Search results for: transactions costs

Authors: Shreyas Kumar, Mili Shangari

Abstract:

Integrating artificial intelligence (AI) in the cyber insurance sector represents a significant advancement, offering the potential to revolutionize risk assessment, fraud detection, and claims processing. However, this integration introduces a range of regulatory and economic challenges that must be addressed to ensure responsible and effective deployment of AI technologies. This paper examines the multifaceted regulatory landscape governing AI in cyber insurance and explores the economic implications of compliance, innovation, and market dynamics. AI's capabilities in processing vast amounts of data and identifying patterns make it an invaluable tool for insurers in managing cyber risks. Yet, the application of AI in this domain is subject to stringent regulatory scrutiny aimed at safeguarding data privacy, ensuring algorithmic transparency, and preventing biases. Regulatory bodies, such as the European Union with its General Data Protection Regulation (GDPR), mandate strict compliance requirements that can significantly impact the deployment of AI systems. These regulations necessitate robust data protection measures, ethical AI practices, and clear accountability frameworks, all of which entail substantial compliance costs for insurers. The economic implications of these regulatory requirements are profound. Insurers must invest heavily in upgrading their IT infrastructure, implementing robust data governance frameworks, and training personnel to handle AI systems ethically and effectively. These investments, while essential for regulatory compliance, can strain financial resources, particularly for smaller insurers, potentially leading to market consolidation. Furthermore, the cost of regulatory compliance can translate into higher premiums for policyholders, affecting the overall affordability and accessibility of cyber insurance. Despite these challenges, the potential economic benefits of AI integration in cyber insurance are significant. AI-enhanced risk assessment models can provide more accurate pricing, reduce the incidence of fraudulent claims, and expedite claims processing, leading to overall cost savings and increased efficiency. These efficiencies can improve the competitiveness of insurers and drive innovation in product offerings. However, balancing these benefits with regulatory compliance is crucial to avoid legal penalties and reputational damage. The paper also explores the potential risks associated with AI integration, such as algorithmic biases that could lead to unfair discrimination in policy underwriting and claims adjudication. Regulatory frameworks need to evolve to address these issues, promoting fairness and transparency in AI applications. Policymakers play a critical role in creating a balanced regulatory environment that fosters innovation while protecting consumer rights and ensuring market stability. In conclusion, the integration of AI in cyber insurance presents both regulatory and economic challenges that require a coordinated approach involving regulators, insurers, and other stakeholders. By navigating these challenges effectively, the industry can harness the transformative potential of AI, driving advancements in risk management and enhancing the resilience of the cyber insurance market. This paper provides insights and recommendations for policymakers and industry leaders to achieve a balanced and sustainable integration of AI technologies in cyber insurance.

Keywords: artificial intelligence (AI), cyber insurance, regulatory compliance, economic impact, risk assessment, fraud detection, cyber liability insurance, risk management, ransomware

Procedia PDF Downloads 34

Authors: Neusa Fernanda Torres, Buyisile Chibi, Lyn E. Middleton, Vernon P. Solomon, Tivani P. Mashamba-Thompson

Abstract:

Background: Self-medication with antibiotics (SMA) is a global concern, with a higher incidence in low and middle-income countries (LMICs). Despite intense world-wide efforts to control and promote the rational use of antibiotics, continuing practices of SMA systematically exposes individuals and communities to the risk of antibiotic resistance and other undesirable antibiotic side effects. Moreover, it increases the health systems costs of acquiring more powerful antibiotics to treat the resistant infection. This review thus maps evidence on the factors influencing self-medication with antibiotics in these settings. Methods: The search strategy for this review involved electronic databases including PubMed, Web of Knowledge, Science Direct, EBSCOhost (PubMed, CINAHL with Full Text, Health Source - Consumer Edition, MEDLINE), Google Scholar, BioMed Central and World Health Organization library, using the search terms:’ Self-Medication’, ‘antibiotics’, ‘factors’ and ‘reasons’. Our search included studies published from 2007 to 2017. Thematic analysis was performed to identify the patterns of evidence on SMA in LMICs. The mixed method quality appraisal tool (MMAT) version 2011 was employed to assess the quality of the included primary studies. Results: Fifteen studies met the inclusion criteria. Studies included population from the rural (46,4%), urban (33,6%) and combined (20%) settings, of the following LMICs: Guatemala (2 studies), India (2), Indonesia (2), Kenya (1), Laos (1), Nepal (1), Nigeria (2), Pakistan (2), Sri Lanka (1), and Yemen (1). The total sample size of all 15 included studies was 7676 participants. The findings of the review show a high prevalence of SMA ranging from 8,1% to 93%. Accessibility, affordability, conditions of health facilities (long waiting, quality of services and workers) as long well as poor health-seeking behavior and lack of information are factors that influence SMA in LMICs. Antibiotics such as amoxicillin, metronidazole, amoxicillin/clavulanic, ampicillin, ciprofloxacin, azithromycin, penicillin, and tetracycline, were the most frequently used for SMA. The major sources of antibiotics included pharmacies, drug stores, leftover drugs, family/friends and old prescription. Sore throat, common cold, cough with mucus, headache, toothache, flu-like symptoms, pain relief, fever, running nose, toothache, upper respiratory tract infections, urinary symptoms, urinary tract infection were the common disease symptoms managed with SMA. Conclusion: Although the information on factors influencing SMA in LMICs is unevenly distributed, the available information revealed the existence of research evidence on antibiotic self-medication in some countries of LMICs. SMA practices are influenced by social-cultural determinants of health and frequently associated with poor dispensing and prescribing practices, deficient health-seeking behavior and consequently with inappropriate drug use. Therefore, there is still a need to conduct further studies (qualitative, quantitative and randomized control trial) on factors and reasons for SMA to correctly address the public health problem in LMICs.

Keywords: antibiotics, factors, reasons, self-medication, low and middle-income countries (LMICs)

Procedia PDF Downloads 219

Authors: Utkarsh A. Mishra, Ankit Bansal

Abstract:

At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

Procedia PDF Downloads 225

Authors: Caroline Lindlar, Eva Jakob

Abstract:

Female entrepreneurs often face significant barriers in accessing funding due to biases from business angels, venture capitalists, and financial institutions, which tend to favor male entrepreneurs. These biases contribute to persistent funding disparities, with female entrepreneurs receiving less financial support than their male counterparts. The situation worsens when female entrepreneurs have prior experiences with venture failure, which diminishes their attractiveness to traditional investors. Venture failure, defined as the cessation of operations due to declining revenues, rising costs, or ownership changes, plays a substantial role in shaping funding opportunities. In response, female entrepreneurs frequently turn to alternative funding sources such as crowdlending, where gender biases are often reversed in favor of women, particularly when their ventures emphasize social value creation. While existing research highlights the positive impact of gender on crowdfunding success, it remains unclear how venture failure, known to negatively bias female entrepreneurs in traditional funding contexts, interacts with the positive effects of gender in crowdlending. This interaction is particularly relevant because crowdlending often involves non-professional funders who make repeated investment decisions under uncertainty, based on limited information and past experiences. Given that approximately one-third of ventures fail to deliver promised returns, the role of gender bias after failure in crowdlending is an important area of investigation. This study addresses How failure affects crowd funders’ gender bias in future funding decisions? Drawing on social role and role congruity theory, we posit that societal perceptions of women as more communal conflict with the agentic qualities traditionally associated with entrepreneurship. This incongruence may result in reduced confidence in the success of female entrepreneurs after failure, limiting their access to future funding. However, we also hypothesize that social framing may mitigate this bias by aligning perceptions of female entrepreneurs with traits such as warmth and caring, enhancing their appeal after failure. To test these assertions, it conducted a between-subject audio vignette experiment with 155 participants who listened to entrepreneur pitches manipulated by gender (male vs. female) and venture framing (social vs. commercial). Participants made initial investment decisions, received failure-related news about the venture, and then made subsequent investment decisions. Pre-tests with 159 participants ensured the validity and reliability of the experimental manipulations. Moreover, we did a metric conjoint analysis with 100 participants, and they had to decide between different crowdfunding campaigns based on the attributes of previous failure, gender, and venture mission. it findings reveal that failure activates gender biases in crowdlending. Female-led ventures receive significantly less funding after failure compared to male-led ventures, suggesting the positive bias toward female entrepreneurs in the pre-funding phase does not persist post-failure. Moreover, framing a venture as socially oriented exacerbates the negative effect of failure for female entrepreneurs, as they secure fewer funds after failure compared to male entrepreneurs leading similar social ventures. This indicates that role-congruent framing does not mitigate gender bias after failure. This study contributes to research on gender in entrepreneurship by exploring how failure impacts future funding for female entrepreneurs. It also expands social crowdfunding literature by examining social value framing and adds to the entrepreneurial failure literature by focusing on crowd funders’ post-failure behavior.

Keywords: gender bias, crowdfunding, investment failure, investment behavior, social entrepreneurship

Procedia PDF Downloads 19

Authors: O. Lopez, F. Pedro, A. Tadeu, J. Antonio, A. Coelho

Abstract:

The future of the railway industry lies in the innovation of lighter, more efficient and more sustainable trains. Weight optimizations in railway vehicles allow reducing power consumption and CO₂ emissions, increasing the efficiency of the engines and the maximum speed reached. Additionally, they reduce wear of wheels and rails, increase the space available for passengers, etc. Among the various systems that integrate railway interiors, the flooring system is one which has greater impact both on passenger safety and comfort, as well as on the weight of the interior systems. Due to the high weight saving potential, relative high mechanical resistance, good acoustic and thermal performance, ease of modular design, cost-effectiveness and long life, the use of new sustainable composite materials and panels provide the latest innovations for competitive solutions in the development of flooring systems. However, one of the main drawbacks of the flooring systems is their relatively poor resistance to point loads. Point loads in railway interiors can be caused by passengers or by components fixed to the flooring system, such as seats and restraint systems, handrails, etc. In this way, they can originate higher fatigue solicitations under service loads or zones with high stress concentrations under exceptional loads (higher longitudinal, transverse and vertical accelerations), thus reducing its useful life. Therefore, to verify all the mechanical and functional requirements of the flooring systems, many physical prototypes would be created during the design phase, with all of the high costs associated with it. Nowadays, the use of virtual prototyping methods by computer-aided design (CAD) and computer-aided engineering (CAE) softwares allow validating a product before committing to making physical test prototypes. The scope of this work was to current computer tools and integrate the processes of innovation, development, and manufacturing to reduce the time from design to finished product and optimise the development of the product for higher levels of performance and reliability. In this case, the mechanical response of several sandwich panels with different cores, polystyrene foams, and composite corks, were assessed, to optimise the weight and the mechanical performance of a flooring solution for railways. Sandwich panels with aluminum face sheets were tested to characterise its mechanical performance and determine the polystyrene foam and cork properties when used as inner cores. Then, a railway flooring solution was fully modelled (including the elastomer pads to provide the required vibration isolation from the car body) and perform structural simulations using FEM analysis to comply all the technical product specifications for the supply of a flooring system. Zones with high stress concentrations are studied and tested. The influence of vibration modes on the comfort level and stability is discussed. The information obtained with the computer tools was then completed with several mechanical tests performed on some solutions, and on specific components. The results of the numerical simulations and experimental campaign carried out are presented in this paper. This research work was performed as part of the POCI-01-0247-FEDER-003474 (coMMUTe) Project funded by Portugal 2020 through COMPETE 2020.

Keywords: cork agglomerate core, mechanical performance, numerical simulation, railway flooring system

Procedia PDF Downloads 180

Authors: William Michael Short

Abstract:

Semantic Web’ technologies such as the Unified Medical Language System Metathesaurus, SNOMED-CT, and MeSH have been touted as transformational for the way users access online medical and health information, enabling both the automated analysis of natural-language data and the integration of heterogeneous healthrelated resources distributed across the Internet through the use of standardized terminologies that capture concepts and relationships between concepts that are expressed differently across datasets. However, the approaches that have so far characterized ‘semantic bioinformatics’ have not yet fulfilled the promise of the Semantic Web for medical and health information retrieval applications. This paper argues within the perspective of cognitive linguistics and cognitive anthropology that four features of human meaning-making must be taken into account before the potential of semantic technologies can be realized for this domain. First, many semantic technologies operate exclusively at the level of the word. However, texts convey meanings in ways beyond lexical semantics. For example, transitivity patterns (distributions of active or passive voice) and modality patterns (configurations of modal constituents like may, might, could, would, should) convey experiential and epistemic meanings that are not captured by single words. Language users also naturally associate stretches of text with discrete meanings, so that whole sentences can be ascribed senses similar to the senses of words (so-called ‘discourse topics’). Second, natural language processing systems tend to operate according to the principle of ‘one token, one tag’. For instance, occurrences of the word sound must be disambiguated for part of speech: in context, is sound a noun or a verb or an adjective? In syntactic analysis, deterministic annotation methods may be acceptable. But because natural language utterances are typically characterized by polyvalency and ambiguities of all kinds (including intentional ambiguities), such methods leave the meanings of texts highly impoverished. Third, ontologies tend to be disconnected from everyday language use and so struggle in cases where single concepts are captured through complex lexicalizations that involve profile shifts or other embodied representations. More problematically, concept graphs tend to capture ‘expert’ technical models rather than ‘folk’ models of knowledge and so may not match users’ common-sense intuitions about the organization of concepts in prototypical structures rather than Aristotelian categories. Fourth, and finally, most ontologies do not recognize the pervasively figurative character of human language. However, since the time of Galen the widespread use of metaphor in the linguistic usage of both medical professionals and lay persons has been recognized. In particular, metaphor is a well-documented linguistic tool for communicating experiences of pain. Because semantic medical knowledge-bases are designed to help capture variations within technical vocabularies – rather than the kinds of conventionalized figurative semantics that practitioners as well as patients actually utilize in clinical description and diagnosis – they fail to capture this dimension of linguistic usage. The failure of semantic technologies in these respects degrades the efficiency and efficacy not only of medical research, where information retrieval inefficiencies can lead to direct financial costs to organizations, but also of care provision, especially in contexts of patients’ self-management of complex medical conditions.

Keywords: ambiguity, bioinformatics, language, meaning, metaphor, ontology, semantic web, semantics

Procedia PDF Downloads 133

Authors: Claudio Loconsole, Daniele Leonardis, Antonio Brunetti, Gianpaolo Francesco Trotta, Nicholas Caporusso, Vitoantonio Bevilacqua

Abstract:

Unfortunately, many people still do not have access to communication, with specific regard to reading and writing. Among them, people who are blind or visually impaired, have several difficulties in getting access to the world, compared to the sighted. Indeed, despite technology advancement and cost reduction, nowadays assistive devices are still expensive such as Braille-based input/output systems which enable reading and writing texts (e.g., personal notes, documents). As a consequence, assistive technology affordability is fundamental in supporting the visually impaired in communication, learning, and social inclusion. This, in turn, has serious consequences in terms of equal access to opportunities, freedom of expression, and actual and independent participation to a society designed for the sighted. Moreover, the visually impaired experience difficulties in recognizing objects and interacting with devices in any activities of daily living. It is not a case that Braille indications are commonly reported only on medicine boxes and elevator keypads. Several software applications for the automatic translation of written text into speech (e.g., Text-To-Speech - TTS) enable reading pieces of documents. However, apart from simple tasks, in many circumstances TTS software is not suitable for understanding very complicated pieces of text requiring to dwell more on specific portions (e.g., mathematical formulas or Greek text). In addition, the experience of reading\writing text is completely different both in terms of engagement, and from an educational perspective. Statistics on the employment rate of blind people show that learning to read and write provides the visually impaired with up to 80% more opportunities of finding a job. Especially in higher educational levels, where the ability to digest very complex text is key, accessibility and availability of Braille plays a fundamental role in reducing drop-out rate of the visually impaired, thus affecting the effectiveness of the constitutional right to get access to education. In this context, the Braille Lab project aims at overcoming these social needs by including affordability in designing and developing assistive tools for visually impaired people. In detail, our awarded project focuses on a technology innovation of the operation principle of existing assistive tools for the visually impaired leaving the Human-Machine Interface unchanged. This can result in a significant reduction of the production costs and consequently of tool selling prices, thus representing an important opportunity for social entrepreneurship. The first two assistive tools designed within the Braille Lab project following the proposed approach aims to provide the possibility to personally print documents and handouts and to read texts written in Braille using refreshable Braille display, respectively. The former, named ‘Braille Cartridge’, represents an alternative solution for printing in Braille and consists in the realization of an electronic-controlled dispenser printing (cartridge) which can be integrated within traditional ink-jet printers, in order to leverage the efficiency and cost of the device mechanical structure which are already being used. The latter, named ‘Braille Cursor’, is an innovative Braille display featuring a substantial technology innovation by means of a unique cursor virtualizing Braille cells, thus limiting the number of active pins needed for Braille characters.

Keywords: Human rights, social challenges and technology innovations, visually impaired, affordability, assistive tools

Procedia PDF Downloads 276

Authors: Tuji Jemal Ahmed, Hussen Beker Yusuf

Abstract:

Food safety is a major concern worldwide, with microbial contamination being one of the leading causes of foodborne illnesses. In Ethiopia, drinking water and untreated groundwater are a primary source of microbial contamination, leading to significant health risks. East Hararghe, Oromia, is one of the regions in Ethiopia that has been affected by this problem. This paper provides an overview of the impact of untreated groundwater on human health in Haramaya Rural District, East Hararghe and highlights the urgent need for sustained efforts to address the water sanitation supply problem. The use of untreated groundwater for drinking and household purposes in Haramaya Rural District, East Hararghe is prevalent, leading to high rates of waterborne illnesses such as diarrhea, typhoid fever, and cholera. The impact of these illnesses on human health is significant, resulting in significant morbidity and mortality, especially among vulnerable populations such as children and the elderly. In addition to the direct health impacts, waterborne illnesses also have indirect impacts on human health, such as reduced productivity and increased healthcare costs. Groundwater sources are susceptible to microbial contamination due to the infiltration of surface water, human and animal waste, and agricultural runoff. In Haramaya Rural District, East Hararghe, poor water management practices, inadequate sanitation facilities, and limited access to clean water sources contribute to the prevalence of untreated groundwater as a primary source of drinking water. These underlying causes of microbial contamination highlight the need for improved water sanitation infrastructure, including better access to safe drinking water sources and the implementation of effective treatment methods. The paper emphasizes the need for regular water quality monitoring, especially for untreated groundwater sources, to ensure safe drinking water for the population. The implementation of effective preventive measures, such as the use of effective disinfectants, proper waste disposal methods, and regular water quality monitoring, is crucial to reducing the risk of contamination and improving public health outcomes in the region. Community education and awareness-raising campaigns can also play a critical role in promoting safe water practices and reducing the risk of contamination. These campaigns can include educating the population on the importance of boiling water before drinking, the use of water filters, and proper sanitation practices. In conclusion, the use of untreated groundwater as a primary source of drinking water in East Hararghe, Oromia, Ethiopia, has significant impacts on human health, leading to widespread waterborne illnesses and posing a significant threat to public health. Sustained efforts are urgently needed to address the root causes of contamination, such as poor sanitation and hygiene practices, improper waste management, and the water sanitation supply problem, including the implementation of effective preventive measures and community-based education programs, ultimately improving public health outcomes in the region. A comprehensive approach that involves community-based water management systems, point-of-use water treatment methods, and awareness-raising campaigns can contribute to reducing the incidence of microbial contamination in the region.

Keywords: food safety, health risks, microbial contamination, untreated groundwater

Procedia PDF Downloads 115

Authors: Laura Norfolk, Georgina Zimbitas, Jan Sefcik, Sarah Staniland

Abstract:

Magnetite nanoparticles (MNP) have been an area of increasing research interest due to their extensive applications in industry, such as in carbon capture, water purification, and crucially, the biomedical industry. The use of MNP in the biomedical industry is rising, with studies on their effect as Magnetic resonance imaging contrast agents, drug delivery systems, and as hyperthermic cancer treatments becoming prevalent in the nanomaterial research community. Particles used for biomedical purposes must meet stringent criteria; the particles must have consistent shape and size between particles. Variation between particle morphology can drastically alter the effective surface area of the material, making it difficult to correctly dose particles that are not homogeneous. Particles of defined shape such as octahedral and cubic have been shown to outperform irregular shaped particles in some applications, leading to the need to synthesize particles of defined shape. In nature, highly homogeneous MNP are found within magnetotactic bacteria, a unique bacteria capable of producing magnetite nanoparticles internally under ambient conditions. Biomineralisation proteins control the properties of the MNPs, enhancing their homogeneity. One of these proteins, Mms6, has been successfully isolated and used in vitro as an additive in room-temperature co-precipitation reactions (RTCP) to produce particles of defined mono-dispersed size & morphology. When considering future industrial scale-up it is crucial to consider the costs and feasibility of an additive, as an additive that is not readily available or easily synthesized at a competitive price will not be sustainable. As such, additives selected for this research are inspired by the functional groups of biomineralisation proteins, but cost-effective, environmentally friendly, and compatible with scale-up. Diethylenetriamine (DETA), triethylenetetramine (TETA), tetraethylenepentamine (TEPA), and pentaethylenehexamine (PEHA) have been successfully used in RTCP to modulate the properties of particles synthesized, leading to the formation of octahedral nanoparticles with no use of organic solvents, heating, or toxic precursors. By extending this principle to a fluidic system, ongoing research will reveal whether the amine additives can also exert morphological control in an environment which is suited toward higher particle yield. Two fluidic systems have been employed; a peristaltic turbulent flow mixing system suitable for the rapid production of MNP, and a macrofluidic system for the synthesis of tailored nanomaterials under a laminar flow regime. The presence of the amine additives in the turbulent flow system in initial results appears to offer similar morphological control as observed under RTCP conditions, with higher proportions of octahedral particles formed. This is a proof of concept which may pave the way to green synthesis of tailored MNP on an industrial scale. Mms6 and amine additives have been used in the macrofluidic system, with Mms6 allowing magnetite to be synthesized at unfavourable ferric ratios, but no longer influencing particle size. This suggests this synthetic technique while still benefiting from the addition of additives, may not allow additives to fully influence the particles formed due to the faster timescale of reaction. The amine additives have been tested at various concentrations, the results of which will be discussed in this paper.

Keywords: bioinspired, green synthesis, fluidic, magnetite, morphological control, scale-up

Procedia PDF Downloads 114

Authors: Sebastião Milton Pinheiro da Silva, Michele Barbosa da Rocha, Ana Lúcia Fernandes Campos, Miquéias Rildo de Souza Silva

Abstract:

Water is an essential natural resource for life on Earth. Rivers, lakes, lagoons and dams are the main sources of water storage for human consumption. The costs of extracting and using these water sources are lower than those of exploiting groundwater on transition zones to semi-arid terrains. However, the volume of surface water has decreased over time, with the depletion of first-order drainage and the disappearance of springs, phenomena which are easily observed in the field. Climate change worsens water scarcity, compromising supply and hydric security for rural populations. To minimize the expected impacts, producing and storing water through watershed management planning requires detailed cartographic information on the relief and topography, and updated data on the stage and intensity of catchment basin environmental degradation problems. The cartography available of the Brazilian northeastern territory dates to the 70s, with topographic maps, printed, at a scale of 1:100,000 which does not meet the requirements to execute this project. Exceptionally, there are topographic maps at scales of 1:50,000 and 1:25,000 of some coastal regions in northeastern Brazil. Still, due to scale limitations and outdatedness, they are products of little utility for mapping low-order watersheds drainage and springs. Remote sensing data and geographic information systems can contribute to guiding the process of mapping and environmental recovery by integrating detailed relief and topographic data besides social and other environmental information in the Guajiru River Basin, located on the east coast of Rio Grande do Norte, on the Northeast region of Brazil. This study aimed to recognize and map catchment basin, springs and low-order drainage features along estimating morphometric parameters. Alos PALSAR and Copernicus DEM digital elevation models were evaluated and provided regional drainage features and the watersheds limits extracted with Terraview/Terrahidro 5.0 software. CBERS 4A satellite images with 2 m spatial resolution, processed with ESA SNAP Toolbox, allowed generating land use land cover map of Guajiru River. A Mappir Survey 3 multiespectral camera onboard of a DJI Phantom 4, a Mavic 2 Pro PPK Drone and an X91 GNSS receiver to collect the precised position of selected points were employed to detail mapping. Satellite images enabled a first knowledge approach of watershed areas on a more regional scale, yet very current, and drone images were essential in mapping details of catchment basins. The drone multispectral image mosaics, the digital elevation model, the contour lines and geomorphometric parameters were generated using OpenDroneMap/ODM and QGis softwares. The drone images generated facilitated the location, understanding and mapping of watersheds, recharge areas and first-order ephemeral watercourses on an adequate scale and will be used in the following project’s phases: watershed management planning, recovery and environmental protection of Rio's springs Guajiru. Environmental degradation is being analyzed from the perspective of the availability and quality of surface water supply.

Keywords: imaging, relief, UAV, water

Procedia PDF Downloads 32

Authors: Annika J. Meyer, Tom Piechotta

Abstract:

Unmanned Aerial Vehicles (UAVs) have increasingly become vital tools in various applications, including surveillance, search and rescue, and environmental monitoring. One common approach to ensure redundant communication systems when flying beyond visual line of sight is for UAVs to employ multiple mobile data modems by different providers. Although widely adopted, this approach suffers from several drawbacks, such as high costs, added weight and potential increases in signal interference. In light of these challenges, this paper proposes a communication framework intermeshing mobile networks and LoRa (Long Range) technology—a low-power, long-range communication protocol. LoRaWAN (Long Range Wide Area Network) is commonly used in Internet of Things applications, relying on stationary gateways and Internet connectivity. This paper, however, utilizes the underlying LoRa protocol, taking advantage of the protocol’s low power and long-range capabilities while ensuring efficiency and reliability. Conducted in collaboration with the Potsdam Fire Department, the implementation of mobile network technology in combination with the LoRa protocol in small UAVs (take-off weight < 0.4 kg), specifically designed for search and rescue and area monitoring missions, is explored. This research aims to test the viability of LoRa as an additional redundant communication system during UAV flights as well as its intermeshing with the primary, mobile network-based controller. The methodology focuses on direct UAV-to-UAV and UAV-to-ground communications, employing different spreading factors optimized for specific operational scenarios—short-range for UAV-to-UAV interactions and long-range for UAV-to-ground commands. This explored use case also dramatically reduces one of the major drawbacks of LoRa communication systems, as a line of sight between the modules is necessary for reliable data transfer. Something that UAVs are uniquely suited to provide, especially when deployed as a swarm. Additionally, swarm deployment may enable UAVs that have lost contact with their primary network to reestablish their connection through another, better-situated UAV. The experimental setup involves multiple phases of testing, starting with controlled environments to assess basic communication capabilities and gradually advancing to complex scenarios involving multiple UAVs. Such a staged approach allows for meticulous adjustment of parameters and optimization of the communication protocols to ensure reliability and effectiveness. Furthermore, due to the close partnership with the Fire Department, the real-world applicability of the communication system is assured. The expected outcomes of this paper include a detailed analysis of LoRa's performance as a communication tool for UAVs, focusing on aspects such as signal integrity, range, and reliability under different environmental conditions. Additionally, the paper seeks to demonstrate the cost-effectiveness and operational efficiency of using a single type of communication technology that reduces UAV payload and power consumption. By shifting from traditional cellular network communications to a more robust and versatile cellular and LoRa-based system, this research has the potential to significantly enhance UAV capabilities, especially in critical applications where reliability is paramount. The success of this paper could pave the way for broader adoption of LoRa in UAV communications, setting a new standard for UAV operational communication frameworks.

Keywords: LoRa communication protocol, mobile network communication, UAV communication systems, search and rescue operations

Procedia PDF Downloads 44

Authors: D. Malouch, M. Berchel, C. Dreanno, S. Stachowski-Haberkorn, P-A. Jaffres

Abstract:

Biofilm is a predominant lifestyle chosen by bacteria. Whether it is developed on an immerged surface or a mobile biofilm known as flocs, the bacteria within this form of life show properties different from its planktonic ones. Within the biofilm, the self-formed matrix of Extracellular Polymeric Substances (EPS) offers hydration, resources capture, enhanced resistance to antimicrobial agents, and allows cell-communication. Biofouling is a complex natural phenomenon that involves biological, physical and chemical properties related to the environment, the submerged surface and the living organisms involved. Bio-colonization of artificial structures can cause various economic and environmental impacts. The increase in costs associated with the over-consumption of fuel from biocolonized vessels has been widely studied. Measurement drifts from submerged sensors, as well as obstructions in heat exchangers, and deterioration of offshore structures are major difficulties that industries are dealing with. Therefore, surfaces that inhibit biocolonization are required in different areas (water treatment, marine paints, etc.) and many efforts have been devoted to produce efficient and eco-compatible antifouling agents. The different steps of surface fouling are widely described in literature. Studying the biofilm and its stages provides a better understanding of how to elaborate more efficient antifouling strategies. Several approaches are currently applied, such as the use of biocide anti-fouling paint6 (mainly with copper derivatives) and super-hydrophobic coatings. While these two processes are proving to be the most effective, they are not entirely satisfactory, especially in a context of a changing legislation. Nowadays, the challenge is to prevent biofouling with non-biocide compounds, offering a cost effective solution, but with no toxic effects on marine organisms. Since the micro-fouling phase plays an important role in the regulation of the following steps of biofilm formation7, it is desired to reduce or delate biofouling of a given surface by inhibiting the micro fouling at its early stages. In our recent works, we reported that some amphiphilic compounds exhibited bacteriostatic or bactericidal properties at a concentration that did not affect eukaryotic cells. These remarkable properties invited us to assess this type of bio-inspired phospholipids9 to prevent the colonization of surfaces by marine bacteria. Of note, other studies reported that amphiphilic compounds interacted with bacteria leading to a reduction of their development. An amphiphilic compound is a molecule consisting of a hydrophobic domain and a polar head (ionic or non-ionic). These compounds appear to have interesting antifouling properties: some ionic compounds have shown antimicrobial activity, and zwitterions can reduce nonspecific adsorption of proteins. Herein, we investigate the potential of amphiphilic compounds as inhibitors of bacterial growth and marine biofilm formation. The aim of this study is to compare the efficacy of four synthetic phospholipids that features a cationic charge (BSV36, KLN47) or a zwitterionic polar-head group (SL386, MB2871) to prevent microfouling with marine bacteria. We also study the toxicity of these compounds in order to identify the most promising compound that must feature high anti-adhesive properties and a low cytotoxicity on two links representative of coastal marine food webs: phytoplankton and oyster larvae.

Keywords: amphiphilic phospholipids, bacterial biofilm, marine microfouling, non-toxic antifouling

Procedia PDF Downloads 149

Authors: Manuel I. Capel, Antonio Tomeu, Alberto Salguero

Abstract:

Tumor growth from a transformed cancer-cell up to a clinically apparent mass spans through a range of spatial and temporal magnitudes. Through computer simulations, Cellular Automata (CA) can accurately describe the complexity of the development of tumors. Tumor development prognosis can now be made -without making patients undergo through annoying medical examinations or painful invasive procedures- if we develop appropriate CA-based software tools. In silico testing mainly refers to Computational Biology research studies of application to clinical actions in Medicine. To establish sound computer-based models of cellular behavior, certainly reduces costs and saves precious time with respect to carrying out experiments in vitro at labs or in vivo with living cells and organisms. These aim to produce scientifically relevant results compared to traditional in vitro testing, which is slow, expensive, and does not generally have acceptable reproducibility under the same conditions. For speeding up computer simulations of cellular models, specific literature shows recent proposals based on the CA approach that include advanced techniques, such the clever use of supporting efficient data structures when modeling with deterministic stochastic cellular automata. Multiparadigm and multiscale simulation of tumor dynamics is just beginning to be developed by the concerned research community. The use of stochastic cellular automata (SCA), whose parallel programming implementations are open to yield a high computational performance, are of much interest to be explored up to their computational limits. There have been some approaches based on optimizations to advance in multiparadigm models of tumor growth, which mainly pursuit to improve performance of these models through efficient memory accesses guarantee, or considering the dynamic evolution of the memory space (grids, trees,…) that holds crucial data in simulations. In our opinion, the different optimizations mentioned above are not decisive enough to achieve the high performance computing power that cell-behavior simulation programs actually need. The possibility of using multicore and GPU parallelism as a promising multiplatform and framework to develop new programming techniques to speed-up the computation time of simulations is just starting to be explored in the few last years. This paper presents a model that incorporates parallel processing, identifying the synchronization necessary for speeding up tumor growth simulations implemented in Java and C++ programming environments. The speed up improvement that specific parallel syntactic constructs, such as executors (thread pools) in Java, are studied. The new tumor growth parallel model is proved using implementations with Java and C++ languages on two different platforms: chipset Intel core i-X and a HPC cluster of processors at our university. The parallelization of Polesczuk and Enderling model (normally used by researchers in mathematical oncology) proposed here is analyzed with respect to performance gain. We intend to apply the model and overall parallelization technique presented here to solid tumors of specific affiliation such as prostate, breast, or colon. Our final objective is to set up a multiparadigm model capable of modelling angiogenesis, or the growth inhibition induced by chemotaxis, as well as the effect of therapies based on the presence of cytotoxic/cytostatic drugs.

Keywords: cellular automaton, tumor growth model, simulation, multicore and manycore programming, parallel programming, high performance computing, speed up

Procedia PDF Downloads 244

Authors: Claire Williams

Abstract:

Randomised controlled Trials (RCTs) of efficacy are still perceived as the gold standard for the generation of evidence, and whilst advances in data collection methods are well developed, this progress has not been matched for the reporting of adverse events (AEs). Assessment and reporting of AEs in clinical trials are fraught with human error and inefficiency and are extremely time and resource intensive. Recent research conducted into the quality of reporting of AEs during clinical trials concluded it is substandard and reporting is inconsistent. Investigators commonly send reports to sponsors who are incorrectly categorised and lacking in critical information, which can complicate the detection of valid safety signals. In our presentation, we will describe an electronic data capture system, which has been designed to support clinical trial processes by reducing the resource burden on investigators, improving overall trial efficiencies, and making trials safer for patients. This proprietary technology was developed using expertise proven in the delivery of the world’s first prospective, phase 3b real-world trial, ‘The Salford Lung Study, ’ which enabled robust safety monitoring and reporting processes to be accomplished by the remote monitoring of patients’ EHRs. This technology enables safety alerts that are pre-defined by the protocol to be detected from the data extracted directly from the patients EHR. Based on study-specific criteria, which are created from the standard definition of a serious adverse event (SAE) and the safety profile of the medicinal product, the system alerts the investigator or study team to the safety alert. Each safety alert will require a clinical review by the investigator or delegate; examples of the types of alerts include hospital admission, death, hepatotoxicity, neutropenia, and acute renal failure. This is achieved in near real-time; safety alerts can be reviewed along with any additional information available to determine whether they meet the protocol-defined criteria for reporting or withdrawal. This active surveillance technology helps reduce the resource burden of the more traditional methods of AE detection for the investigators and study teams and can help eliminate reporting bias. Integration of multiple healthcare data sources enables much more complete and accurate safety data to be collected as part of a trial and can also provide an opportunity to evaluate a drug’s safety profile long-term, in post-trial follow-up. By utilising this robust and proven method for safety monitoring and reporting, a much higher risk of patient cohorts can be enrolled into trials, thus promoting inclusivity and diversity. Broadening eligibility criteria and adopting more inclusive recruitment practices in the later stages of drug development will increase the ability to understand the medicinal products risk-benefit profile across the patient population that is likely to use the product in clinical practice. Furthermore, this ground-breaking approach to AE detection not only provides sponsors with better-quality safety data for their products, but it reduces the resource burden on the investigator and study teams. With the data taken directly from the source, trial costs are reduced, with minimal data validation required and near real-time reporting enables safety concerns and signals to be detected more quickly than in a traditional RCT.

Keywords: more comprehensive and accurate safety data, near real-time safety alerts, reduced resource burden, safer trials

Procedia PDF Downloads 86

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

Abstract:

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

Procedia PDF Downloads 276

Authors: Abdulkarim Nasir, Alhassan T. Yahaya, Hauwa T. Abdulkarim, Abdussalam El-Suleiman, Yakubu K. Abubakar

Abstract:

The need for sustainable and reliable electricity supply in rural communities of Nigeria remains a pressing issue, given the country's vast energy deficit and the significant number of inhabitants lacking access to electricity. This research focuses on the development of a portable hybrid renewable energy system designed to provide a sustainable and efficient electricity supply to these underserved regions. The proposed system integrates multiple renewable energy sources, specifically solar and wind, to harness the abundant natural resources available in Nigeria. The design and development process involves the selection and optimization of components such as photovoltaic panels, wind turbines, energy storage units (batteries), and power management systems. These components are chosen based on their suitability for rural environments, cost-effectiveness, and ease of maintenance. The hybrid system is designed to be portable, allowing for easy transportation and deployment in remote locations with limited infrastructure. Key to the system's effectiveness is its hybrid nature, which ensures continuous power supply by compensating for the intermittent nature of individual renewable sources. Solar energy is harnessed during the day, while wind energy is captured whenever wind conditions are favourable, thus ensuring a more stable and reliable energy output. Energy storage units are critical in this setup, storing excess energy generated during peak production times and supplying power during periods of low renewable generation. These studies include assessing the solar irradiance, wind speed patterns, and energy consumption needs of rural communities. The simulation results inform the optimization of the system's design to maximize energy efficiency and reliability. This paper presents the development and evaluation of a 4 kW standalone hybrid system combining wind and solar power. The portable device measures approximately 8 feet 5 inches in width, 8 inches 4 inches in depth, and around 38 feet in height. It includes four solar panels with a capacity of 120 watts each, a 1.5 kW wind turbine, a solar charge controller, remote power storage, batteries, and battery control mechanisms. Designed to operate independently of the grid, this hybrid device offers versatility for use in highways and various other applications. It also presents a summary and characterization of the device, along with photovoltaic data collected in Nigeria during the month of April. The construction plan for the hybrid energy tower is outlined, which involves combining a vertical-axis wind turbine with solar panels to harness both wind and solar energy. Positioned between the roadway divider and automobiles, the tower takes advantage of the air velocity generated by passing vehicles. The solar panels are strategically mounted to deflect air toward the turbine while generating energy. Generators and gear systems attached to the turbine shaft enable power generation, offering a portable solution to energy challenges in Nigerian communities. The study also addresses the economic feasibility of the system, considering the initial investment costs, maintenance, and potential savings from reduced fossil fuel use. A comparative analysis with traditional energy supply methods highlights the long-term benefits and sustainability of the hybrid system.

Keywords: renewable energy, solar panel, wind turbine, hybrid system, generator

Procedia PDF Downloads 44

Authors: Jia H. Wong, Jingli Zhang, Habsah Mohamad, Iswatun H. Abdullah Ripain, Muhammad Bilal, Amelia J. Lloyd, Abdul A. Mohamed Yusoff, Jafri M. Abdullah

Abstract:

Epilepsy is one of the most common neurological diseases affecting more than 50 million of people worldwide. Epilepsy is a state of recurrent, spontaneous seizures with multiple syndromes and symptoms of different causes of brain dysfunction, prognosis, and treatments; characterized by transient, occasional and stereotyped interruptions of behavior whereby the excitatory-inhibitory activities within the central nervous system (CNS) are thrown out of balance due to various kinds of interferences. The goal of antiepileptic treatment is to enable patients to be free from seizures or to achieve control of seizures through surgical treatment and/or pharmacotherapy. Pharmacotherapy through AED plays an important role especially in countries with epilepsy treatment gap due to costs and availability of health facilities, skills and resources, yet there are about one-third of the people with epilepsy have drug-resistant seizures. Hence, this poses considerable challenges to the healthcare system and the effort in providing cost-effective treatment as well as the search for alternatives to treatment and management of epilepsy. Enhancement of γ-aminobutyric acid (GABA)-mediated inhibitory neurotransmission is one of the key mechanisms of actions of antiepileptic drugs. GABA type > a receptors (GABAAR) are ligand-gated ion channels that mediate rapid inhibitory neurotransmission upon the binding of GABA with a heteropentameric structure forming a central pore that is permeable to the influx of chloride ions in its activated state. The major isoform of GABAA receptors consists of two α1, two β2, and one γ2 subunit. It is the most abundantly expressed combinations in the brain and the most commonly researched through Xenopus laevis oocytes. With the advancing studies on ethnomedicine and traditional treatments using medicinal plants, increasing evidence reveal that spice and herb plants with medicinal properties play an important role in the treatment of ailments within communities across different cultures. Capsaicin is the primary natural capsaicinoid in hot peppers of plant genus Capsicum, consist of an aromatic ring, an amide linkage and a hydrophobic side chain. The study showed that capsaicins conferred neuroprotection in status epilepticus mouse models through anti-ictogenic, hypothermic, antioxidative, anti-inflammatory, and anti-apoptotic actions in a dose-dependent manner. In this study, five capsaicin derivatives were tested for their ability to increase the GABA-induced chloride current on α1β2γ2S of GABAAR expressed on Xenopus laevis oocytes using the method of two-microelectrode voltage clamp. Two of the capsaicin derivatives, IS5 (N-(4-hydroxy-3-methoxybenzyl)-3-methylbutyramide) and IS10 (N-(4-hydroxy-3-methoxybenzyl)-decanamide) at a concentration of 30µM were able to significantly increase the GABA-induced chloride current with p=0.002 and p=0.026 respectively. This study were able to show the enhancement effect of two capsaicin derivatives with moderate length of hydrocarbon chain on this receptor subtype, revealing the promising inhibitory activity of capsaicin derivatives through enhancement of GABA-induced chloride current and further investigations should be carried out to verify its antiepileptic effects in animal models.

Keywords: α1β2γ2 GABAA receptors, α1β2γ2S, antiepileptic, capsaicin derivatives, two-microelectrode voltage clamp, Xenopus laevis oocytes

Procedia PDF Downloads 362

Authors: Nursuhaili Najwa Masrol, Nur Hafizah Mohammed, Nur Nadhirah Rusyda Rosnan, Vijaya Subramaniam, Sim Choon Cheak

Abstract:

Replanting in oil palm cultivation is vital to enable the introduction of planting materials and provides an opportunity to improve the road, drainage, terrace design, and planting density. Oil palm replanting is fundamentally necessary every 25 years. The adoption of the digital replanting blueprint is imperative as it can assist the Malaysia Oil Palm industry in addressing challenges such as labour shortages and limited expertise related to replanting tasks. Effective replanting planning should commence at least 6 months prior to the actual replanting process. Therefore, this study will help to plan and design the replanting blueprint with high-precision translation on the ground. With the advancement of geospatial technology, it is now feasible to engage in thoroughly researched planning, which can help maximize the potential yield. A blueprint designed before replanting is to enhance management’s ability to optimize the planting program, address manpower issues, or even increase productivity. In terrace planting blueprints, geographic tools have been utilized to design the roads, drainages, terraces, and planting points based on the ARM standards. These designs are mapped with location information and undergo statistical analysis. The geospatial approach is essential in precision agriculture and ensuring an accurate translation of design to the ground by implementing high-accuracy technologies. In this study, geospatial and remote sensing technologies played a vital role. LiDAR data was employed to determine the Digital Elevation Model (DEM), enabling the precise selection of terraces, while ortho imagery was used for validation purposes. Throughout the designing process, Geographical Information System (GIS) tools were extensively utilized. To assess the design’s reliability on the ground compared with the current conventional method, high-precision GPS instruments like EOS Arrow Gold and HIPER VR GNSS were used, with both offering accuracy levels between 0.3 cm and 0.5cm. Nearest Distance Analysis was generated to compare the design with actual planting on the ground. The analysis revealed that it could not be applied to the roads due to discrepancies between actual roads and the blueprint design, which resulted in minimal variance. In contrast, the terraces closely adhered to the GPS markings, with the most variance distance being less than 0.5 meters compared to actual terraces constructed. Considering the required slope degrees for terrace planting, which must be greater than 6 degrees, the study found that approximately 65% of the terracing was constructed at a 12-degree slope, while over 50% of the terracing was constructed at slopes exceeding the minimum degrees. Utilizing blueprint replanting promising strategies for optimizing land utilization in agriculture. This approach harnesses technology and meticulous planning to yield advantages, including increased efficiency, enhanced sustainability, and cost reduction. From this study, practical implementation of this technique can lead to tangible and significant improvements in agricultural sectors. In boosting further efficiencies, future initiatives will require more sophisticated techniques and the incorporation of precision GPS devices for upcoming blueprint replanting projects besides strategic progression aims to guarantee the precision of both blueprint design stages and its subsequent implementation on the field. Looking ahead, automating digital blueprints are necessary to reduce time, workforce, and costs in commercial production.

Keywords: replanting, geospatial, precision agriculture, blueprint

Procedia PDF Downloads 84

Authors: Jessica Ho

Abstract:

AI has helped government, businesses and industries transform the way they do things. AI is used in automating tasks to improve decision-making and efficiency. AI is embedded in sensors and used in automation to help save time and eliminate human errors in repetitive tasks. Today, we saw the growth in AI using the collection of vast amounts of data to forecast with greater accuracy, inform decision-making, adapt to changing market conditions and offer more personalised service based on consumer habits and preferences. Government around the world share the opportunity to leverage these disruptive technologies to improve productivity while reducing costs. In addition, these intelligent solutions can also help streamline government processes to deliver more seamless and intuitive user experiences for employees and citizens. This is a critical challenge for NSW Government as we are unable to determine the risk that is brought by the unprecedented pace of adoption of AI solutions in government. Government agencies must ensure that their use of AI complies with relevant laws and regulatory requirements, including those related to data privacy and security. Furthermore, there will always be ethical concerns surrounding the use of AI, such as the potential for bias, intellectual property rights and its impact on job security. Within NSW’s public sector, agencies are already testing AI for crowd control, infrastructure management, fraud compliance, public safety, transport, and police surveillance. Citizens are also attracted to the ease of use and accessibility of AI solutions without requiring specialised technical skills. This increased accessibility also comes with balancing a higher risk and exposure to the health and safety of citizens. On the other side, public agencies struggle with keeping up with this pace while minimising risks, but the low entry cost and open-source nature of generative AI led to a rapid increase in the development of AI powered apps organically – “There is an AI for That” in Government. Other challenges include the fact that there appeared to be no legislative provisions that expressly authorise the NSW Government to use an AI to make decision. On the global stage, there were too many actors in the regulatory space, and a sovereign response is needed to minimise multiplicity and regulatory burden. Therefore, traditional corporate risk and governance framework and regulation and legislation frameworks will need to be evaluated for AI unique challenges due to their rapidly evolving nature, ethical considerations, and heightened regulatory scrutiny impacting the safety of consumers and increased risks for Government. Creating an effective, efficient NSW Government’s governance regime, adapted to the range of different approaches to the applications of AI, is not a mere matter of overcoming technical challenges. Technologies have a wide range of social effects on our surroundings and behaviours. There is compelling evidence to show that Australia's sustained social and economic advancement depends on AI's ability to spur economic growth, boost productivity, and address a wide range of societal and political issues. AI may also inflict significant damage. If such harm is not addressed, the public's confidence in this kind of innovation will be weakened. This paper suggests several AI regulatory approaches for consideration that is forward-looking and agile while simultaneously fostering innovation and human rights. The anticipated outcome is to ensure that NSW Government matches the rising levels of innovation in AI technologies with the appropriate and balanced innovation in AI governance.

Keywords: artificial inteligence, machine learning, rules, governance, government

Procedia PDF Downloads 71

Authors: Luzie Krings

Abstract:

The electrification of the transport sector is increasingly recognized as a vital strategy for decarbonization. However, integrating electric vehicles (EVs) into the energy grid poses challenges due to decentralized power units and the intermittent nature of renewable energy sources. Vehicle-to-grid (V2G) technology offers a compelling solution by enabling EVs to function as mobile storage units, providing system services, reducing grid congestion, and offering economic incentives. This potential is particularly significant in freight transport, which accounts for 38% of transport-related emissions. The aggregated use of energy storage in this sector can facilitate grid stability and renewable energy integration. Despite this, existing optimization methods for energy markets frequently overlook operational constraints, such as fixed schedules and state-of-charge requirements, while redispatch markets remain underutilized. This study introduces a risk-averse optimization model for marketing EV flexibilities across multiple energy markets in Germany. Using a linear optimization framework, the model incorporates technical, regulatory, and user constraints. EVs are modeled as energy storage units, and the integration of renewable energy sources, such as photovoltaic (PV) and wind energy, is evaluated. To benchmark performance, unidirectional charging with dynamic tariffs is used as the reference scenario. The research examines four distinct logistics depot fleets, each with varying capacities and schedules, to simulate commercial EV operations. The methodology employs a multi-market optimization model that integrates Day-Ahead, Intraday, and Redispatch energy markets, each with specific trading conditions and temporal offsets. The tool, developed using the Python-based library energy pilot by Fraunhofer IEE, also explores scenarios where proprietary renewable energy sources are incorporated to maximize benefits. By accounting for charging schedules, market requirements, and technical constraints, the study aims to enhance grid stability and improve economic outcomes and integration of renewable energies. The findings highlight the economic, environmental, and grid-related advantages of optimizing EV flexibility. Compared to the reference scenario of unidirectional charging, bidirectional strategies delivered an approximate economic benefit of 20%. Furthermore, the integration of proprietary renewable energy sources increased by 15%, demonstrating the potential for environmental gains. The study revealed that the duration of a single charging cycle has a greater impact on economic benefits than the total daily charging time spread across multiple cycles. This underscores the marketing potential of vehicles with extended idle times rather than frequent charging cycles. In conclusion, optimizing energy trading through flexible EV portfolios and efficient charging infrastructure offers substantial cost savings, particularly by increasing the number of charging stations and extending charging cycle durations. By leveraging multiple marketing options, high investment costs can be offset through enhanced revenues. Further gains could be achieved by simultaneously optimizing all trading options, though this approach introduces risks from price volatility and unreliable redispatch capacities. As electrified trucks are modeled as energy storage units, the study's findings are applicable to other forms of energy storage, offering a scalable and transferable framework for future energy systems.

Keywords: electric vehicles, energy markets, energy storage, energy grid

Procedia PDF Downloads 15

Authors: Alberto Alfano, Sergio D’ambrosio, Darshankumar Parecha, Donatella Cimini, Chiara Schiraldi.

Abstract:

The main objective of this study regards the setup of an efficient small-scale platform for the conversion of local renewable waste materials, such as whey, into added-value products, thereby reducing environmental impact and costs deriving from the disposal of processing waste products. The buffalo milk whey derived from the cheese-making process, called second cheese whey, is the main by-product of the dairy industry. Whey is the main and most polluting by-product obtained from cheese manufacturing consisting of lactose, lactic acid, proteins, and salts, making whey an added-value product. In Italy, and in particular, in the Campania region, soft cheese production needs a large volume of liquid waste, especially during late spring and summer. This project is part of a circular economy perspective focused on the conversion of potentially polluting and difficult to purify waste into a resource to be exploited, and it embodies the concept of the three “R”: reduce, recycle, and reuse. Special focus was paid to the production of health-promoting biomolecules and biopolymers, which may be exploited in different segments of the food and pharmaceutical industries. These biomolecules may be recovered through appropriate processes and reused in an attempt to obtain added value products. So, ultrafiltration and nanofiltration processes were performed to fractionate bioactive components starting from buffalo milk whey. In this direction, the present study focused on the implementation of a downstream process that converts waste generated from food and food processing industries into added value products with potential applications. Owing to innovative downstream and biotechnological processes, rather than a waste product may be considered a resource to obtain high added value products, such as food supplements (probiotics), cosmeceuticals, biopolymers, and recyclable purified water. Besides targeting gastrointestinal disorders, probiotics such as Lactobacilli have been reported to improve immunomodulation and protection of the host against infections caused by viral and bacterial pathogens. Interestingly, also inactivated microbial (probiotic) cells and their metabolic products, indicated as parabiotic and postbiotics, respectively, have a crucial role and act as mediators in the modulation of the host’s immune function. To boost the production of biomass (both viable and/or heat inactivated cells) and/or the synthesis of growth-related postbiotics, such as EPS, efficient and sustainable fermentation processes are necessary. Based on a “zero-waste” approach, wastes generated from local industries can be recovered and recycled to develop sustainable biotechnological processes to obtain probiotics as well as post and parabiotic, to be tested as bioactive compounds against gastrointestinal disorders. The results have shown it was possible to recover an ultrafiltration retentate with suitable characteristics to be used in skin dehydration, to perform films (i.e., packaging for food industries), or as a wound repair agent and a nanofiltration retentate to recover lactic acid and carbon sources (e.g., lactose, glucose..) used for microbial cultivation. On the side, the last goal is to obtain purified water that can be reused throughout the process. In fact, water reclamation and reuse provide a unique and viable opportunity to augment traditional water supplies, a key issue nowadays.

Keywords: biotech process, downstream process, probiotic growth, from waste to product, buffalo whey

Procedia PDF Downloads 69

Authors: Kumar Satyam Das, Murali Raghunathan

Abstract:

This note discusses the feasibility of field development of a challenging shallow offshore field in South East Asia and how its learnings can be applied to marginal field development across the world especially developing marginal fields in this low oil price world. The field was found to be economically challenging even during high oil prices and the project was put on hold. Shell started development study with the aim to significantly reduce cost through competitively scoping and revive stranded projects. The proposed strategy to achieve this involved Improve Per platform recovery and Reduction in CAPEX. Methodology: Based on various Benchmarking Tool such as Woodmac for similar projects in the region and economic affordability, a challenging target of 50% reduction in unit development cost (UDC) was set for the project. Technical scope was defined to the minimum as to be a wellhead platform with minimum functionality to ensure production. The evaluation of key project decisions like Well location and number, well design, Artificial lift methods and wellhead platform type under different development concept was carried out through integrated multi-discipline approach. Key elements influencing per platform recovery were Wellhead Platform (WHP) location, Well count, well reach and well productivity. Major Findings: Reservoir being shallow posed challenges in well design (dog-leg severity, casing size and the achievable step-out), choice of artificial lift and sand-control method. Integrated approach amongst relevant disciplines with challenging mind-set enabled to achieve optimized set of development decisions. This led to significant improvement in per platform recovery. It was concluded that platform recovery largely depended on the reach of the well. Choice of slim well design enabled designing of high inclination and better productivity wells. However, there is trade-off between high inclination Gas Lift (GL) wells and low inclination wells in terms of long term value, operational complexity, well reach, recovery and uptime. Well design element like casing size, well completion, artificial lift and sand control were added successively over the minimum technical scope design leading to a value and risk staircase. Logical combinations of options (slim well, GL) were competitively screened to achieve 25% reduction in well cost. Facility cost reduction was achieved through sourcing standardized Low Cost Facilities platform in combination with portfolio execution to maximizing execution efficiency; this approach is expected to reduce facilities cost by ~23% with respect to the development costs. Further cost reductions were achieved by maximizing use of existing facilities nearby; changing reliance on existing water injection wells and utilizing existing water injector (W.I.) platform for new injectors. Conclusion: The study provides a spectrum of technically feasible options. It also made clear that different drivers lead to different development concepts and the cost value trade off staircase made this very visible. Scoping of the project through competitive way has proven to be valuable for decision makers by creating a transparent view of value and associated risks/uncertainty/trade-offs for difficult choices: elements of the projects can be competitive, whilst other parts will struggle, even though contributing to significant volumes. Reduction in UDC through proper scoping of present projects and its benchmarking paves as a learning for the development of marginal fields across the world, especially in this low oil price scenario. This way of developing a field has on average a reduction of 40% of cost for the Shell projects.

Keywords: benchmarking, full field development, CAPEX, feasibility

Procedia PDF Downloads 159

Authors: Adela Diepoltova, Klara Konecna, Ondrej Jandourek, Petr Nachtigal

Abstract:

A loss of control over antibiotic-resistant pathogens has become a global issue due to severe and often untreatable infections. This state is reflected in complicated treatment, health costs, and higher mortality. All these factors emphasize the urgent need for the discovery and development of new anti-infectives. One of the most common pathogens mentioned in the phenomenon of antibiotic resistance are bacteria of the genus Staphylococcus. These bacterial agents have developed several mechanisms against the effect of antibiotics. One of them is biofilm formation. In staphylococci, biofilms are associated with infections such as endocarditis, osteomyelitis, catheter-related bloodstream infections, etc. To author's best knowledge, no validated and standardized methodology evaluating candidate compound activity against staphylococcal biofilms exists. However, a variety of protocols for in vitro drug activity testing has been suggested, yet there are often fundamental differences. Based on our experience, a key methodological step that leads to credible results is to form a robust biofilm with appropriate attributes such as firm adherence to the substrate, a complex arrangement in layers, and the presence of extracellular polysaccharide matrix. At first, for the purpose of drug antibiofilm activity evaluation, the focus was put on various conditions (supplementation of cultivation media by human plasma/fetal bovine serum, shaking mode, the density of initial inoculum) that should lead to reproducible and robust in vitro staphylococcal biofilm formation in microtiter plate model. Three model staphylococcal reference strains were included in the study: Staphylococcus aureus (ATCC 29213), methicillin-resistant Staphylococcus aureus (ATCC 43300), and Staphylococcus epidermidis (ATCC 35983). The total biofilm biomass was quantified using the Christensen method with crystal violet, and results obtained from at least three independent experiments were statistically processed. Attention was also paid to the viability of the biofilm-forming staphylococcal cells and the presence of extracellular polysaccharide matrix. The conditions that led to robust biofilm biomass formation with attributes for biofilms mentioned above were then applied by introducing an alternative method analogous to the commercially available test system, the Calgary Biofilm Device. In this test system, biofilms are formed on pegs that are incorporated into the lid of the microtiter plate. This system provides several advantages (in situ detection and quantification of biofilm microbial cells that have retained their viability after drug exposure). Based on our preliminary studies, it was found that the attention to the peg surface and substrate on which the bacterial biofilms are formed should also be paid to. Therefore, further steps leading to the optimization were introduced. The surface of pegs was coated by human plasma, fetal bovine serum, and L-polylysine. Subsequently, the willingness of bacteria to adhere and form biofilm was monitored. In conclusion, suitable conditions were revealed, leading to the formation of reproducible, robust staphylococcal biofilms in vitro for the microtiter model and the system analogous to the Calgary biofilm device, as well. The robustness and typical slime texture could be detected visually. Likewise, an analysis by confocal laser scanning microscopy revealed a complex three-dimensional arrangement of biofilm forming organisms surrounded by an extracellular polysaccharide matrix.

Keywords: anti-biofilm drug activity screening, in vitro biofilm formation, microtiter plate model, the Calgary biofilm device, staphylococcal infections, substrate modification, surface coating

Procedia PDF Downloads 156

Authors: Pei Yi Lin

Abstract:

Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

Procedia PDF Downloads 79

Authors: Kalaumari Mayoral-Peña, Ana I. Montejano-Montelongo, Josué Reyes-Muñoz, Gonzalo A. Ortiz-Mancilla, Mayrin Rodríguez-Cruz, Víctor Hernández-Villalobos, Jesús A. Guzmán-López, Santiago García-Jacobo, Iván Licona-Vázquez, Grisel Fierros-Romero, Rosario Flores-Vallejo

Abstract:

The group B-lactamic antibiotics include some of the most frequently used small drug molecules against bacterial infections. Nevertheless, an alarming decrease in their efficacy has been reported due to the emergence of antibiotic-resistant bacteria. Infections caused by bacteria expressing extended Spectrum B-lactamases (ESBLs) are difficult to treat and account for higher morbidity and mortality rates, delayed recovery, and high economic burden. According to the Global Report on Antimicrobial Resistance Surveillance, it is estimated that mortality due to resistant bacteria will ascend to 10 million cases per year worldwide. These facts highlight the importance of developing low-cost and readily accessible detection methods of drug-resistant ESBLs bacteria to prevent their spread and promote accurate and fast diagnosis. Bacterial detection is commonly done using molecular diagnostic techniques, where PCR stands out for its high performance. However, this technique requires specialized equipment not available everywhere, is time-consuming, and has a high cost. Loop-Mediated Isothermal Amplification (LAMP) is an alternative technique that works at a constant temperature, significantly decreasing the equipment cost. It yields double-stranded DNA of several lengths with repetitions of the target DNA sequence as a product. Although positive and negative results from LAMP can be discriminated by colorimetry, fluorescence, and turbidity, there is still a large room for improvement in the point-of-care implementation. DNA origami is a technique that allows the formation of 3D nanometric structures by folding a large single-stranded DNA (scaffold) into a determined shape with the help of short DNA sequences (staples), which hybridize with the scaffold. This research aimed to generate DNA origami structures using LAMP products as scaffolds to improve the sensitivity to detect ESBLs in point-of-care diagnosis. For this study, the coding sequence of the CTM-X-15 ESBL of E. coli was used to generate the LAMP products. The set of LAMP primers were designed using PrimerExplorerV5. As a result, a target sequence of 200 nucleotides from CTM-X-15 ESBL was obtained. Afterward, eight different DNA origami structures were designed using the target sequence in the SDCadnano and analyzed with CanDo to evaluate the stability of the 3D structures. The designs were constructed minimizing the total number of staples to reduce costs and complexity for point-of-care applications. After analyzing the DNA origami designs, two structures were selected. The first one was a zig-zag flat structure, while the second one was a wall-like shape. Given the sequence repetitions in the scaffold sequence, both were able to be assembled with only 6 different staples each one, ranging between 18 to 80 nucleotides. Simulations of both structures were performed using scaffolds of different sizes yielding stable structures in all the cases. The generation of the LAMP products were tested by colorimetry and electrophoresis. The formation of the DNA structures was analyzed using electrophoresis and colorimetry. The modeling of novel detection methods through bioinformatics tools allows reliable control and prediction of results. To our knowledge, this is the first study that uses LAMP products and DNA-origami in combination to delect ESBL-producing bacterial strains, which represent a promising methodology for diagnosis in the point-of-care.

Keywords: beta-lactamases, antibiotic resistance, DNA origami, isothermal amplification, LAMP technique, molecular diagnosis

Procedia PDF Downloads 223

Authors: Zbigniew Czyz, Ksenia Siadkowska, Krzysztof Skiba, Karol Scislowski

Abstract:

Today’s progress in the rotorcraft is mostly associated with an optimization of aircraft performance achieved by active and passive modifications of main rotor assemblies and a tail propeller. The key task is to improve their performance, improve the hover quality factor for rotors but not change in specific fuel consumption. One of the tasks to improve the helicopter is an active optimization of the main rotor providing for flight stages, i.e., an ascend, flight, a descend. An active interference with the airflow around the rotor blade section can significantly change characteristics of the aerodynamic airfoil. The efficiency of actuator systems modifying aerodynamic coefficients in the current solutions is relatively high and significantly affects the increase in strength. The solution to actively change aerodynamic characteristics assumes a periodic change of geometric features of blades depending on flight stages. Changing geometric parameters of blade warping enables an optimization of main rotor performance depending on helicopter flight stages. Structurally, an adaptation of shape memory alloys does not significantly affect rotor blade fatigue strength, which contributes to reduce costs associated with an adaptation of the system to the existing blades, and gains from a better performance can easily amortize such a modification and improve profitability of such a structure. In order to obtain quantitative and qualitative data to solve this research problem, a number of numerical analyses have been necessary. The main problem is a selection of design parameters of the main rotor and a preliminary optimization of its performance to improve the hover quality factor for rotors. This design concept assumes a three-bladed main rotor with a chord of 0.07 m and radius R = 1 m. The value of rotor speed is a calculated parameter of an optimization function. To specify the initial distribution of geometric warping, a special software has been created that uses a numerical method of a blade element which respects dynamic design features such as fluctuations of a blade in its joints. A number of performance analyses as a function of rotor speed, forward speed, and altitude have been performed. The calculations were carried out for the full model assembly. This approach makes it possible to observe the behavior of components and their mutual interaction resulting from the forces. The key element of each rotor is the shaft, hub and pins holding the joints and blade yokes. These components are exposed to the highest loads. As a result of the analysis, the safety factor was determined at the level of k > 1.5, which gives grounds to obtain certification for the strength of the structure. The construction of the joint rotor has numerous moving elements in its structure. Despite the high safety factor, the places with the highest stresses, where the signs of wear and tear may appear, have been indicated. The numerical analysis carried out showed that the most loaded element is the pin connecting the modular bearing of the blade yoke with the element of the horizontal oscillation joint. The stresses in this element result in a safety factor of k=1.7. The other analysed rotor components have a safety factor of more than 2 and in the case of the shaft, this factor is more than 3. However, it must be remembered that the structure is as strong as the weakest cell is. Designed rotor for unmanned aerial vehicles adapted to work with blades with intelligent materials in its structure meets the requirements for certification testing. Acknowledgement: This work has been financed by the Polish National Centre for Research and Development under the LIDER program, Grant Agreement No. LIDER/45/0177/L-9/17/NCBR/2018.

Keywords: main rotor, rotorcraft aerodynamics, shape memory alloy, materials, unmanned helicopter

Procedia PDF Downloads 159

Authors: Liane J. Ioannou, Jonathan Serpell, Cino Bendinelli, David Walters, Jenny Gough, Dean Lisewski, Win Meyer-Rochow, Julie Miller, Duncan Topliss, Bill Fleming, Stephen Farrell, Andrew Kiu, James Kollias, Mark Sywak, Adam Aniss, Linda Fenton, Danielle Ghusn, Simon Harper, Aleksandra Popadich, Kate Stringer, David Watters, Susannah Ahern

Abstract:

BACKGROUND: There are significant variations in the management, treatment and outcomes of thyroid cancer, particularly in the role of: diagnostic investigation and pre-treatment scanning; optimal extent of surgery (total or hemi-thyroidectomy); use of active surveillance for small low-risk cancers; central lymph node dissections (therapeutic or prophylactic); outcomes following surgery (e.g. recurrent laryngeal nerve palsy, hypocalcaemia, hypoparathyroidism); post-surgical hormone, calcium and vitamin D therapy; and provision and dosage of radioactive iodine treatment. A proven strategy to reduce variations in the outcome and to improve survival is to measure and compare it using high-quality clinical registry data. Clinical registries provide the most effective means of collecting high-quality data and are a tool for quality improvement. Where they have been introduced at a state or national level, registries have become one of the most clinically valued tools for quality improvement. To benchmark clinical care, clinical quality registries require systematic measurement at predefined intervals and the capacity to report back information to participating clinical units. OBJECTIVE: The aim of this study was to develop a core set clinical indicators that enable measurement and reporting of quality of care for patients with thyroid cancer. We hypothesise that measuring clinical quality indicators, developed to identify differences in quality of care across sites, will reduce variation and improve patient outcomes and survival, thereby lessening costs and healthcare burden to the Australian community. METHOD: Preparatory work and scoping was conducted to identify existing high quality, clinical guidelines and best practice for thyroid cancer both nationally and internationally, as well as relevant literature. A bi-national panel was invited to participate in a modified Delphi process. Panelists were asked to rate each proposed indicator on a Likert scale of 1–9 in a three-round iterative process. RESULTS: A total of 236 potential quality indicators were identified. One hundred and ninety-two indicators were removed to reflect the data capture by the Australian and New Zealand Thyroid Cancer Registry (ANZTCR) (from diagnosis to 90-days post-surgery). The remaining 44 indicators were presented to the panelists for voting. A further 21 indicators were later added by the panelists bringing the total potential quality indicators to 65. Of these, 21 were considered the most important and feasible indicators to measure quality of care in thyroid cancer, of which 12 were recommended for inclusion in the final set. The consensus indicator set spans the spectrum of care, including: preoperative; surgery; surgical complications; staging and post-surgical treatment planning; and post-surgical treatment. CONCLUSIONS: This study provides a core set of quality indicators to measure quality of care in thyroid cancer. This indicator set can be applied as a tool for internal quality improvement, comparative quality reporting, public reporting and research. Inclusion of these quality indicators into monitoring databases such as clinical quality registries will enable opportunities for benchmarking and feedback on best practice care to clinicians involved in the management of thyroid cancer.

Keywords: clinical registry, Delphi survey, quality indicators, quality of care

Procedia PDF Downloads 181

Authors: Alexandria Carey, Angela Starkweather, Ann Horgas, Hwayoung Cho, Jason Beneciuk

Abstract:

Background/Significance: Over 3.4 million acute axial low back pain (aLBP) cases are treated annually in the United States (US) emergency departments (ED). ED patients with aLBP receive varying verbal and written discharge routine care (RC), leading to ineffective patient self-management. Ineffective self-management increase chronic low back pain (cLPB) transition risks, a chief cause of worldwide disability, with associated costs >$60 million annually. This research addresses this significant problem by evaluating an ED digital pain self-management intervention (EDPSI) focused on improving self-management through improved knowledge retainment, skills, and self-efficacy (confidence) (KSC) thus reducing aLBP to cLBP transition in ED patients discharged with aLBP. The research has significant potential to increase self-efficacy, one of the most potent mechanisms of behavior change and improve health outcomes. Focusing on accessibility and usability, the intervention may reduce discharge disparities in aLBP self-management, especially with low health literacy. Study Questions: This research will answer the following questions: 1) Will an EDPSI focused on improving KSC progress patient self-management behaviors and health status?; 2) Is the EDPSI sustainable to improve pain severity, interference, and pain recurrence?; 3) Will an EDPSI reduce aLBP to cLBP transition in patients discharged with aLBP? Aims: The pilot randomized-controlled trial (RCT) study’s objectives assess the effects of a 12-week digital self-management discharge tool in patients with aLBP. We aim to 1) Primarily assess the feasibility [recruitment, enrollment, and retention], and [intervention] acceptability, and sustainability of EDPSI on participant’s pain self-management; 2) Determine the effectiveness and sustainability of EDPSI on pain severity/interference among participants. 3) Explore patient preferences, health literacy, and changes among participants experiencing the transition to cLBP. We anticipate that EDPSI intervention will increase likelihood of achieving self-management milestones and significantly improve pain-related symptoms in aLBP. Methods: The study uses a two-group pilot RCT to enroll 30 individuals who have been seen in the ED with aLBP. Participants are randomized into RC (n=15) or RC + EDPSI (n=15) and receive follow-up surveys for 12-weeks post-intervention. EDPSI innovative content focuses on 1) highlighting discharge education; 2) provides self-management treatment options; 3) actor demonstration of ergonomics, range of motion movements, safety, and sleep; 4) complementary alternative medicine (CAM) options including acupuncture, yoga, and Pilates; 5) combination therapies including thermal application, spinal manipulation, and PT treatments. The intervention group receives Booster sessions via Zoom to assess and reinforce their knowledge retention of techniques and provide return demonstration reinforcing ergonomics, in weeks two and eight. Outcome Measures: All participants are followed for 12-weeks, assessing pain severity/ interference using the Brief Pain Inventory short-form (BPI-sf) survey, self-management (measuring KSC) using the short 13-item Patient Activation Measure (PAM), and self-efficacy using the Pain Self-Efficacy Questionnaire (PSEQ) weeks 1, 6, and 12. Feasibility is measured by recruitment, enrollment, and retention percentages. Acceptability and education satisfaction are measured using the Education-Preference and Satisfaction Questionnaire (EPSQ) post-intervention. Self-management sustainment is measured including PSEQ, PAM, and patient satisfaction and healthcare utilization (PSHU) requesting patient overall satisfaction, additional healthcare utilization, and pain management related to continued back pain or complications post-injury.

Keywords: digital, pain self-management, education, tool

Procedia PDF Downloads 53

Authors: Savvas Rogotis, Nikolaos Kalatzis, Stergios Dimou-Sakellariou, Nikolaos Marianos

Abstract:

As precision holds the key for the introduction of distinct benefits in agriculture (e.g., energy savings, reduced labor costs, optimal application of inputs, improved products, and yields), it steadily becomes evident that new initiatives should focus on rendering Precision Agriculture (PA) more accessible to the average farmer. PA leverages on technologies such as the Internet of Things (IoT), earth observation, robotics and positioning systems (e.g., the Global Navigation Satellite System – GNSS - as well as individual positioning systems like GPS, Glonass, Galileo) that allow: from simple data georeferencing to optimal navigation of agricultural machinery to even more complex tasks like Variable Rate Applications. An identified customer pain point is that, from one hand, typical triangulation-based positioning systems are not accurate enough (with errors up to several meters), while on the other hand, high precision positioning systems reaching centimeter-level accuracy, are very costly (up to thousands of euros). Within this paper, a Ground-Based Augmentation System (GBAS) is introduced, that can be adapted to any existing IoT field-sensing station infrastructure. The latter should cover a minimum set of requirements, and in particular, each station should operate as a fixed, obstruction-free towards the sky, energy supplying unit. Station augmentation will allow them to function in pairs with GNSS rovers following the differential GNSS base-rover paradigm. This constitutes a key innovation element for the proposed solution that encompasses differential GNSS capabilities into an IoT field-sensing infrastructure. Integrating this kind of information supports the provision of several additional PA beneficial services such as spatial mapping, route planning, and automatic field navigation of unmanned vehicles (UVs). Right at the heart of the designed system, there is a high-end GNSS toolkit with base-rover variants and Real-Time Kinematic (RTK) capabilities. The GNSS toolkit had to tackle all availability, performance, interfacing, and energy-related challenges that are faced for a real-time, low-power, and reliable in the field operation. Specifically, in terms of performance, preliminary findings exhibit a high rover positioning precision that can even reach less than 10-centimeters. As this precision is propagated to the full dataset collection, it enables tractors, UVs, Android-powered devices, and measuring units to deal with challenging real-world scenarios. The system is validated with the help of Gaiatrons, a mature network of agro-climatic telemetry stations with presence all over Greece and beyond ( > 60.000ha of agricultural land covered) that constitutes part of “gaiasense” (www.gaiasense.gr) smart farming (SF) solution. Gaiatrons constantly monitor atmospheric and soil parameters, thus, providing exact fit to operational requirements asked from modern SF infrastructures. Gaiatrons are ultra-low-cost, compact, and energy-autonomous stations with a modular design that enables the integration of advanced GNSS base station capabilities on top of them. A set of demanding pilot demonstrations has been initiated in Stimagka, Greece, an area with a diverse geomorphological landscape where grape cultivation is particularly popular. Pilot demonstrations are in the course of validating the preliminary system findings in its intended environment, tackle all technical challenges, and effectively highlight the added-value offered by the system in action.

Keywords: GNSS, GBAS, precision agriculture, RTK, smart farming

Procedia PDF Downloads 116

Authors: Teesta Dey

Abstract:

Integrated Transport development with proper traffic management leads to sustainable growth of any urban sphere. Appropriate mass transport planning is essential for the populous cities in third world countries like India. The exponential growth of motor vehicles with unplanned road network is now the common feature of major urban centres in India. Kolkata, the third largest mega city in India, is not an exception of it. The imbalance between demand and supply of unplanned transport services in this city is manifested in the high economic and environmental costs borne by the associated society. With the passage of time, the growth and extent of passenger demand for rapid urban transport has outstripped proper infrastructural planning and causes severe transport problems in the overall urban realm. Hence Kolkata stands out in the world as one of the most crisis-ridden metropolises. The urban transport crisis of this city involves severe traffic congestion, the disparity in mass transport services on changing peripheral land uses, route overlapping, lowering of travel speed and faulty implementation of governmental plans as mostly induced by rapid growth of private vehicles on limited road space with huge carbon footprint. Therefore the paper will critically analyze the extant road network pattern for improving regional connectivity and accessibility, assess the degree of congestion, identify the deviation from demand and supply balance and finally evaluate the emerging alternate transport options as promoted by the government. For this purpose, linear, nodal and spatial transport network have been assessed based on certain selected indices viz. Road Degree, Traffic Volume, Shimbel Index, Direct Bus Connectivity, Average Travel and Waiting Tine Indices, Route Variety, Service Frequency, Bus Intensity, Concentration Analysis, Delay Rate, Quality of Traffic Transmission, Lane Length Duration Index and Modal Mix. Total 20 Traffic Intersection Points (TIPs) have been selected for the measurement of nodal accessibility. Critical Congestion Zones (CCZs) are delineated based on one km buffer zones of each TIP for congestion pattern analysis. A total of 480 bus routes are assessed for identifying the deficiency in network planning. Apart from bus services, the combined effects of other mass and para transit modes, containing metro rail, auto, cab and ferry services, are also analyzed. Based on systematic random sampling method, a total of 1500 daily urban passengers’ perceptions were studied for checking the ground realities. The outcome of this research identifies the spatial disparity among the 15 boroughs of the city with severe route overlapping and congestion problem. North and Central Kolkata-based mass transport services exceed the transport strength of south and peripheral Kolkata. Faulty infrastructural condition, service inadequacy, economic loss and workers’ inefficiency are the most dominant reasons behind the defective mass transport network plan. Hence there is an urgent need to revive the extant road based mass transport system of this city by implementing a holistic management approach by upgrading traffic infrastructure, designing new roads, better cooperation among different mass transport agencies, better coordination of transport and changing land use policies, large increase in funding and finally general passengers’ awareness.

Keywords: carbon footprint, critical congestion zones, direct bus connectivity, integrated transport development

Procedia PDF Downloads 273