a goal position and adversary tasked with intercepting the agent as demonstrated previously. Fidelities will be modified by adjusting the size of a time-step, with higher-fidelity effectively allowing for more responsive closed loop feedback. Results will compare the single KWIK AST learner with the multi-fidelity algorithm with respect to number of samples, distinct failure modes found, and relative effect of learning after a number of trials.

Keywords: multi-fidelity reinforcement learning, multi-fidelity simulation, safety validation, falsification

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Authors: Seongjun Kim, Jinwooung Kim, Sung-Ah Kim

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The development of information and communication technology also affects human cognition and thinking, especially in the field of design, new techniques are being tried. In architecture, new design methodologies such as machine learning or data-driven design are being applied. In particular, these methodologies are used in analyzing the factors related to the value of real estate or analyzing the feasibility in the early planning stage of the apartment housing. However, since the value of apartment buildings is often determined by external factors such as location and traffic conditions, rather than the interior elements of buildings, data is rarely used in the design process. Therefore, although the technical conditions are provided, the internal elements of the apartment are difficult to apply the data-driven design in the design process of the apartment. As a result, the designers of apartment housing were forced to rely on designer experience or modular design alternatives rather than data-driven design at the design stage, resulting in a uniform arrangement of space in the apartment house. The purpose of this study is to propose a methodology to support the designers to design the apartment unit plan with high consumer preference by deriving the correlation and importance of the floor plan elements of the apartment preferred by the consumers through the machine learning and reflecting this information from the early design process. The data on the pre-sale competition rate and the elements of the floor plan are collected as data, and the correlation between pre-sale competition rate and independent variables is analyzed through machine learning. This analytical model can be used to review the apartment unit plan produced by the designer and to assist the designer. Therefore, it is possible to make a floor plan of apartment housing with high preference because it is possible to feedback apartment unit plan by using trained model when it is used in floor plan design of apartment housing.

Keywords: apartment unit plan, data-driven design, design methodology, machine learning

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Authors: Tarik Sipahi

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Photonics research continues to push the boundaries of optical science, and the development of metasurface technology has emerged as a transformative force in this domain. The work presents the intricacies of a unified metasurface design tailored for efficient polarization and color control in optical systems. The proposed unified metasurface serves as a singular, nanoengineered optical element capable of simultaneous polarization modulation and color encoding. Leveraging principles from metamaterials and nanophotonics, this design allows for unprecedented control over the behavior of light at the subwavelength scale. The metasurface's spatially varying architecture enables seamless manipulation of both polarization states and color wavelengths, paving the way for a paradigm shift in optical system design. The advantages of this unified metasurface are diverse and impactful. By consolidating functions that traditionally require multiple optical components, the design streamlines optical systems, reducing complexity and enhancing overall efficiency. This approach is particularly promising for applications where compactness, weight considerations, and multifunctionality are crucial. Furthermore, the proposed unified metasurface design not only enhances multifunctionality but also addresses key challenges in optical system design, offering a versatile solution for applications demanding compactness and lightweight structures. The metasurface's capability to simultaneously manipulate polarization and color opens new possibilities in diverse technological fields. The research contributes to the evolution of optical science by showcasing the transformative potential of metasurface technology, emphasizing its role in reshaping the landscape of optical system architectures. This work represents a significant step forward in the ongoing pursuit of pushing the boundaries of photonics, providing a foundation for future innovations in compact and efficient optical devices.

Keywords: metasurface, nanophotonics, optical system design, polarization control

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Authors: Iulianna Taritsa, Kuldeep Neote, Eric Fossel

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Lysosome-induced immunogenic cell death (LIICD) is a powerful mechanism of targeting cancer cells that kills circulating malignant cells and primes the host’s immune cells against future remission. Current immunotherapies for cancer are limited in preventing recurrence – a gap that can be bridged by training the immune system to recognize cancer neoantigens. Lysosomal leakage can be induced therapeutically to traffic antigens from dying cells to dendritic cells, which can later present those tumorigenic antigens to T cells. Previous research has shown that oxidative agents administered in the tumor microenvironment can initiate LIICD. We generated a fusion protein between an oxidative agent known as xanthine oxidase (XO) and a mini-antibody specific for EGFR/HER2-sensitive breast tumor cells. The anti-EGFR single domain antibody fragment is uniquely sourced from llama, which is functional without the presence of a light chain. These llama micro-antibodies have been shown to be better able to penetrate tissues and have improved physicochemical stability as compared to traditional monoclonal antibodies. We demonstrate that the fusion protein created is stable and can induce early markers of immunogenic cell death in an in vitro human breast cancer cell line (SkBr3). Specifically, we measured overall cell death, as well as surface-expressed calreticulin, extracellular ATP release, and HMGB1 production. These markers are consensus indicators of ICD. Flow cytometry, luminescence assays, and ELISA were used respectively to quantify biomarker levels between treated versus untreated cells. We also included a positive control group of SkBr3 cells dosed with doxorubicin (a known inducer of LIICD) and a negative control dosed with cisplatin (a known inducer of cell death, but not of the immunogenic variety). We looked at each marker at various time points after cancer cells were treated with the XO/antibody fusion protein, doxorubicin, and cisplatin. Upregulated biomarkers after treatment with the fusion protein indicate an immunogenic response. We thus show the potential for this fusion protein to induce an anticancer effect paired with an adaptive immune response against EGFR/HER2+ cells. Our research in human cell lines here provides evidence for the success of the same therapeutic method for patients and serves as the gateway to developing a new treatment approach against breast cancer.

Keywords: apoptosis, breast cancer, immunogenic cell death, lysosome

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Authors: Shimaa Nagro, Russell Campion

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Mobile devices are becoming ever more widely available, with growing functionality, and are increasingly used as an enabling technology to give students access to educational material anytime and anywhere. However, the design of educational material user interfaces for mobile devices is beset by many unresolved research issues such as those arising from emphasising the information concepts then mapping this information to appropriate media (modelling information then mapping media effectively). This report describes a multimedia user interface design method for mobile learning. The method covers specification of user requirements and information architecture, media selection to represent the information content, design for directing attention to important information, and interaction design to enhance user engagement based on Human-Computer Interaction design strategies (HCI). The method will be evaluated by three different case studies to prove the method is suitable for application to different areas / applications, these are; an application to teach about major computer networking concepts, an application to deliver a history-based topic; (after these case studies have been completed, the method will be revised to remove deficiencies and then used to develop a third case study), an application to teach mathematical principles. At this point, the method will again be revised into its final format. A usability evaluation will be carried out to measure the usefulness and effectiveness of the method. The investigation will combine qualitative and quantitative methods, including interviews and questionnaires for data collection and three case studies for validating the MDMLM method. The researcher has successfully produced the method at this point which is now under validation and testing procedures. From this point forward in the report, the researcher will refer to the method using the MDMLM abbreviation which means Multimedia Design Mobile Learning Method.

Keywords: human-computer interaction, interface design, mobile learning, education

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Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

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Authors: Wilai Masanga, Chirapha Tannanonta, Sangutid Thongsawad, Sasikarn Chamchod, Todsaporn Fuangrod

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The major factors of radiotherapy for head and neck (HN) cancers include patient’s anatomical changes and tumour shrinkage. These changes can significantly affect the planned dose distribution that causes the treatment plan deterioration. A measured transit EPID images compared to a predicted EPID images using gamma analysis has been clinically implemented to verify the dose accuracy as part of adaptive radiotherapy protocol. However, a global gamma analysis dose not sensitive to some critical organ changes as the entire treatment field is compared. The objective of this feasibility study is to evaluate the dosimetric response to patient anatomical changes during the treatment course in HN IMRT (Head and Neck Intensity-Modulated Radiation Therapy) using a novel comparison method; organ-of-interest gamma analysis. This method provides more sensitive to specific organ change detection. Random replanned 5 HN IMRT patients with causes of tumour shrinkage and patient weight loss that critically affect to the parotid size changes were selected and evaluated its transit dosimetry. A comprehensive physics-based model was used to generate a series of predicted transit EPID images for each gantry angle from original computed tomography (CT) and replan CT datasets. The patient structures; including left and right parotid, spinal cord, and planning target volume (PTV56) were projected to EPID level. The agreement between the transit images generated from original CT and replanned CT was quantified using gamma analysis with 3%, 3mm criteria. Moreover, only gamma pass-rate is calculated within each projected structure. The gamma pass-rate in right parotid and PTV56 between predicted transit of original CT and replan CT were 42.8%( ± 17.2%) and 54.7%( ± 21.5%). The gamma pass-rate for other projected organs were greater than 80%. Additionally, the results of organ-of-interest gamma analysis were compared with 3-dimensional cone-beam computed tomography (3D-CBCT) and the rational of replan by radiation oncologists. It showed that using only registration of 3D-CBCT to original CT does not provide the dosimetric impact of anatomical changes. Using transit EPID images with organ-of-interest gamma analysis can provide additional information for treatment plan suitability assessment.

Keywords: re-plan, anatomical change, transit electronic portal imaging device, EPID, head, and neck

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Authors: Mohammad Javad Seddighi, Avar Almukhtar

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The occurrence of natural disasters, such as floods and earthquakes, can cause significant damage to heritage sites and surrounding areas. In Iran, the city of Bam was devastated by an earthquake in 2003, which had a major impact on the rivers and watercourses around the city. This study aims to investigate the environmental design techniques and sustainable hazard mitigation strategies that can be employed to preserve heritage sites in the face of natural disasters, using the Bam experience as a case study. The research employs a mixed-methods approach, combining both qualitative and quantitative data collection and analysis methods. The study begins with a comprehensive literature review of recent publications on environmental design techniques and sustainable hazard mitigation strategies in heritage conservation. This is followed by a field study of the rivers and watercourses around Bam, including the Adoori River (Talangoo) and other watercourses, to assess the current conditions and identify potential hazards. The data collected from the field study is analysed using statistical methods and GIS mapping techniques. The findings of this study reveal the importance of sustainable hazard mitigation strategies and environmental design techniques in preserving heritage sites during natural disasters. The study suggests that these techniques can be used to prevent the outbreak of another natural disaster in Bam and the surrounding areas. Specifically, the study recommends the establishment of a comprehensive early warning system, the creation of flood-resistant landscapes, and the use of eco-friendly building materials in the reconstruction of heritage sites. These findings contribute to the current knowledge of sustainable hazard mitigation and environmental design in heritage conservation.

Keywords: natural disasters, heritage conservation, sustainable hazard mitigation, environmental design, landscape architecture, flood management, disaster resilience

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Authors: Anila Hayat

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Pakistan is one of those developing countries that are least involved in emissions but has the most vulnerable environmental conditions. Pakistan is ranked 8th in most affected countries by climate change on the climate risk index 1992-2011. Pakistan is facing severe water shortages and flooding as a result of changes in rainfall patterns, specifically in the least developed areas such as Tharparkar. Nagarparkar, once an attractive tourist spot located in Tharparkar because of its tropical desert climate, is now facing severe drought conditions for the last few decades. This study investigates the present socio-economic situation of local communities, major impacts of droughts and their underlying causes and current mitigation strategies adopted by local communities. The study uses both secondary (quantitative in nature) and primary (qualitative in nature) methods to understand the impacts and explore causes on the socio-economic life of local communities of the study area. The relevant data has been collected through household surveys using structured questionnaires, focus groups and in-depth interviews of key personnel from local and international NGOs to explore the sensitivity of impacts and adaptation to droughts in the study area. This investigation is limited to four rural communities of union council Pilu of Nagarparkar district, including Bheel, BhojaBhoon, Mohd Rahan Ji Dhani and Yaqub Ji Dhani villages. The results indicate that drought has caused significant economic and social hardships for the local communities as more than 60% of the overall population is dependent on rainfall which has been disturbed by irregular rainfall patterns. The decline in Crop yields has forced the local community to migrate to nearby areas in search of livelihood opportunities. Communities have not undertaken any appropriate adaptive actions to counteract the adverse effect of drought; they are completely dependent on support from the government and external aid for survival. Respondents also reported that poverty is a major cause of their vulnerability to drought. An increase in population, limited livelihood opportunities, caste system, lack of interest from the government sector, unawareness shaped their vulnerability to drought and other social issues. Based on the findings of this study, it is recommended that the local authorities shall create awareness about drought hazards and improve the resilience of communities against drought. It is further suggested to develop, introduce and implement water harvesting practices at the community level to promote drought-resistant crops.

Keywords: migration, vulnerability, awareness, Drought

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Authors: Dominic Huschke, Rudolf Keil

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New driving functionalities like highly automated driving have a major impact on the electrics/electronics architecture of future vehicles and inevitably lead to higher safety requirements. Partly due to these increased requirements, the vehicle industry is increasingly looking at semiconductor switches as an alternative to conventional melting fuses. The protective functionality of semiconductor switches can be implemented in hardware as well as in software. A current approach discussed in science and industry is the implementation of a model of the protected low voltage power cable on a microcontroller to calculate its temperature. Here, the information regarding the current is provided by the continuous current measurement of the semiconductor switch. The signal to open the semiconductor switch is provided by the microcontroller when a previously defined limit for the temperature of the low voltage power cable is exceeded. A setup for the testing of the described principle for electronic fuse protection of a low voltage power cable is built and successfullyvalidated with experiments afterwards. Here, the evaluation criterion is the deviation of the measured temperature of the low voltage power cable from the specified limit temperature when the semiconductor switch is opened. The analysis is carried out with an assumed ambient temperature as well as with a measured ambient temperature. Subsequently, the experimentally performed investigations are simulated in a virtual environment. The explicit focus is on the simulation of the behavior of the microcontroller with an implemented model of a low voltage power cable in a real-time environment. Subsequently, the generated results are compared with those of the experiments. Based on this, the completely virtual design of the described approach is assumed to be valid.

Keywords: automotive wire harness, electronic fuse protection, low voltage power cable, semiconductor-based fuses, software-based validation

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Authors: Prashanth Pillai, Purnaprajna Mangsuli

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Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

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Authors: Pooja Jain

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Art education is often ignored in syllabus of developing countries like India and in educational planning for development but now days Indian Art with a global recognition is becoming an integral part of the education at all levels. The term art, widely used in all parts of the modern world, carried varied significance in India as its meaning was continuously being extended, covering the many varieties of creative expression such as painting, sculpture, commercial art, design, poetry, music, dance, and architecture. Over the last 100 years Indian artists of all forms have evolved a wide variety of expressive styles. With the recommendations and initiatives by Government of India, Art Education has subsequently gained pace at the school level as a mandatory subject for all making a path way for students with a creative bend of mind. This paper investigates curriculum in various schools of the country at secondary and senior secondary levels along with some eminent institutions running the program. Findings depicted the role of art education and justified its importance primarily with commercial art being perceived to be essential for students learning skills for economic gain in their career ahead. With so many art colleges spread across India, emerging artists and designers are being trained and are creating art of infinite variety and style and have opened up many career avenues. Commercial Art being a plethora of artistic expressions has confidently come of age wherein a creative perception is mixed with an introspective imagination to bring out multi faceted career options with a significant future enveloped in art. Visual arts in education thus is an expanding field of result assured research.

Keywords: modern art, commercial art, introspective imagination, career

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Authors: A. Rostampouryasouri, A. Maghoul, S. Tahersima

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The rapid growth of urbanization and the subsequent increase in population in cities have resulted in the destruction of the environment to cater to the needs of citizens. The industrialization of urban life has led to the production of pollutants, which has significantly contributed to the rise of air pollution. Infrastructure can have both positive and negative effects on air pollution. The effects of infrastructure on air pollution are complex and depend on various factors such as the type of infrastructure, location, and context. This study examines the effects of infrastructure on air pollution, drawing on a range of empirical evidence from Iran and China. Our paper focus for analyzing the data is on the following concepts: 1. Urban design and planning principles and practices 2. Infrastructure efficiency and optimization strategies 3. Public transportation systems and their environmental impact 4. GHG emissions reduction strategies in urban areas 5. Case studies and best practices in sustainable urban development This paper employs a mixed methodology approach with a focus on developmental and applicative purposes. The mixed methods approach combines both quantitative and qualitative research methods to provide a more comprehensive understanding of the research topic. A group of 20 architectural specialists and experts who are proficient in the field of research, design, and implementation of green architecture projects were interviewed in a systematic and purposeful manner. The research method was based on content analysis using MAXQDA2020 software. The findings suggest that policymakers and urban planners should consider the potential impacts of infrastructure on air pollution and take measures to mitigate negative effects while maximizing positive ones. This includes adopting a nature-based approach to urban planning and infrastructure development, investing in information infrastructure, and promoting modern logistic transport infrastructure.

Keywords: GHG emissions, infrastructure efficiency, urban development, urban design

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Authors: Hubert Feiglstorfer

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Due to its location in a transition zone from the Pannonian to the pre-Alpine region, the east of Austria shows a small-scale diversity in the regional development of certain vernacular building techniques. In this article the relationship between natural building material resources, topography and climate will be examined. Besides environmental preconditions, social and economic historical factors have developed different construction techniques within certain regions in the Weinviertel and Burgenland, the two eastern federal states of Austria. But even within these regions, varying building techniques were found, due to the locally different use of raw materials like wood, stone, clay, lime, or organic fibres. Within these small-scale regions, building traditions were adapted over the course of time due to changes in the use of the building material, for example from wood to brick or from wood to earth. The processing of the raw materials varies from region to region, for example as rammed earth, cob, log, or brick construction. Environmental preconditions cross national borders. For that reason, developments in the neighbouring countries, the Czech Republic, Slovakia, Hungary and Slovenia are included in this analysis. As an outcome of this research a map was drawn which shows the interrelation between locally available building materials, topography, climate and local building techniques? As a result of this study, which covers the last 300 years, one can see how the local population used natural resources very sensitively adapted to local environmental preconditions. In the case of clay, for example, changes of proportions of lime and particular minerals cause structural changes that differ from region to region. Based on material analyses in the field of clay mineralogy, on ethnographic research, literature and archive research, explanations for certain local structural developments will be given for the first time over the region of East Austria.

Keywords: European crafts, material culture, architectural history, earthen architecture, earth building history

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Authors: Mohammed Badereldien, Rezk Diab, Mohamoud Ali, Ayman Aboelkassem

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The stone surfaces of historical architectural heritage in Egypt are under threat from of various environmental factors such as temperature fluctuation, humidity, pollution, and microbes. Due to these factors, the facades of buildings are deteriorating deformation and disfiguration of external decoration and the formation of black accretion also often from the stone works. The aim of this study is to evaluate the effectiveness of CaCO₃ nano-particles as consolidation and protection material for calcareous stone monuments. Selected tests were carried out in order to estimate the superficial consolidating and protective effect of the treatment. When applied the nanoparticles dispersed in the acrylic copolymer; poly ethylmethacrylate (EMA)/methylacrylate (MA) (70/30, respectively) (EMA)/methylacrylate (MA) (70/30, respectively). The synthesis process of CaCO₃ nanoparticles/polymer nano-composite was prepared using in situ emulsion polymerization system. The consolidation and protection were characterized by TEM, while the penetration depth, re-aggregating effects of the deposited phase, and the surface morphology before and after treatment were examined by SEM (Scanning Electron Microscopy). Improvement of the stones' mechanical properties was evaluated by compressive strength tests. Changes in water-interaction properties were evaluated by water absorption capillarity measurements, and colorimetric measurements were used to evaluate the optical appearance. Together the results appear to demonstrate that CaCO₃/polymer nanocomposite is an efficient material for the consolidation of limestone architecture and monuments. As compared with samples treated with pure acrylic copolymer without Calcium carbonate nanoparticles, for example, CaCO₃ nanoparticles are completely compatible, strengthening limestone against thermal aging and improving its mechanical properties.

Keywords: calcium carbonate nanoparticles, consolidation, nanocomposites, calcareous stone, colorimetric measurements, compressive strength

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Shanmugasundaram Selvadurai, Amal Chandran

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Small satellites have become an alternative low-cost solution for several missions to accomplish specific missions such as Earth imaging, Technology demonstration, Education, and other commercial purposes. Small satellite missions focusing on Infrared imaging applications require lower temperature for scientific instruments and such low temperature can be achieved only using external cryocoolers but the disadvantage is that they generate a large amount of waste heat. Existing passive thermal control techniques are not capable to handle such large thermal loads and hence one of the traditional active Thermal Control System (TCS) is studied for a small satellite configuration. This work aims to downscale the existing Mechanically Pumped Fluid Loop (MPFL) TCS to a 27U CubeSat platform for an imaginary scientific instrument. The temperature-sensitive detector in the instrument considered to be maintained between 130K and 150K to reduce dark current noise and increase the data quality. A Single-Phase fluid based MPFL is chosen for this system-level study and this TCS consists of a microfluid pump, a micro-cryocooler, a fluid accumulator, external heaters, flow regulators, and sensors. This work also explains the thermal control system architecture with a conceptual design, arrangement of all the components, and thermal analysis for different low orbit conditions. Sizing and extensive trade studies for the components are conducted and the results have shown that the Single-phase MPFL system is able to handle the given thermal loads and maintain the satellite’s interface temperature within the desired limit.

Keywords: active thermal control system, satellite thermal, mechanically pumped fluid loop system, cryogenics, cryocooler

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Authors: O.Ofoegbu, S. Roongnapa, A.N. Eboatu

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Most polluted environments, most challengingly, aerosol types, contain a cocktail of different toxicants. Multi-templating of matrices have been the recent target by researchers in a bid to solving complex mixed-toxicant challenges using single or common remediation systems. This investigation looks at the effect of such multi-templated system vis-a-vis the synthesis by non-covalent interaction, of a molecularly imprinted polymer architecture using nicotine and its structural analogue Phenylalanine amide individually and, in the blend, (50:50), as template materials in a Chitosan-Methacrylic acid functional monomer matrix. The temperature for polymerization is 60OC and time for polymerization, 12hrs (water bath heating), 4mins for (microwave heating). The characteristic thermal properties of the molecularly imprinted materials are investigated using Simultaneous Thermal Analysis (STA) profiling, while the absorption and separation efficiencies based on the relative retention times and peak areas of templates were studied amongst other properties. Transmission Electron Microscopy (TEM) results obtained, show the creation of heterogeneous nanocavities, regardless, the introduction of Caffeine a close structural analogue presented near-zero perfusion. This confirms the selectivity and specificity of the templated polymers despite its dual-templated nature. The STA results presented the materials as having decomposition temperatures above 250OC and a relative loss in mass of less than19% over a period within 50mins of heating. Consequent to this outcome, multi-templated systems can be fabricated to sequester specifically and selectively targeted toxicants in a mixed toxicant populated system effectively.

Keywords: chitosan, dual-templated, methacrylic acid, mixed-toxicants, molecularly-imprinted-polymer

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Authors: Heribert R. Kaijage, Samuel N. A. Codjoe, Simon H. D. Mamuya, Mangi J. Ezekiel

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There is strong evidence that climate has changed significantly affecting various sectors including public health. The recommended feasible solution is adopting development trajectories which combine both mitigation and adaptation measures for improving resilience pathways. This approach demands a consideration for complex interactions between climate and social-ecological systems. While other sectors such as agriculture and water have developed climate resilience indices, the public health sector in Tanzania is still lagging behind. The aim of this study was to find out how can we use Demographic and Health Surveys (DHS) linked with Remote Sensing (RS) technology and metrological information as tools to inform climate change resilient development and evaluation for the health sector. Methodological review was conducted whereby a number of studies were content analyzed to find appropriate indicators and indices for climate resilience household and their integration approach. These indicators were critically reviewed, listed, filtered and their sources determined. Preliminary identification and ranking of indicators were conducted using participatory approach of pairwise weighting by selected national stakeholders from meeting/conferences on human health and climate change sciences in Tanzania. DHS datasets were retrieved from Measure Evaluation project, processed and critically analyzed for possible climate change indicators. Other sources for indicators of climate change exposure were also identified. For the purpose of preliminary reporting, operationalization of selected indicators was discussed to produce methodological approach to be used in resilience comparative analysis study. It was found that household climate resilient index depends on the combination of three indices namely Household Adaptive and Mitigation Capacity (HC), Household Health Sensitivity (HHS) and Household Exposure Status (HES). It was also found that, DHS alone cannot complement resilient evaluation unless integrated with other data sources notably flooding data as a measure of vulnerability, remote sensing image of Normalized Vegetation Index (NDVI) and Metrological data (deviation from rainfall pattern). It can be concluded that if these indices retrieved from DHS data sets are computed and scientifically integrated can produce single climate resilience index and resilience maps could be generated at different spatial and time scales to enhance targeted interventions for climate resilient development and evaluations. However, further studies are need to test for the sensitivity of index in resilience comparative analysis among selected regions.

Keywords: climate change, resilience, remote sensing, demographic and health surveys

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Authors: Ibrahim Musa, Mohammed Abdul-Aziz Mabrouk, Yusuf Tanko

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Introduction: Long term physical training affect the performance of athletes especially the females. Soccer which is a team sport, played in an outdoor field, require adequate oxygen transport system for the maximal aerobic power during exercise in order to complete 90 minutes of competitive play. Suboptimal haematological status has often been recorded in athletes with intensive physical activity. It may be due to the iron depletion caused by hemolysis or haemodilution results from plasma volume expansion. There is lack of data regarding the dynamics of red blood cell variables, in male football players. We hypothesized that, a long competitive season involving frequent matches and intense training could influence red blood cell variables, as a consequence of applying repeated physical loads when compared with sedentary. Methods: This cross sectional study was carried on 40 adult males (20 athletes and 20 non athletes) between 18-25 years of age. The 20 apparently healthy male non athletes were taken as sedentary and 20 male footballers comprise the study group. The university institutional review board (ABUTH/HREC/TRG/36) gave approval for all procedures in accordance with the Declaration of Helsinki. Red blood cell (RBC) concentration, packed cell volume (PCV), and plasma volume were measured in fasting state and immediately after exercise. Statistical analysis was done by using SPSS/ win.20.0 for comparison within and between the groups, using student’s paired and unpaired “t” test respectively. Results: The finding from our study shows that, immediately after termination of exercise, the mean RBC counts and PCV significantly (p<0.005) decreased with significant increased (p<0.005) in plasma volume when compared with pre-exercised values in both group. In addition the post exercise RBC was significantly higher in untrained (261.10±8.5) when compared with trained (255.20±4.5). However, there was no significant differences in the post exercise hematocrit and plasma volume parameters between the sedentary and the footballers. Moreover, beside changes in pre-exercise values among the sedentary and the football players, the resting red blood cell counts and Plasma volume (PV %) was significantly (p < 0.05) higher in the sedentary group (306.30±10.05 x 104 /mm3; 58.40±0.54%) when compared with football players (293.70±4.65 x 104 /mm3; 55.60±1.18%). On the other hand, the sedentary group exhibited significant (p < 0.05) decrease in PCV (41.60±0.54%) when compared with the football players (44.40±1.18%). Conclusions: It is therefore proposed that the acute football exercise induced reduction in RBC and PCV is entirely due to plasma volume expansion, and not of red blood cell hemolysis. In addition, the training status also influenced haematological indices of male football players differently from the sedentary at rest due to adaptive response. This is novel.

Keywords: Haematological Indices, Performance Status, Sedentary, Male Football Players

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

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

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

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Authors: G. Ravindranath, S. Savitha

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This paper presents heat transfer analysis of single horizontal bare tube and heat transfer analysis of staggered arrangement of bare tube bundles bare tube bundles in gas-solid (air-solid) fluidized bed and predictions are done by using Artificial Neural Network (ANN) based on experimental data. Fluidized bed provide nearly isothermal environment with high heat transfer rate to submerged objects i.e. due to through mixing and large contact area between the gas and the particle, a fully fluidized bed has little temperature variation and gas leaves at a temperature which is close to that of the bed. Measurement of average heat transfer coefficient was made by local thermal simulation technique in a cold bubbling air-fluidized bed of size 0.305 m. x 0.305 m. Studies were conducted for single horizontal Bare Tube of length 305mm and 28.6mm outer diameter and for bare tube bundles of staggered arrangement using beds of large (average particle diameter greater than 1 mm) particle (raagi and mustard). Within the range of experimental conditions influence of bed particle diameter ( Dp), Fluidizing Velocity (U) were studied, which are significant parameters affecting heat transfer. Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, and non-linearity. Here, feed-forward architecture and trained by back-propagation technique is adopted to predict heat transfer analysis found from experimental results. The ANN is designed to suit the present system which has 3 inputs and 2 out puts. The network predictions are found to be in very good agreement with the experimental observed values of bare heat transfer coefficient (hb) and nusselt number of bare tube (Nub).

Keywords: fluidized bed, large particles, particle diameter, ANN

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Authors: Nour Eddine Nachouane, Aicha Knidiri

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The Hispano-Moorish art was born in 786 when Abd ar-Rahman built the first mosque in Cordoba. It is a still-living art in the trades of the big Moroccan cities. Everyone agrees that the different artistic forms of Arab-Muslim art find their full development in traditional Moroccan architecture, and this heritage allows artists and artisans to create magnificent masterpieces. Marrakech, by way of example, constitutes a symbolic city, which represents the reflection of a rich history of this art carried by a long artisanal tradition that is still living nowadays. Despite its ratification by UNESCO as intangible cultural heritage, and beyond official speeches, several of those craft trades are endangered, and with them the whole history of millennial savoir-faire. From the empirical study of the old historic center, 'the medina' of Marrakech, we explore in this article the opportunity offered by the tourism industry in order to protect these craft trades. We question artisans on the evolution of the sector and the challenges of the transmission of this heritage. We evoke the case of Spanish cities like Granada in a comparative reflection on the strategies and perceptions of the public administrations of a part, and, on the other hand, on the shared experience of artisans and tourists. In an interdisciplinary approach mixing anthropology, history, sociology, and even geography, we question the capacity of heritage processes to mobilize and involve a set of actors and activate a trajectory for the safeguarding of Andalusian arts and techniques. The basic assumption of this research is that the promotion of traditional craft trades through tourism and based on good scientific knowledge can present an original offer to cope with globalization and guarantee the transmission of that savoir-faire to new generations. Research in the field of Islamic arts does not constitute a retreat into the nationalist identity or a fixation on the past but an opening towards cultural diversity, free from any standardization.

Keywords: heritage, art andalusi, handcraft, tourism

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Authors: Zhen Cheng, Xinyu Dai, Shujian Huang, Jiajun Chen

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Recently, explanatory natural language inference has attracted much attention for the interpretability of logic relationship prediction, which is also known as explanation generation for Natural Language Inference (NLI). Existing explanation generators based on discriminative Encoder-Decoder architecture have achieved noticeable results. However, we find that these discriminative generators usually generate explanations with correct evidence but incorrect logic semantic. It is due to that logic information is implicitly encoded in the premise-hypothesis pairs and difficult to model. Actually, logic information identically exists between premise-hypothesis pair and explanation. And it is easy to extract logic information that is explicitly contained in the target explanation. Hence we assume that there exists a latent space of logic information while generating explanations. Specifically, we propose a generative model called Variational Explanation Generator (VariationalEG) with a latent variable to model this space. Training with the guide of explicit logic information in target explanations, latent variable in VariationalEG could capture the implicit logic information in premise-hypothesis pairs effectively. Additionally, to tackle the problem of posterior collapse while training VariaztionalEG, we propose a simple yet effective approach called Logic Supervision on the latent variable to force it to encode logic information. Experiments on explanation generation benchmark—explanation-Stanford Natural Language Inference (e-SNLI) demonstrate that the proposed VariationalEG achieves significant improvement compared to previous studies and yields a state-of-the-art result. Furthermore, we perform the analysis of generated explanations to demonstrate the effect of the latent variable.

Keywords: natural language inference, explanation generation, variational auto-encoder, generative model

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Authors: Osvaldo N. Oliveira Jr.

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The control of molecular architecture inherent in some experimental methods to produce nanostructured films has had great impact on devices of various types, including sensors and biosensors. The self-assembly monolayers (SAMs) and the electrostatic layer-by-layer (LbL) techniques, for example, are now routinely used to produce tailored architectures for biosensing where biomolecules are immobilized with long-lasting preserved activity. Enzymes, antigens, antibodies, peptides and many other molecules serve as the molecular recognition elements for detecting an equally wide variety of analytes. The principles of detection are also varied, including electrochemical methods, fluorescence spectroscopy and impedance spectroscopy. In this presentation an overview will be provided of biosensors made with nanostructured films to detect antibodies associated with tropical diseases and HIV, in addition to detection of analytes of medical interest such as cholesterol and triglycerides. Because large amounts of data are generated in the biosensing experiments, use has been made of computational and statistical methods to optimize performance. Multidimensional projection techniques such as Sammon´s mapping have been shown more efficient than traditional multivariate statistical analysis in identifying small concentrations of anti-HIV antibodies and for distinguishing between blood serum samples of animals infected with two tropical diseases, namely Chagas´ disease and Leishmaniasis. Optimization of biosensing may include a combination of another information visualization method, the Parallel Coordinate technique, with artificial intelligence methods in order to identify the most suitable frequencies for reaching higher sensitivity using impedance spectroscopy. Also discussed will be the possible convergence of technologies, through which machine learning and other computational methods may be used to treat data from biosensors within an expert system for clinical diagnosis.

Keywords: clinical diagnosis, information visualization, nanostructured films, layer-by-layer technique

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Authors: Abdulfattah A. Q. Alwah, Amal Al‑Attar, Sumyah M. Al-Fanini, Ellen Fetzer

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Cultural landscapes enhance the spiritual relationship between people and their environment. They represent civilized evidence of peoples' interaction with nature and the exploitation of its resources to build their civilization. Yemeni urban and rural environments are rich in many cultural landscape elements that reflect the ingenuity of Yemeni people in interacting with nature. Yemen's mountain cities and villages appear in harmony with mountains, with vertical tower building patterns, local building materials, and unique architectural and urban elements and features. Such cities and villages are still full of life today, such as the cities of Taiz, Ibb, Lahj, and historical Jableh and hundreds of mountain villages in the provinces of the mountainous highlands. The cultivated mountain terraces reflect the ability of Yemenis to create arable areas in the tall mountains and to use successful means of irrigation and rainwater drainage. Unfortunately, there is a severe shortage of research studies that discuss the cultural landscapes in Yemen and the mechanisms for their preservation. Therefore, this study aimed to shed light on the types of mountain cultural landscapes in Yemen and discuss the means of their preservation. The study achieved its objectives through a theoretical review of available studies and field visits to some sites in Ibb, Jableh, and Taiz cities. The study highlighted the human contribution to these sites and elements and showed the Yemenis’ skills in adapting to nature and benefiting from it ideally. This study can guide the competent authorities to assess, develop, and protect cultural landscape sites in Yemen.

Keywords: civilization, urban environment, Yemeni mountain architecture, human heritage conservation, cultural identity

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Authors: Mustafa Eruyar, Ersoy Pehlivan, Fatih Kafalı, Fatih Gundogan

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All megacities are not only under the pressure of common urbanization and growth problems but also dealing with different challenges according to their specific circumstances. However, the majority of cities focuses mainly on popular smart city projects, which are usually driven by strong private sector, regardless of their characteristics, each city needs to develop customized projects within a tailor-made smart city roadmap to be able to solve its own challenges. Smart city manifest, helps citizens to feel the action better than good reading smart city vision statements, which consists of five elements; namely purpose, values, mission, vision, and strategy. This study designs a methodology for smart city roadmap based on a top-down approach, breaking down of smart city manifest to feasible projects for a systematic smart city transformation. This methodology was implemented in Istanbul smart city transformation program which includes smart city literature review, current state analysis, roadmap, and architecture projects, respectively. Istanbul smart city roadmap project followed an extensive literature review of certain leading smart cities around the world and benchmarking of the city’s current state using well known smart city indices. In the project, needs of citizens and service providers of the city were identified via stakeholder, persona and social media analysis. The project aimed to develop smart city projects targeting fulfilling related needs by implementing a gap analysis between current state and foreseen plans. As a result, in 11 smart city domains and enablers; 24 strategic objectives, 50 programs, and 101 projects were developed with the support of 183 smart city stakeholder entities and based on 125 citizen persona profiles and last one-year social media analysis. In conclusion, the followed methodology helps cities to identify and prioritize their needs and plan for long-term sustainable development, despite limited resources.

Keywords: needs-based, manifest, roadmap, smart city, top-down approach

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Authors: Olubisi Friday Oluduro

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The Paris Agreement 2015, the result of negotiations under the United Nations Framework Convention on Climate Change (UNFCCC), after Kyoto Protocol expiration, sets a long-term goal of limiting the increase in the global average temperature to well below 2 degrees Celsius above pre-industrial levels, and of pursuing efforts to limiting this temperature increase to 1.5 degrees Celsius. An advancement on the erstwhile Kyoto Protocol which sets commitments to only a limited number of Parties to reduce their greenhouse gas (GHGs) emissions, it includes the goal to increase the ability to adapt to the adverse impacts of climate change and to make finance flows consistent with a pathway towards low GHGs emissions. For it achieve these goals, the Agreement requires all Parties to undertake efforts towards reaching global peaking of GHG emissions as soon as possible and towards achieving a balance between anthropogenic emissions by sources and removals by sinks in the second half of the twenty-first century. In addition to climate change mitigation, the Agreement aims at enhancing adaptive capacity, strengthening resilience and reducing the vulnerability to climate change in different parts of the world. It acknowledges the importance of addressing loss and damage associated with the adverse of climate change. The Agreement also contains comprehensive provisions on support to be provided to developing countries, which includes finance, technology transfer and capacity building. To ensure that such supports and actions are transparent, the Agreement contains a number reporting provisions, requiring parties to choose the efforts and measures that mostly suit them (Nationally Determined Contributions), providing for a mechanism of assessing progress and increasing global ambition over time by a regular global stocktake. Despite the somewhat global look of the Agreement, it has been fraught with manifold limitations threatening its very existential capability to produce any meaningful result. Considering these obvious limitations some of which were the very cause of the failure of its predecessor—the Kyoto Protocol—such as the non-participation of the United States, non-payment of funds into the various coffers for appropriate strategic purposes, among others. These have left the developing countries largely threatened eve the more, being more vulnerable than the developed countries, which are really responsible for the climate change scourge. The paper seeks to examine the mitigation and adaptation measures under the Paris Agreement 2015, appraise the present situation since the Agreement was concluded and ascertain whether the developing countries have been better or worse off since the Agreement was concluded, and examine why and how, while projecting a way forward in the present circumstance. It would conclude with recommendations towards ameliorating the situation.

Keywords: mitigation, adaptation, climate change, Paris agreement 2015, framework

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Authors: Lawrence Babatunde Ogunsanya

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The university has been in existence, in one form or another, for over a thousand years and has contributed in multiple ways to modern society. It is considered a center of culture, aesthetic direction, and moral forces shaping the civilized society. Universities also contribute in important ways to the economic health and physical landscape of neighborhoods and cities, serving as permanent fixtures of the urban economy and the built environment. Due to the size and location of university campuses, they put demands on the urban character, systems, and infrastructure of the neighboring communities. These demands or impacts have substantial implications for the built environment. It is important to understand the impacts university campuses have on their surrounding communities and urban environments because the destiny of the university is inextricably linked to the destiny of the adjacent neighborhoods. This paper identifies the diverse factors generated by universities in shaping the built environments of their local communities within different spatial contexts such as urban, rural, and township regions situated in South Africa.By applying a mixed methods approach in four university campuses within the province of KwaZulu-Natal in South Africa. Several data collection instruments were used, such as in-depth interviews, a survey, remote sensing, and onsite observations. The thematic findings revealed numerous factors which influence the morphology of neighbourhood built environments and the myriad of relationships the university has with its local community. This paper also reveals that the university campus is more than a precinct which accommodates buildings and academic endeavours, the role of the university in this century has changed dramatically from its traditional roots of being an elite enclave of academics to a more inclusive and engaged entity that is concerned about providing relevant holistic solutions to society’s current challenges in the built environment.

Keywords: university campus, built environment, architecture, neighborhood planning

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Authors: Carmela Nardelli, Laura Iaffaldano, Valentina Capobianco, Antonietta Tafuto, Maddalena Ferrigno, Angela Capone, Giuseppe Maria Maruotti, Maddalena Raia, Rosa Di Noto, Luigi Del Vecchio, Pasquale Martinelli, Lucio Pastore, Lucia Sacchetti

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Maternal obesity and nutrient excess in utero increase the risk of future metabolic diseases in the adult life. The mechanisms underlying this process are probably based on genetic, epigenetic alterations and changes in foetal nutrient supply. In mammals, the placenta is the main interface between foetus and mother, it regulates intrauterine development, modulates adaptive responses to sub optimal in uterus conditions and it is also an important source of human amniotic mesenchymal stem cells (hA-MSCs). We previously highlighted a specific microRNA (miRNA) profiling in amnion from obese (Ob) pregnant women, here we compared the miRNA expression profile of hA-MSCs isolated from (Ob) and control (Co) women, aimed to search for any alterations in metabolic pathways that could predispose the new-born to the obese phenotype. Methods: We isolated, at delivery, hA-MSCs from amnion of 16 Ob- and 7 Co-women with pre-pregnancy body mass index (mean/SEM) 40.3/1.8 and 22.4/1.0 kg/m2, respectively. hA-MSCs were phenotyped by flow cytometry. Globally, 384 miRNAs were evaluated by the TaqMan Array Human MicroRNA Panel v 1.0 (Applied Biosystems). By the TargetScan program we selected the target genes of the miRNAs differently expressed in Ob- vs Co-hA-MSCs; further, by KEGG database, we selected the statistical significant biological pathways. Results: The immunophenotype characterization confirmed the mesenchymal origin of the isolated hA-MSCs. A large percentage of the tested miRNAs, about 61.4% (232/378), was expressed in hA-MSCs, whereas 38.6% (146/378) was not. Most of the expressed miRNAs (89.2%, 207/232) did not differ between Ob- and Co-hA-MSCs and were not further investigated. Conversely, 4.8% of miRNAs (11/232) was higher and 6.0% (14/232) was lower in Ob- vs Co-hA-MSCs. Interestingly, 7/232 miRNAs were obesity-specific, being expressed only in hA-MSCs isolated from obese women. Bioinformatics showed that these miRNAs significantly regulated (P<0.001) genes belonging to several metabolic pathways, i.e. MAPK signalling, actin cytoskeleton, focal adhesion, axon guidance, insulin signaling, etc. Conclusions: Our preliminary data highlight an altered miRNA profile in Ob- vs Co-hA-MSCs and suggest that an epigenetic miRNA-based mechanism of gene regulation could affect pathways involved in placental growth and function, thereby potentially increasing the newborn’s risk of metabolic diseases in the adult life.

Keywords: hA-MSCs, obesity, miRNA, biosystem

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