Search results for: advanced monitoring and metering infrastructure

Authors: Syeda Fatima Manzelat

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This study investigates the algal genera responsible for biodeterioration, biodegradation, and biological pollution in two historic parks in Milton Keynes, UK: Campbell Park and Great Linford Manor Park. Various sites within these parks were selected to evaluate the morphological, aesthetic, and physical effects of algal growth on park structures and natural features. Specimens and swabs were mechanically collected from the selected sites. Algal specimens were preserved in Lugol’s solution and labelled with standard information for subsequent analysis. Using photomicrography and taxonomic keys, researchers identified algal species from aerial, terrestrial, and aquatic habitats. This comprehensive analysis revealed a diverse range of algae, both homogeneously and non-homogeneously mixed across different environments. The qualitative study identified seven classes of algae. Chlorophyceae, the predominant class, was represented by eleven genera: Chlorella, Chlorococcum, Cladophora, Coenochloris, Cylindrocapsa, Microspora, Prasiola, Spirogyra, Trentepholia, Ulothrix, and Zygnema. Charophyceae included four genera: Cosmarium, Klebsormidium, Mesotaenium, and Mougeotia. Xanthophyceae had two genera: Tribonema and Vaucheria. Bacillariophyceae (diatoms) included six genera: Acnanthes, Bacillaria, Fragilaria, Gomphonema, Synedra, and Tabellaria. Dinophyceae had one Dinoflagellate genus. Rhodophyceae included Bangia and Batrachospermum. Cyanophyceae comprised five genera: Chroococcus, Gloeocapsa, Scytonema, Stigonema, and Oscillatoria. Quantitative analysis revealed that Chlorophyceae was the predominant class across the two parks. Coenochloris, a member of Chlorophyceae, was isolated from thirteen sites, while Gloeocapsa from Cyanophyceae was found at twelve sites. These algae impart various shades of green to the surfaces they colonise, forming biofilms that affect the aesthetic and physical integrity of the structures. Certain algae were park-specific. Prasiola, Vaucheria, and Trentepholia were isolated exclusively from Great Linford Park, with Trentepholia imparting a distinctive orange colour to walls and trees due to the pigments chlorophyll, β-carotene, and quinone. Mesotaenium, Dinoflagellate, Gomphonema, Fragilaria, Tabellaria, and two unidentified genera were exclusive to Campbell Park. The study found the highest number of algal genera (25) in Campbell Park's canal, followed by 21 in the canal at Great Linford Manor Park. Algae were also found on walls, wooden fences, metal sculptures, and railings, causing surface erosion, natural weathering, and cracking. These physical changes lead to technical and mechanical instability, resulting in significant damage to building materials. Algal biofilms secrete organic acids that contribute to the biosolubilisation and biodeterioration of these materials. Additionally, aquatic algal blooms identified during the study release toxins that pose health risks, including allergies, skin rashes, vomiting, diarrhoea, fever, muscle spasms, and respiratory infections. This study highlights specific areas within these historic sites that need attention and provides valuable insights into conservation strategies to mitigate the negative impacts of algal biocolonisation. Recommendations include regular monitoring and preventive measures through various treatments to preserve the integrity of these historic parks.

Keywords: biodeterioration, historic parks, algae, UK

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Authors: Sarah M. Schoellhammer, Stephen Gibb

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Bureaucracy, in particular, its core element, a formal and stable hierarchy of authority, is proving less and less appropriate under the conditions of today’s knowledge economy. Centralization and formalization were consistently found to hinder innovation, undermining cross-functional collaboration, personal responsibility, and flexibility. With its focus on systematical planning, controlling and monitoring the development of new or improved solutions for customers, even innovation management as a discipline is to a significant extent based on a mechanistic understanding of organizations. The most important drivers of innovation, human creativity, and initiative, however, can be more hindered than supported by central elements of classic innovation management, such as predefined innovation strategies, rigid stage gate processes, and decisions made in management gate meetings. Heterarchy, as an alternative network form of organization, is essentially characterized by its dynamic influence structures, whereby the biggest influence is allocated by the collective to the persons perceived the most competent in a certain issue. Theoretical arguments that the non-hierarchical concept better supports innovation than bureaucracy have been supported by empirical research. These prior studies either focus on the structure and general functioning of non-hierarchical organizations or on their innovativeness, that means innovation as an outcome. Complementing classic innovation management approaches, this work aims to shed light on how innovations are initiated and realized in heterarchies in order to identify alternative solutions practiced under conditions of the post-bureaucratic organization. Through an initial individual case study, which is part of a multiple-case project, the innovation practices of an innovative and highly heterarchical medium-sized company in the German fire engineering industry are investigated. In a pragmatic mixed methods approach media resonance, company documents, and workspace architecture are analyzed, in addition to qualitative interviews with the CEO and employees of the case company, as well as a quantitative survey aiming to characterize the company along five scaled dimensions of a heterarchy spectrum. The analysis reveals some similarities and striking differences to approaches suggested by classic innovation management. The studied heterarchy has no predefined innovation strategy guiding new product and service development. Instead, strategic direction is provided by the CEO, described as visionary and creative. Procedures for innovation are hardly formalized, with new product ideas being evaluated on the basis of gut feeling and flexible, rather general criteria. Employees still being hesitant to take responsibility and make decisions, hierarchical influence is still prominent. Described as open-minded and collaborative, culture and leadership were found largely congruent with definitions of innovation culture. Overall, innovation efforts at the case company tend to be coordinated more through cultural than through formal organizational mechanisms. To better enable innovation in mainstream organizations, responsible practitioners are recommended not to limit changes to reducing the central elements of the bureaucratic organization, formalization, and centralization. The freedoms this entails need to be sustained through cultural coordination mechanisms, with personal initiative and responsibility by employees as well as common innovation-supportive norms and values. These allow to integrate diverse competencies, opinions, and activities and, thus, to guide innovation efforts.

Keywords: bureaucracy, heterarchy, innovation management, values

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Authors: Stephan Treuke

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The paper analyses the neighbourhood effects on the economic mobility of the inhabitants of three segregated communities of Salvador (Brazil), in other words, the socio-economic advantages and disadvantages affecting the lives of poor people due to their embeddedness in specific socio-residential contexts. Recent studies performed in Brazilian metropolis have concentrated on the structural dimensions of negative externalities in order to explain neighbourhood-level variations in a field of different phenomena (delinquency, violence, access to the labour market and education) in spatial isolated and socially homogeneous slum areas (favelas). However, major disagreement remains whether the contiguity between residents of poor neighbourhoods and higher-class condominio-dwellers provides structures of opportunities or whether it fosters socio-spatial stigmatization. Based on a set of interviews, investigating the variability of interpersonal networks and their activation in the struggle for economic inclusion, the study confirms that the proximity of Nordeste de Amaralina to middle-/upper-class communities affects positively the access to labour opportunities. Nevertheless, residential stigmatization, as well as structures of social segmentation, annihilate these potentials. The lack of exposition to individuals and groups extrapolating from the favela’s social, educational and cultural context restricts the structures of opportunities to local level. Therefore, residents´ interpersonal networks reveal a high degree of redundancy and localism, based on bonding ties connecting family and neighbourhood members. The resilience of segregational structures in Plataforma contributes to the naturalization of social distance patters. It’s embeddedness in a socially homogeneous residential area (Subúrbio Ferroviário), growing informally and beyond official urban politics, encourages the construction of isotopic patterns of sociability, sharing the same values, social preferences, perspectives and behaviour models. Whereas it’s spatial isolation correlates with the scarcity of economic opportunities, the social heterogeneity of Fazenda Grande II interviewees and the socialising effects of public institutions mitigate the negative repercussions of segregation. The networks’ composition admits a higher degree of heterophilia and a greater proportion of bridging ties accounting for the access to broader information actives and facilitating economic mobility. The variability observed within the three different scenarios urges to reflect about the responsability of urban politics when it comes to the prevention or consolidation of the social segregation process in Salvador. Instead of promoting the local development of the favela Plataforma, public housing programs priorize technocratic habitational solutions without providing the residents’ socio-economic integration. The impact of negative externalities related to the homogeneously poor neighbourhood is potencialized in peripheral areas, turning its’ inhabitants socially invisible, thus being isolated from other social groups. The example of Nordeste de Amaralina portrays the failing interest of urban politics to bridge the social distances structuring the brazilian society’s rigid stratification model, founded on mecanisms of segmentation (unequal access to labour market and education system, public transport, social security and law protection) and generating permanent conflicts between the two socioeconomically distant groups living in geographic contiguity. Finally, in the case of Fazenda Grande II, the public investments in both housing projects and complementary infrastructure (e.g. schools, hospitals, community center, police stations, recreation areas) contributes to the residents’ socio-economic inclusion.

Keywords: economic mobility, neighborhood effects, Salvador, segregation

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Authors: Inna Kornienko, Svetlana Guryeva, Natalia Danilova, Elena Petersen

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Drug toxicity often goes undetected until clinical trials, the most expensive and dangerous phase of drug development. Both human cell culture and animal studies have limitations that cannot be overcome by improvements in drug testing protocols. Tissue engineering is an emerging alternative approach to creating models of human malignant tumors for experimental oncology, personalized medicine, and drug discovery studies. This new generation of bioengineered tumors provides an opportunity to control and explore the role of every component of the model system including cell populations, supportive scaffolds, and signaling molecules. An area that could greatly benefit from these models is cancer research. Recent advances in tissue engineering demonstrated that decellularized tissue is an excellent scaffold for tissue engineering. Decellularization of donor organs such as heart, liver, and lung can provide an acellular, naturally occurring three-dimensional biologic scaffold material that can then be seeded with selected cell populations. Preliminary studies in animal models have provided encouraging results for the proof of concept. Decellularized Organs preserve organ microenvironment, which is critical for cancer metastasis. Utilizing 3D tumor models results greater proximity of cell culture morphological characteristics in a model to its in vivo counterpart, allows more accurate simulation of the processes within a functioning tumor and its pathogenesis. 3D models allow study of migration processes and cell proliferation with higher reliability as well. Moreover, cancer cells in a 3D model bear closer resemblance to living conditions in terms of gene expression, cell surface receptor expression, and signaling. 2D cell monolayers do not provide the geometrical and mechanical cues of tissues in vivo and are, therefore, not suitable to accurately predict the responses of living organisms. 3D models can provide several levels of complexity from simple monocultures of cancer cell lines in liquid environment comprised of oxygen and nutrient gradients and cell-cell interaction to more advanced models, which include co-culturing with other cell types, such as endothelial and immune cells. Following this reasoning, spheroids cultivated from one or multiple patient-derived cell lines can be utilized to seed the matrix rather than monolayer cells. This approach furthers the progress towards personalized medicine. As an initial step to create a new ex vivo tissue engineered model of a cancer tumor, optimized protocols have been designed to obtain organ-specific acellular matrices and evaluate their potential as tissue engineered scaffolds for cultures of normal and tumor cells. Decellularized biomatrix was prepared from animals’ kidneys, urethra, lungs, heart, and liver by two decellularization methods: perfusion in a bioreactor system and immersion-agitation on an orbital shaker with the use of various detergents (SDS, Triton X-100) in different concentrations and freezing. Acellular scaffolds and tissue engineered constructs have been characterized and compared using morphological methods. Models using decellularized matrix have certain advantages, such as maintaining native extracellular matrix properties and biomimetic microenvironment for cancer cells; compatibility with multiple cell types for cell culture and drug screening; utilization to culture patient-derived cells in vitro to evaluate different anticancer therapeutics for developing personalized medicines.

Keywords: 3D models, decellularization, drug discovery, drug toxicity, scaffolds, spheroids, tissue engineering

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Authors: Carlos Amnael Orozco-Diaz, Robert David Moorehead, Gwendolen Reilly, Fiona Gilchrist, Cheryl Ann Miller

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The current gold-standard for maxillofacial reconstruction surgery (MRS) utilizes auto-grafted cancellous bone as a filler. This study was aimed towards developing a polylactic-acid/hydroxyapatite (PLA-HA) composite suitable for fused-deposition 3D printing. Functionalization of the polymer through the addition of HA was directed to promoting bone-regeneration properties so that the material can rival the performance of cancellous bone grafts in terms of bone-lesion repair. This kind of composite enables the production of MRS implants based off 3D-reconstructions from image studies – namely computed tomography – for anatomically-correct fitting. The present study encompassed in-vitro degradation and in-vitro biocompatibility profiling for 3D-printed PLA and PLA-HA composites. PLA filament (Verbatim Co.) and Captal S hydroxyapatite micro-scale HA powder (Plasma Biotal Ltd) were used to produce PLA-HA composites at 5, 10, and 20%-by-weight HA concentration. These were extruded into 3D-printing filament, and processed in a BFB-3000 3D-Printer (3D Systems Co.) into tensile specimens, and were mechanically challenged as per ASTM D638-03. Furthermore, tensile specimens were subjected to accelerated degradation in phosphate-buffered saline solution at 70°C for 23 days, as per ISO-10993-13-2010. This included monitoring of mass loss (through dry-weighing), crystallinity (through thermogravimetric analysis/differential thermal analysis), molecular weight (through gel-permeation chromatography), and tensile strength. In-vitro biocompatibility analysis included cell-viability and extracellular matrix deposition, which were performed both on flat surfaces and on 3D-constructs – both produced through 3D-printing. Discs of 1 cm in diameter and cubic 3D-meshes of 1 cm3 were 3D printed in PLA and PLA-HA composites (n = 6). The samples were seeded with 5000 MG-63 osteosarcoma-like cells, with cell viability extrapolated throughout 21 days via resazurin reduction assays. As evidence of osteogenicity, collagen and calcium deposition were indirectly estimated through Sirius Red staining and Alizarin Red staining respectively. Results have shown that 3D printed PLA loses structural integrity as early as the first day of accelerated degradation, which was significantly faster than the literature suggests. This was reflected in the loss of tensile strength down to untestable brittleness. During degradation, mass loss, molecular weight, and crystallinity behaved similarly to results found in similar studies for PLA. All composite versions and pure PLA were found to perform equivalent to tissue-culture plastic (TCP) in supporting the seeded-cell population. Significant differences (p = 0.05) were found on collagen deposition for higher HA concentrations, with composite samples performing better than pure PLA and TCP. Additionally, per-cell-calcium deposition on the 3D-meshes was significantly lower when comparing 3D-meshes to discs of the same material (p = 0.05). These results support the idea that 3D-printable PLA-HA composites are a viable resorbable material for artificial grafts for bone-regeneration. Degradation data suggests that 3D-printing of these materials – as opposed to other manufacturing methods – might result in faster resorption than currently-used PLA implants.

Keywords: bone regeneration implants, 3D-printing, in vitro testing, biocompatibility, polymer degradation, polymer-ceramic composites

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Authors: Dhekra Khazri, Hakim Gabtni

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Because of Sidi Bouzid water table overexploitation, this study aims at integrating geophysical methods to determinate aquifers geometry assessing their geological situation and geophysical characteristics. However in highly tectonic zones controlled by Atlassic structural features with NE-SW major directions (central Tunisia), Bouguer gravimetric responses of some areas can be as much dominated by the regional structural tendency, as being non-identified or either defectively interpreted such as the case of Sidi Bouzid basin. This issue required a residual gravity anomaly elaboration isolating the Sidi Bouzid basin gravity response ranging between -8 and -14 mGal and crucial for its aquifers geometry characterization. Several gravity techniques helped constructing the Sidi Bouzid basin's residual gravity anomaly, such as Upwards continuation compared to polynomial regression trends and power spectrum analysis detecting deep basement sources at (3km), intermediate (2km) and shallow sources (1km). A 3D Euler Deconvolution was also performed detecting deepest accidents trending NE-SW, N-S and E-W with depth values reaching 5500 m and delineating the main outcropping structures of the study area. Further gravity treatments highlighted the subsurface geometry and structural features of Sidi Bouzid basin over Horizontal and vertical gradient, and also filters based on them such as Tilt angle and Source Edge detector locating rooted edges or peaks from potential field data detecting a new E-W lineament compartmentalizing the Sidi Bouzid gutter into two unequally residual anomaly and subsiding domains. This subsurface morphology is also detected by the used 2D seismic reflection sections defining the Sidi Bouzid basin as a deep gutter within a tectonic set of negative flower structures, and collapsed and tilted blocks. Furthermore, these structural features were confirmed by forward gravity modeling process over several modeled residual gravity profiles crossing the main area. Sidi Bouzid basin (central Tunisia) is also of a big interest cause of the unknown total thickness and the undefined substratum of its siliciclastic Tertiary package, and its aquifers unbounded structural subsurface features and deep accidents. The Combination of geological, hydrogeological and geophysical methods is then of an ultimate need. Therefore, a geophysical methods integration based on gravity survey supporting available seismic data through forward gravity modeling, enhanced lateral and vertical extent definition of the basin's complex sedimentary fill via 3D gravity models, improved depth estimation by a depth to basement modeling approach, and provided 3D isochronous seismic mapping visualization of the basin's Tertiary complex refining its geostructural schema. A subsurface basin geomorphology mapping, over an ultimate matching between the basin's residual gravity map and the calculated theoretical signature map, was also displayed over the modeled residual gravity profiles. An ultimate multidisciplinary geophysical study of the Sidi Bouzid basin aquifers can be accomplished via an aeromagnetic survey and a 4D Microgravity reservoir monitoring offering temporal tracking of the target aquifer's subsurface fluid dynamics enhancing and rationalizing future groundwater exploitation in this arid area of central Tunisia.

Keywords: aquifer geometry, geophysics, 3D gravity modeling, improved depths, source edge detector

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Authors: Anne E. Goodenough

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One of the most important roles of higher education professionals is to ensure that graduates have excellent employment prospects. This means providing students with the skills necessary to be immediately effective in the workplace. Increasingly, universities are seeking to achieve this by moving from lecture-based and campus-delivered curricula to more varied delivery, which takes students out of their academic comfort zone and allows them to engage with, and be challenged by, real world issues. One popular approach is integration of problem-based learning (PBL) projects into curricula. However, although the potential benefits of PBL are considerable, it can be difficult to devise projects that are meaningful, such that they can be regarded as mere ‘hoop jumping’ exercises. This study examines three-way partnerships between academics, students, and external link organizations. It studied the experiences of all partners involved in different collaborative projects to identify how benefits can be maximized and challenges overcome. Focal collaborations included: (1) development of real-world modules with novel assessment whereby the organization became the ‘client’ for student consultancy work; (2) frameworks where students collected/analyzed data for link organizations in research methods modules; (3) placement-based internships and dissertations; (4) immersive fieldwork projects in novel locations; and (5) students working as partners on staff-led research with link organizations. Focus groups, questionnaires and semi-structured interviews were used to identify opportunities and barriers, while quantitative analysis of students’ grades was used to determine academic effectiveness. Common challenges identified by academics were finding suitable link organizations and devising projects that simultaneously provided education opportunities and tangible benefits. There was no ‘one size fits all’ formula for success, but careful planning and ensuring clarity of roles/responsibilities were vital. Students were very positive about collaboration projects. They identified benefits to confidence, time-keeping and communication, as well as conveying their enthusiasm when their work was of benefit to the wider community. They frequently highlighted employability opportunities that collaborative projects opened up and analysis of grades demonstrated the potential for such projects to increase attainment. Organizations generally recognized the value of project outputs, but often required considerable assistance to put the right scaffolding in place to ensure projects worked. Benefits were maximized by ensuring projects were well-designed, innovative, and challenging. Co-publication of projects in peer-reviewed journals sometimes gave additional benefits for all involved, being especially beneficial for student curriculum vitae. PBL and student projects are by no means new pedagogic approaches: the novelty here came from creating meaningful three-way partnerships between academics, students, and link organizations at all undergraduate levels. Such collaborations can allow students to make a genuine contribution to knowledge, answer real questions, solve actual problems, all while providing tangible benefits to organizations. Because projects are actually needed, students tend to engage with learning at a deep level. This enhances student experience, increases attainment, encourages development of subject-specific and transferable skills, and promotes networking opportunities. Such projects frequently rely upon students and staff working collaboratively, thereby also acting to break down the traditional teacher/learner division that is typically unhelpful in developing students as advanced learners.

Keywords: higher education, employability, link organizations, innovative teaching and learning methods, interactions between enterprise and education, student experience

Procedia PDF Downloads 175

Authors: T. Schilirò, S. Bonetta, S. Bonetta, E. Ceretti, D. Feretti, I. Zerbini, V. Romanazzi, S. Levorato, T. Salvatori, S. Vannini, M. Verani, C. Pignata, F. Bagordo, G. Gilli, S. Bonizzoni, A. Bonetti, E. Carraro, U. Gelatti

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Air pollution is one of the most important worldwide health concern. In the last years, in both the US and Europe, new directives and regulations supporting more restrictive pollution limits were published. However, the early effects of air pollution occur, especially for the urban population. Several epidemiological and toxicological studies have documented the remarkable effect of particulate matter (PM) in increasing morbidity and mortality for cardiovascular disease, lung cancer and natural cause mortality. The finest fractions of PM (PM with aerodynamic diameter <2.5 µm and less) play a major role in causing chronic diseases. The International Agency for Research on Cancer (IARC) has recently classified air pollution and fine PM as carcinogenic to human (1 Group). The structure and composition of PM influence the biological properties of particles. The chemical composition varies with season and region of sampling, photochemical-meteorological conditions and sources of emissions. The aim of the MAPEC (Monitoring Air Pollution Effects on Children for supporting public health policy) study is to evaluate the associations between air pollution and biomarkers of early biological effects in oral mucosa cells of 6-8 year old children recruited from first grade schools. The study was performed in five Italian towns (Brescia, Torino, Lecce, Perugia and Pisa) characterized by different levels of airborne PM (PM10 annual average from 44 µg/m3 measured in Torino to 20 µg/m3 measured in Lecce). Two to five schools for each town were chosen to evaluate the variability of pollution within the same town. Child exposure to urban air pollution was evaluated by collecting ultrafine PM (PM0.5) in the school area, on the same day of biological sampling. PM samples were collected for 72h using a high-volume gravimetric air sampler and glass fiber filters in two different seasons (winter and spring). Gravimetric analysis of the collected filters was performed; PM0.5 organic extracts were chemically analyzed (PAH, Nitro-PAH) and tested on A549 by the Comet assay and Micronucleus test and on Salmonella strains (TA100, TA98, TA98NR and YG1021) by Ames test. Results showed that PM0.5 represents a high variable PM10 percentage (range 19.6-63%). PM10 concentration were generally lower than 50µg/m3 (EU daily limit). All PM0.5 extracts showed a mutagenic effect with TA98 strain (net revertant/m3 range 0.3-1.5) and suggested the presence of indirect mutagens, while lower effect was observed with TA100 strain. The results with the TA98NR and YG1021 strains showed the presence of nitroaromatic compounds as confirmed by the chemical analysis. No genotoxic or oxidative effect of PM0.5 extracts was observed using the comet assay (with/without Fpg enzyme) and micronucleus test except for some sporadic samples. The low biological effect observed could be related to the low level of air pollution observed in this winter sampling associated to a high atmospheric instability. For a greater understanding of the relationship between PM size, composition and biological effects the results obtained in this study suggest to investigate the biological effect of the other PM fractions and in particular of the PM0.5-1 fraction.

Keywords: airborne PM, ames test, comet assay, micronucleus test

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Authors: George Charkoftakis, Panagiotis Liosatos, Nicolas-Alexander Tatlas, Dimitrios Goustouridis, Stelios M. Potirakis

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E-maintenance is a relatively new concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification by means of a global navigation satellite system (GNSS), cellular connectivity by means of 3G/long-term evolution (LTE) modem, connectivity to on-board diagnostics (OBD), and connectivity to analog and digital sensors by means of a novel design of expansion board. Specifically, the later provides eight analog plus three digital sensor channels, as well as one on-board temperature / relative humidity sensor. The specific device offers a number of adaptability features based on appropriate zero-ohm resistor placement and appropriate value selection for limited number of passive components. For example, although in the standard configuration four voltage analog channels with constant voltage sources for the power supply of the corresponding sensors are available, up to two of these voltage channels can be converted to provide power to the connected sensors by means of corresponding constant current source circuits, whereas all parameters of analog sensor power supply and matching circuits are fully configurable offering the advantage of covering a wide variety of industrial sensors. Note that a key feature of the proposed sensor node, ensuring the reliable operation of the connected sensors, is the appropriate supply of external power to the connected sensors and their proper matching to the IoT sensor node. In standard mode, the IoT sensor node communicates to the data center through 3G/LTE, transmitting all digital/digitized sensor data, IoT device identity, and position. Moreover, the proposed IoT sensor node offers WiFi connectivity to mobile devices (smartphones, tablets) equipped with an appropriate application for the manual registration of vehicle- and driver-specific information, and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware. It is programmed with a high-level language (Python) on top of a modern operating system (Linux). Acknowledgment: This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH—CREATE—INNOVATE (project code: T1EDK- 01359, IntelligentLogger).

Keywords: IoT sensor nodes, e-maintenance, single-board computers, sensor expansion boards, on-board diagnostics

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Authors: Eduardo Lanzagorta Garcia, Chaitra Venkatesh, Romina Pezzoli, Laura Gabriela Rodriguez Barroso, Declan Devine, Margaret E. Brennan Fournet

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New antimicrobial interventions are urgently required to combat rising global health and medical infection challenges. Here, an innovative antimicrobial technology, providing price competitive alternatives to antibiotics and readily integratable with currently technological systems is presented. Two cutting edge antimicrobial materials, antimicrobial peptides (AMPs) and uncompromised sustained Ag+ action from triangular silver nanoplates (TSNPs) reservoirs, are merged for versatile effective antimicrobial action where current approaches fail. Antimicrobial peptides (AMPs) exist widely in nature and have recently been demonstrated for broad spectrum of activity against bacteria, viruses, and fungi. TSNP’s are highly discrete, homogenous and readily functionisable Ag+ nanoreseviors that have a proven amenability for operation within in a wide range of bio-based settings. In a design for advanced antimicrobial sustainable plastics, antimicrobial TSNPs are formulated for processing within biodegradable biopolymers. Histone H5 AMP was selected for its reported strong antimicrobial action and functionalized with the TSNP (AMP-TSNP) in a similar fashion to previously reported TSNP biofunctionalisation methods. A synergy between the propensity of biopolymers for degradation and Ag+ release combined with AMP activity provides a novel mechanism for the sustained antimicrobial action of biopolymeric thin films. Nanoplates are transferred from aqueous phase to an organic solvent in order to facilitate integration within hydrophobic polymers. Extrusion is used in combination with calendering rolls to create thin polymerc film where the nanoplates are embedded onto the surface. The resultant antibacterial functional films are suitable to be adapted for food packing and biomedical applications. TSNP synthesis were synthesized by adapting a previously reported seed mediated approach. TSNP synthesis was scaled up for litre scale batch production and subsequently concentrated to 43 ppm using thermally controlled H2O removal. Nanoplates were transferred from aqueous phase to an organic solvent in order to facilitate integration within hydrophobic polymers. This was acomplised by functionalizing the TSNP with thiol terminated polyethylene glycol and using centrifugal force to transfer them to chloroform. Polycaprolactone (PCL) and Polylactic acid (PLA) were individually processed through extrusion, TSNP and AMP-TSNP solutions were sprayed onto the polymer immediately after exiting the dye. Calendering rolls were used to disperse and incorporate TSNP and TSNP-AMP onto the surface of the extruded films. Observation of the characteristic blue colour confirms the integrity of the TSNP within the films. Antimicrobial tests were performed by incubating Gram + and Gram – strains with treated and non-treated films, to evaluate if bacterial growth was reduced due to the presence of the TSNP. The resulting films successfully incorporated TSNP and AMP-TSNP. Reduced bacterial growth was observed for both Gram + and Gram – strains for both TSNP and AMP-TSNP compared with untreated films indicating antimicrobial action. The largest growth reduction was observed for AMP-TSNP treated films demonstrating the additional antimicrobial activity due to the presence of the AMPs. The potential of this technology to impede bacterial activity in food industry and medical surfaces will forge new confidence in the battle against antibiotic resistant bacteria, serving to greatly inhibit infections and facilitate patient recovery.

Keywords: antimicrobial, biodegradable, peptide, polymer, nanoparticle

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Authors: G. K. Viswanadh, B. Rajasekhar, G. Venkata Ramana

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Water distribution networks play a vital role in ensuring a reliable supply of clean water to urban areas. However, they face several challenges, including pressure control, pump speed optimization, and burst event detection. This paper combines insights from two studies to address these critical issues in Water distribution networks, focusing on the specific context of Kapra Municipality, India. The first part of this research concentrates on optimizing pressure control and pump speed in complex Water distribution networks. It utilizes the EPANET- MATLAB Toolkit to integrate EPANET functionalities into the MATLAB environment, offering a comprehensive approach to network analysis. By optimizing Pressure Reduce Valves (PRVs) and variable speed pumps (VSPs), this study achieves remarkable results. In the Benchmark Water Distribution System (WDS), the proposed PRV optimization algorithm reduces average leakage by 20.64%, surpassing the previous achievement of 16.07%. When applied to the South-Central and East zone WDS of Kapra Municipality, it identifies PRV locations that were previously missed by existing algorithms, resulting in average leakage reductions of 22.04% and 10.47%. These reductions translate to significant daily Water savings, enhancing Water supply reliability and reducing energy consumption. The second part of this research addresses the pressing issue of burst event detection and localization within the Water Distribution System. Burst events are a major contributor to Water losses and repair expenses. The study employs wireless sensor technology to monitor pressure and flow rate in real time, enabling the detection of pipeline abnormalities, particularly burst events. The methodology relies on transient analysis of pressure signals, utilizing Cumulative Sum and Wavelet analysis techniques to robustly identify burst occurrences. To enhance precision, burst event localization is achieved through meticulous analysis of time differentials in the arrival of negative pressure waveforms across distinct pressure sensing points, aided by nodal matrix analysis. To evaluate the effectiveness of this methodology, a PVC Water pipeline test bed is employed, demonstrating the algorithm's success in detecting pipeline burst events at flow rates of 2-3 l/s. Remarkably, the algorithm achieves a localization error of merely 3 meters, outperforming previously established algorithms. This research presents a significant advancement in efficient burst event detection and localization within Water pipelines, holding the potential to markedly curtail Water losses and the concomitant financial implications. In conclusion, this combined research addresses critical challenges in Water distribution networks, offering solutions for optimizing pressure control, pump speed, burst event detection, and localization. These findings contribute to the enhancement of Water Distribution System, resulting in improved Water supply reliability, reduced Water losses, and substantial cost savings. The integrated approach presented in this paper holds promise for municipalities and utilities seeking to improve the efficiency and sustainability of their Water distribution networks.

Keywords: pressure reduce valve, complex networks, variable speed pump, wavelet transform, burst detection, CUSUM (Cumulative Sum), water pipeline monitoring

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Authors: Glauco M. M. M. Lustosa, João Paulo C. Costa, Sonia M. Zanetti, Mario Cilense, Leinig Antônio Perazolli, Maria Aparecida Zaghete

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The contamination of the environment has been one of the biggest problems of our time, mostly due to developments of many industries. SnO2 is an n-type semiconductor with band gap about 3.5 eV and has its electrical conductivity dependent of type and amount of modifiers agents added into matrix ceramic during synthesis process, allowing applications as sensing of gaseous pollutants on ambient. The chemical synthesis by polymeric precursor method consists in a complexation reaction between tin ion and citric acid at 90 °C/2 hours and subsequently addition of ethyleneglycol for polymerization at 130 °C/2 hours. It also prepared polymeric resin of zinc, cobalt and niobium ions. Stoichiometric amounts of the solutions were mixed to obtain the systems (Zn, Nb)-SnO2 and (Co, Nb) SnO2 . The metal immobilization reduces its segregation during the calcination resulting in a crystalline oxide with high chemical homogeneity. The resin was pre-calcined at 300 °C/1 hour, milled in Atritor Mill at 500 rpm/1 hour, and then calcined at 600 °C/2 hours. X-Ray Diffraction (XDR) indicated formation of SnO2 -rutile phase (JCPDS card nº 41-1445). The characterization by Scanning Electron Microscope of High Resolution showed spherical ceramic powder nanostructured with 10-20 nm of diameter. 20 mg of SnO2 -based powder was kept in 20 ml of isopropyl alcohol and then taken to an electrophoretic deposition (EPD) system. The EPD method allows control the thickness films through the voltage or current applied in the electrophoretic cell and by the time used for deposition of ceramics particles. This procedure obtains films in a short time with low costs, bringing prospects for a new generation of smaller size devices with easy integration technology. In this research, films were obtained in an alumina substrate with interdigital electrodes after applying 2 kV during 5 and 10 minutes in cells containing alcoholic suspension of (Zn, Nb)-SnO2 and (Co, Nb) SnO2 of powders, forming a sensing layer. The substrate has designed integrated micro hotplates that provide an instantaneous and precise temperature control capability when a voltage is applied. The films were sintered at 900 and 1000 °C in a microwave oven of 770 W, adapted by the research group itself with a temperature controller. This sintering is a fast process with homogeneous heating rate which promotes controlled growth of grain size and also the diffusion of modifiers agents, inducing the creation of intrinsic defects which will change the electrical characteristics of SnO2 -based powders. This study has successfully demonstrated a microfabricated system with an integrated micro-hotplate for detection of CO and NO2 gas at different concentrations and temperature, with self-heating SnO2 - based nanoparticles films, being suitable for both industrial process monitoring and detection of low concentrations in buildings/residences in order to safeguard human health. The results indicate the possibility for development of gas sensors devices with low power consumption for integration in portable electronic equipment with fast analysis. Acknowledgments The authors thanks to the LMA-IQ for providing the FEG-SEM images, and the financial support of this project by the Brazilian research funding agencies CNPq, FAPESP 2014/11314-9 and CEPID/CDMF- FAPESP 2013/07296-2.

Keywords: chemical synthesis, electrophoretic deposition, self-heating, gas sensor

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Authors: Taikchan Lildar, Ayesha Samad, Suraj Sookhu

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Atrial fibrillation with rapid ventricular response results in the loss of atrial kick and shortened ventricular filling time, which often leads to decompensated heart failure. Pharmacologic rhythm control is the treatment of choice, and patients frequently benefit from the restoration of sinus rhythm. When pharmacologic treatment is unsuccessful or a patient declines hemodynamically, direct cardioversion is the treatment of choice. Torsades de pointes or “twisting of the points'' in French, is a rare but under-appreciated risk of cardioversion therapy and accounts for a significant number of sudden cardiac death each year. A 61-year-old female with no significant past medical history presented to the Emergency Department with worsening dyspnea. An electrocardiogram showed atrial fibrillation with rapid ventricular response, and a chest X-ray was significant for bilateral pulmonary vascular congestion. Full-dose anticoagulation and diuresis were initiated with moderate improvement in symptoms. A transthoracic echocardiogram revealed biventricular systolic dysfunction with a left ventricular ejection fraction of 30%. After consultation with an electrophysiologist, the consensus was to proceed with the restoration of sinus rhythm, which would likely improve the patient’s heart failure symptoms and possibly the ejection fraction. A transesophageal echocardiogram was negative for left atrial appendage thrombus; the patient was treated with a loading dose of amiodarone and underwent successful direct current cardioversion with 200 Joules. The patient was placed on telemetry monitoring for 24 hours and was noted to have frequent premature ventricular contractions with subsequent degeneration to torsades de pointes. The patient was found unresponsive and pulseless; cardiopulmonary resuscitation was initiated with cardioversion, and return of spontaneous circulation was achieved after four minutes to normal sinus rhythm. Post-cardiac arrest electrocardiogram showed sinus bradycardia with heart-rate corrected QT interval of 592 milliseconds. The patient continued to have frequent premature ventricular contractions and required two additional cardioversions to achieve a return of spontaneous circulation with intravenous magnesium and lidocaine. An automatic implantable cardioverter-defibrillator was subsequently implanted for secondary prevention of sudden cardiac death. The backup pacing rate of the automatic implantable cardioverter-defibrillator was set higher than usual in an attempt to prevent premature ventricular contractions-induced torsades de pointes. The patient did not have any further ventricular arrhythmias after implantation of the automatic implantable cardioverter-defibrillator. Overdrive pacing is a method utilized to treat premature ventricular contractions-induced torsades de pointes by preventing a patient’s susceptibility to R on T-wave-induced ventricular arrhythmias. Pacing at a rate of 90 beats per minute succeeded in controlling the arrhythmia without the need for traumatic cardiac defibrillation. In our patient, conversion of atrial fibrillation with rapid ventricular response to normal sinus rhythm resulted in a slower heart rate and an increased probability of premature ventricular contraction occurring on the T-wave and ensuing ventricular arrhythmia. This case highlights direct current cardioversion for atrial fibrillation with rapid ventricular response resulting in persistent ventricular arrhythmia requiring an automatic implantable cardioverter-defibrillator placement with overdrive pacing to prevent a recurrence.

Keywords: refractory atrial fibrillation, atrial fibrillation, overdrive pacing, torsades de pointes

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Authors: Christian J. Kennett, Mark A. Baldwin

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As several companies are working towards returning American astronauts back to space on US-made spacecraft, NASA developed a human flight certification-by-test and analysis approach due to the cost-prohibitive nature of extensive testing. This process relies heavily on the quality of analytical models to accurately predict crew injury potential specific to each spacecraft and under dynamic environments not tested. As the prime contractor on the Orion spacecraft, Lockheed Martin was tasked with quantifying the correlation of analytical anthropometric test devices (ATDs), also known as crash test dummies, against test measurements under representative impact conditions. Multiple dynamic impact sled tests were conducted to characterize Hybrid III 5th ATD lumbar, head, and neck responses with and without a modified shuttle-era advanced crew escape suit (ACES) under simulated Orion landing and abort conditions. Each ATD was restrained via a 5-point harness in a mockup Orion seat fixed to a dynamic impact sled at the Wright Patterson Air Force Base (WPAFB) Biodynamics Laboratory in the horizontal impact accelerator (HIA). ATDs were subject to multiple impact magnitudes, half-sine pulse rise times, and XZ - ‘eyeballs out/down’ or Z-axis ‘eyeballs down’ orientations for landing or an X-axis ‘eyeballs in’ orientation for abort. Several helmet constraint devices were evaluated during suited testing. Unique finite element models (FEMs) were developed of the unsuited and suited sled test configurations using an analytical 5th ATD model developed by LSTC (Livermore, CA) and deformable representations of the seat, suit, helmet constraint countermeasures, and body restraints. Explicit FE analyses were conducted using the non-linear solver LS-DYNA. Head linear and rotational acceleration, head rotational velocity, upper neck force and moment, and lumbar force time histories were compared between test and analysis using the enhanced error assessment of response time histories (EEARTH) composite score index. The EEARTH rating paired with the correlation and analysis (CORA) corridor rating provided a composite ISO score that was used to asses model correlation accuracy. NASA occupant protection subject matter experts established an ISO score of 0.5 or greater as the minimum expectation for correlating analytical and experimental ATD responses. Unsuited 5th ATD head X, Z, and resultant linear accelerations, head Y rotational accelerations and velocities, neck X and Z forces, and lumbar Z forces all showed consistent ISO scores above 0.5 in the XZ impact orientation, regardless of peak g-level or rise time. Upper neck Y moments were near or above the 0.5 score for most of the XZ cases. Similar trends were found in the XZ and Z-axis suited tests despite the addition of several different countermeasures for restraining the helmet. For the X-axis ‘eyeballs in’ loading direction, only resultant head linear acceleration and lumbar Z-axis force produced ISO scores above 0.5 whether unsuited or suited. The analytical LSTC 5th ATD model showed good correlation across multiple head, neck, and lumbar responses in both the unsuited and suited configurations when loaded in the XZ ‘eyeballs out/down’ direction. Upper neck moments were consistently the most difficult to predict, regardless of impact direction or test configuration.

Keywords: impact biomechanics, manned spaceflight, model correlation, multi-axial loading

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Authors: Lauren B. Birney

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The envisioned long-term outcome of this three-year research, and implementation plan is for 1) teachers and students to design and build their own computational models of real-world environmental-human health phenomena occurring within the context of the “Human Harbor” and 2) project researchers to evaluate the degree to which these integrated Computer Science (CS) education experiences in New York City (NYC) public school classrooms (PreK-12) impact students’ computational-technical skill development, job readiness, career motivations, and measurable abilities to understand, articulate, and solve the underlying phenomena at the center of their models. This effort builds on the partnership’s successes over the past eight years in developing a benchmark Model of restoration-based Science, Technology, Engineering, and Math (STEM) education for urban public schools and achieving relatively broad-based implementation in the nation’s largest public school system. The Billion Oyster Project Curriculum and Community Enterprise for Restoration Science (BOP-CCERS STEM + Computing) curriculum, teacher professional developments, and community engagement programs have reached more than 200 educators and 11,000 students at 124 schools, with 84 waterfront locations and Out of School of Time (OST) programs. The BOP-CCERS Partnership is poised to develop a more refined focus on integrating computer science across the STEM domains; teaching industry-aligned computational methods and tools; and explicitly preparing students from the city’s most under-resourced and underrepresented communities for upwardly mobile careers in NYC’s ever-expanding “digital economy,” in which jobs require computational thinking and an increasing percentage require discreet computer science technical skills. Project Objectives include the following: 1. Computational Thinking (CT) Integration: Integrate computational thinking core practices across existing middle/high school BOP-CCERS STEM curriculum as a means of scaffolding toward long term computer science and computational modeling outcomes. 2. Data Science and Data Analytics: Enabling Researchers to perform interviews with Teachers, students, community members, partners, stakeholders, and Science, Technology, Engineering, and Mathematics (STEM) industry Professionals. Collaborative analysis and data collection were also performed. As a centerpiece, the BOP-CCERS partnership will expand to include a dedicated computer science education partner. New York City Department of Education (NYCDOE), Computer Science for All (CS4ALL) NYC will serve as the dedicated Computer Science (CS) lead, advising the consortium on integration and curriculum development, working in tandem. The BOP-CCERS Model™ also validates that with appropriate application of technical infrastructure, intensive teacher professional developments, and curricular scaffolding, socially connected science learning can be mainstreamed in the nation’s largest urban public school system. This is evidenced and substantiated in the initial phases of BOP-CCERS™. The BOP-CCERS™ student curriculum and teacher professional development have been implemented in approximately 24% of NYC public middle schools, reaching more than 250 educators and 11,000 students directly. BOP-CCERS™ is a fully scalable and transferable educational model, adaptable to all American school districts. In all settings of the proposed Phase IV initiative, the primary beneficiary group will be underrepresented NYC public school students who live in high-poverty neighborhoods and are traditionally underrepresented in the STEM fields, including African Americans, Latinos, English language learners, and children from economically disadvantaged households. In particular, BOP-CCERS Phase IV will explicitly prepare underrepresented students for skilled positions within New York City’s expanding digital economy, computer science, computational information systems, and innovative technology sectors.

Keywords: computer science, data science, equity, diversity and inclusion, STEM education

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Authors: Marija Mihajlovic Pereira

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Teaching and learning a musical instrument is challenging for both teachers and students. Teachers generally use diverse strategies to resolve students' particular issues in a one-to-one context. Considering individual sessions as a supportive educational context, the teacher can play a decisive role in stimulating and promoting self-regulated learning strategies, especially with beginning learners. The teachers who promote self-controlling behaviors, strategic monitoring, and regulation of actions toward goals could expect their students to practice more qualitatively and consciously. When encouraged to adopt self-regulation habits, students' could benefit from greater productivity on a longer path. Founded on Bary Zimmerman's cyclical model that comprehends three phases - forethought, performance, and self-reflection, this work aims to articulate self-regulated and music learning. Self-regulated learning appeals to the individual's attitude in planning, controlling, and reflecting on their performance. Furthermore, this study aimed to present an observation grid for perceiving teaching instructions that encourage students' controlling cognitive behaviors in light of the belief that conscious promotion of self-regulation may motivate strategic actions toward goals in musical performance. The participants, two teachers, and two students have been involved in the social inclusion project in Lisbon (Portugal). The author and one independent inter-observer analyzed six video-recorded string instrument lessons. The data correspond to three sessions per teacher lectured to one (different) student. Violin (f) and violoncello (m) teachers hold a Master's degree in music education and approximately five years of experience. In their second year of learning an instrument, students have acquired reasonable skills in musical reading, posture, and sound quality until then. The students also manifest positive learning behaviors, interest in learning a musical instrument, although their study habits are still inconsistent. According to the grid's four categories (parent codes), in-class rehearsal frames were coded using MaxQda software, version 20, according to the grid's four categories (parent codes): self-regulated learning, teaching verbalizations, teaching strategies, and students' in-class performance. As a result, selected rehearsal frames qualitatively describe teaching instructions that might promote students' body and hearing awareness, such as "close the eyes while playing" or "sing to internalize the pitch." Another analysis type, coding the short video events according to the observation grid's subcategories (child codes), made it possible to perceive the time teachers dedicate to specific verbal or non-verbal strategies. Furthermore, a coding overlay analysis indicated that teachers tend to stimulate. (i) Forethought – explain tasks, offer feedback and ensure that students identify a goal, (ii) Performance – teach study strategies and encourage students to sing and use vocal abilities to ensure inner audition, (iii) Self-reflection – frequent inquiring and encouraging the student to verbalize their perception of performance. Although developed in the context of individual string instrument lessons, this classroom observation grid brings together essential variables in a one-to-one lesson. It may find utility in a broader context of music education due to the possibility to organize, observe and evaluate teaching practices. Besides that, this study contributes to cognitive development by suggesting a practical approach to fostering self-regulated learning.

Keywords: music education, observation grid, self-regulated learning, string instruments, teaching practices

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Authors: Aparajita Bhattacharya, Mousumi Dutta, Zakir Husain, Dionne Sequeira, Asima Mukhopadhyay

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Background: Tata Medical Centre (TMC), Kolkata is a major cancer referral centre in Eastern India and neighbouring countries providing state of the art facilities; however, it is a non-profit organisation with patients requiring to pay at subsidised rates. Although a system for social assessment and applying for governmental/ non-governmental (NGO) funds is in place, access is challenging. Amongst gynaecological cancers (GC), ovarian cancer (OC) is associated with the highest treatment cost; majority of which is required at the beginning when complex surgery is performed and funding arrangements cannot be made in time. We therefore appointed a dedicated Medical Social Worker (MSW) in 2016, supported by NGO for GC patients in order to assist patients/family members to access/avail these funds more readily and assist in economic evaluation for both direct and opportunity costs. Objectives: To reflect on our experience and challenges in collecting data on economic evaluation of cancer patients and compare success rates in achieving fund mobilization after introduction of MSW. Methods: A Retrospective survey. Patients with OC and their relatives were seen by the MSW during the initial outpatients department visit and followed though till discharge from the hospital and during follow-up visits. Assistance was provided in preparing the essential documents/paperwork/contacts for the funding agencies including both governmental (Chief-Minister/Prime-Minister/President) and NGO sources. In addition, a detailed questionnaire was filled up for economic assessment of direct/opportunity costs during the entire treatment and 12 months follow up period which forms a part of the study called HEPTROC (Health economic evaluation of primary treatment for ovarian cancer) developed in collaboration with economics departments of Universities. Results: In 2015, 102 patients were operated for OC; only 16 patients (15.68 %) had availed funding of a total sum of INR 1640000 through the hospital system for social assessment. Following challenges were faced by majority of the relatives: 1. Gathering important documents/proper contact details for governmental funding bodies and difficulty in following up the current status 3. Late arrival of funds. In contrast in 2016, 104 OC patients underwent surgery; the direct cost of treatment was significantly higher (median, INR 300000- 400000) compared to other GCs (n=274). 98/104 (94.23%) OC patients could be helped to apply for funds and 90/104(86.56%) patients received funding amounting to a total of INR 10897000. There has been a tenfold increase in funds mobilized in 2016 after the introduction of dedicated MSW in GC. So far, in 2017 (till June), 46/54(85.18%) OC patients applied for funds and 37/54(68.51%) patients have received funding. In a qualitative survey, all patients appreciated the role of the MSW who subsequently became the key worker for patient follow up and the chief portal for patient reported outcome monitoring. Data collection quality for the HEPTROC study was improved when questionnaires were administered by the MSW compared to researchers. Conclusion: Introduction of cancer specific MSW can expedite the availability of funds required for cancer patients and it can positively impact on patient satisfaction and outcome reporting. The economic assessment will influence fund allocation and decision for policymaking in ovarian cancer. Acknowledgement: Jivdaya Foundation Dallas, Texas.

Keywords: economic evaluation, funding, medical social worker, ovarian cancer

Procedia PDF Downloads 142

Authors: Ali R. Alshawawreh, Francisco Liébana-Cabanillas, Francisco J. Blanco-Encomienda

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Collaboration between marketing and business intelligence (BI) is crucial in today's ever-evolving business landscape. These two domains play pivotal roles in molding customers' experiential knowledge. Marketing insights offer valuable information regarding customer needs, preferences, and behaviors, thus refining marketing strategies and enhancing overall customer experiences. Conversely, BI facilitates data-driven decision-making, leading to heightened operational efficiency, product quality, and customer satisfaction. The analysis of customer data through BI unveils patterns and trends, informing product development, marketing campaigns, and customer service initiatives aimed at enriching experiences and knowledge. Customer experiential knowledge (CEK) encompasses customers' implicit comprehension of consumption experiences influenced by diverse factors, including social and cultural influences. This study primarily focuses on telecommunications companies in Jordan, scrutinizing how experiential customer knowledge mediates the relationship between marketing intelligence, business intelligence, and innovation in product and service offerings. Drawing on theoretical frameworks such as the resource-based view (RBV) and service-dominant logic (SDL), the research aims to comprehend how organizations utilize their resources, particularly knowledge, to foster innovation. Employing a quantitative research approach, the study collected and analyzed primary data to explore hypotheses. The chosen method was justified for its efficacy in handling large sample sizes. Structural equation modeling (SEM) facilitated by Smart PLS software evaluated the relationships between the constructs, followed by mediation analysis to assess the indirect associations in the model. The study findings offer insights into the intricate dynamics of organizational innovation, uncovering the interconnected relationships between business intelligence, customer experiential knowledge-based innovation (CEK-DI), marketing intelligence (MI), and product and service innovation (PSI), underscoring the pivotal role of advanced intelligence capabilities in developing innovative practices rooted in a profound understanding of customer experiences. Organizations equipped with cutting-edge BI tools are better positioned to devise strategies informed by precise insights into customer needs and behaviors. Furthermore, the positive impact of BI on PSI reaffirms the significance of data-driven decision-making in shaping the innovation landscape. Companies leveraging BI demonstrate adeptness in identifying market opportunities guiding the development of novel products and services. The substantial impact of CEK-DI on PSI highlights the crucial role of customer experiences in driving organizational innovation. Firms actively integrating customer insights into their innovation processes are more likely to create offerings aligned with customer expectations, fostering higher levels of product and service innovation. Additionally, the positive and significant effect of MI on CEK-DI underscores the critical role of market insights in shaping innovative strategies. While the relationship between MI and PSI is positive, a slightly weaker significance level indicates a nuanced association, suggesting that while MI contributes to innovation, other factors may also influence the innovation landscape, warranting further exploration. In conclusion, the study underscores the essential role of intelligence capabilities, particularly artificial intelligence, in driving innovation, emphasizing the necessity for organizations to leverage market and customer intelligence for effective and competitive innovation practices. Collaborative efforts between marketing and business intelligence serve as pivotal drivers of innovation, influencing experiential customer knowledge and shaping organizational strategies and practices, ultimately enhancing overall customer experiences and organizational performance.

Keywords: marketing intelligence, business intelligence, product, customer experiential knowledge-driven innovation

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Authors: Oleg Shovkovyy

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This research conducted in response to one of the most pressing questions on the agenda of many public administration offices around the world: “What could be done for better integration and assimilation of immigrants into hosting communities?” In author’s view, the answer could be suggested by immigrants themselves. They, often ‘bogged down in the past,’ snared by own idols and demons, perceive things differently, which, in turn, may result in their inability to integrate smoothly into hosting communities. Brief literature review suggests that perceptions of immigrants are completely neglected or something unsought in the current research on migrants, which, often, based on opinion polls by members of hosting communities themselves or superficial research data by various research organizations. Even those specimens that include voices of immigrants, unlikely to shed any additional light onto the problem simply because certain things are not made to speak out loud, especially to those in whose hands immigrants’ fate is (authorities). In this regard, this qualitative study, conducted by an insider to a few Russian-speaking communities, represents a unique opportunity for all stakeholders to look at the question of integration through the eyes of immigrants, from a different perspective and thus, makes research findings especially valuable for better understanding of the problem. Case study research employed ethnographic methods of gathering data where, approximately 200 Russian-speaking immigrants of first and second generations were closely observed by the Russian-speaking researcher in their usual setting, for eight months, and at different venues. The number of informal interviews with 27 key informants, with whom the researcher managed to establish a good rapport and who were keen enough to share their experiences voluntarily, were conducted. The field notes were taken at 14 locations (study sites) within the Brisbane region of Queensland, Australia. Moreover, all this time, researcher lived in dwelling of one of the immigrants and was an active participant in the social life (worship, picnics, dinners, weekend schools, concerts, cultural events, social gathering, etc.) of observed communities, whose members, to a large extent, belong to various religious lines of the Russian and Protestant Church. It was found that the majority of immigrants had experienced some discrimination in matters of hiring, employment, recognition of educational qualifications from home countries, and simply felt a sort of dislike from society in various everyday situations. Many noted complete absences or very limited state assistance in terms of employment, training, education, and housing. For instance, the Australian Government Department of Human Services not only does not stimulate job search but, on the contrary, encourages to refuse short-term works and employment. On the other hand, offered free courses on adaptation, and the English language proved to be ineffective and unpopular amongst immigrants. Many interviewees have reported overstated requirements for English proficiency and local work experience, whereas it was not critical for the given task or job. Based on the result of long-term monitoring, the researcher also had the courage to assert the negative and decelerating roles of immigrants’ communities, particularly religious communities, on processes of integration and assimilation. The findings suggest that governments should either change current immigration policies in the direction of their toughening or to take more proactive and responsible role in dealing with immigrant-related issues; for instance, increasing assistance and support to all immigrants and probably, paying more attention to and taking stake in managing and organizing lives of immigrants’ communities rather, simply leaving it all to chance.

Keywords: Australia, immigration, integration, perceptions

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Authors: Fahimeh Palizban, Farshad Noravesh, Amir Hossein Saeidian, Mahya Mehrmohamadi

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In the recent decade, the emergence of liquid biopsy has significantly improved cancer monitoring and detection. Dying cells, including those originating from tumors, shed their DNA into the blood and contribute to a pool of circulating fragments called cell-free DNA. Accordingly, identifying the tissue origin of these DNA fragments from the plasma can result in more accurate and fast disease diagnosis and precise treatment protocols. Open chromatin regions are important epigenetic features of DNA that reflect cell types of origin. Profiling these features by DNase-seq, ATAC-seq, and histone ChIP-seq provides insights into tissue-specific and disease-specific regulatory mechanisms. There have been several studies in the area of cancer liquid biopsy that integrate distinct genomic and epigenomic features for early cancer detection along with tissue of origin detection. However, multimodal analysis requires several types of experiments to cover the genomic and epigenomic aspects of a single sample, which will lead to a huge amount of cost and time. To overcome these limitations, the idea of predicting OCRs from WGS is of particular importance. In this regard, we proposed a computational approach to target the prediction of open chromatin regions as an important epigenetic feature from cell-free DNA whole genome sequence data. To fulfill this objective, local sequencing depth will be fed to our proposed algorithm and the prediction of the most probable open chromatin regions from whole genome sequencing data can be carried out. Our method integrates the signal processing method with sequencing depth data and includes count normalization, Discrete Fourie Transform conversion, graph construction, graph cut optimization by linear programming, and clustering. To validate the proposed method, we compared the output of the clustering (open chromatin region+, open chromatin region-) with previously validated open chromatin regions related to human blood samples of the ATAC-DB database. The percentage of overlap between predicted open chromatin regions and the experimentally validated regions obtained by ATAC-seq in ATAC-DB is greater than 67%, which indicates meaningful prediction. As it is evident, OCRs are mostly located in the transcription start sites (TSS) of the genes. In this regard, we compared the concordance between the predicted OCRs and the human genes TSS regions obtained from refTSS and it showed proper accordance around 52.04% and ~78% with all and the housekeeping genes, respectively. Accurately detecting open chromatin regions from plasma cell-free DNA-seq data is a very challenging computational problem due to the existence of several confounding factors, such as technical and biological variations. Although this approach is in its infancy, there has already been an attempt to apply it, which leads to a tool named OCRDetector with some restrictions like the need for highly depth cfDNA WGS data, prior information about OCRs distribution, and considering multiple features. However, we implemented a graph signal clustering based on a single depth feature in an unsupervised learning manner that resulted in faster performance and decent accuracy. Overall, we tried to investigate the epigenomic pattern of a cell-free DNA sample from a new computational perspective that can be used along with other tools to investigate genetic and epigenetic aspects of a single whole genome sequencing data for efficient liquid biopsy-related analysis.

Keywords: open chromatin regions, cancer, cell-free DNA, epigenomics, graph signal processing, correlation clustering

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Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: E Tambo, O. O. Olalubi, E. C. Ugwu, J. Y. Ngogang

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Despite the World Health Organization (WHO) declaration of international health emergency concern, the status quo of responses and efforts to stem the worst-recorded Ebola epidemic Ebola outbreak is still precariously inadequate in most of the affected in West. Mining natural resources have been shown to play a key role in both motivating and fuelling ethnic, civil and armed conflicts that have plagued a number of African countries over the last decade. Revenues from the exploitation of natural resources are not only used in sustaining the national economy but also armies, personal enrichment and building political support. Little is documented on the mining and ecological impact on the emergence and geographical distribution of Ebola in Africa over time and space. We aimed to provide a better understanding of the interconnectedness among issues of mining natural, resource management, mining conflict and post-conflict on Ebola outbreak and how wealth generated from abundant natural resources could be better managed in promoting research and development towards strengthening environmental, socioeconomic and health systems sustainability on Ebola outbreak and other emerging diseases surveillance and responses systems prevention and control, early warning alert, durable peace and sustainable development rather than to fuel conflicts, resurgence and emerging diseases epidemics in the perspective of community and national/regional approach. Our results showed the first assessment of systematic impact of all major minerals conflict events diffusion over space and time and mining activities on nine Ebola genesis and geo-distribution in affected countries across Africa. We demonstrate how, where and when mining activities in Africa increase ecological degradation, conflicts at the local level and then spreads violence across territory and time by enhancing the financial capacities of fighting groups/ethnics and diseases onset. In addition, led process of developing minimum standards for natural resource governance; improving governmental and civil society capacity for natural resource management, including the strengthening of monitoring and enforcement mechanisms; understanding the post-mining and conflicts community or national reconstruction and rehabilitation programmes in strengthening or developing community health systems and regulatory mechanisms. In addition the quest for the control over these resources and illegal mining across the landscape forest incursion provided increase environmental and ecological instability and displacement and disequilibrium, therefore affecting the intensity and duration of mining and conflict/wars and episode of Ebola outbreaks over time and space. We highlight the key findings and lessons learnt in promoting country or community-led process in transforming natural resource wealth from a peace liability to a peace asset. The imperative necessity for advocacy and through facilitating intergovernmental deliberations on critical issues and challenges affecting Africa community transforming exploitation of natural resources from a peace liability to outbreak prevention and control. The vital role of mining in increasing government revenues and expenditures, equitable distribution of wealth and health to all stakeholders, in particular local communities requires coordination, cooperative leadership and partnership in fostering sustainable developmental initiatives from mining context to outbreak and other infectious diseases surveillance responses systems in prevention and control, and judicious resource management.

Keywords: mining, mining conflicts, mines, ecological, Ebola, outbreak, mining companies, miners, impact

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Authors: Sam Weber, Deepak Mishra, Susan Wilde, Elizabeth Kramer

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The frequency and severity of cyanobacteria harmful blooms (CyanoHABs) have been increasing over time, with point and non-point source eutrophication and shifting climate paradigms being blamed as the primary culprits. Excessive nutrients, warm temperatures, quiescent water, and heavy and less regular rainfall create more conducive environments for CyanoHABs. CyanoHABs have the potential to produce a spectrum of toxins that cause gastrointestinal stress, organ failure, and even death in humans and animals. To promote enhanced, proactive CyanoHAB management, risk modeling using geospatial tools can act as predictive mechanisms to supplement current CyanoHAB monitoring, management and mitigation efforts. The risk maps would empower water managers to focus their efforts on high risk water bodies in an attempt to prevent CyanoHABs before they occur, and/or more diligently observe those waterbodies. For this research, exploratory spatial data analysis techniques were used to identify the strongest predicators for CyanoHAB blooms based on remote sensing-derived cyanobacteria cell density values for 771 waterbodies in the Georgia Piedmont and landscape characteristics of their watersheds. In-situ datasets for cyanobacteria cell density, nutrients, temperature, and rainfall patterns are not widely available, so free gridded geospatial datasets were used as proxy variables for assessing CyanoHAB risk. For example, the percent of a watershed that is agriculture was used as a proxy for nutrient loading, and the summer precipitation within a watershed was used as a proxy for water quiescence. Cyanobacteria cell density values were calculated using atmospherically corrected images from the European Space Agency’s Sentinel-2A satellite and multispectral instrument sensor at a 10-meter ground resolution. Seventeen explanatory variables were calculated for each watershed utilizing the multi-petabyte geospatial catalogs available within the Google Earth Engine cloud computing interface. The seventeen variables were then used in a multiple linear regression model, and the strongest predictors of cyanobacteria cell density were selected for the final regression model. The seventeen explanatory variables included land cover composition, winter and summer temperature and precipitation data, topographic derivatives, vegetation index anomalies, and soil characteristics. Watershed maximum summer temperature, percent agriculture, percent forest, percent impervious, and waterbody area emerged as the strongest predictors of cyanobacteria cell density with an adjusted R-squared value of 0.31 and a p-value ~ 0. The final regression equation was used to make a normalized cyanobacteria cell density index, and a Jenks Natural Break classification was used to assign waterbodies designations of low, medium, or high risk. Of the 771 waterbodies, 24.38% were low risk, 37.35% were medium risk, and 38.26% were high risk. This study showed that there are significant relationships between free geospatial datasets representing summer maximum temperatures, nutrient loading associated with land use and land cover, and the area of a waterbody with cyanobacteria cell density. This data analytics approach to CyanoHAB risk assessment corroborated the literature-established environmental triggers for CyanoHABs, and presents a novel approach for CyanoHAB risk mapping in waterbodies across the greater southeastern United States.

Keywords: cyanobacteria, land use/land cover, remote sensing, risk mapping

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Authors: Julien Caudeville, Muriel Ismert

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Analyzing the relationship between environment and health has become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. These plans have identified the following two priorities: (1) to identify and manage geographic areas, where hotspot exposures are suspected to generate a potential hazard to human health; (2) to reduce exposure inequalities. At a regional scale and fine resolution of exposure outcome prerequisite, environmental monitoring networks are not sufficient to characterize the multidimensionality of the exposure concept. In an attempt to increase representativeness of spatial exposure assessment approaches, risk composite indicators could be built using additional available databases and theoretical framework approaches to combine factor risks. To achieve those objectives, combining data process and transfer modeling with a spatial approach is a fundamental prerequisite that implies the need to first overcome different scientific limitations: to define interest variables and indicators that could be built to associate and describe the global source-effect chain; to link and process data from different sources and different spatial supports; to develop adapted methods in order to improve spatial data representativeness and resolution. A GIS-based modeling platform for quantifying human exposure to chemical substances (PLAINE: environmental inequalities analysis platform) was used to build health risk indicators within the Lorraine region (France). Those indicators combined chemical substances (in soil, air and water) and noise risk factors. Tools have been developed using modeling, spatial analysis and geostatistic methods to build and discretize interest variables from different supports and resolutions on a 1 km2 regular grid within the Lorraine region. By example, surface soil concentrations have been estimated by developing a Kriging method able to integrate surface and point spatial supports. Then, an exposure model developed by INERIS was used to assess the transfer from soil to individual exposure through ingestion pathways. We used distance from polluted soil site to build a proxy for contaminated site. Air indicator combined modeled concentrations and estimated emissions to take in account 30 polluants in the analysis. For water, drinking water concentrations were compared to drinking water standards to build a score spatialized using a distribution unit serve map. The Lden (day-evening-night) indicator was used to map noise around road infrastructures. Aggregation of the different factor risks was made using different methodologies to discuss weighting and aggregation procedures impact on the effectiveness of risk maps to take decisions for safeguarding citizen health. Results permit to identify pollutant sources, determinants of exposure, and potential hotspots areas. A diagnostic tool was developed for stakeholders to visualize and analyze the composite indicators in an operational and accurate manner. The designed support system will be used in many applications and contexts: (1) mapping environmental disparities throughout the Lorraine region; (2) identifying vulnerable population and determinants of exposure to set priorities and target for pollution prevention, regulation and remediation; (3) providing exposure database to quantify relationships between environmental indicators and cancer mortality data provided by French Regional Health Observatories.

Keywords: health risk, environment, composite indicator, hotspot areas

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Authors: Xu Fei (Philip) WU

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As waste recycling concept been accepted more and more in modern societies, the organic portion of the municipal waste become a sires issue in today’s life. Depend on location and season, the organic waste can bee anywhere between 40-65% of total municipal solid waste. Also composting and anaerobic digestion technologies been applied in this field for years, however both process have difficulties been selected by economical and environmental factors. Beside environmental pollution and risk of virus spread, the compost is not a product been welcomed by people even the waste management has to give up them at no cost. The anaerobic digester has to have 70% of water and keep at 35 degree C or above; base on above conditions, the retention time only can be up to two weeks and remain solid has to be dewater and composting again. The enhancive waste water treatment has to be added after. Because these reasons, the voice of suggesting cancelling recycling program and turning all waste to mass burn incinerations have been raised-A process has already been proved has least energy efficiency and most air pollution problem associated process. A newly developed WXF Bio-energy process employs recently developed and patented pre-designed separation, multi-layer and multi-cavity successive bioreactor landfill technology. It features an improved leachate recycling technology, technologies to maximize the biogas generation rate and a reduced overall turnaround period on the land. A single properly designed and operated site can be used indefinitely. In this process, all collected biogas will be processed to eliminate H2S and other hazardous gases. The methane, carbon dioxide and hydrogen will be utilized in a proprietary process to manufacture methanol which can be sold to mitigate operating costs of the landfill. This integration of new processes offers a more advanced alternative to current sanitary landfill, incineration and compost technology. Xu Fei (Philip) Wu Xu Fei Wu is founder and Chief Scientist of W&Y Environmental International Inc. (W & Y), a Canadian environmental and sustainable energy technology company with patented landfill processes and proprietary waste to energy technologies. He has worked in environmental and sustainable energy fields over the last 25 years. Before W&Y, he worked for Conestoga-Rovers & Associates Limited, Microbe Environmental Science and Technology Inc. of Canada and The Ministry of Nuclear Industry and Ministry of Space Flight Industry of China. Xu Fei Wu holds a Master of Engineering Science degree from The University of Western Ontario. I wish present this paper as an oral presentation only Selected Conference Presentations: • “Removal of Phenolic Compounds with Algae” Presented at 25th Canadian Symposium on Water Pollution Research (CAWPRC Conference), Burlington, Ontario Canada. February, 1990 • “Removal of Phenolic Compounds with Algae” Presented at Annual Conference of Pollution Control Association of Ontario, London, Ontario, Canada. April, 1990 • “Removal of Organochlorine Compounds in a Flocculated Algae Photo-Bioreactor” Presented at International Symposium on Low Cost and Energy Saving Wastewater Treatment Technologies (IAWPRC Conference), Kiyoto, Japan, August, 1990 • “Maximizing Production and Utilization of Landfill Gas” 2009 Wuhan International Conference on Environment(CAWPRC Conference, sponsored by US EPA) Wuhan, China. October, 2009. • “WXF Bio-Energy-A Green, Sustainable Waste to Energy Process” Presented at 9Th International Conference Cooperation for Waste Issues, Kharkiv, Ukraine March, 2012 • “A Lannfill Site Can Be Recycled Indefinitely” Presented at 28th International Conference on solid Waste Technology and Management, Philadelphia, Pennsylvania, USA. March, 2013. Hosted by The Journal of Solid Waste Technology and Management.

Keywords: green fuel, waste management, bio-energy, sustainable development, methanol

Procedia PDF Downloads 266

Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

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Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

Procedia PDF Downloads 58

Authors: Dimitrios Tzilopoulos, Panagiotis Symeonidis, Michael Loufakis, Dimosthenis Ioannidis, Dimitrios Tzovaras

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The domestic film industry in Greece has traditionally relied heavily on state support. While film productions are crucial for the country's economy, it has not fully capitalized on attracting and promoting foreign productions. The lack of motivation, organized state support for attraction and licensing, and the absence of location scouting have hindered its potential. Although recent legislative changes have addressed the first two of these issues, the development of a comprehensive location database and a search engine that would effectively support location scouting at the pre-production location scouting is still in its early stages. In addition to the expected benefits of the film, television, marketing, and multimedia industries, a location-scouting service platform has the potential to yield significant financial gains locally and nationally. By promoting featured places like cultural and archaeological sites, natural monuments, and attraction points for visitors, it plays a vital role in both cultural promotion and facilitating tourism development. This study introduces LOCATION3, an internet platform revolutionizing film production location management. It interconnects location providers, film crews, and multimedia stakeholders, offering a comprehensive environment for seamless collaboration. The platform's central geodatabase (PostgreSQL) stores each location’s attributes, while web technologies like HTML, JavaScript, CSS, React.js, and Redux power the user-friendly interface. Advanced functionalities, utilizing deep learning models, developed in Python, are integrated via Node.js. Visual data presentation is achieved using the JS Leaflet library, delivering an interactive map experience. LOCATION3 sets a new standard, offering a range of essential features to enhance the management of film production locations. Firstly, it empowers users to effortlessly upload audiovisual material enriched with geospatial and temporal data, such as location coordinates, photographs, videos, 360-degree panoramas, and 3D location models. With the help of cutting-edge deep learning algorithms, the application automatically tags these materials, while users can also manually tag them. Moreover, the application allows users to record locations directly through its user-friendly mobile application. Users can then embark on seamless location searches, employing spatial or descriptive criteria. This intelligent search functionality considers a combination of relevant tags, dominant colors, architectural characteristics, emotional associations, and unique location traits. One of the application's standout features is the ability to explore locations by their visual similarity to other materials, facilitated by a reverse image search. Also, the interactive map serves as both a dynamic display for locations and a versatile filter, adapting to the user's preferences and effortlessly enhancing location searches. To further streamline the process, the application facilitates the creation of location lightboxes, enabling users to efficiently organize and share their content via email. Going above and beyond location management, the platform also provides invaluable liaison, matchmaking, and online marketplace services. This powerful functionality bridges the gap between visual and three-dimensional geospatial material providers, local agencies, film companies, production companies, etc. so that those interested in a specific location can access additional material beyond what is stored on the platform, as well as access production services supporting the functioning and completion of productions in a location (equipment provision, transportation, catering, accommodation, etc.).

Keywords: deep learning models, film industry, geospatial data management, location scouting

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Authors: Federica Verna, Alessandra Pautasso, Maria Caramelli, Cristiana Maurella, Walter Mignone, Cristina Casalone

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Mosquito-Borne Diseases (MBDs) are dangerously increasing in prevalence, geographical distribution and severity, representing an emerging threat for both humans and animals. Interaction between multiple disciplines is needed for an effective early warning, surveillance and control of MBDs, according to the One Health concept. This work reports the integrated surveillance system enforced by IZSPLV in Piedmont, Liguria and Valle d’Aosta regions (Northwestern Italy) in order to control MDBs spread. Veterinary services and local human health authority are involved in an information network, to connect the surveillance of human clinical cases with entomological surveillance and veterinary monitoring in order to implement control measures in case of outbreak. A systematic entomological surveillance is carried out during the vector season using mosquitoes traps located in sites selected according to risk factors. Collected mosquitoes are counted, identified to species level by morphological standard classification keys and pooled by collection site, date and species with a maximum of 100 individuals. Pools are analyzed, after RNA extraction, by Real Time RT-PCR distinctive for West Nile Virus (WNV) Lineage 1 and Lineage 2, Real Time RT-PCR USUTU virus (USUV) and a traditional flavivirus End-point RT-PCR. Positive pools are sequenced and the related sequences employed to perform a basic local alignment search tool (BLAST) in the GenBank library. Positive samples are sent to the National Reference Centre for Animal Exotic Diseases (CESME, Teramo) for confirmation. With particular reference to WNV, after the confirmation, as provided by national legislation, control measures involving both local veterinary and human health services are activated: equine sera are randomly sampled within a 4 km radius from the positive collection sites and tested with ELISA kit and WNV NAT screening of blood donors is introduced. This surveillance network allowed to detect since 2011 USUV circulation in this area of Italy. WNV was detected in Piedmont and Liguria for the first time in 2014 in mosquitoes. During the 2015 vector season, we observed the expansion of its activity in Piedmont. The virus was detected in almost all Provinces both in mosquitoes (6 pools) and animals (19 equine sera, 4 birds). No blood bag tested resulted infected. The first neuroinvasive human case occurred too. Competent authorities should be aware of a potentially increased risk of MBDs activity during the 2016 vector season. This work shows that this surveillance network allowed to early detect the presence of MBDs in humans and animals, and provided useful information to public authorities, in order to apply control measures. Finally, an additional value of our diagnostic protocol is the ability to detect all viruses belonging to the Flaviviridae family, considering the emergence caused by other Flaviviruses in humans such as the recent Zika virus infection in South America. Italy has climatic and environmental features conducive to Zika virus transmission, the competent vector and many travellers from Brazil reported every year.

Keywords: integrated surveillance, mosquito borne disease, West Nile virus, Zika virus

Procedia PDF Downloads 348

Authors: Subhash Nerella, Ziyuan Guan, Azra Bihorac, Parisa Rashidi

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Intensive care units (ICUs) provide care to critically ill patients in severe and life-threatening conditions. However, patient monitoring in the ICU is limited by the time and resource constraints imposed on healthcare providers. Many critical care indices such as mobility are still manually assessed, which can be subjective, prone to human errors, and lack granularity. Other important aspects, such as environmental factors, are not monitored at all. For example, critically ill patients often experience circadian disruptions due to the absence of effective environmental “timekeepers” such as the light/dark cycle and the systemic effect of acute illness on chronobiologic markers. Although the occurrence of delirium is associated with circadian disruption risk factors, these factors are not routinely monitored in the ICU. Hence, there is a critical unmet need to develop systems for precise and real-time assessment through novel enabling technologies. We have developed the mobility and circadian disruption quantification system (Mobi-DiQ) by augmenting biomarker and clinical data with pervasive sensing data to generate mobility and circadian cues related to mobility, nightly disruptions, and light and noise exposure. We hypothesize that Mobi-DiQ can provide accurate mobility and circadian cues that correlate with bedside clinical mobility assessments and circadian biomarkers, ultimately important for delirium risk assessment and prevention. The collected multimodal dataset consists of depth images, Electromyography (EMG) data, patient extremity movement captured by accelerometers, ambient light levels, Sound Pressure Level (SPL), and indoor air quality measured by volatile organic compounds, and the equivalent CO₂ concentration. For delirium risk assessment, the system recognizes mobility cues (axial body movement features and body key points) and circadian cues, including nightly disruptions, ambient SPL, and light intensity, as well as other environmental factors such as indoor air quality. The Mobi-DiQ system consists of three major components: the pervasive sensing system, a data storage and analysis server, and a data annotation system. For data collection, six local pervasive sensing systems were deployed, including a local computer and sensors. A video recording tool with graphical user interface (GUI) developed in python was used to capture depth image frames for analyzing patient mobility. All sensor data is encrypted, then automatically uploaded to the Mobi-DiQ server through a secured VPN connection. Several data pipelines are developed to automate the data transfer, curation, and data preparation for annotation and model training. The data curation and post-processing are performed on the server. A custom secure annotation tool with GUI was developed to annotate depth activity data. The annotation tool is linked to the MongoDB database to record the data annotation and to provide summarization. Docker containers are also utilized to manage services and pipelines running on the server in an isolated manner. The processed clinical data and annotations are used to train and develop real-time pervasive sensing systems to augment clinical decision-making and promote targeted interventions. In the future, we intend to evaluate our system as a clinical implementation trial, as well as to refine and validate it by using other data sources, including neurological data obtained through continuous electroencephalography (EEG).

Keywords: deep learning, delirium, healthcare, pervasive sensing

Procedia PDF Downloads 80

Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

Procedia PDF Downloads 243