Search results for: healthcare access and efficiency

Authors: Luan Vardari, Dena Arapi Vardari

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The Balkan countries, known for their diverse landscapes and cultural heritage, face the dual challenge of promoting economic growth while addressing pressing environmental concerns. In recent years, the concept of green finance has emerged as a powerful tool to achieve sustainable development and mitigate the environmental impact of various sectors, including architecture. This extended abstract explores the untapped potential of green finance in architecture within the Balkan region and highlights its role in driving sustainable construction practices and fostering a greener future. The abstract begins by defining green finance and emphasizing its relevance in the context of the architectural sector in Balkan countries. It underlines the benefits of green finance, such as economic growth, environmental conservation, and social well-being. Integrating green finance into architectural projects is important as a means to achieve sustainable development goals while promoting financial viability. Also, delves into the current state of green building practices in the Balkan countries and identifies the need for financial support to further drive adoption. It explores the existing regulatory frameworks and policies that promote sustainable architecture and discusses how green finance can complement these initiatives. Unique challenges faced by Balkan countries are highlighted, along with the potential opportunities that green finance presents in overcoming these challenges. We highlight successful sustainable architectural projects in the region to showcase the practical application of green finance in the Balkans. These projects exemplify the effective utilization of green finance mechanisms, resulting in tangible economic and environmental impacts, including job creation, energy efficiency, and reduced carbon emissions. The abstract concludes by identifying replicable models and lessons learned from these projects that can serve as a blueprint for future sustainable architecture initiatives in the Balkans. The importance of collaboration and knowledge sharing among stakeholders is emphasized. Engaging architects, financial institutions, governments, and local communities is crucial to promoting green finance in architecture. The abstract suggests the establishment of knowledge exchange platforms and regional/international networks to foster collaboration and facilitate the sharing of expertise among Balkan countries.

Keywords: sustainable finance, renewable energy, Balkan region, investment opportunities, green infrastructure, ESG criteria, architecture

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Authors: Ayodele A. Otaiku

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Purpose: Nigeria has become the largest importer of rice in Africa and second in the world, 2015. Investigate interactions of organic rice farming on soil quality and health from bio-waste converted to biofertilizer and its environmental impact on rice crop. Methodology: Bio-wastes, poultry waste, organic agriculture wastes, wood ash mixed with microbial inoculant organisms called OBD-Plus microbes (broad spectrum) composted in anaerobic digester to OBD-biofertilizer (2010 - 2012) uses microbes to build humus and other stable carbons. Two field experiments were carried out at Badeggi, Niger state in 2011 and 2012 to evaluate the response of lowland rice production using biofertilizer. The experimental field was laid out in a strip-plot design with five treatments and three replications and at twenty-one day old seedlings of FARO 44 and FARO 52 rice varieties were transplanted. Plots without fertiliser application served as control. Findings: The highest rice grain yield increase of 4.4 t/ha over the control in 2012 against the Nigeria average of lowland rice grain yields of 1.5 t/ha. The utilization of OBD-Biofertilizer can decrease the use of chemical nitrogen fertilizer, prevent the depletion of soil organic matter and reduce environmental pollution. Increasing the floodwater productivity and optimizing the recycling of nutrients cum grazer populations and disease by biocontrols microbes present in the OBD-Biofertilizer. Organic matter in the soil improves by 58% and C/N 15 (2011) and 13.35 (2012). Implications: OBD- Biofertilizer produce plant growth hormones such as indole acetic acid (IAA), glomalin related soil protein and extracellular enzymes as phosphatases that promote soil health and quality. Conclusion: Microorganisms can enhance nutrients use efficiency by increasing root surface area e.g., mycorrhizal, fungi, promoting other beneficial symbioses of the host plant and microbial interactions resulting to increase in soil organic matter. By 2030, climate change is projected to depress cereal production in Africa by 2 to 3 percent. Improved seeds and increased fertilizer use should more than compensate, but this factor will still weigh heavily on efforts to make progress.

Keywords: OBD-plus microbial consortia, OBD-biofertilizer, rice production, soil quality, sustainable agriculture

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Authors: Amit Kumar, Archana Gupta, Poonam Tandon, E. D. D’Silva

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Nonlinear optical (NLO) materials are the key materials for the fast processing of information and optical data storage applications. In the last decade, materials showing nonlinear optical properties have been the object of increasing attention by both experimental and computational points of view. Chalcones are one of the most important classes of cross conjugated NLO chromophores that are reported to exhibit good SHG efficiency, ultra fast optical nonlinearities and are easily crystallizable. The basic structure of chalcones is based on the π-conjugated system in which two aromatic rings are connected by a three-carbon α, β-unsaturated carbonyl system. Due to the overlap of π orbitals, delocalization of electronic charge distribution leads to a high mobility of the electron density. On a molecular scale, the extent of charge transfer across the NLO chromophore determines the level of SHG output. Hence, the functionalization of both ends of the π-bond system with appropriate electron donor and acceptor groups can enhance the asymmetric electronic distribution in either or both ground and excited states, leading to an increased optical nonlinearity. In this research, the experimental and theoretical study on the structure and vibrations of (2E)-3-[4-(methylsulfanyl) phenyl]-1-(3-bromophenyl) prop-2-en-1-one (3Br4MSP) is presented. The FT-IR and FT-Raman spectra of the NLO material in the solid phase have been recorded. Density functional theory (DFT) calculations at B3LYP with 6-311++G(d,p) basis set were carried out to study the equilibrium geometry, vibrational wavenumbers, infrared absorbance and Raman scattering activities. The interpretation of vibrational features (normal mode assignments, for instance) has an invaluable aid from DFT calculations that provide a quantum-mechanical description of the electronic energies and forces involved. Perturbation theory allows one to obtain the vibrational normal modes by estimating the derivatives of the Kohn−Sham energy with respect to atomic displacements. The molecular hyperpolarizability β plays a chief role in the NLO properties, and a systematical study on β has been carried out. Furthermore, the first order hyperpolarizability (β) and the related properties such as dipole moment (μ) and polarizability (α) of the title molecule are evaluated by Finite Field (FF) approach. The electronic α and β of the studied molecule are 41.907×10-24 and 79.035×10-24 e.s.u. respectively, indicating that 3Br4MSP can be used as a good nonlinear optical material.

Keywords: DFT, MEP, NLO, vibrational spectra

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Authors: Omer Zvi Shaked

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Intimate Partner Violence (IPV) is a widespread social problem. Since the 1970's, and due to political changes resulting from the feminist movement, western society has been changing its attitude towards the phenomenon and has been taking an active approach to reduce its magnitude. Enterprises in the form of legislation, awareness and prevention campaigns, women's shelters, and community intervention programs became more prevalent as years progressed. Although many initiatives were found to be productive, the effectiveness of one, however, remained questionable throughout the years: intervention programs for men's intimate violence. Surveys outline two main intervention models for men's intimate violence. The first is the Duluth model, which argued that men are socialized to be dominant - while women are socialized to be subordinate - and men are therefore required by social imperative to enforce, physically if necessary, their dominance. The Duluth model became the chief authorized intervention program, and some states in the US even regulated it as the standard criminal justice program for men's intimate violence. However, meta-analysis findings demonstrated that based on a partner's reports, Duluth treatment completers have 44% recidivism rate, and between 40% and 85% dropout range. The second model is the Cognitive-Behavioral Model (CBT), which is a highly accepted intervention worldwide. The model argues that cognitive misrepresentations of intimate situations precede violent behaviors frequently when anger predisposition exists. Since anger dysregulation mediates between one's cognitive schemes and violent response, anger regulation became the chief purpose of the intervention. Yet, a meta-analysis found only a 56% risk reduction for CBT interventions. It is, therefore, crucial to understand the background behind the domination of both the Duluth model and CBT interventions. This presentation will discuss the ways in which theoretical conceptualizations of men's intimate violence, as well as ideologies, had contributed to the above-mentioned interventions' wide acceptance, despite known lack of scientific and evidential support. First, the presentation will review the prominent interventions for male intimate violence, the Duluth model, and CBT. Second, the presentation will review the prominent theoretical models explaining men's intimate violence: The Patriarchal model, the Abusive Personality model, and the Post-Traumatic Stress model. Third, the presentation will discuss the interrelation between theory and practice, and the nature of affinity between research and practice regarding men's intimate violence. Finally, the presentation will set new directions for further research, aiming to improve intervention's efficiency with men's intimate violence and advance social work practice in the field.

Keywords: intimate partner violence, theory and practice relationship, Duluth, CBT, abusive personality, post-traumatic stress

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Authors: Johannes Gantner, Michael Held, Matthias Fischer

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The refurbishment of the building stock in terms of energy supply and efficiency is one of the major challenges of the German turnaround in energy policy. As the building sector accounts for 40% of Germany’s total energy demand, additional insulation is key for energy efficient refurbished buildings. Nevertheless the energetic benefits often the environmental and economic performances of insulation materials are questioned. The methods Life Cycle Assessment (LCA) as well as Life Cycle Costing (LCC) can form the standardized basis for answering this doubts and more and more become important for material producers due efforts such as Product Environmental Footprint (PEF) or Environmental Product Declarations (EPD). Due to increasing use of LCA and LCC information for decision support the robustness and resilience of the results become crucial especially for support of decision and policy makers. LCA and LCC results are based on respective models which depend on technical parameters like efficiencies, material and energy demand, product output, etc.. Nevertheless, the influence of parameter uncertainties on lifecycle results are usually not considered or just studied superficially. Anyhow the effect of parameter uncertainties cannot be neglected. Based on the example of an exterior wall the overall lifecycle results are varying by a magnitude of more than three. As a result simple best case worst case analyses used in practice are not sufficient. These analyses allow for a first rude view on the results but are not taking effects into account such as error propagation. Thereby LCA practitioners cannot provide further guidance for decision makers. Probabilistic analyses enable LCA practitioners to gain deeper understanding of the LCA and LCC results and provide a better decision support. Within this study, the environmental and economic impacts of an exterior wall system over its whole lifecycle are illustrated, and the effect of different uncertainty analysis on the interpretation in terms of resilience and robustness are shown. Hereby the approaches of error propagation and Monte Carlo Simulations are applied and combined with statistical methods in order to allow for a deeper understanding and interpretation. All in all this study emphasis the need for a deeper and more detailed probabilistic evaluation based on statistical methods. Just by this, misleading interpretations can be avoided, and the results can be used for resilient and robust decisions.

Keywords: uncertainty, life cycle assessment, life cycle costing, Monte Carlo simulation

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Federico Garrido, Mostafa El Hayani, Ahmed Shams

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The exploration of the potential of artificial intelligence (AI) in architecture is still embryonic, however, its latent capacity to change design disciplines is significant. 'Synthetic Classism' is a research project that questions the underlying aspects of classically organized architecture not just in aesthetic terms but also from a geometrical and morphological point of view, intending to generate new architectural information using historical examples as source material. The main aim of this paper is to explore the uses of artificial intelligence and machine learning algorithms in architectural design while creating a coherent narrative to be contained within a design process. The purpose is twofold: on one hand, to develop and train machine learning algorithms to produce architectural information of small pavilions and on the other, to synthesize new information from previous architectural drawings. These algorithms intend to 'interpret' graphical information from each pavilion and then generate new information from it. The procedure, once these algorithms are trained, is the following: parting from a line profile, a synthetic 'front view' of a pavilion is generated, then using it as a source material, an isometric view is created from it, and finally, a top view is produced. Thanks to GAN algorithms, it is also possible to generate Front and Isometric views without any graphical input as well. The final intention of the research is to produce isometric views out of historical information, such as the pavilions from Sebastiano Serlio, James Gibbs, or John Soane. The idea is to create and interpret new information not just in terms of historical reconstruction but also to explore AI as a novel tool in the narrative of a creative design process. This research also challenges the idea of the role of algorithmic design associated with efficiency or fitness while embracing the possibility of a creative collaboration between artificial intelligence and a human designer. Hence the double feature of this research, both analytical and creative, first by synthesizing images based on a given dataset and then by generating new architectural information from historical references. We find that the possibility of creatively understand and manipulate historic (and synthetic) information will be a key feature in future innovative design processes. Finally, the main question that we propose is whether an AI could be used not just to create an original and innovative group of simple buildings but also to explore the possibility of fostering a novel architectural sensibility grounded on the specificities on the architectural dataset, either historic, human-made or synthetic.

Keywords: architecture, central pavilions, classicism, machine learning

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Authors: Raghuram Kandimalla, Sanjeeb Kalita, Bhaswati Choudhury, Jibon Kotoky

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The quest for developing an ideal suture material prompted our interest to develop a novel suture with advantageous characteristics to market available ones. We developed novel suture biomaterial from muga silk (Antheraea assama) and ramie (Boehmeria nivea) plant fiber. Field emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDX), attenuated total reflection fourier transform infrared spectroscopy (ATR-FTIR) and thermo gravimetric analysis (TGA) results revealed the physicochemical properties of the fibers which supports the suitability of fibers for suture fabrication. Tensile properties of the prepared sutures were comparable with market available sutures and it found to be biocompatible towards human erythrocytes and nontoxic to mammalian cells. The prepared sutures completely healed the superficial deep wound incisions within seven days in adult male wister rats leaving no rash and scar. Histopathology studies supports the wound healing ability of sutures, as rapid synthesis of collagen, connective tissue and other skin adnexal structures were observed within seven days of surgery. Further muga suture surface modified by exposing the suture to oxygen plasma which resulted in formation of nanotopography on suture surface. Broad spectrum antibiotic amoxicillin was functionalized on the suture surface to prepare an advanced antimicrobial muga suture. Surface hydrophilicity induced by oxygen plasma results in an increase in drug-impregnation efficiency of modified muga suture by 16.7%. In vitro drug release profiles showed continuous and prolonged release of amoxicillin from suture up to 336 hours. The advanced muga suture proves to be effective against growth inhibition of Staphylococcus aureus and Escherichia coli, whereas normal muga suture offers no antibacterial activity against both types of bacteria. In vivo histopathology studies and colony-forming unit count data revealed accelerated wound healing activity of advanced suture over normal one through rapid synthesis and proliferation of collagen, hair follicle and connective tissues.

Keywords: sutures, biomaterials, silk, Ramie

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Authors: Marcelo Pereira Introini

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The global value chains (GVC) approach contributes to a better understanding of the international production organization amid globalization’s second unbundling from the 1970s on. Mainly due to the tools that help to understand the importance of critical competences, technological capabilities, and functions performed by each player, GVC research flourished in recent years, rooted in discussing the possibilities of integration and repositioning along regional and global value chains. Regarding this context, part of the literature endorsed a more optimistic view that engaging in fragmented production networks could represent learning opportunities for developing countries’ firms, since the relationship with transnational corporations could allow them build skills and competences. Increasing recognition that GVCs are based on asymmetric power relations provided another sight about benefits, costs, and development possibilities though. Once leading companies tend to restrict the replication of their technologies and capabilities by their suppliers, alternative strategies beyond the functional specialization, seen as a way to integrate value chains, began to be broadly highlighted. This paper organizes a coherent narrative about the shortcomings of the GVC analytical framework, while recognizing its multidimensional contributions and recent developments. We adopt two different and complementary perspectives to explore the idea of integration in the international production. On one hand, we emphasize obstacles beyond production components, analyzing the role played by intangible assets and intellectual property regimes. On the other hand, we consider the importance of domestic production and innovation systems for technological development. In order to provide a deeper understanding of the restrictions on technological learning of developing countries’ firms, we firstly build from the notion of intellectual monopoly to analyze how flagship companies can prevent subordinated firms from improving their positions in fragmented production networks. Based on intellectual property protection regimes we discuss the increasing asymmetries between these players and the decreasing access of part of them to strategic intangible assets. Second, we debate the role of productive-technological ecosystems and of interactive and systemic technological development processes, as concepts of the Innovation Systems approach. Supporting the idea that not only endogenous advantages are important for international competition of developing countries’ firms, but also that the building of these advantages itself can be a source of technological learning, we focus on local efforts as a crucial element, which is not replaceable for technology imported from abroad. Finally, the paper contributes to the discussion about technological development as a two-dimensional dynamic. If GVC analysis tends to underline a company-based perspective, stressing the learning opportunities associated to GVC integration, historical involvement of national States brings up the debate about technology as a central aspect of interstate disputes. In this sense, technology is seen as part of military modernization before being also used in civil contexts, what presupposes its role for national security and productive autonomy strategies. From this outlook, it is important to consider it as an asset that, incorporated in sophisticated machinery, can be the target of state policies besides the protection provided by intellectual property regimes, such as in export controls and inward-investment restrictions.

Keywords: global value chains, innovation systems, intellectual monopoly, technological development

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Authors: Eduardas Spiriajevas

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Since the end of the 20th century, when Lithuania regained its independence, a process of demographic shrinkage started. Recently, it affects the efficiency of implementation of actions related to regional development policy and geographic scopes of created value added in the regions. The demographic structures of human resources reflect onto the regions and their economic geographic environment. Due to reshaping economies and state reforms on restructuration of economic branches such as agriculture and industry, it affects the economic significance of services’ sector. These processes influence the competitiveness of labor market and its demographic characteristics. Such vivid consequences are appropriate for the structures of human migrations, which affected the processes of demographic ageing of human resources in the regions, especially in peripheral ones. These phenomena of modern times induce the demographic shrinkage of society and its economic geographic characteristics in the actions of regional development and in regional policy. The internal and external migrations of population captured numerous regional economic disparities, and influenced on territorial density and concentration of population of the country and created the economies of spatial unevenness in such small geographically compact country as Lithuania. The processes of territorial reshaping of distribution of population create new regions and their economic environment, which is not corresponding to the main principles of regional policy and its power to create the well-being and to promote the attractiveness for economic development. These are the new challenges of national regional policy and it should be researched in a systematic way of taking into consideration the analytical approaches of regional economy in the context of economic geographic research methods. A comparative territorial analysis according to administrative division of Lithuania in relation to retrospective approach and introduction of method of location quotients, both give the results of economic geographic character with cartographic representations using the tools of spatial analysis provided by technologies of Geographic Information Systems. A set of these research methods provide the new spatially evidenced based results, which must be taken into consideration in reshaping of national regional policy in economic geographic context. Due to demographic shrinkage and increasing differentiation of economic developments within the regions, an input of economic geographic dimension is inevitable. In order to sustain territorial balanced economic development, there is a need to strengthen the roles of regional centers (towns) and to empower them with new economic functionalities for revitalization of peripheral regions, and to increase their economic competitiveness and social capacities on national scale.

Keywords: demographic shrinkage, economic geography, Lithuania, regions

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Authors: Asim Abbasi, Muhammad Sufyan, Iqra, Muhammad Ibrahim Shahid, Muhammad Ashfaq

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The foundation of human life on earth relies on many ecosystem services provided by insects of which pollination owes a vital role. The pollination service offered by insects has annual worth of approximately €153 billion. The majority of the flowering plants depends on entomophiles pollination for their reproduction and formation of seeds and fruits. The quantity and quality of insect pollination have multiple implications for stable ecosystem, diverse species level, food security and climate change resilience. The rapidly mounting human population, depletion of natural resources and the global climate change forced us to enter an era of pollination crisis. Climate change not only alters the phenology, population abundance and geographic ranges of different pollinators but also hinders their pollination activities. The successful pollination process relies heavily on the synchronization of biological events of pollinators with the phenological stages of the flowering plants. However, there are possibilities that impending climatic changes may result in asynchrony between plant-pollinators interactions and also mitigate the extent of pollination. The trophic mismatch mostly occurs when pollinators and plants inhabiting the same environment use different environmental cues to regulate their biological events, as these cues are not equally affected by climate change. Synchrony has also been disrupted when one of the interacting species has migratory nature and depend on cues for migration. Moreover, irregular rainfalls and up-surging temperature also disrupts the foraging behaviour of pollinators resulting in reduced flowers visits by insect. Climate change has a direct impact on the behavior and physiology of honey bees, the best known pollinators owing to their extreme floral fidelity. Rising temperature not only alleviates the quantity and quality of floral environment but also alters the bee’s colony harvesting and development ability. Furthermore, a possible earlier decline of flowers is expected in a growing season due to this rising temperature. This may also lead to disrupt the efficiency bumblebee queen that require a constant and adequate nectar and pollen supply throughout the entire growing season for healthy colony production. Considering the role of insect pollination in our ecosystem, their associated risks regarding climate change should be addressed properly for devising a well-focused research needed for their conservation.

Keywords: climate change, phenological, pollination, synchronization

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Authors: Magdalena Diaka, Paweł Mazierski, Joanna Żebrowska, Michał Winiarski, Tomasz Klimczuk, Adriana Zaleska-Medynska

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During the last years, TiO2 nanotubes have been widely studied due to their unique highly ordered array structure, unidirectional charge transfer and higher specific surface area compared to conventional TiO2 powder. These photoactive materials, in the form of thin layer, can be activated by low powered and low cost irradiation sources (such as LEDs) to remove VOCs, microorganism and to deodorize air streams. This is possible due to their directly growth on a support material and high surface area, which guarantee enhanced photon absorption together with an extensive adsorption of reactant molecules on the photocatalyst surface. TiO2 nanotubes exhibit also lots of other attractive properties, such as potential enhancement of electron percolation pathways, light conversion, and ion diffusion at the semiconductor-electrolyte interface. Pure TiO2 nanotubes were previously used to remove organic compounds from the gas phase as well as in water splitting reaction. The major factors limiting the use of TiO2 nanotubes, which have not been fully overcome, are their relatively large band gap (3-3,2 eV) and high recombination rate of photogenerated electron–hole pairs. Many different strategies were proposed to solve this problem, however titania nanostructures containing incorporated metal oxides like Ag2O shows very promising, new optical and photocatalytic properties. Unfortunately, there is still very limited number of reports regarding application of TiO2/MxOy nanostructures. In the present work, we prepared TiO2/Ag2O nanotubes obtained by anodization of Ti-Ag alloys containing 5, 10 and 15 wt. % Ag. Photocatalysts prepared in this way were characterized by X-ray diffraction spectroscopy (XRD), scanning electron microscopy (SEM), luminescence spectroscopy and UV-Vis spectroscopy. The activities of new TiO2/Ag2O were examined by photocatalytic degradation of toluene in gas phase reaction and phenol in aqueous phase using 1000 W Xenon lamp (Oriel) and light emitting diodes (LED) as a irradiation sources. Additionally efficiency of bacteria (Pseudomonas aeruginosa) removal from the gas phase was estimated. The number of surviving bacteria was determined by the serial twofold dilution microtiter plate method, in Tryptic Soy Broth medium (TSB, GibcoBRL).

Keywords: photocatalysis, antibacterial properties, titania nanotubes, new TiO2/MxOy nanostructures

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Authors: K. C. Tanuja, Mamatha P. Raj

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"People have always lived on streets. They have been the places where children first learned about the world, where neighbours met, the social centres of towns and cities, the rallying points for revolts, the scenes of repression. The street has always been the scene of this conflict, between living and access, between resident and traveller, between street life and the threat of death.” Livable Streets by Donald Appleyard. Urbanisation is happening rapidly all over the world. As population increasing in the urban settlements, its required to provide quality of life to all the inhabitants who live in. Urban design is a place making strategic planning. Urban design principles promote visualising any place environmentally, socially and economically viable. Urban design strategies include building mass, transit development, economic viability and sustenance and social aspects. Cities are wonderful inventions of diversity- People, things, activities, ideas and ideologies. Cities should be smarter and adjustable to present technology and intelligent system. Streets represent the community in terms of social and physical aspects. Streets are an urban form that responds to many issues and are central to urban life. Streets are for livability, safety, mobility, place of interest, economic opportunity, balancing the ecology and for mass transit. Urban streets are places where people walk, shop, meet and engage in different types of social and recreational activities which make urban community enjoyable. Streets knit the urban fabric of activities. Urban streets become livable with the introduction of social network enhancing the pedestrian character by providing good design features which in turn should achieve the minimal impact of motor vehicle use on pedestrians. Livable streets are the spatial definition to the public right of way on urban streets. Streets in India have traditionally been the public spaces where social life happened or created from ages. Streets constitute the urban public realm where people congregate, celebrate and interact. Streets are public places that can promote social interaction, active living and community identity. Streets as potential contributors to a better living environment, knitting together the urban fabric of people and places that make up a community. Livable streets or complete streets are making our streets as social places, roadways and sidewalks accessible, safe, efficient and useable for all people. The purpose of this paper is to understand the concept of livable street and parameters of livability on urban streets. Streets to be designed as the pedestrians are the main users and create spaces and furniture for social interaction which serves for the needs of the people of all ages and abilities. The problems of streets like congestion due to width of the street, traffic movement and adjacent land use and type of movement need to be redesigned and improve conditions defining the clear movement path for vehicles and pedestrians. Well-designed spatial qualities of street enhances the street environment, livability and then achieves quality of life to the pedestrians. A methodology been derived to arrive at the typologies in street design after analysis of existing situation and comparing with livable standards. It was Donald Appleyard‟s Livable Streets laid out the social effects on streets creating the social network to achieve Livable Streets.

Keywords: livable streets, social interaction, pedestrian use, urban design

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Authors: Moustafa Osman Mohammed

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The resilient and sustainable of construction ecology is essential to world’s socio-economic development. Environmental resilience is crucial in relating construction ecology to topology of spatial-economic model. Sustainability of spatial-economic model gives attention to green business to comply with Earth’s System for naturally exchange patterns of ecosystems. The systems ecology has consistent and periodic cycles to preserve energy and materials flow in Earth’s System. When model structure is influencing communication of internal and external features in system networks, it postulated the valence of the first-level spatial outcomes (i.e., project compatibility success). These instrumentalities are dependent on second-level outcomes (i.e., participant security satisfaction). These outcomes of model are based on measuring database efficiency, from 2015 to 2025. The model topology has state-of-the-art in value-orientation impact and correspond complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic model; develop a set of sustainability indicators associated with model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate environmental resilience. The model is managing and developing schemes from perspective of multiple sources pollutants through the input–output criteria. These criteria are evaluated the external insertions effects to conduct Monte Carlo simulations and analysis for using matrices in a unique spatial structure. The balance “equilibrium patterns” such as collective biosphere features, has a composite index of the distributed feedback flows. These feedback flows have a dynamic structure with physical and chemical properties for gradual prolong of incremental patterns. While these structures argue from system ecology, static loads are not decisive from an artistic/architectural perspective. The popularity of system resilience, in the systems structure related to ecology has not been achieved without the generation of confusion and vagueness. However, this topic is relevant to forecast future scenarios where industrial regions will need to keep on dealing with the impact of relative environmental deviations. The model attempts to unify analytic and analogical structure of urban environments using database software to integrate sustainability outcomes where the process based on systems topology of construction ecology.

Keywords: system ecology, construction ecology, industrial ecology, spatial-economic model, systems topology

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Authors: George Kyriakopoulos, Photini Pazartzis, Anthi Koskina, Crystalie Bourcha

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The need for securing safe access to and return from outer space, as well as ensuring the viability of outer space operations, maintains vivid the debate over the promotion of organization of space traffic through a Space Traffic Management System (STM). The proliferation of outer space activities in recent years as well as the dynamic emergence of the private sector has gradually resulted in a diverse universe of actors operating in outer space. The said developments created an increased adverse impact on outer space sustainability as the case of the growing number of space debris clearly demonstrates. The above landscape sustains considerable threats to outer space environment and its operators that need to be addressed by a combination of scientific-technological measures and regulatory interventions. In this context, recourse to recent technological advancements and, in particular, to Artificial Intelligence (AI) and machine learning systems, could achieve exponential results in promoting space traffic management with respect to collision avoidance as well as launch and re-entry procedures/phases. New technologies can support the prospects of a successful space traffic management system at an international scale by enabling, inter alia, timely, accurate and analytical processing of large data sets and rapid decision-making, more precise space debris identification and tracking and overall minimization of collision risks and reduction of operational costs. What is more, a significant part of space activities (i.e. launch and/or re-entry phase) takes place in airspace rather than in outer space, hence the overall discussion also involves the highly developed, both technically and legally, international (and national) Air Traffic Management System (ATM). Nonetheless, from a regulatory perspective, the use of AI for the purposes of space traffic management puts forward implications that merit particular attention. Key issues in this regard include the delimitation of AI-based activities as space activities, the designation of the applicable legal regime (international space or air law, national law), the assessment of the nature and extent of international legal obligations regarding space traffic coordination, as well as the appropriate liability regime applicable to AI-based technologies when operating for space traffic coordination, taking into particular consideration the dense regulatory developments at EU level. In addition, the prospects of institutionalizing international cooperation and promoting an international governance system, together with the challenges of establishment of a comprehensive international STM regime are revisited in the light of intervention of AI technologies. This paper aims at examining regulatory implications advanced by the use of AI technology in the context of space traffic management operations and its key correlating concepts (SSA, space debris mitigation) drawing in particular on international and regional considerations in the field of STM (e.g. UNCOPUOS, International Academy of Astronautics, European Space Agency, among other actors), the promising advancements of the EU approach to AI regulation and, last but not least, national approaches regarding the use of AI in the context of space traffic management, in toto. Acknowledgment: The present work was co-funded by the European Union and Greek national funds through the Operational Program "Human Resources Development, Education and Lifelong Learning " (NSRF 2014-2020), under the call "Supporting Researchers with an Emphasis on Young Researchers – Cycle B" (MIS: 5048145).

Keywords: artificial intelligence, space traffic management, space situational awareness, space debris

Procedia PDF Downloads 260

Authors: Murad A. Channa, Mehdi Khiadani. Yasir Al-Abdeli

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Considering the severity of water scarcity around the world and its widening at an alarming rate, practical improvements in desalination techniques need to be engineered at the earliest. Atomization is the major aspect of flashing phenomena, yet it has been paid less attention to until now. There is a need to test efficient ways of atomization for the flashing process. Flash evaporation together with reverse osmosis is also a commercially matured desalination technique commonly famous as Multi-stage Flash (MSF). Even though reverse osmosis is massively practical, it is not economical or sustainable compared to flash evaporation. However, flashing evaporation has its drawbacks as well such as lower efficiency of water production per higher consumption of power and time. Flash evaporation is simply the instant boiling of a subcooled liquid which is introduced as droplets in a well-maintained negative environment. This negative pressure inside the vacuum increases the temperature of the liquid droplets far above their boiling point, which results in the release of latent heat, and the liquid droplets turn into vapor which is collected to be condensed back into an impurity-free liquid in a condenser. Atomization is the main difference between pool and spray flash evaporation. Atomization is the heart of the flash evaporation process as it increases the evaporating surface area per drop atomized. Atomization can be categorized into many levels depending on its drop size, which again becomes crucial for increasing the droplet density (drop count) per given flow rate. This review comprehensively summarizes the selective results relating to the methods of atomization and their effectiveness on the evaporation rate from earlier works to date. In addition, the reviewers propose using centrifugal atomization for the flashing application, which brings several advantages viz ultra-fine droplets, uniform droplet density, and the swirling geometry of the spray with kinetically more energetic sprays during their flight. Finally, several challenges of using rotary bell atomizer (RBA) and RBA Sprays inside the chamber have been identified which will be explored in detail. A schematic of rotary bell atomizer (RBA) integration with the chamber has been designed. This powerful centrifugal atomization has the potential to increase potable water production in commercial multi-stage flash evaporators, where it would be preferably advantageous.

Keywords: atomization, desalination, flash evaporation, rotary bell atomizer

Procedia PDF Downloads 84

Authors: Nikola Toshikj, Michel Ramonda, Sylvain Catrouillet, Jean-Jacques Robin, Sebastien Blanquer

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Biodegradable and biocompatible block copolymers have risen as the golden materials in both medical and environmental applications. Moreover, if their architecture is of controlled manner, higher applications can be foreseen. In the meantime, organocatalytic ROP has been promoted as more rapid and immaculate route, compared to the traditional organometallic catalysis, towards efficient synthesis of block copolymer architectures. Therefore, herein we report novel organocatalytic pathway with guanidine molecules (TBD) for supported synthesis of trimethylene carbonate initiated by poly(caprolactone) as pre-polymer. Pristine PTMC-b-PCL-b-PTMC block copolymer structure, without any residual products and clear desired block proportions, was achieved under 1.5 hours at room temperature and verified by NMR spectroscopies and size-exclusion chromatography. Besides, when elaborating block copolymer films, further stability and amelioration of mechanical properties can be achieved via additional reticulation step of precedently methacrylated block copolymers. Subsequently, stimulated by the insufficient studies on the phase-separation/crystallinity relationship in these semi-crystalline block copolymer systems, their intrinsic thermal and morphology properties were investigated by differential scanning calorimetry and atomic force microscopy. Firstly, by DSC measurements, the block copolymers with χABN values superior to 20 presented two distinct glass transition temperatures, close to the ones of the respecting homopolymers, demonstrating an initial indication of a phase-separated system. In the interim, the existence of the crystalline phase was supported by the presence of melting temperature. As expected, the crystallinity driven phase-separated morphology predominated in the AFM analysis of the block copolymers. Neither crosslinking at melted state, hence creation of a dense polymer network, disturbed the crystallinity phenomena. However, the later revealed as sensible to rapid liquid nitrogen quenching directly from the melted state. Therefore, AFM analysis of liquid nitrogen quenched and crosslinked block copolymer films demonstrated a thermodynamically driven phase-separation clearly predominating over the originally crystalline one. These AFM films remained stable with their morphology unchanged even after 4 months at room temperature. However, as demonstrated by DSC analysis once rising the temperature above the melting temperature of the PCL block, neither the crosslinking nor the liquid nitrogen quenching shattered the semi-crystalline network, while the access to thermodynamical phase-separated structures was possible for temperatures under the poly (caprolactone) melting point. Precisely this coexistence of dual crosslinked/crystalline networks in the same copolymer structure allowed us to establish, for the first time, the shape-memory properties in such materials, as verified by thermomechanical analysis. Moreover, the response temperature to the material original shape depended on the block copolymer emplacement, hence PTMC or PCL as end-block. Therefore, it has been possible to reach a block copolymer with transition temperature around 40°C thus opening potential real-life medical applications. In conclusion, the initial study of phase-separation/crystallinity relationship in PTMC-b-PCL-b-PTMC block copolymers lead to the discovery of novel shape memory materials with superior properties, widely demanded in modern-life applications.

Keywords: biodegradable block copolymers, organocatalytic ROP, self-assembly, shape-memory

Procedia PDF Downloads 129

Authors: A. H. Taghdisi, M. Mirmohammadi, S. Kamali

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Evening primrose (Oenothera biennis L.) is a biennial and herbaceous and one of the most important species of medicinal plants in the world. due to the production of unsaturated fatty acids such as linoleic acid, alpha-linolenic acid, etc. in its seeds and roots, and compounds such as kaempferol in its leaves, Evening primrose has important medicinal efficiency such as reducing premenstrual problems, acceleration of wound healing, inhibiting platelet aggregation, sedation of cardiovascular diseases, and treatment of viral infections. The sap of the plant is used to treat warts, and the plant itself is used as a charm against mental and spiritual diseases and poisonous animals. Its leaves have significant antibacterial activity against yellow staphylococci. It is also used in the treatment of poisoning, especially the toxication caused by the consumption of alcoholic beverages, in the treatment of arteriosclerosis and diseases caused by liver cell insufficiency. Low germination and production speed are the problems of evening primrose growth and propagation. In the present study, extracts were obtained from four components (flowers, stems, seeds, leaves) of the evening primrose plant using the Soxhlet apparatus. To measure the antibacterial properties against MDR bacteria, microbial methods, including dilution, cultivation on a plate containing nutrient agar culture medium, and disc diffusion in agar, were performed using Staphylococcus aureus and Escherichia coli bacteria on all four extracts. The maximum antibacterial activity related to the dilution method was obtained in all extracts. In the plate culture method, antibacterial activity was obtained for all extracts in the nutrient agar medium. The maximum diameter of the non-growth halo was obtained in the disc diffusion method in agar in the leaf extract. The statistical analysis of the microbial part was done by one-way ANOVA test (SPSS). By comparing the amount of omega-3 in extracts of Iranian and foreign oils available in the market and the extracts extracted from evening primrose plant samples with gas chromatography, it is shown that the stem extract had the most omega-3 (oleic acid) and compared to the extract of the mentioned oils, it had the highest amount of omega-3 overall. Also, the amount of omega-3 in the extract of Iranian oils was much higher than in the extract of foreign oils. It should be noted that the extract of foreign oils had a more complete composition of omega-3 than the extract of Iranian oils.

Keywords: antibacterial activity, MDR bacteria, evening primrose, omega-3

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Authors: Rostyslav Horbay, Nick Korolis, Vahid Anvari, Rostyslav Stoika

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Introduction: Giant cancer cells (GCC) are common in all types of cancer, especially after poor therapy. Some specific features of such cells include ~10-fold enlargement, drug resistance, and the ability to propagate similar daughter cells. We used murine NK/Ly lymphoma, an aggressive and fast growing lymphoma model that has already shown drastic changes in GCC comparing to parental cells (chromatin condensation, nuclear fragmentation, tighter OXPHOS/cellular respiration coupling, multidrug resistance). Materials and methods: In this study, we compared morpho-functional changes of GCC that predominantly show either a cytostatic or a cytotoxic effect after treatment with drugs. We studied the effect of a combined cytostatic/cytotoxic drug treatment to determine the correlation of drug efficiency and GCC formation. Doses of G1/S-specific drug paclitaxel/PTX (G2/M-specific, 50 mg/mouse), vinblastine/VBL (50 mg/mouse), and DNA-targeting agents doxorubicin/DOX (125 ng/mouse) and cisplatin/CP (225 ng/mouse) on C57 black mice. Several tests were chosen to estimate morphological and physiological state (propidium iodide, Rhodamine-123, DAPI, JC-1, Janus Green, Giemsa staining and other), which included cell integrity, nuclear fragmentation and chromatin condensation, mitochondrial activity, and others. A single and double factor ANOVA analysis were performed to determine correlation between the criteria of applied drugs and cytomorphological changes. Results: In all cases of treatment, several morphological changes were observed (intracellular vacuolization, membrane blebbing, and interconnected mitochondrial network). A lower gain in ascites (49.97% comparing to control group) and longest lifespan (22+9 days) after tumor injection was obtained with single VBL and single DOX injections. Such ascites contained the highest number of GCC (83.7%+9.2%), lowest cell count number (72.7+31.0 mln/ml), and a strong correlation coefficient between increased mitochondrial activity and percentage of giant NK/Ly cells. A high number of viable GCC (82.1+9.2%) was observed compared to the parental forms (15.4+11.9%) indicating that GCC are more drug resistant than the parental cells. All this indicates that the giant cell formation and its ability to obtain drug resistance is an expanding field in cancer research.

Keywords: ANOVA, cisplatin, doxorubicin, drug resistance, giant cancer cells, NK/Ly lymphoma, paclitaxel, vinblastine

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Authors: Parker Murray, Marci Johnson, Tyson S. Burnham, Alina K. Fong, Mark D. Allen, Bruce McIff

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Purpose: Pathological dysregulation of Neurovascular Coupling (NVC) caused by mild traumatic brain injury (mTBI) is the predominant source of chronic post-concussion syndrome (PCS) symptomology. fNCI has the ability to localize dysregulation in NVC by measuring blood-oxygen-level-dependent (BOLD) signaling during the performance of fMRI-adapted neuropsychological evaluations. With fNCI, 57 brain areas consistently affected by concussion were identified as PCS neural markers, which were validated on large samples of concussion patients and healthy controls. These neuromarkers provide the basis for a computation of PCS severity which is referred to as the Severity Index Score (SIS). The SIS has proven valuable in making pre-treatment decisions, monitoring treatment efficiency, and assessing long-term stability of outcomes. Methods and Materials: After being scanned while performing various cognitive tasks, 476 concussed patients received an SIS score based on the neural dysregulation of the 57 previously identified brain regions. These scans provide an objective measurement of attentional, subcortical, visual processing, language processing, and executive functioning abilities, which were used as biomarkers for post-concussive neural dysregulation. Initial SIS scores were used to develop individualized therapy incorporating cognitive, occupational, and neuromuscular modalities. These scores were also used to establish pre-treatment benchmarks and measure post-treatment improvement. Results: Changes in SIS were calculated in percent change from pre- to post-treatment. Patients showed a mean improvement of 76.5 percent (σ= 23.3), and 75.7 percent of patients showed at least 60 percent improvement. Longitudinal reassessment of 24 of the patients, measured an average of 7.6 months post-treatment, shows that SIS improvement is maintained and improved, with an average of 90.6 percent improvement from their original scan. Conclusions: fNCI provides a reliable measurement of NVC allowing for identification of concussion pathology. Additionally, fNCI derived SIS scores direct tailored therapy to restore NVC, subsequently resolving chronic PCS resulting from mTBI.

Keywords: concussion, functional magnetic resonance imaging (fMRI), neurovascular coupling (NVC), post-concussion syndrome (PCS)

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Authors: Mustafa Sengul, Enes Sahin, Sertac Arslan

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Pumpjets are one of the marine propulsion systems frequently used in underwater vehicles nowadays. The reasons for frequent use of pumpjet as a propulsion system are that it has higher relative efficiency at high speeds, better cavitation, and acoustic performance than its rivals. Pumpjets are composed of rotor, stator, and duct, and there are two different types of pumpjet configurations depending on the desired hydrodynamic characteristic, which are with accelerating and decelerating duct. Pumpjet with an accelerating channel is used at cargo ships where it works at low speeds and high loading conditions. The working principle of this type of pumpjet is to maximize the thrust by reducing the pressure of the fluid through the channel and throwing the fluid out from the channel with high momentum. On the other hand, for decelerating ducted pumpjets, the main consideration is to prevent the occurrence of the cavitation phenomenon by increasing the pressure of the fluid about the rotor region. By postponing the cavitation, acoustic noise naturally falls down, so decelerating ducted systems are used at noise-sensitive vehicle systems where acoustic performance is vital. Therefore, duct design becomes a crucial step during pumpjet design. This study, it is aimed to optimize the duct geometry of a decelerating ducted pumpjet for a highly speed underwater vehicle by using proper optimization tools. The target output of this optimization process is to obtain a duct design that maximizes fluid pressure around the rotor region to prevent from cavitation and minimizes drag force. There are two main optimization techniques that could be utilized for this process which are parameter-based optimization and gradient-based optimization. While parameter-based algorithm offers more major changes in interested geometry, which makes user to get close desired geometry, gradient-based algorithm deals with minor local changes in geometry. In parameter-based optimization, the geometry should be parameterized first. Then, by defining upper and lower limits for these parameters, design space is created. Finally, by proper optimization code and analysis, optimum geometry is obtained from this design space. For this duct optimization study, a commercial codedparameter-based optimization algorithm is used. To parameterize the geometry, duct is represented with b-spline curves and control points. These control points have x and y coordinates limits. By regarding these limits, design space is generated.

Keywords: pumpjet, decelerating duct design, optimization, underwater vehicles, cavitation, drag minimization

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Authors: Saud Hamdan Alshammari

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Photocatalytic water splitting to produce hydrogen (H₂) has obtained significant attention as an environmentally friendly technology. This process, which produces hydrogen from water and sunlight, represents a renewable energy source. Titanium dioxide (TiO₂) plays a critical role in photocatalytic hydrogen production due to its chemical stability, availability, and low cost. Nevertheless, TiO₂'s wide band gap (3.2 eV) limits its visible light absorption and might affect the effectiveness of the photocatalytic. Coupling TiO₂ with other semiconductors is a strategy that can enhance TiO₂ by narrowing its band gap and improving visible light absorption. This paper studies the modification of TiO₂ by coupling it with another semiconductor such as CdS nanoparticles using a reflux reactor and autoclave reactor that helps form a core-shell structure. Characterization techniques, including TEM and UV-Vis spectroscopy, confirmed successful coating of TiO₂ on CdS core, reduction of the band gap from 3.28 eV to 3.1 eV, and enhanced light absorption in the visible region. These modifications are attributed to the heterojunction structure between TiO₂ and CdS.The essential goal of this study is to improve TiO₂ for use in photocatalytic water splitting to enhance hydrogen production. The core-shell TiO₂@CdS nanoparticles exhibited promising results, due to band gap narrowing and improved light absorption. Future work will involve adding Pt as a co-catalyst, which is known to increase surface reaction activity by enhancing proton adsorption. Evaluation of the TiO₂@CdS@Pt catalyst will include performance assessments and hydrogen productivity tests, considering factors such as effective shapes and material ratios. Moreover, the study could be enhanced by studying further modifications to the catalyst and displaying additional performance evaluations. For instance, doping TiO₂ with metals such as nickel (Ni), iron (Fe), and cobalt (Co) and non-metals such as nitrogen (N), carbon (C), and sulfur (S) could positively influence the catalyst by reducing the band gap, enhancing the separation of photogenerated electron-hole pairs, and increasing the surface area, respectively. Additionally, to further improve catalytic performance, examining different catalyst morphologies, such as nanorods, nanowires, and nanosheets, in hydrogen production could be highly beneficial. Optimizing photoreactor design for efficient photon delivery and illumination will further enhance the photocatalytic process. These strategies collectively aim to overcome current challenges and improve the efficiency of hydrogen production via photocatalysis.

Keywords: hydrogen production, photocatalytic, water spliiting, semiconductor, nanoparticles

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Authors: Sergio Celaschi, Henrique Canavarro de Alencar, Claaudecir Biazoli

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Effluent quality is of the highest priority for compliance with the permit limits of environmental protection agencies and ensures the protection of their local water system. Of the pollutants monitored, the biochemical oxygen demand (BOD) posed one of the greatest challenges. This work presents a solution for wastewater treatment plants - WWTP’s ability to react to different situations and meet treatment goals. Delayed BOD5 results from the lab take 7 to 8 analysis days, hindered the WWTP’s ability to react to different situations and meet treatment goals. Reducing BOD turnaround time from days to hours is our quest. Such a solution is based on a system of two BOD bioreactors associated with Digital Twin (DT) and Machine Learning (ML) methodologies via an Internet of Things (IoT) platform to monitor and control a WWTP to support decision making. DT is a virtual and dynamic replica of a production process. DT requires the ability to collect and store real-time sensor data related to the operating environment. Furthermore, it integrates and organizes the data on a digital platform and applies analytical models allowing a deeper understanding of the real process to catch sooner anomalies. In our system of continuous time monitoring of the BOD suppressed by the effluent treatment process, the DT algorithm for analyzing the data uses ML on a chemical kinetic parameterized model. The continuous BOD monitoring system, capable of providing results in a fraction of the time required by BOD5 analysis, is composed of two thermally isolated batch bioreactors. Each bioreactor contains input/output access to wastewater sample (influent and effluent), hydraulic conduction tubes, pumps, and valves for batch sample and dilution water, air supply for dissolved oxygen (DO) saturation, cooler/heater for sample thermal stability, optical ODO sensor based on fluorescence quenching, pH, ORP, temperature, and atmospheric pressure sensors, local PLC/CPU for TCP/IP data transmission interface. The dynamic BOD system monitoring range covers 2 mg/L < BOD < 2,000 mg/L. In addition to the BOD monitoring system, there are many other operational WWTP sensors. The CPU data is transmitted/received to/from the digital platform, which in turn performs analyses at periodic intervals, aiming to feed the learning process. BOD bulletins and their credibility intervals are made available in 12-hour intervals to web users. The chemical kinetics ML algorithm is composed of a coupled system of four first-order ordinary differential equations for the molar masses of DO, organic material present in the sample, biomass, and products (CO₂ and H₂O) of the reaction. This system is solved numerically linked to its initial conditions: DO (saturated) and initial products of the kinetic oxidation process; CO₂ = H₂0 = 0. The initial values for organic matter and biomass are estimated by the method of minimization of the mean square deviations. A real case of continuous monitoring of BOD wastewater effluent quality is being conducted by deploying an IoT application on a large wastewater purification system located in S. Paulo, Brazil.

Keywords: effluent treatment, biochemical oxygen demand, continuous monitoring, IoT, machine learning

Procedia PDF Downloads 74

Authors: Shinji Kajiwara

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The basic ability of a vehicle is the ability to “run”, “turn” and “stop”. The safeness and comfort during a drive on various road surfaces and speed depends on the performance of these basic abilities of the vehicle. Stability and maneuverability of a vehicle is vital in automotive engineering. Stability of a vehicle is the ability of the vehicle to revert back to a stable state during a drive when faced with crosswind and irregular road conditions. Maneuverability of a vehicle is the ability of the vehicle to change direction during a drive swiftly based on the steering of the driver. The stability and maneuverability of a vehicle can also be defined as the driving stability of the vehicle. Since fossil fueled vehicle is the main type of transportation today, the environmental factor in automotive engineering is also vital. By improving the fuel efficiency of the vehicle, the overall carbon emission will be reduced thus reducing the effect of global warming and greenhouse gas on the Earth. Another main focus of the automotive engineering is the safety performance of the vehicle especially with the worrying increase of vehicle collision every day. With better safety performance on a vehicle, every driver will be more confidence driving every day. Next, let us focus on the “turn” ability of a vehicle. By improving this particular ability of the vehicle, the cornering limit of the vehicle can be improved thus increasing the stability and maneuverability factor. In order to improve the cornering limit of the vehicle, a study to find the balance between the steering systems, the stability of the vehicle, higher lateral acceleration and the cornering limit detection must be conducted. The aim of this research is to study and develop a new suspension system that that will boost the lateral acceleration of the vehicle and ultimately improving the cornering limit of the vehicle. This research will also study environmental factor and the stability factor of the new suspension system. The double wishbone suspension system is widely used in four-wheel vehicle especially for high cornering performance sports car and racing car. The double wishbone designs allow the engineer to carefully control the motion of the wheel by controlling such parameters as camber angle, caster angle, toe pattern, roll center height, scrub radius, scuff and more. The development of the new suspension system will focus on the ability of the new suspension system to optimize the camber control and to improve the camber limit during a cornering motion. The research will be carried out using the CAE analysis tool. Using this analysis tool we will develop a JSAE Formula Machine equipped with the double wishbone system and also the new suspension system and conduct simulation and conduct studies on performance of both suspension systems.

Keywords: automobile, camber thrust, cornering force, suspension

Procedia PDF Downloads 323

Authors: Aishwarya Venkat, Anastasia Marshak, Ryan B. Simpson, Elena N. Naumova

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Livestock ownership is simultaneously linked to improved nutritional status through increased availability of animal-source protein, and increased risk of enteric infections through higher exposure to contaminated water sources. Agrarian and agro-pastoral households, especially those with cattle, goats, and sheep, are highly dependent on seasonally various environmental conditions, which directly impact nutrition and health. This study explores global spatiotemporally explicit evidence regarding the relationship between livestock ownership, enteric infections, and malnutrition. Seasonal and cyclical fluctuations, as well as mediating effects, are further examined to elucidate health and nutrition outcomes of individual and communal livestock ownership. The US Agency for International Development’s Demographic and Health Surveys (DHS) and the United Nations International Children's Emergency Fund’s Multi-Indicator Cluster Surveys (MICS) provide valuable sources of household-level information on anthropometry, asset ownership, and disease outcomes. These data are especially important in data-sparse regions, where surveys may only be conducted in the aftermath of emergencies. Child-level disease history, anthropometry, and household-level asset ownership information have been collected since DHS-V (2003-present) and MICS-III (2005-present). This analysis combines over 15 years of survey data from DHS and MICS to study 2,466,257 children under age five from 82 countries. Subnational (administrative level 1) measures of diarrhea prevalence, mean livestock ownership by type, mean and median anthropometric measures (height for age, weight for age, and weight for height) were investigated. Effects of several environmental, market, community, and household-level determinants were studied. Such covariates included precipitation, temperature, vegetation, the market price of staple cereals and animal source proteins, conflict events, livelihood zones, wealth indices and access to water, sanitation, hygiene, and public health services. Children aged 0 – 6 months, 6 months – 2 years, and 2 – 5 years of age were compared separately. All observations were standardized to interview day of year, and administrative units were harmonized for consistent comparisons over time. Geographically weighted regressions were constructed for each outcome and subnational unit. Preliminary results demonstrate the importance of accounting for seasonality in concurrent assessments of malnutrition and enteric infections. Household assets, including livestock, often determine the intensity of these outcomes. In many regions, livestock ownership affects seasonal fluxes in malnutrition and enteric infections, which are also directly affected by environmental and local factors. Regression analysis demonstrates the spatiotemporal variability in nutrition outcomes due to a variety of causal factors. This analysis presents a synthesis of evidence from global survey data on the interrelationship between enteric infections, malnutrition, and livestock. These results provide a starting point for locally appropriate interventions designed to address this nexus in a timely manner and simultaneously improve health, nutrition, and livelihoods.

Keywords: diarrhea, enteric infections, households, livestock, malnutrition, seasonality

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Authors: Yuexi Xiong, Jingwu He

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The structural components in an energy facility such as steam turbine machines are operated under high stress and elevated temperature in an endured time period and thus the creep deformation and creep rupture failure are important issues that need to be addressed in the design of such components. There are numerous creep models being used for creep analysis that have both advantages and disadvantages in terms of accuracy and efficiency. The Isochronous Creep Analysis is one of the simplified approaches in which a full-time dependent creep analysis is avoided and instead an elastic-plastic analysis is conducted at each time point. This approach has been established based on the rupture dependent creep equations using the well-known Larson-Miller parameter. In this paper, some fundamental aspects of creep deformation and the rupture dependent creep models are reviewed and the analysis procedures using isochronous creep curves are discussed. Four rupture failure criteria are examined from creep fundamental perspectives including criteria of Stress Damage, Strain Damage, Strain Rate Damage, and Strain Capability. The accuracy of these criteria in predicting creep life is discussed and applications of the creep analysis procedures and failure predictions of simple models will be presented. In addition, a new failure criterion is proposed to improve the accuracy and effectiveness of the existing criteria. Comparisons are made between the existing criteria and the new one using several examples materials. Both strain increase and stress relaxation form a full picture of the creep behaviour of a material under high temperature in an endured time period. It is important to bear this in mind when dealing with creep problems. Accordingly there are two sets of rupture dependent creep equations. While the rupture strength vs LMP equation shows how the rupture time depends on the stress level under load controlled condition, the strain rate vs rupture time equation reflects how the rupture time behaves under strain-controlled condition. Among the four existing failure criteria for rupture life predictions, the Stress Damage and Strain Damage Criteria provide the most conservative and non-conservative predictions, respectively. The Strain Rate and Strain Capability Criteria provide predictions in between that are believed to be more accurate because the strain rate and strain capability are more determined quantities than stress to reflect the creep rupture behaviour. A modified Strain Capability Criterion is proposed making use of the two sets of creep equations and therefore is considered to be more accurate than the original Strain Capability Criterion.

Keywords: creep analysis, high temperature mateials, rapture evalution, steam turbine machines

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Authors: Veerle Van Hoeck, Ingrid Somers, Dany Morisset

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Anti-nutritional factors such as non-starch polysaccharides (NSP) are present in viscous cereals used to feed poultry. Therefore, exogenous carbohydrases are commonly added to monogastric feed to degrade these NSP. Our hypothesis is that xylanase not only improves laying hen performance and digestibility but also induces a significant shift in microbial composition within the intestinal tract and, thereby, can cause a prebiotic effect. In this context, a better understanding of whether and how the chicken gut flora can be modulated by xylanase is needed. To do so, in the herein laying hen study, the effects of dietary supplementation of xylanase on performance, digestibility, and cecal microbiome were evaluated. A total of 96 HiSex laying hens was used in this experiment (3 diets and 16 replicates of 2 hens). Xylanase was added to the diets at concentrations of 0, 45,000 (15 g/t XygestTM HT) and 90,000 U/kg (30 g/t Xygest HT). The diets were based on wheat (~55 %), soybean, and sunflower meal. The lowest dosage, 45,000 U/kg, significantly increased average egg weight and improved feed efficiency compared to the control treatment (p < 0.05). Egg quality parameters were significantly improved in the experiment in response to the xylanase addition. For example, during the last 28 days of the trial, the 45,000 U/kg and the 90,000 U/kg treatments exhibited an increase in Haugh units and albumin heights (p < 0.05). Compared with the control, organic matter digestibility and N retention were drastically improved in the 45,000 U/kg treatment group, which implies better nutrient digestibility at this lowest recommended dosage compared to the control (p < 0.05). Furthermore, gross energy and crude fat digestibility were improved significantly for birds fed 90,000 U/kg group compared to the control. Importantly, 16S rRNA gene analysis revealed that xylanase at 45,000 U/kg dosages can exert a prebiotic effect. This conclusion was drawn based on studying the sequence variation in the 16S rRNA gene in order to characterize diverse microbial communities of the cecal content. A significant increase in beneficial bacteria (Lactobacilli spp and Enterococcus casseliflavus) was documented when adding 45,000 U/kg xylanase to the diet of laying hens. In conclusion, dietary supplementation of xylanase, even at the lowest dose of (45,000 U/kg), significantly improved laying hen performance and digestibility. Furthermore, it is generally accepted that a proper bacterial balance between the number of beneficial bacteria and pathogenic bacteria in the intestine is vital for the host. It seems that the xylanase enzyme is able to modulate the laying hen microbiome beneficially and thus exerts a prebiotic effect. This microbiome plasticity in response to the xylanase provides an attractive target for stimulating intestinal health.

Keywords: laying hen, prebiotic, XygestTM HT, xylanase

Procedia PDF Downloads 128

Authors: Stefano Fantin

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The present analysis outcomes from the research undertaken in the course of the European-funded project EUNITY, which targets the gaps in research and development on cybersecurity and privacy between Europe and Japan. Under these auspices, the research presents a study on the policy approach of Japan, the EU and a number of Member States of the Union with regard to the handling and discovery of software vulnerabilities, with the aim of identifying methodological differences and similarities. This research builds upon a functional comparative analysis of both public policies and legal instruments from the identified jurisdictions. The result of this analysis is based on semi-structured interviews with EUNITY partners, as well as by the participation of the researcher to a recent report from the Center for EU Policy Study on software vulnerability. The European Union presents a rather fragmented legal framework on software vulnerabilities. The presence of a number of different legislations at the EU level (including Network and Information Security Directive, Critical Infrastructure Directive, Directive on the Attacks at Information Systems and the Proposal for a Cybersecurity Act) with no clear focus on such a subject makes it difficult for both national governments and end-users (software owners, researchers and private citizens) to gain a clear understanding of the Union’s approach. Additionally, the current data protection reform package (general data protection regulation), seems to create legal uncertainty around security research. To date, at the member states level, a few efforts towards transparent practices have been made, namely by the Netherlands, France, and Latvia. This research will explain what policy approach such countries have taken. Japan has started implementing a coordinated vulnerability disclosure policy in 2004. To date, two amendments can be registered on the framework (2014 and 2017). The framework is furthermore complemented by a series of instruments allowing researchers to disclose responsibly any new discovery. However, the policy has started to lose its efficiency due to a significant increase in reports made to the authority in charge. To conclude, the research conducted reveals two asymmetric policy approaches, time-wise and content-wise. The analysis therein will, therefore, conclude with a series of policy recommendations based on the lessons learned from both regions, towards a common approach to the security of European and Japanese markets, industries and citizens.

Keywords: cybersecurity, vulnerability, European Union, Japan

Procedia PDF Downloads 157

Authors: Pushplata Garg

Abstract:

Mobility, is an integral part of living and sustainability of urban mobility, is essential not only for, but also for addressing global warming and climate change. However, very little is understood about the obstacles/hurdles and likely challenges in the success of plans for sustainable urban mobility in Indian cities from the public perspective. Whereas some of the problems and issues are common to all cities, others vary considerably with financial status, function, the size of cities and culture of a place. Problems and issues similar in all cities relate to availability, efficiency and safety of public transport, last mile connectivity, universal accessibility, and essential planning and design requirements of pedestrians and cyclists are same. However, certain aspects like the type of means of public transportation, priority for cycling and walking, type of roadside activities, are influenced by the size of the town, average educational and income level of public, financial status of the local authorities, and culture of a place. The extent of public awareness, civic sense, maintenance of public spaces and law enforcement vary significantly from large metropolitan cities to small and medium towns in countries like India. Besides, design requirements for shading, location of public open spaces and sitting areas, street furniture, landscaping also vary depending on the climate of the place. Last mile connectivity plays a major role in success/ effectiveness of public transport system in a city. In addition to the provision of pedestrian footpaths connecting important destinations, sitting spaces and necessary amenities/facilities along footpaths; pedestrian movement to public transit stations is encouraged by the presence of quality roadside public spaces. It is not only the visual attractiveness of streetscape or landscape or the public open spaces along pedestrian movement channels but the activities along that make a street vibrant and attractive. These along with adequate spaces to rest and relax encourage people to walk as is observed in cities with successful public transportation systems. The paper discusses problems and issues of pedestrians for last mile connectivity in the context of Delhi, Chandigarh, Gurgaon, and Roorkee- four Indian cities representing varying urban contexts, that is, of metropolitan, large and small cities.

Keywords: pedestrianisation, roadside public spaces, last mile connectivity, sustainable urban mobility

Procedia PDF Downloads 253

Authors: Eiman Kattan, Hong Wei

Abstract:

In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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