Search results for: mining operations

Authors: Panagiota Katsikouli, William Hamilton Byrne, Thomas Gammeltoft-Hansen, Tijs Slaats

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An individual who demonstrates a well-founded fear of persecution or faces real risk of being subjected to torture is eligible for asylum. In Danish law, the exact legal thresholds reflect those established by international conventions, notably the 1951 Refugee Convention and the 1950 European Convention for Human Rights. These international treaties, however, remain largely silent when it comes to how states should assess asylum claims. As a result, national authorities are typically left to determine an individual’s legal eligibility on a narrow basis consisting of an oral testimony, which may itself be hampered by several factors, including imprecise language interpretation, insecurity or lacking trust towards the authorities among applicants. The leaky ground, on which authorities must assess their subjective perceptions of asylum applicants' credibility, questions whether, in all cases, adjudicators make the correct decision. Moreover, the subjective element in these assessments raises questions on whether individual asylum cases could be afflicted by implicit biases or stereotyping amongst adjudicators. In fact, recent studies have uncovered significant correlations between decision outcomes and the experience and gender of the assigned judge, as well as correlations between asylum outcomes and entirely external events such as weather and political elections. In this study, we analyze a publicly available dataset containing approximately 8,000 summaries of asylum cases, initially rejected, and re-tried by the Refugee Appeals Board (RAB) in Denmark. First, we look for variations in the recognition rates, with regards to a number of applicants’ features: their country of origin/nationality, their identified gender, their identified religion, their ethnicity, whether torture was mentioned in their case and if so, whether it was supported or not, and the year the applicant entered Denmark. In order to extract those features from the text summaries, as well as the final decision of the RAB, we applied natural language processing and regular expressions, adjusting for the Danish language. We observed interesting variations in recognition rates related to the applicants’ country of origin, ethnicity, year of entry and the support or not of torture claims, whenever those were made in the case. The appearance (or not) of significant variations in the recognition rates, does not necessarily imply (or not) bias in the decision-making progress. None of the considered features, with the exception maybe of the torture claims, should be decisive factors for an asylum seeker’s fate. We therefore investigate whether the decision can be predicted on the basis of these features, and consequently, whether biases are likely to exist in the decisionmaking progress. We employed a number of machine learning classifiers, and found that when using the applicant’s country of origin, religion, ethnicity and year of entry with a random forest classifier, or a decision tree, the prediction accuracy is as high as 82% and 85% respectively. tentially predictive properties with regards to the outcome of an asylum case. Our analysis and findings call for further investigation on the predictability of the outcome, on a larger dataset of 17,000 cases, which is undergoing.

Keywords: asylum adjudications, automated decision-making, machine learning, text mining

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Authors: Solanki Ravirajsinh, Kudo Kuniaki, Sharma Ankit, Devi Sherine, Kuboshima Misaki, Tachi Shuntaro

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In software development life cycles, the absence of scalable CI/CD significantly impacts organizations, leading to increased overall maintenance costs, prolonged release delivery times, heightened manual efforts, and difficulties in meeting tight deadlines. Implementing CI/CD with standard serverless technologies using cloud services overcomes all the above-mentioned issues and helps organizations improve efficiency and faster delivery without the need to manage server maintenance and capacity. By integrating scalable CI/CD with scalable automation testing, productivity, quality, and agility are enhanced while reducing the need for repetitive work and manual efforts. Implementing scalable CI/CD for development using cloud services like ECS (Container Management Service), AWS Fargate, ECR (to store Docker images with all dependencies), Serverless Computing (serverless virtual machines), Cloud Log (for monitoring errors and logs), Security Groups (for inside/outside access to the application), Docker Containerization (Docker-based images and container techniques), Jenkins (CI/CD build management tool), and code management tools (GitHub, Bitbucket, AWS CodeCommit) can efficiently handle the demands of diverse development environments and are capable of accommodating dynamic workloads, increasing efficiency for faster delivery with good quality. CI/CD pipelines encourage collaboration among development, operations, and quality assurance teams by providing a centralized platform for automated testing, deployment, and monitoring. Scalable CI/CD streamlines the development process by automatically fetching the latest code from the repository every time the process starts, building the application based on the branches, testing the application using a scalable automation testing framework, and deploying the builds. Developers can focus more on writing code and less on managing infrastructure as it scales based on the need. Serverless CI/CD eliminates the need to manage and maintain traditional CI/CD infrastructure, such as servers and build agents, reducing operational overhead and allowing teams to allocate resources more efficiently. Scalable CI/CD adjusts the application's scale according to usage, thereby alleviating concerns about scalability, maintenance costs, and resource needs. Creating scalable automation testing using cloud services (ECR, ECS Fargate, Docker, EFS, Serverless Computing) helps organizations run more than 500 test cases in parallel, aiding in the detection of race conditions, performance issues, and reducing execution time. Scalable CI/CD offers flexibility, dynamically adjusting to varying workloads and demands, allowing teams to scale resources up or down as needed. It optimizes costs by only paying for the resources as they are used and increases reliability. Scalable CI/CD pipelines employ automated testing and validation processes to detect and prevent errors early in the development cycle.

Keywords: achieve parallel execution, cloud services, scalable automation testing, scalable continuous integration and deployment

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Authors: Pompilia Buzatu, Hazim Qiblawey, Albert Odai, Jana Jamaleddin, Mustafa Nasser, Simon J. Judd

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Membrane bioreactor (MBR) technology is challenged by the tendency for the membrane permeability to decrease due to ‘clogging’. Clogging includes ‘sludging’, the filling of the membrane channels with sludge solids, and ‘ragging’, the aggregation of short filaments to form long rag-like particles. Both sludging and ragging demand manual intervention to clear out the solids, which is time-consuming, labour-intensive and potentially damaging to the membranes. These factors impact on costs more significantly than membrane surface fouling which, unlike clogging, is largely mitigated by the chemical clean. However, practical evaluation of MBR clogging has thus far been limited. This paper presents the results of recent work attempting to quantify sludging and clogging based on simple bench-scale tests. Results from a novel ragging simulation trial indicated that rags can be formed within 24-36 hours from dispersed < 5 mm-long filaments at concentrations of 5-10 mg/L under gently agitated conditions. Rag formation occurred for both a cotton wool standard and samples taken from an operating municipal MBR, with between 15% and 75% of the added fibrous material forming a single rag. The extent of rag formation depended both on the material type or origin – lint from laundering operations forming zero rags – and the filament length. Sludging rates were quantified using a bespoke parallel-channel test cell representing the membrane channels of an immersed flat sheet MBR. Sludge samples were provided from two local MBRs, one treating municipal and the other industrial effluent. Bulk sludge properties measured comprised mixed liquor suspended solids (MLSS) concentration, capillary suction time (CST), particle size, soluble COD (sCOD) and rheology (apparent viscosity μₐ vs shear rate γ). The fouling and sludging propensity of the sludge was determined using the test cell, ‘fouling’ being quantified as the pressure incline rate against flux via the flux step test (for which clogging was absent) and sludging by photographing the channel and processing the image to determine the ratio of the clogged to unclogged regions. A substantial difference in rheological and fouling behaviour was evident between the two sludge sources, the industrial sludge having a higher viscosity but less shear-thinning than the municipal. Fouling, as manifested by the pressure increase Δp/Δt, as a function of flux from classic flux-step experiments (where no clogging was evident), was more rapid for the industrial sludge. Across all samples of both sludge origins the expected trend of increased fouling propensity with increased CST and sCOD was demonstrated, whereas no correlation was observed between clogging rate and these parameters. The relative contribution of fouling and clogging was appraised by adjusting the clogging propensity via increasing the MLSS both with and without a commensurate increase in the COD. Results indicated that whereas for the municipal sludge the fouling propensity was affected by the increased sCOD, there was no associated increased in the sludging propensity (or cake formation). The clogging rate actually decreased on increasing the MLSS. Against this, for the industrial sludge the clogging rate dramatically increased with solids concentration despite a decrease in the soluble COD. From this was surmised that sludging did not relate to fouling.

Keywords: clogging, membrane bioreactors, ragging, sludge

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Authors: Yumei Han, Ling Li, Naiqing Song, Xiaoping Yang, Yuping Han

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Educational think tank is agreeably regarded as significant part of a nation’s soft power to promote the scientific and democratic level of educational policy making, and it plays critical role of bridging educational research in higher institutions and educational policy making. This study explores the concept, functions and significance of educational think tank in China, and conceptualizes a three dimensional framework to analyze the approaches of transforming research-based higher institutions into effective educational think tanks to serve educational policy making in the nation wide. Since 2014, the Ministry of Education P.R. China has been promoting the strategy of developing new type of educational think tanks in higher institutions, and such a strategy has been put into the agenda for the 13th Five Year Plan for National Education Development released in 2017.In such context, increasing scholars conduct studies to put forth strategies of promoting the development and transformation of new educational think tanks to serve educational policy making process. Based on literature synthesis, policy text analysis, and analysis of theories about policy making process and relationship between educational research and policy-making, this study constructed a three dimensional conceptual framework to address the following questions: (a) what are the new features of educational think tanks in the new era comparing traditional think tanks, (b) what are the functional objectives of the new educational think tanks, (c) what are the organizational patterns and mechanism of the new educational think tanks, (d) in what approaches traditional research-based higher institutions can be developed or transformed into think tanks to effectively serve the educational policy making process. The authors adopted case study approach on five influential education policy study centers affiliated with top higher institutions in China and applied the three dimensional conceptual framework to analyze their functional objectives, organizational patterns as well as their academic pathways that researchers use to contribute to the development of think tanks to serve education policy making process.Data was mainly collected through interviews with center administrators, leading researchers and academic leaders in the institutions. Findings show that: (a) higher institution based think tanks mainly function for multi-level objectives, providing evidence, theoretical foundations, strategies, or evaluation feedbacks for critical problem solving or policy-making on the national, provincial, and city/county level; (b) higher institution based think tanks organize various types of research programs for different time spans to serve different phases of policy planning, decision making, and policy implementation; (c) in order to transform research-based higher institutions into educational think tanks, the institutions must promote paradigm shift that promotes issue-oriented field studies, large data mining and analysis, empirical studies, and trans-disciplinary research collaborations; and (d) the five cases showed distinguished features in their way of constructing think tanks, and yet they also exposed obstacles and challenges such as independency of the think tanks, the discourse shift from academic papers to consultancy report for policy makers, weakness in empirical research methods, lack of experience in trans-disciplinary collaboration. The authors finally put forth implications for think tank construction in China and abroad.

Keywords: education policy-making, educational research, educational think tank, higher institution

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Authors: Mukondi Esther Nethavhakone

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In 2020 World Health Organization announced the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as Coronavirus disease 2019 (COVID-19) pandemic. To curb or contain the spread of the novel coronavirus (COVID 19), global governments implemented social distancing and lockdown regulations. Subsequently, it was no longer business as per usual, life as we knew it had changed, and so many aspects of people's lives were negatively affected, including financial and employment stability. Mainly, because companies/businesses had to put their operations on hold, some had to shut down completely, resulting in the loss of income for many people globally. Finances and employment insecurities are some of the issues that exacerbated many social issues that the world was already faced with, such as school drop-outs, teenage pregnancies, sexual assaults, gender-based violence, crime, child abuse, elderly abuse, to name a few. Expectedly the majority of the population's mental health state was threatened. This resulted in an increased number of people seeking mental healthcare services. The increasing need for mental healthcare services in Low and Middle-income countries proves to be a challenge because it is a well-known fact due to financial constraints and not well-established healthcare systems, mental healthcare provision is not as prioritised as the primary healthcare in these countries. It is against this backdrop that the researcher seeks to find viable, cost-effective, and accessible mental health solutions for low and middle-income countries amid the pressures of any pandemic. The researcher will undertake a systematic review of the technology-based mental health solutions that have been implemented/adopted by developed countries during COVID 19 lockdown and social distancing periods. This systematic review study aims to determine if low and middle-income countries can adopt the cost-effective version of digital mental health solutions for the healthcare system to adequately provide mental healthcare services during critical times such as pandemics (when there's an overwhelming diminish in mental health globally). The researcher will undertake a systematic review study through mixed methods. It will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The mixed-methods uses findings from both qualitative and quantitative studies in one review study. It will be beneficial to conduct this kind of study using mixed methods because it is a public health topic that involves social interventions and it is not purely based on medical interventions. Therefore, the meta-ethnographic (qualitative data) analysis will be crucial in understanding why and which digital methods work and for whom does it work, rather than only the meta-analysis (quantitative data) providing what digital mental health methods works. The data collection process will be extensive, involving the development of a database, table of summary of evidence/findings, and quality assessment process lastly, The researcher will ensure that ethical procedures are followed and adhered to, ensuring that sensitive data is protected and the study doesn't pose any harm to the participants.

Keywords: digital, mental health, covid, low and middle-income countries

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Authors: Alberto Azevedo, Ricardo Martins, André B. Fortunato, Anabela Oliveira

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Water is under severe threat today because of the rising population, increased agricultural and industrial needs, and the intensifying effects of climate change. Due to sea-level rise, erosion, and demographic pressure, the coastal regions are of significant concern to the scientific community. The Water Monitoring Sentinel Cloud platform (WORSICA) service is focused on providing new tools for monitoring water in coastal and inland areas, taking advantage of remote sensing, in situ and tidal modeling data. WORSICA is a service that can be used to determine the coastline, coastal inundation areas, and the limits of inland water bodies using remote sensing (satellite and Unmanned Aerial Vehicles - UAVs) and in situ data (from field surveys). It applies to various purposes, from determining flooded areas (from rainfall, storms, hurricanes, or tsunamis) to detecting large water leaks in major water distribution networks. This service was built on components developed in national and European projects, integrated to provide a one-stop-shop service for remote sensing information, integrating data from the Copernicus satellite and drone/unmanned aerial vehicles, validated by existing online in-situ data. Since WORSICA is operational using the European Open Science Cloud (EOSC) computational infrastructures, the service can be accessed via a web browser and is freely available to all European public research groups without additional costs. In addition, the private sector will be able to use the service, but some usage costs may be applied, depending on the type of computational resources needed by each application/user. Although the service has three main sub-services i) coastline detection; ii) inland water detection; iii) water leak detection in irrigation networks, in the present study, an application of the service to Óbidos lagoon in Portugal is shown, where the user can monitor the evolution of the lagoon inlet and estimate the topography of the intertidal areas without any additional costs. The service has several distinct methodologies implemented based on the computations of the water indexes (e.g., NDWI, MNDWI, AWEI, and AWEIsh) retrieved from the satellite image processing. In conjunction with the tidal data obtained from the FES model, the system can estimate a coastline with the corresponding level or even topography of the inter-tidal areas based on the Flood2Topo methodology. The outcomes of the WORSICA service can be helpful for several intervention areas such as i) emergency by providing fast access to inundated areas to support emergency rescue operations; ii) support of management decisions on hydraulic infrastructures operation to minimize damage downstream; iii) climate change mitigation by minimizing water losses and reduce water mains operation costs; iv) early detection of water leakages in difficult-to-access water irrigation networks, promoting their fast repair.

Keywords: remote sensing, coastline detection, water detection, satellite data, sentinel, Copernicus, EOSC

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Authors: Yael Rieder, Yael Gilboa, S. O. Adva, Efrat Halevi, Ronnie Tepper

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Background: Operation of ultrasound equipment is a core skill for many clinical specialties. As part of the training program at -Simultech- a simulation center for Ob\Gyn at the Meir Medical Center, Israel, teaching how to operate ultrasound equipment requires dealing with misunderstandings of spatial and 3D orientation, failure of the operator to hold a transducer correctly, and limited ability to evaluate the data on the screen. We have developed a platform intended to endow physicians and sonographers with clinical and operational skills of obstetric ultrasound. Simultech's simulations are focused on medical knowledge, risk management, technology operations and physician-patient communication. The simulations encompass extreme work conditions. Setup: Between eight and ten of the eight hundred and fifty physicians and sonographers of the Clalit health services from seven hospitals and eight community centers across Israel, participate in individual Ob/Gyn training sessions each week. These include Ob/Gyn specialists, experts, interns, and sonographers. Innovative teaching and training methodologies: The six-hour training program includes: (1) An educational computer program that challenges trainees to deal with medical questions based upon ultrasound pictures and films. (2) Sophisticated hands-on simulators that challenge the trainees to practice correct grip of the transducer, elucidate pathology, and practice daily tasks such as biometric measurements and analysis of sonographic data. (3) Participation in a video-taped simulation which focuses on physician-patient communications. In the simulation, the physician is required to diagnose the clinical condition of a hired actress based on the data she provides and by evaluating the assigned ultrasound films accordingly. Giving ‘bad news’ to the patient may put the physician in a stressful situation that must be properly managed. (4) Feedback at the end of each phase is provided by a designated trainer, not a physician, who is specially qualified by Ob\Gyn senior specialists. (5) A group exercise in which the trainer presents a medico-legal case in order to encourage the participants to use their own experience and knowledge to conduct a productive ‘brainstorming’ session. Medical cases are presented and analyzed by the participants together with the trainer's feedback. Findings: (1) The training methods and content that Simultech provides allows trainees to review their medical and communications skills. (2) Simultech training sessions expose physicians to both basic and new, up-to-date cases, refreshing and expanding the trainee's knowledge. (3) Practicing on advanced simulators enables trainees to understand the sonographic space and to implement the basic principles of ultrasound. (4) Communications simulations were found to be beneficial for trainees who were unaware of their interpersonal skills. The trainer feedback, supported by the recorded simulation, allows the trainee to draw conclusions about his performance. Conclusion: Simultech was found to contribute to physicians at all levels of clinical expertise who deal with ultrasound. A break in daily routine together with attendance at a neutral educational center can vastly improve performance and outlook.

Keywords: medical training, simulations, ultrasound, Simultech

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Authors: Supriyo Das, Elbir Jove, Ajay Singh, Sophie Corbet, Noel Carr, Martin Deetz

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Water is a critical commodity in the healthcare and medical field. The utility of medical-grade water spans from washing surgical equipment, drug preparation to the key element of life-saving therapy such as hydrotherapy and hemodialysis for patients. A properly treated medical water reduces the bioburden load and mitigates the risk of infection, ensuring patient safety. However, any compromised condition during the production of medical-grade water can create a favorable environment for microbial growth putting patient safety at high risk. Therefore, proper upstream treatment of the medical water is essential before its application in healthcare, pharma and medical space. Reverse Osmosis (RO) is one of the most preferred treatments within healthcare industries and is recommended by all International Pharmacopeias to achieve the quality level demanded by global regulatory bodies. The RO process can remove up to 99.5% of constituents from feed water sources, eliminating bacteria, proteins and particles sizes of 100 Dalton and above. The combination of RO with other downstream water treatment technologies such as Electrodeionization and Ultrafiltration meet the quality requirements of various pharmacopeia monographs to produce highly purified water or water for injection for medical use. In the reverse osmosis process, the water from a liquid with a high concentration of dissolved solids is forced to flow through an especially engineered semi-permeable membrane to the low concentration side, resulting in high-quality grade water. However, these specially engineered RO membranes need to be sanitized either chemically or at high temperatures at regular intervals to keep the bio-burden at the minimum required level. In this paper, we talk about Dupont´s FilmTec Heat Sanitizable Reverse Osmosis membrane (HSRO) for the production of medical-grade water. An HSRO element must be pre-conditioned prior to initial use by exposure to hot water (80°C-85°C) for its stable performance and to meet the manufacturer’s specifications. Without pre-conditioning, the membrane will show variations in feed pressure operations and salt rejection. The paper will discuss the critical variables of pre-conditioning steps that can affect the overall performance of the HSRO membrane and demonstrate the data to support the need for pre-conditioning of HSRO elements. Our preliminary data suggests that there can be up to 35 % reduction in flow due to initial heat treatment, which also positively affects the increase in salt rejection. The paper will go into detail about the fundamental understanding of the performance change of HSRO after the pre-conditioning step and its effect on the quality of medical water produced. The paper will also discuss another critical point, “regular hot water sanitization” of these HSRO membranes. Regular hot water sanitization (at 80°C-85°C) is necessary to keep the membrane bioburden free; however, it can negatively impact the performance of the membrane over time. We will demonstrate several data points on hot water sanitization using FilmTec HSRO elements and challenge its robustness to produce quality medical water. The last part of this paper will discuss the construction details of the FilmTec HSRO membrane and features that make it suitable to pre-condition and sanitize at high temperatures.

Keywords: heat sanitizable reverse osmosis, HSRO, medical water, hemodialysis water, water for Injection, pre-conditioning, heat sanitization

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Authors: Thilina Ranaweera, Enes Makalic, John L. Hopper, Adrian Bickerstaffe

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Data are the primary asset of biomedical researchers, and the engine for both discovery and research translation. As the volume and complexity of research datasets increase, especially with new technologies such as large single nucleotide polymorphism (SNP) chips, so too does the requirement for software to manage, process and analyze the data. Researchers often need to execute complicated queries and conduct complex analyzes of large-scale datasets. Existing tools to analyze such data, and other types of high-dimensional data, unfortunately suffer from one or more major problems. They typically require a high level of computing expertise, are too simplistic (i.e., do not fit realistic models that allow for complex interactions), are limited by computing power, do not exploit the computing power of large-scale parallel architectures (e.g. supercomputers, GPU clusters etc.), or are limited in the types of analysis available, compounded by the fact that integrating new analysis methods is not straightforward. Solutions to these problems, such as those developed and implemented on parallel architectures, are currently available to only a relatively small portion of medical researchers with access and know-how. The past decade has seen a rapid expansion of data management systems for the medical domain. Much attention has been given to systems that manage phenotype datasets generated by medical studies. The introduction of heterogeneous genomic data for research subjects that reside in these systems has highlighted the need for substantial improvements in software architecture. To address this problem, we have developed SPARK, an enabling and translational system for medical research, leveraging existing high performance computing resources, and analysis techniques currently available or being developed. It builds these into The Ark, an open-source web-based system designed to manage medical data. SPARK provides a next-generation biomedical data management solution that is based upon a novel Micro-Service architecture and Big Data technologies. The system serves to demonstrate the applicability of Micro-Service architectures for the development of high performance computing applications. When applied to high-dimensional medical datasets such as genomic data, relational data management approaches with normalized data structures suffer from unfeasibly high execution times for basic operations such as insert (i.e. importing a GWAS dataset) and the queries that are typical of the genomics research domain. SPARK resolves these problems by incorporating non-relational NoSQL databases that have been driven by the emergence of Big Data. SPARK provides researchers across the world with user-friendly access to state-of-the-art data management and analysis tools while eliminating the need for high-level informatics and programming skills. The system will benefit health and medical research by eliminating the burden of large-scale data management, querying, cleaning, and analysis. SPARK represents a major advancement in genome research technologies, vastly reducing the burden of working with genomic datasets, and enabling cutting edge analysis approaches that have previously been out of reach for many medical researchers.

Keywords: biomedical research, genomics, information systems, software

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Authors: Naomi Grigoryan, Alexandros Loutsioli Daskalakis, Anna Elisse Uy, Yihe Huang, Aude Laurent (Webanck)

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In response to the building and construction sectors accounting for a third of all energy demand and emissions, the European Union has placed new laws and regulations in the construction sector that emphasize material circularity, energy efficiency, biodiversity, and social impact. Existing design tools assess sustainability in early-stage design for products or buildings; however, there is no standardized methodology for measuring the circularity performance of building components. Existing assessment methods for building components focus primarily on carbon footprint but lack the comprehensive analysis required to design for circularity. The research conducted in this paper covers the parameters needed to assess sustainability in the design process of architectural products such as doors, windows, and facades. It maps a framework for a tool that assists designers with real-time sustainability metrics. Considering the life cycle of building components such as façades, windows, and doors involves the life cycle stages applied to product design and many of the methods used in the life cycle analysis of buildings. The current industry standards of sustainability assessment for metal building components follow cradle-to-grave life cycle assessment (LCA), track Global Warming Potential (GWP), and document the parameters used for an Environmental Product Declaration (EPD). Developed by the Ellen Macarthur Foundation, the Material Circularity Indicator (MCI) is a methodology utilizing the data from LCA and EPDs to rate circularity, with a "value between 0 and 1 where higher values indicate a higher circularity+". Expanding on the MCI with additional indicators such as the Water Circularity Index (WCI), the Energy Circularity Index (ECI), the Social Circularity Index (SCI), Life Cycle Economic Value (EV), and calculating biodiversity risk and uncertainty, the assessment methodology of an architectural product's impact can be targeted more specifically based on product requirements, performance, and lifespan. Broadening the scope of LCA calculation for products to incorporate aspects of building design allows product designers to account for the disassembly of architectural components. For example, the Material Circularity Indicator for architectural products such as windows and facades is typically low due to the impact of glass, as 70% of glass ends up in landfills due to damage in the disassembly process. The low MCI can be combatted by expanding beyond cradle-to-grave assessment and focusing the design process on disassembly, recycling, and repurposing with the help of real-time assessment tools. Design for Disassembly and Urban Mining has been integrated within the construction field on small scales as project-based exercises, not addressing the entire supply chain of architectural products. By adopting more comprehensive sustainability metrics and incorporating uncertainty calculations, the sustainability assessment of building components can be more accurately assessed with decarbonization and disassembly in mind, addressing the large-scale commercial markets within construction, some of the most significant contributors to climate change.

Keywords: architectural products, early-stage design, life cycle assessment, material circularity indicator

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Authors: Paola Clerici Maestosi

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Positive Energy District (PED) is a rather recent concept whose aim is to contribute to the main objectives of the Energy Union strategy. It is based on an integrated multi-sectoral approach in response to Europe's most complex challenges. PED integrates energy efficiency, renewable energy production, and energy flexibility in an integrated, multi-sectoral approach at the city level. The core idea behind Positive Energy Districts (PEDs) is to establish an urban area that can generate more energy than it consumes. Additionally, it should be flexible enough to adapt to changes in the energy market. This is crucial because a PED's goal is not just to achieve an annual surplus of net energy but also to help reduce the impact on the interconnected centralized energy networks. It achieves this by providing options to increase on-site load matching and self-consumption, employing technologies for short- and long-term energy storage, and offering energy flexibility through smart control. Thus, it seems that PEDs can encompass all types of buildings in the city environment. Given this which is the added value of having green buildings being constitutive part of PEDS? The paper will present a systematic literature review identifying the role of green building in Positive Energy District to provide answer to following questions: (RQ1) the state of the art of PEDs implementation; (RQ2) penetration of green building in Positive Energy District selected case studies. Methodological approach is based on a broad holistic study of bibliographic sources according to Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) further data will be analysed, mapped and text mining through VOSviewer. Main contribution of research is a cognitive framework on Positive Energy District in Europe and a selection of case studies where green building supported the transition to PED. The inclusion of green buildings within Positive Energy Districts (PEDs) adds significant value for several reasons. Firstly, green buildings are designed and constructed with a focus on environmental sustainability, incorporating energy-efficient technologies, materials, and design principles. As integral components of PEDs, these structures contribute directly to the district's overall ability to generate more energy than it consumes. Secondly, green buildings typically incorporate renewable energy sources, such as solar panels or wind turbines, further boosting the district's capacity for energy generation. This aligns with the PED objective of achieving a surplus of net energy. Moreover, green buildings often feature advanced systems for on-site energy management, load-matching, and self-consumption. This enhances the PED's capability to respond to variations in the energy market, making the district more agile and flexible in optimizing energy use. Additionally, the environmental considerations embedded in green buildings align with the broader sustainability goals of PEDs. By reducing the ecological footprint of individual structures, PEDs with green buildings contribute to minimizing the overall impact on centralized energy networks and promote a more sustainable urban environment. In summary, the incorporation of green buildings within PEDs not only aligns with the district's energy objectives but also enhances environmental sustainability, energy efficiency, and the overall resilience of the urban environment.

Keywords: positive energy district, renewables energy production, energy flexibility, energy efficiency

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Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

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Authors: Anzal Abbas Jaffari, Wajiha Javed, Naseem Salahuddin

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Rationale: Rabies, a vaccine preventable disease, continues to be a critical public health issue as it kills around 2000-5000 people annually in Pakistan. Along with the disease spread among animals, the dog population remains a victim of brutal culling practices by the local authorities, which adversely affects ecosystem (sinking of poison in the soil – affecting vegetation & contaminating water) and the disease spread. The dog population has been exponentially rising primarily because a lack of a consolidated nationwide Animal Birth Control program and awareness among the local communities in general and children in particular. This is reflected in Pakistan’s low SARE score - 1.5, which makes the country trails behind other developing countries like Bangladesh (2.5) and Philippines (3.5).According to an estimate, the province of Sindh alone is home to almost 2.5 million dogs. The clustering of dogs in Peri-Urban areas and inner cities localities leads to an increase of reported dog bite cases in these areas specifically. Objective: Rabies Free Pakistan (RFP), which is a joint venture of Getz Pharma Private Limited and Indus Hospital & Health Network (IHHN); it was established in 2018 to eliminate Rabies from Pakistan by 2030 using the One Health Approach. Methodology: The RFP team is actively working on advocacy and policy front with both the Federal & Provincial government to ensure that all stakeholders currently involved in dog culling in Pakistan have a paradigm shift towards humane methods of vaccination and ABC. Along with the federal government, RFP aims to declare Rabies as a notifiable disease. Whereas RFP closely works with the provincial government of Sindh to initiate a province wide Rabies Control Program.RFP program follows international standards and WHO approved protocols for this program in Pakistan.RFP team has achieved various milestones in the fight against Rabies after successfully scaling up project operations and has vaccinated more than 30,000 dogs and neutered around 7,000 dogs since 2018. Recommendations: Effective implementation of Rabies program (MDV and ABC) requires a concentrated effort to address a variety of structural and policy challenges. This essentially demands a massive shift in the attitude of individuals towards rabies. The two most significant challenges in implementing a standard policy at the structural level are lack of institutional capacity, shortage of vaccine, and absence of inter-departmental coordination among major stakeholders: federal government, provincial ministry of health, livestock, and local bodies (including local councils). The lack of capacity in health care workers to treat dog bite cases emerges as a critical challenge at the clinical level. Conclusion: Pakistan can learn from the successful international models of Sri Lanka and Mexico as they adopted the One Health Approach to eliminate rabies like RFP. The WHO advised One Health approach provides the policymakers with an interactive and cross-sectoral guide, which involves all the essential elements of the eco system (including animals, humans, and other components).

Keywords: animal birth control, dog population, mass dog vaccination, one health, rabies elimination

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Authors: Leonie Bradfield, Stephen Fityus, John Simmons

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The shearing behavior of current and planned coal mine spoil dumps up to 400m in height is studied using large-sample-high-stress direct shear tests performed on a range of spoils common to the coalfields of Eastern Australia. The motivation for the study is to address industry concerns that some constructed spoil dump heights ( > 350m) are exceeding the scale ( ≤ 120m) for which reliable design information exists, and because modern geotechnical laboratories are not equipped to test representative spoil specimens at field-scale stresses. For more than two decades, shear strength estimation for spoil dumps has been based on either infrequent, very small-scale tests where oversize particles are scalped to comply with device specimen size capacity such that the influence of prototype-sized particles on shear strength is not captured; or on published guidelines that provide linear shear strength envelopes derived from small-scale test data and verified in practice by slope performance of dumps up to 120m in height. To date, these published guidelines appear to have been reliable. However, in the field of rockfill dam design there is a broad acceptance of a curvilinear shear strength envelope, and if this is applicable to coal mine spoils, then these industry-accepted guidelines may overestimate the strength and stability of dumps at higher stress levels. The pressing need to rationally define the shearing behavior of more representative spoil specimens at field-scale stresses led to the successful design, construction and operation of a large direct shear machine (LDSM) and its subsequent application to provide reliable design information for current and planned very-high dumps. The LDSM can test at a much larger scale, in terms of combined specimen size (720mm x 720mm x 600mm) and stress (σn up to 4.6MPa), than has ever previously been achieved using a direct shear machine for geotechnical testing of rockfill. The results of an extensive LDSM testing program on a wide range of coal-mine spoils are compared to a published framework that widely accepted by the Australian coal mining industry as the standard for shear strength characterization of mine spoil. A critical outcome is that the LDSM data highlights several non-compliant spoils, and stress-dependent shearing behavior, for which the correct application of the published framework will not provide reliable shear strength parameters for design. Shear strength envelopes developed from the LDSM data are also compared with dam engineering knowledge, where failure envelopes of rockfills are curved in a concave-down manner. The LDSM data indicates that shear strength envelopes for coal-mine spoils abundant with rock fragments are not in fact curved and that the shape of the failure envelope is ultimately determined by the strength of rock fragments. Curvilinear failure envelopes were found to be appropriate for soil-like spoils containing minor or no rock fragments, or hard-soil aggregates.

Keywords: coal mine, direct shear test, high dump, large scale, mine spoil, shear strength, spoil dump

Procedia PDF Downloads 142

Authors: S. S. Kharintsev, E. A. Chernykh, S. K. Saikin, A. I. Fishman, S. G. Kazarian

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Recent advances in improving information storage performance are inseparably linked with circumvention of fundamental constraints such as the supermagnetic limit in heat assisted magnetic recording, charge loss tolerance in solid-state memory and the Abbe’s diffraction limit in optical storage. A substantial breakthrough in the development of nonvolatile storage devices with dimensional scaling has been achieved due to phase-change chalcogenide memory, which nowadays, meets the market needs to the greatest advantage. A further progress is aimed at the development of versatile nonvolatile high-speed memory combining potentials of random access memory and archive storage. The well-established properties of light at the nanoscale empower us to use them for recording optical information with ultrahigh density scaled down to a single molecule, which is the size of a pit. Indeed, diffraction-limited optics is able to record as much information as ~1 Gb/in2. Nonlinear optical effects, for example, two-photon fluorescence recording, allows one to decrease the extent of the pit even more, which results in the recording density up to ~100 Gb/in2. Going beyond the diffraction limit, due to the sub-wavelength confinement of light, pushes the pit size down to a single chromophore, which is, on average, of ~1 nm in length. Thus, the memory capacity can be increased up to the theoretical limit of 1 Pb/in2. Moreover, the field confinement provides faster recording and readout operations due to the enhanced light-matter interaction. This, in turn, leads to the miniaturization of optical devices and the decrease of energy supply down to ~1 μW/cm². Intrinsic features of light such as multimode, mixed polarization and angular momentum in addition to the underlying optical and holographic tools for writing/reading, enriches the storage and encryption of optical information. In particular, the finite extent of the near-field penetration, falling into a range of 50-100 nm, gives the possibility to perform 3D volume (layer-to-layer) recording/readout of optical information. In this study, we demonstrate a comprehensive evidence of isotropic-to-homeotropic phase transition of the azobenzene-functionalized polymer thin film exposed to light and dc electric field using near-field optical microscopy and scanning capacitance microscopy. We unravel a near-field Raman dichroism of a sub-10 nm thick epoxy-based side-chain azo-polymer films with polarization-controlled tip-enhanced Raman scattering. In our study, orientation of azo-chromophores is controlled with a bias voltage gold tip rather than light polarization. Isotropic in-plane and homeotropic out-of-plane arrangement of azo-chromophores in glassy environment can be distinguished with transverse and longitudinal optical near-fields. We demonstrate that both phases are unambiguously visualized by 2D mapping their local dielectric properties with scanning capacity microscopy. The stability of the polar homeotropic phase is strongly sensitive to the thickness of the thin film. We make an analysis of α-transition of the azo-polymer by detecting a temperature-dependent phase jump of an AFM cantilever when passing through the glass temperature. Overall, we anticipate further improvements in optical storage performance, which approaches to a single molecule level.

Keywords: optical memory, azo-dye, near-field, tip-enhanced Raman scattering

Procedia PDF Downloads 158

Authors: B. Philip, J. Littlewood, R. Radford, N. Evans, T. Whyman, D. P. Jones

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UK buildings and energy infrastructures are heavily dependent on natural gas, a large proportion of which is used for domestic space heating. However, approximately half of the gas consumed in the UK is imported. Improving energy security and reducing carbon emissions are major government drivers for reducing gas dependency. In order to do so there needs to be a wholesale shift in the energy provision to householders without impacting on thermal comfort levels, convenience or cost of supply to the end user. Heat pumps are seen as a potential alternative in modern well insulated homes, however, can the same be said of older homes? A large proportion of housing stock in Britain was built prior to 1919. The age of the buildings bears testimony to the quality of construction; however, their thermal performance falls far below the minimum currently set by UK building standards. In recent years significant sums of money have been invested to improve energy efficiency and combat fuel poverty in some of the most deprived areas of Wales. Increasing energy efficiency of older properties remains a significant challenge, which cannot be achieved through insulation and air-tightness interventions alone, particularly when alterations to historically important architectural features of the building are not permitted. This paper investigates the energy demand of pre-1919 dwellings in a former Welsh mining village, the feasibility of meeting that demand using water from the disused mine workings to supply a district heat network and potential barriers to success of the scheme. The use of renewable solar energy generation and storage technologies, both thermal and electrical, to reduce the load and offset increased electricity demand, are considered. A wholistic surveying approach to provide a more accurate assessment of total household heat demand is proposed. Several surveying techniques, including condition surveys, air permeability, heat loss calculations, and thermography were employed to provide a clear picture of energy demand. Additional insulation can bring unforeseen consequences which are detrimental to the fabric of the building, potentially leading to accelerated dilapidation of the asset being ‘protected’. Increasing ventilation should be considered in parallel, to compensate for the associated reduction in uncontrolled infiltration. The effectiveness of thermal performance improvements are demonstrated and the detrimental effects of incorrect material choice and poor installation are highlighted. The findings show estimated heat demand to be in close correlation to household energy bills. Major areas of heat loss were identified such that improvements to building thermal performance could be targeted. The findings demonstrate that the use of heat pumps in older buildings is viable, provided sufficient improvement to thermal performance is possible. Addition of passive solar thermal and photovoltaic generation can help reduce the load and running cost for the householder. The results were used to predict future heat demand following energy efficiency improvements, thereby informing the size of heat pumps required.

Keywords: heat demand, heat pump, renewable energy, retrofit

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Authors: Diego Giuseppe Romano, Gianvito Apuleo, Jiri Duda

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Mobility is one of the most important societal needs for amusement, business activities and health. Thus, transport needs are continuously increasing, with the consequent traffic congestion and pollution increase. Aeronautic effort aims at smarter infrastructures use and in introducing greener concepts. A possible solution to address the abovementioned topics is the development of Small Air Transport (SAT) system, able to guarantee operability from today underused airfields in an affordable and green way, helping meanwhile travel time reduction, too. In the framework of Horizon2020, EU (European Union) has funded the Clean Sky 2 SAT TA (Transverse Activity) initiative to address market innovations able to reduce SAT operational cost and environmental impact, ensuring good levels of operational safety. Nowadays, most of the key technologies to improve passenger comfort and to reduce community noise, DOC (Direct Operating Costs) and pilot workload for SAT have reached an intermediate level of maturity TRL (Technology Readiness Level) 3/4. Thus, the key technologies must be developed, validated and integrated on dedicated ground and flying aircraft demonstrators to reach higher TRL levels (5/6). Particularly, SAT TA focuses on the integration at aircraft level of the following technologies [1]: 1)    Low-cost composite wing box and engine nacelle using OoA (Out of Autoclave) technology, LRI (Liquid Resin Infusion) and advance automation process. 2) Innovative high lift devices, allowing aircraft operations from short airfields (< 800 m). 3) Affordable small aircraft manufacturing of metallic fuselage using FSW (Friction Stir Welding) and LMD (Laser Metal Deposition). 4)       Affordable fly-by-wire architecture for small aircraft (CS23 certification rules). 5) More electric systems replacing pneumatic and hydraulic systems (high voltage EPGDS -Electrical Power Generation and Distribution System-, hybrid de-ice system, landing gear and brakes). 6) Advanced avionics for small aircraft, reducing pilot workload. 7) Advanced cabin comfort with new interiors materials and more comfortable seats. 8) New generation of turboprop engine with reduced fuel consumption, emissions, noise and maintenance costs for 19 seats aircraft. (9) Alternative diesel engine for 9 seats commuter aircraft. To address abovementioned market innovations, two different platforms have been designed: Reference and Green aircraft. Reference aircraft is a virtual aircraft designed considering 2014 technologies with an existing engine assuring requested take-off power; Green aircraft is designed integrating the technologies addressed in Clean Sky 2. Preliminary integration of the proposed technologies shows an encouraging reduction of emissions and operational costs of small: about 20% CO₂ reduction, about 24% NO_x reduction, about 10 db (A) noise reduction at measurement point and about 25% DOC reduction. Detailed description of the performed studies, analyses and validations for each technology as well as the expected benefit at aircraft level are reported in the present paper.

Keywords: affordable, European, green, mobility, technologies development, travel time reduction

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Sunil Arora, Anitya Kumar Jena, S. A. Ravi

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India is at the cusp of major reforms in the hydrocarbon sector. Oil and gas sector is highly liberalised to attract private investment and to increase domestic production. Major hydrocarbon Exploration & Production (E&P) activity here have been undertaken by Government owned companies but with easing up and reworking of hydro carbon exploration licensing policies private players have also joined the fray towards achieving energy security for India. Government of India has come up with policy and administrative reforms including Hydrocarbon Exploration and Licensing Policy (HELP), Sagarmala (port-led development with coastal connectivity), and Development of Small Discovered Fields, etc. with the intention to make industry friendly conditions for investment, ease of doing business and reduce gestation period. To harness the potential resources of Deep water and Ultra deep water, High Pressure – High Temperature (HP-HT) regions, Coal Bed Methane (CBM), Shale Hydrocarbons besides Gas Hydrates, participation shall be required from both domestic and international players. Companies engaged in E&P activities in India have traditionally been managing through their captive supply base, but with crude prices under hammer, the need is being felt to outsource non-core activities. This necessitates establishment of a robust support services to cater to E&P Industry, which is currently non-existent to meet the bourgeon challenges. This paper outlines an agenda for creating an Integrated Services Hub (ISH) under Special Economic Zone (SEZ) to facilitate complete gamut of non-core support activities of E&P industry. This responsive and proficient multi-usage facility becomes viable with better resource utilization, economies of scale to offer cost effective services. The concept envisages companies to bring-in their core technical expertise leaving complete hardware peripherals outsourced to this ISH. The Integrated Services Hub, complying with the best in class global standards, shall typically provide following Services under Single Window Solution, but not limited to: a) Logistics including supply base operations, transport of manpower and material, helicopters, offshore supply vessels, warehousing, inventory management, sourcing and procurement activities, international freight forwarding, domestic trucking, customs clearance service etc. b) Trained/Experienced pool of competent Manpower (Technical, Security etc.) will be available for engagement by companies on either short or long term basis depending upon the requirements with provisions of meeting any training requirements. c) Specialized Services through tie-up with global best companies for Crisis Management, Mud/Cement, Fishing, Floating Dry-dock besides provision of Workshop, Repair and Testing facilities, etc. d) Tools and Tackles including drill strings, etc. A pre-established Integrated Services Hub shall facilitate an early start-up of activities with substantial savings in time lines. This model can be replicated at other parts of the world to expedite E&P activities.

Keywords: integrated service hub, India, oil gas, offshore supply base

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

Procedia PDF Downloads 47

Authors: Andrew D. Henshaw

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The research examines the influence of familial and kinship based leadership on the resilience of politically violent organizations. Organizations of this type frequently fight in the same conflicts though are called 'terrorist' or 'insurgent' depending on political foci of the time, and thus different approaches are used to combat them. The research considers them correlated phenomena with significant overlap and identifies strengths and vulnerabilities in resilience processes. The research employs paired case studies to examine resilience in organizations under significant external pressure, and achieves this by measuring three variables. 1: Organizational robustness in terms of leadership and governance. 2. Bounce-back response efficiency to external pressures and adaptation to endogenous and exogenous shock. 3. Perpetuity of operational and attack capability, and political legitimacy. The research makes three hypotheses. First, familial/kinship leadership groups have a significant effect on organizational resilience in terms of informal operations. Second, non-familial/kinship organizations suffer in terms of heightened security transaction costs and social economics surrounding recruitment, retention, and replacement. Third, resilience in non-familial organizations likely stems from critical external supports like state sponsorship or powerful patrons, rather than organic resilience dynamics. The case studies pair familial organizations with non-familial organizations. Set 1: The Haqqani Network (HQN) - Pair: Lashkar-e-Toiba (LeT). Set 2: Jemaah Islamiyah (JI) - Pair: The Abu Sayyaf Group (ASG). Case studies were selected based on three requirements, being: contrasting governance types, exposure to significant external pressures and, geographical similarity. The case study sets were examined over 24 months following periods of significantly heightened operational activities. This enabled empirical measurement of the variables as substantial external pressures came into force. The rationale for the research is obvious. Nearly all organizations have some nexus of familial interconnectedness. Examining familial leadership networks does not provide further understanding of how terrorism and insurgency originate, however, the central focus of the research does address how they persist. The sparse attention to this in existing literature presents an unexplored yet important area of security studies. Furthermore, social capital in familial systems is largely automatic and organic, given at birth or through kinship. It reduces security vetting cost for recruits, fighters and supporters which lowers liabilities and entry costs, while raising organizational efficiency and exit costs. Better understanding of these process is needed to exploit strengths into weaknesses. Outcomes and implications of the research have critical relevance to future operational policy development. Increased clarity of internal trust dynamics, social capital and power flows are essential to fracturing and manipulating kinship nexus. This is highly valuable to external pressure mechanisms such as counter-terrorism, counterinsurgency, and strategic intelligence methods to penetrate, manipulate, degrade or destroy the resilience of politically violent organizations.

Keywords: Counterinsurgency (COIN), counter-terrorism, familial influence, insurgency, intelligence, kinship, resilience, terrorism

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Authors: Alison C. Essary, Victor Trastek

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Introduction: The current state of the health care system in the U.S. is characterized by an unprecedented number of people living with multiple chronic conditions, unsustainable rise in health care costs, inadequate access to care, and wide variation in health outcomes throughout the country. An estimated two-thirds of Americans are living with two or more chronic conditions, contributing to 75% of all health care spending. In 2013, the School for the Science of Health Care Delivery (SHCD) was charged with redesigning the health care system through education and research. Faculty in business, law, and public policy, and thought leaders in health care delivery, administration, public health and health IT created undergraduate, graduate, and executive academic programs to address this pressing need. Faculty and students work across disciplines, and with community partners and employers to improve care delivery and increase value for patients. Methods: Curricula apply content in health care administration and operations within the clinical context. Graduate modules are team-taught by faculty across academic units to model team-based practice. Seminars, team-based assignments, faculty mentoring, and applied projects are integral to student success. Cohort-driven models enhance networking and collaboration. This observational study evaluated two years of admissions data, and one year of graduate data to assess program outcomes and inform the current graduate-level curricula. Descriptive statistics includes means, percentages. Results: Fall 2013, the program received 51 applications. The mean GPA of the entering class of 37 students was 3.38. Ninety-seven percent of the fall 2013 cohort successfully completed the program (n=35). Sixty-six percent are currently employed in the health care industry (n=23). Of the remaining 12 graduates, two successfully matriculated to medical school; one works in the original field of study; four await results on the MCAT or DAT, and five were lost to follow up. Attrition of one student was attributed to non-academic reasons. Fall 2014, the program expanded to include both on-ground and online cohorts. Applications were evenly distributed between on-ground (n=70) and online (n=68). Thirty-eight students enrolled in the on-ground program. The mean GPA was 3.95. Ninety-five percent of students successfully completed the program (n=36). Thirty-six students enrolled in the online program. The mean GPA was 3.85. Graduate outcomes are pending. Discussion: Challenges include demographic variability between online and on-ground students; yet, both profiles are similar in that students intend to become change agents in the health care system. In the past two years, on-ground applications increased by 31%, persistence to graduation is > 95%, mean GPA is 3.67, graduates report admission to six U.S. medical schools, the Mayo Medical School integrates SHCD content within their curricula, and there is national interest in collaborating on industry and academic partnerships. This places SHCD at the forefront of developing innovative curricula in order to improve high-value, patient-centered care.

Keywords: delivery science, education, health care delivery, high-value care, innovation in education, patient-centered

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Authors: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

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Authors: Rouzbeh Jafari, Joe Nava

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This study includes learnings from an engineering practice normally performed on large scale biohydrogen processes. If properly scale-up is done, biohydrogen can be a reliable pathway for biowaste valorization. Most of the studies on biohydrogen process development have used model feedstock to investigate process key performance indicators (KPIs). This study does not intend to compare different technologies with model feedstock. However, it reports economic drivers and technical challenges which help in developing a road map for expanding biohydrogen economy deployment in Canada. BBA is a consulting firm responsible for the design of hydrogen production projects. Through executing these projects, activity has been performed to identify, register and mitigate technical drawbacks of large-scale hydrogen production. Those learnings, in this study, have been applied to the biohydrogen process. Through data collected by a comprehensive literature review, a base case has been considered as a reference, and several case studies have been performed. Critical parameters of the process were identified and through common engineering practice (process design, simulation, cost estimate, and life cycle assessment) impact of these parameters on the commercialization risk matrix and class 5 cost estimations were reported. The process considered in this study is food waste and woody biomass dark fermentation. To propose a reliable road map to develop a sustainable biohydrogen production process impact of critical parameters was studied on the end-to-end process. These parameters were 1) feedstock composition, 2) feedstock pre-treatment, 3) unit operation selection, and 4) multi-product concept. A couple of emerging technologies also were assessed such as photo-fermentation, integrated dark fermentation, and using ultrasound and microwave to break-down feedstock`s complex matrix and increase overall hydrogen yield. To properly report the impact of each parameter KPIs were identified as 1) Hydrogen yield, 2) energy consumption, 3) secondary waste generated, 4) CO2 footprint, 5) Product profile, 6) $/kg-H2 and 5) environmental impact. The feedstock is the main parameter defining the economic viability of biohydrogen production. Through parametric studies, it was found that biohydrogen production favors feedstock with higher carbohydrates. The feedstock composition was varied, by increasing one critical element (such as carbohydrate) and monitoring KPIs evolution. Different cases were studied with diverse feedstock, such as energy crops, wastewater slug, and lignocellulosic waste. The base case process was applied to have reference KPIs values and modifications such as pretreatment and feedstock mix-and-match were implemented to investigate KPIs changes. The complexity of the feedstock is the main bottleneck in the successful commercial deployment of the biohydrogen process as a reliable pathway for waste valorization. Hydrogen yield, reaction kinetics, and performance of key unit operations highly impacted as feedstock composition fluctuates during the lifetime of the process or from one case to another. In this case, concept of multi-product becomes more reliable. In this concept, the process is not designed to produce only one target product such as biohydrogen but will have two or multiple products (biohydrogen and biomethane or biochemicals). This new approach is being investigated by the BBA team and the results will be shared in another scientific contribution.

Keywords: biohydrogen, process scale-up, economic evaluation, commercialization uncertainties, hydrogen economy

Procedia PDF Downloads 72

Authors: John Hardy

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Over the last decade, the increasing utility of extremist narratives to the operational effectiveness of terrorist organizations has been evidenced by the proliferation of inspired or affiliated attacks across the world. Famous examples such as regional al-Qaeda affiliates and the self-styled “Islamic State” demonstrate the effectiveness of leveraging communication technologies to disseminate propaganda, recruit members, and orchestrate attacks. Terrorist organizations with the capacity to harness the communicative power offered by digital communication technologies and effective political narratives have held an advantage over their targets in recent years. Terrorists have leveraged the perceived legitimacy of grass-roots actors to appeal to a global audience of potential supporters and enemies alike, and have wielded a proficiency in profile-raising which remains unmatched by counter terrorism narratives around the world. In contrast, many attempts at propagating official counter-narratives have been received by target audiences as illegitimate, top-down and impersonally bureaucratic. However, the benefits provided by widespread communication and extremist narratives have come at an operational cost. Terrorist organizations now face a significant challenge in protecting their access to communications technologies and authority over the content they create and endorse. The dissemination of effective narratives has emerged as a core function of terrorist organizations with international reach via inspired or affiliated attacks. As such, it has become a critical function which can be targeted by intelligence and security forces. This study applies network targeting principles which have been used by coalition forces against a range of non-state actors in the Middle East and South Asia to the communicative function of terrorist organizations. This illustrates both a conceptual link between functional targeting and operational disruption in the abstract and a tangible impact on the operational effectiveness of terrorists by degrading communicative ability and legitimacy. Two case studies highlight the utility of applying functional targeting against terrorist organizations. The first case is the targeted killing of Anwar al-Awlaki, an al-Qaeda propagandist who crafted a permissive narrative and effective propaganda videos to attract recruits who committed inspired terrorist attacks in the US and overseas. The second is a series of operations against Islamic State propagandists in Syria, including the capture or deaths of a cadre of high profile Islamic State members, including Junaid Hussain, Abu Mohammad al-Adnani, Neil Prakash, and Rachid Kassim. The group of Islamic State propagandists were linked to a significant rise in affiliated and enabled terrorist attacks and were subsequently targeted by law enforcement and military agencies. In both cases, the disruption of communication between the terrorist organization and recruits degraded both communicative and operational functions. Effective functional targeting on member recruitment and operational tempo suggests that narratives are a critical function which can be leveraged against terrorist organizations. Further application of network targeting methods to terrorist narratives may enhance the efficacy of a range of counter terrorism techniques employed by security and intelligence agencies.

Keywords: countering violent extremism, counter terrorism, intelligence, terrorism, violent extremism

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Authors: Indika Fernando, Jiangang Fei, Roger Stanley, Hossein Enshaei

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Delicate produce such as fresh fruits are increasingly susceptible to physiological damage during the essential post-harvest operations such as transport and handling. Vibration and shock during the distribution are identified factors for produce damage within post-harvest supply chains. Mechanical damages caused during transit may significantly diminish the quality of fresh produce which may also result in a substantial wastage. Bananas are one of the staple fruit crops and the most sold supermarket produce in Australia. It is also the largest horticultural industry in the state of Queensland where 95% of the total production of bananas are cultivated. This results in significantly lengthy interstate supply chains where fruits are exposed to prolonged vibration and shocks. This paper is focused on determining the shock and vibration levels experienced by packaged bananas during transit from the farm gate to the retail market. Tri-axis acceleration data were captured by custom made accelerometer based data loggers which were set to a predetermined sampling rate of 400 Hz. The devices recorded data continuously for 96 Hours in the interstate journey of nearly 3000 Km from the growing fields in far north Queensland to the central distribution centre in Melbourne in Victoria. After the bananas were ripened at the ripening facility in Melbourne, the data loggers were used to capture the transport and handling conditions from the central distribution centre to three retail outlets within the outskirts of Melbourne. The quality of bananas were assessed before and after transport at each location along the supply chain. Time series vibration and shock data were used to determine the frequency and the severity of the transient shocks experienced by the packages. Frequency spectrogram was generated to determine the dominant frequencies within each segment of the post-harvest supply chain. Root Mean Square (RMS) acceleration levels were calculated to characterise the vibration intensity during transport. Data were further analysed by Fast Fourier Transform (FFT) and the Power Spectral Density (PSD) profiles were generated to determine the critical frequency ranges. It revealed the frequency range in which the escalated energy levels were transferred to the packages. It was found that the vertical vibration was the highest and the acceleration levels mostly oscillated between ± 1g during transport. Several shock responses were recorded exceeding this range which were mostly attributed to package handling. These detrimental high impact shocks may eventually lead to mechanical damages in bananas such as impact bruising, compression bruising and neck injuries which affect their freshness and visual quality. It was revealed that the frequency range between 0-5 Hz and 15-20 Hz exert an escalated level of vibration energy to the packaged bananas which may result in abrasion damages such as scuffing, fruit rub and blackened rub. Further research is indicated specially in the identified critical frequency ranges to minimise exposure of fruits to the harmful effects of vibration. Improving the handling conditions and also further study on package failure mechanisms when exposed to transient shock excitation will be crucial to improve the visual quality of bananas within the post-harvest supply chain in Australia.

Keywords: bananas, handling, post-harvest, supply chain, shocks, transport, vibration

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Authors: Despoina Chochtoula, Aristidis Ilias, Yannis Stamatiou

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Modbus is a protocol that enables the communication among devices which are connected to the same network. This protocol is, often, deployed in connecting sensor and monitoring units to central supervisory servers in Supervisory Control and Data Acquisition, or SCADA, systems. These systems monitor critical infrastructures, such as factories, power generation stations, nuclear power reactors etc. in order to detect malfunctions and ignite alerts and corrective actions. However, due to their criticality, SCADA systems are vulnerable to attacks that range from simple eavesdropping on operation parameters, exchanged messages, and valuable infrastructure information to malicious modification of vital infrastructure data towards infliction of damage. Thus, the SCADA research community has been active over strengthening SCADA systems with suitable data protection mechanisms based, to a large extend, on cryptographic methods for data encryption, device authentication, and message integrity protection. However, due to the limited computation power of many SCADA sensor and embedded devices, the usual public key cryptographic methods are not appropriate due to their high computational requirements. As an alternative, Elliptic Curve Cryptography has been proposed, which requires smaller key sizes and, thus, less demanding cryptographic operations. Until now, however, no such implementation has been proposed in the SCADA literature, to the best of our knowledge. In order to fill this gap, our methodology was focused on integrating Modbus, a frequently used SCADA communication protocol, with Elliptic Curve based cryptography and develop a server/client application to demonstrate the proof of concept. For the implementation we deployed two C language libraries, which were suitably modify in order to be successfully integrated: libmodbus (https://github.com/stephane/libmodbus) and ecc-lib https://www.ceid.upatras.gr/webpages/faculty/zaro/software/ecc-lib/). The first library provides a C implementation of the Modbus/TCP protocol while the second one offers the functionality to develop cryptographic protocols based on Elliptic Curve Cryptography. These two libraries were combined, after suitable modifications and enhancements, in order to give a modified version of the Modbus/TCP protocol focusing on the security of the data exchanged among the devices and the supervisory servers. The mechanisms we implemented include key generation, key exchange/sharing, message authentication, data integrity check, and encryption/decryption of data. The key generation and key exchange protocols were implemented with the use of Elliptic Curve Cryptography primitives. The keys established by each device are saved in their local memory and are retained during the whole communication session and are used in encrypting and decrypting exchanged messages as well as certifying entities and the integrity of the messages. Finally, the modified library was compiled for the Android environment in order to run the server application as an Android app. The client program runs on a regular computer. The communication between these two entities is an example of the successful establishment of an Elliptic Curve Cryptography based, secure Modbus wireless communication session between a portable device acting as a supervisor station and a monitoring computer. Our first performance measurements are, also, very promising and demonstrate the feasibility of embedding Elliptic Curve Cryptography into SCADA systems, filling in a gap in the relevant scientific literature.

Keywords: elliptic curve cryptography, ICT security, modbus protocol, SCADA, TCP/IP protocol

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Authors: Jose Neri, Fabrice Canto, Alastair Magnaldo, Laurent Guillerme, Vincent Dugas

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A miniaturized and automated approach for the volumetric titration of free nitric acid in U(VI) solutions is presented. Free acidity measurement refers to the acidity quantification in solutions containing hydrolysable heavy metal ions such as U(VI), U(IV) or Pu(IV) without taking into account the acidity contribution from the hydrolysis of such metal ions. It is, in fact, an operation having an essential role for the control of the nuclear fuel recycling process. The main objective behind the technical optimization of the actual ‘beaker’ method was to reduce the amount of radioactive substance to be handled by the laboratory personnel, to ease the instrumentation adjustability within a glove-box environment and to allow a high-throughput analysis for conducting more cost-effective operations. The measurement technique is based on the concept of the Taylor-Aris dispersion in order to create inside of a 200 μm x 5cm circular cylindrical micro-channel a linear concentration gradient in less than a second. The proposed analytical methodology relies on the actinide complexation using pH 5.6 sodium oxalate solution and subsequent alkalimetric titration of nitric acid with sodium hydroxide. The titration process is followed with a CCD camera for fluorescence detection; the neutralization boundary can be visualized in a detection range of 500nm- 600nm thanks to the addition of a pH sensitive fluorophore. The operating principle of the developed device allows the active generation of linear concentration gradients using a single cylindrical micro channel. This feature simplifies the fabrication and ease of use of the micro device, as it does not need a complex micro channel network or passive mixers to generate the chemical gradient. Moreover, since the linear gradient is determined by the liquid reagents input pressure, its generation can be fully achieved in faster intervals than one second, being a more timely-efficient gradient generation process compared to other source-sink passive diffusion devices. The resulting linear gradient generator device was therefore adapted to perform for the first time, a volumetric titration on a chip where the amount of reagents used is fixed to the total volume of the micro channel, avoiding an important waste generation like in other flow-based titration techniques. The associated analytical method is automated and its linearity has been proven for the free acidity determination of U(VI) samples containing up to 0.5M of actinide ion and nitric acid in a concentration range of 0.5M to 3M. In addition to automation, the developed analytical methodology and technique greatly improves the standard off-line oxalate complexation and alkalimetric titration method by reducing a thousand fold the required sample volume, forty times the nuclear waste per analysis as well as the analysis time by eight-fold. The developed device represents, therefore, a great step towards an easy-to-handle nuclear-related application, which in the short term could be used to improve laboratory safety as much as to reduce the environmental impact of the radioanalytical chain.

Keywords: free acidity, lab-on-a-chip, linear concentration gradient, Taylor-Aris dispersion, volumetric titration

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Authors: Melissa de Zeeuw, Peter Smolianov, Arnold Bohl

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This study was designed to help and improve international performance as well increase swimming participation in the Netherlands. Over 200 sources of literature on sport delivery systems from 28 Australasian, North and South American, Western and Eastern European countries were analyzed to construct a globally applicable model of high performance swimming integrated with mass participation, comprising of the following seven elements and three levels: Micro level (operations, processes, and methodologies for development of individual athletes): 1. Talent search and development, 2. Advanced athlete support. Meso level (infrastructures, personnel, and services enabling sport programs): 3. Training centers, 4. Competition systems, 5. Intellectual services. Macro level (socio-economic, cultural, legislative, and organizational): 6. Partnerships with supporting agencies, 7. Balanced and integrated funding and structures of mass and elite sport. This model emerged from the integration of instruments that have been used to analyse and compare national sport systems. The model has received scholarly validation and showed to be a framework for program analysis that is not culturally bound. It has recently been accepted as a model for further understanding North American sport systems, including (in chronological order of publications) US rugby, tennis, soccer, swimming and volleyball. The above model was used to design a questionnaire of 42 statements reflecting desired practices. The statements were validated by 12 international experts, including executives from sport governing bodies, academics who published on high performance and sport development, and swimming coaches and administrators. In this study both a highly structured and open ended qualitative analysis tools were used. This included a survey of swim coaches where open responses accompanied structured questions. After collection of the surveys, semi-structured discussions with Federation coaches were conducted to add triangulation to the findings. Lastly, a content analysis of Dutch Swimming’s website and organizational documentation was conducted. A representative sample of 1,600 Dutch Swim coaches and administrators was collected via email addresses from Royal Dutch Swimming Federation' database. Fully completed questionnaires were returned by 122 coaches from all key country’s regions for a response rate of 7,63% - higher than the response rate of the previously mentioned US studies which used the same model and method. Results suggest possible enhancements at macro level (e.g., greater public and corporate support to prepare and hire more coaches and to address the lack of facilities, monies and publicity at mass participation level in order to make swimming affordable for all), at meso level (e.g., comprehensive education for all coaches and full spectrum of swimming pools particularly 50 meters long), and at micro level (e.g., better preparation of athletes for a future outside swimming and better use of swimmers to stimulate swimming development). Best Dutch swimming management practices (e.g., comprehensive support to most talented swimmers who win Olympic medals) as well as relevant international practices available for transfer to the Netherlands (e.g., high school competitions) are discussed.

Keywords: sport development, high performance, mass participation, swimming

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Authors: Sabina Auhunas

Abstract:

These days in Ukraine, Open Science dramatically develops for the sake of scientists of all branches, providing an opportunity to take a more close look on the studies by foreign scientists, as well as to deliver their own scientific data to national and international journals. However, when it comes to the generalization of data on science activities by Ukrainian scientists, these data are often integrated into E-systems that operate inconsistent and barely related information sources. In order to resolve these issues, developed countries productively use E-systems, designed to store and manage research data, such as Current Research Information Systems that enable combining uncompiled data obtained from different sources. An algorithm for selecting SARS-CoV-2 research articles was designed, by means of which we collected the set of papers published by Ukrainian scientists and uploaded by August 1, 2020. Resulting metadata (document type, open access status, citation count, h-index, most cited documents, international research funding, author counts, the bibliographic relationship of journals) were taken from Scopus and Web of Science databases. The study also considered the info from COVID-19/SARS-CoV-2-related documents published from December 2019 to September 2020, directly from documents published by authors depending on territorial affiliation to Ukraine. These databases are enabled to get the necessary information for bibliometric analysis and necessary details: copyright, which may not be available in other databases (e.g., Science Direct). Search criteria and results for each online database were considered according to the WHO classification of the virus and the disease caused by this virus and represented (Table 1). First, we identified 89 research papers that provided us with the final data set after consolidation and removing duplication; however, only 56 papers were used for the analysis. The total number of documents by results from the WoS database came out at 21641 documents (48 affiliated to Ukraine among them) in the Scopus database came out at 32478 documents (41 affiliated to Ukraine among them). According to the publication activity of Ukrainian scientists, the following areas prevailed: Education, educational research (9 documents, 20.58%); Social Sciences, interdisciplinary (6 documents, 11.76%) and Economics (4 documents, 8.82%). The highest publication activity by institution types was reported in the Ministry of Education and Science of Ukraine (its percent of published scientific papers equals 36% or 7 documents), Danylo Halytsky Lviv National Medical University goes next (5 documents, 15%) and P. L. Shupyk National Medical Academy of Postgraduate Education (4 documents, 12%). Basically, research activities by Ukrainian scientists were funded by 5 entities: Belgian Development Cooperation, the National Institutes of Health (NIH, U.S.), The United States Department of Health & Human Services, grant from the Whitney and Betty MacMillan Center for International and Area Studies at Yale, a grant from the Yale Women Faculty Forum. Based on the results of the analysis, we obtained a set of published articles and preprints to be assessed on the variety of features in upcoming studies, including citation count, most cited documents, a bibliographic relationship of journals, reference linking. Further research on the development of the national scientific E-database continues using brand new analytical methods.

Keywords: content analysis, COVID-19, scientometrics, text mining

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