Search results for: predictive modelling

Authors: Diogo Prosdocimi, Don Ross, Matthew Townshend

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Road authorities are mandated within limited budgets to both deliver improved access to basic services and facilitate economic growth. This responsibility is further complicated if maintenance backlogs and funding shortfalls exist, as evident in many countries including South Africa. These conditions require authorities to make difficult prioritisation decisions, with the effect that Road Asset Management Systems with a one-dimensional focus on traffic volumes may overlook the maintenance of low-volume roads that provide isolated communities with vital access to basic services. Given these challenges, this paper overlays the full South African road network with geo-referenced information for population, primary and secondary schools, and healthcare facilities to identify the network of connective roads between communities and basic service centres. This connective network is then rationalised according to the Gross Value Added and number of jobs per mesozone, administrative and functional road classifications, speed limit, and road length, location, and name to estimate the Basic Access Road Network. A two-step floating catchment area (2SFCA) method, capturing a weighted assessment of drive-time to service centres and the ratio of people within a catchment area to teachers and healthcare workers, is subsequently applied to generate a Multivariate Road Index. This Index is used to assign higher maintenance priority to roads within the Basic Access Road Network that provide more people with better access to services. The relatively limited incidence of Basic Access Roads indicates that authorities could maintain the entire estimated network without exhausting the available road budget before practical economic considerations get any purchase. Despite this fact, a final case study modelling exercise is performed for the Namakwa District Municipality to demonstrate the extent to which optimal relocation of schools and healthcare facilities could minimise the Basic Access Road Network and thereby release budget for investment in roads that best promote GDP growth.

Keywords: basic access roads, multivariate road index, road prioritisation, two-step floating catchment area method

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Authors: Chow Jeng Hei, Pavel Tkalich, Low Kai Sheng Bryan

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Due to the growing demand for sustainability in the maritime industry, there has been a significant increase in focus on alternative fuels such as biofuels, liquefied natural gas (LNG), hydrogen, methanol and ammonia to reduce the carbon footprint of vessels. Alternative fuels offer efficient transportability and significantly reduce carbon dioxide emissions, a critical factor in combating global warming. In an era where the world is determined to tackle climate change, the utilization of methanol is projected to witness a consistent rise in demand, even during downturns in the oil and gas industry. Since 2022, there has been an increase in methanol loading and discharging operations for industrial use in Singapore. These operations were conducted across various storage tank terminals at Jurong Island of varying capacities, which are also used to store alternative fuels for bunkering requirements. The key objective of this research is to support the green shipping industries in the transformation to new fuels such as methanol and ammonia, especially in evolving the capability to inform risk assessment and management of spills. In the unlikely event of accidental spills, a highly reliable forecasting system must be in place to provide mitigation measures and ahead planning. The outcomes of this research would lead to an enhanced metocean prediction capability and, together with advanced sensing, will continuously build up a robust digital twin of the bunkering operating environment. Outputs from the developments will contribute to management strategies for alternative marine fuel spills, including best practices, safety challenges and crisis management. The outputs can also benefit key port operators and the various bunkering, petrochemicals, shipping, protection and indemnity, and emergency response sectors. The forecasted datasets provide a forecast of the expected atmosphere and hydrodynamic conditions prior to bunkering exercises, enabling a better understanding of the metocean conditions ahead and allowing for more refined spill incident management planning

Keywords: clean fuels, hydrodynamics, coastal engineering, impact assessments

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Authors: F. Elhaouzi, H. Lahlali, M. Zaghrioui, I. El Aboudi A. BelfKira, A. Mdarhri

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The effect of physico chemical properties of solvents on the transport process and mechanical properties in elastomeric nano composite materials is reported. The investigated samples are formed by a semi-crystalline ethylene-co-butyl acrylate polymer filled with hard spherical carbon black (CB) nano particles. The swelling behavior was studied by immersion the dried samples in selected solvents at room temperature during 2 days. For this purpose, two chemical compounds methyl derivatives of aromatic hydrocarbons of benzene, i.e. toluene and xylene, are used to search for the mass and molar volume dependence on the absorption kinetics. Mass gain relative to the mass of dry material at specific times was recorded to probe the absorption kinetics. The transport of solvent molecules in these filled elastomeric composites is following a Fickian diffusion mechanism. Additionally, the swelling ratio and diffusivity coefficient deduced from the Fickian law are found to decrease with the CB concentration. These results indicate that the CB nano particles increase the effective path length for diffusion and consequently limit the absorption of the solvent by occupation free volumes in the material. According to physico chemical properties of the two used solvents, it is found that the diffusion is more important for the toluene molecules solvent due to their low values of the molecular weight and volume molar compared to those for the xylene. Differential Scanning Calorimetry (DSC) and X-ray photo electron (XPS) were also used to probe the eventual change in the chemical composition for the swollen samples. Mechanically speaking, the stress-strain curves of uniaxial tensile tests pre- and post- swelling highlight a remarkably decrease of the strength and elongation at break of the swollen samples. This behavior can be attributed to the decrease of the load transfer density between the matrix and the CB in the presence of the solvent. We believe that the results reported in this experimental investigation can be useful for some demanding applications e.g. tires, sealing rubber.

Keywords: nanocomposite, absorption kinetics, mechanical behavior, diffusion, modelling, XPS, DSC

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Authors: Kylie Mueller, Nijole Bernaitis, Shailendra Anoopkumar-Dukie

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Background: Vitamin K antagonists particularly warfarin is the most frequently used oral medication for deep vein thrombosis (DVT) treatment and prophylaxis. Time in therapeutic range (TITR) of the international normalised ratio (INR) is widely accepted as a measure to assess the quality of warfarin therapy. Multiple factors can affect warfarin control and the subsequent adverse outcomes including thromboembolic and bleeding events. Predictor models have been developed to assess potential contributing factors and measure the individual risk of these adverse events. These predictive models have been validated in atrial fibrillation (AF) patients, however, there is a lack of literature on whether these can be successfully applied to other warfarin users including DVT patients. Therefore, the aim of the study was to assess the ability of these risk models (HAS BLED and CHADS2) to predict haemorrhagic and ischaemic incidences in DVT patients treated with warfarin. Methods: A retrospective analysis of DVT patients receiving warfarin management by a private pathology clinic was conducted. Data was collected from November 2007 to September 2014 and included demographics, medical and drug history, INR targets and test results. Patients receiving continuous warfarin therapy with an INR reference range between 2.0 and 3.0 were included in the study with mean TITR calculated using the Rosendaal method. Bleeding and thromboembolic events were recorded and reported as incidences per patient. The haemorrhagic risk model HAS BLED and ischaemic risk model CHADS2 were applied to the data. Patients were then stratified into either the low, moderate, or high-risk categories. The analysis was conducted to determine if a correlation existed between risk assessment tool and patient outcomes. Data was analysed using GraphPad Instat Version 3 with a p value of <0.05 considered to be statistically significant. Patient characteristics were reported as mean and standard deviation for continuous data and categorical data reported as number and percentage. Results: Of the 533 patients included in the study, there were 268 (50.2%) female and 265 (49.8%) male patients with a mean age of 62.5 years (±16.4). The overall mean TITR was 78.3% (±12.7) with an overall haemorrhagic incidence of 0.41 events per patient. For the HAS BLED model, there was a haemorrhagic incidence of 0.08, 0.53, and 0.54 per patient in the low, moderate and high-risk categories respectively showing a statistically significant increase in incidence with increasing risk category. The CHADS2 model showed an increase in ischaemic events according to risk category with no ischaemic events in the low category, and an ischaemic incidence of 0.03 in the moderate category and 0.47 high-risk categories. Conclusion: An increasing haemorrhagic incidence correlated to an increase in the HAS BLED risk score in DVT patients treated with warfarin. Furthermore, a greater incidence of ischaemic events occurred in patients with an increase in CHADS2 category. In an Australian population of DVT patients, the HAS BLED and CHADS2 accurately predicts incidences of haemorrhage and ischaemic events respectively.

Keywords: anticoagulant agent, deep vein thrombosis, risk assessment, warfarin

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Authors: Elisabeth Maidl

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The interdependence of climate change and natural hazard goes along with large uncertainties regarding future risks. Regional stakeholders, experts in natural hazards management and scientists have specific knowledge, resp. mental models on such risks. This diversity of views makes it difficult to find common and broadly accepted prevention measures. If the specific knowledge of these types of actors is shared in an interactive knowledge production process, this enables a broader and common understanding of complex risks and allows to agree on long-term solution strategies. Previous studies on mental models confirm that actors with specific vulnerabilities perceive different aspects of a topic and accordingly prefer different measures. In bringing these perspectives together, there is the potential to reduce uncertainty and to close blind spots in solution finding. However, studies that examine the mental models of regional actors on future concrete mass movement risks are lacking so far. The project tests and evaluates the feasibility of knowledge co-creation for the anticipatory prevention of climate change-induced mass movement risks in the Alps. As a key element, mental models of the three included groups of actors are compared. Being integrated into the research program Climate Change Impacts on Alpine Mass Movements (CCAMM2), this project is carried out in two Swiss mountain regions. The project is structured in four phases: 1) the preparatory phase, in which the participants are identified, 2) the baseline phase, in which qualitative interviews and a quantitative pre-survey are conducted with actors 3) the knowledge-co-creation phase, in which actors have a moderated exchange meeting, and a participatory modelling workshop on specific risks in the region, and 4) finally a public information event. Results show that participants' mental models are based on the place of origin, profession, believes, values, which results in narratives on climate change and hazard risks. Further, the more intensively participants interact with each other, the more likely is that they change their views. This provides empirical evidence on how changes in opinions and mindsets can be induced and fostered.

Keywords: climate change, knowledge-co-creation, participatory process, natural hazard risks

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: Rafal Bryk, Holger Schmidt, Thomas Mull, Ingo Ganzmann, Oliver Herbst

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Prediction of the two-phase water mixture level during fast depressurization of the Reactor Pressure Vessel (RPV) resulting from an accident scenario is an important issue from the view point of the reactor safety. Since the level swell may influence the behavior of some passive safety systems, it has been recognized that an assumption which at the beginning may be considered as a conservative one, not necessary leads to a conservative result. This paper discusses outcomes obtained during simulations of the water dynamics and heat transfer during sudden depressurization of a vessel filled up to a certain level with liquid water under saturation conditions and with the rest of the vessel occupied by saturated steam. In case of the pressure decrease e.g. due to the main steam line break, the liquid water evaporates abruptly, being a reason thereby, of strong transients in the vessel. These transients and the sudden emergence of void in the region occupied at the beginning by liquid, cause elevation of the two-phase mixture. In this work, several models calculating the water collapse and swell levels are presented and validated against experimental data. Each of the models uses different approach to calculate void fraction. The object-oriented models were developed with the Modelica modelling language and the OpenModelica environment. The models represent the RPV of the Integral Test Facility Karlstein (INKA) – a dedicated test rig for simulation of KERENA – a new Boiling Water Reactor design of Framatome. The models are based on dynamic mass and energy equations. They are divided into several dynamic volumes in each of which, the fluid may be single-phase liquid, steam or a two-phase mixture. The heat transfer between the wall of the vessel and the fluid is taken into account. Additional heat flow rate may be applied to the first volume of the vessel in order to simulate the decay heat of the reactor core in a similar manner as it is simulated at INKA. The comparison of the simulations results against the reference data shows a good agreement.

Keywords: boiling water reactor, level swell, Modelica, RPV depressurization, thermal-hydraulics

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Authors: Bruna P. De Souza, Ricardo C. De Almeida

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In some cities in the State of Parana – Brazil and in other countries atmospheric bromeliads (Tillandsia spp - Bromeliaceae) are considered weeds in trees, electric power lines, satellite dishes and other artificial supports. In this study, a numerical model was developed to simulate the seed dispersal of the Tillandsia recurvata species by wind with the objective of evaluating seeds displacement in the city of Ponta Grossa – PR, Brazil, since it is considered that the region is already infested. The model simulates the dispersal of each individual seed integrating parameters from the atmospheric boundary layer (ABL) and the local wind, simulated by the Weather Research Forecasting (WRF) mesoscale atmospheric model for the 2012 to 2015 period. The dispersal model also incorporates the approximate number of bromeliads and source height data collected from most infested electric power lines. The seeds terminal velocity, which is an important input data but was not available in the literature, was measured by an experiment with fifty-one seeds of Tillandsia recurvata. Wind is the main dispersal agent acting on plumed seeds whereas atmospheric turbulence is a determinant factor to transport the seeds to distances beyond 200 meters as well as to introduce random variability in the seed dispersal process. Such variability was added to the model through the application of an Inverse Fast Fourier Transform to wind velocity components energy spectra based on boundary-layer meteorology theory and estimated from micrometeorological parameters produced by the WRF model. Seasonal and annual wind means were obtained from the surface wind data simulated by WRF for Ponta Grossa. The mean wind direction is assumed to be the most probable direction of bromeliad seed trajectory. Moreover, the atmospheric turbulence effect and dispersal distances were analyzed in order to identify likely regions of infestation around Ponta Grossa urban area. It is important to mention that this model could be applied to any species and local as long as seed’s biological data and meteorological data for the region of interest are available.

Keywords: atmospheric turbulence, bromeliad, numerical model, seed dispersal, terminal velocity, wind

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Authors: Shreya Saxena

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Background: Choledocholithiasis is a common complication of gallstone disease. Risk scoring systems exist to guide the need for further imaging or endoscopy in managing choledocholithiasis. We completed an audit to review the American Society for Gastrointestinal Endoscopy (ASGE) scoring system for prediction and management of choledocholithiasis against the current practice at a tertiary hospital to assess its utility in resource optimisation. We have now conducted a cost focused sub-analysis on patients categorized high-risk for choledocholithiasis according to the guidelines to determine any associated cost benefits. Method: Data collection from our prior audit was used to retrospectively identify thirteen patients considered high-risk for choledocholithiasis. Their ongoing management was mapped against the guidelines. Individual costs for the key investigations were obtained from our hospital financial data. Total cost for the different management pathways identified in clinical practice were calculated and compared against predicted costs associated with recommendations in the guidelines. We excluded the cost of laparoscopic cholecystectomy and considered a set figure for per day hospital admission related expenses. Results: Based on our previous audit data, we identified a77% positive predictive value for the ASGE risk stratification tool to determine patients at high-risk of choledocholithiasis. 47% (6/13) had an magnetic resonance cholangiopancreatography (MRCP) prior to endoscopic retrograde cholangiopancreatography (ERCP), whilst 53% (7/13) went straight for ERCP. The average length of stay in the hospital was 7 days, with an additional day and cost of £328.00 (£117 for ERCP) for patients awaiting an MRCP prior to ERCP. Per day hospital admission was valued at £838.69. When calculating total cost, we assumed all patients had admission bloods and ultrasound done as the gold standard. In doing an MRCP prior to ERCP, there was a 130% increase in cost incurred (£580.04 vs £252.04) per patient. When also considering hospital admission and the average length of stay, it was an additional £1166.69 per patient. We then calculated the exact costs incurred by the department, over a three-month period, for all patients, for key investigations or procedures done in the management of choledocholithiasis. This was compared to an estimate cost derived from the recommended pathways in the ASGE guidelines. Overall, 81% (£2048.45) saving was associated with following the guidelines compared to clinical practice. Conclusion: MRCP is the most expensive test associated with the diagnosis and management of choledocholithiasis. The ASGE guidelines recommend endoscopy without an MRCP in patients stratified as high-risk for choledocholithiasis. Our audit that focused on assessing the utility of the ASGE risk scoring system showed it to be relatively reliable for identifying high-risk patients. Our cost analysis has shown significant cost savings per patient and when considering the average length of stay associated with direct endoscopy rather than an additional MRCP. Part of this is also because of an increased average length of stay associated with waiting for an MRCP. The above data supports the ASGE guidelines for the management of high-risk for choledocholithiasis patients from a cost perspective. The only caveat is our small data set that may impact the validity of our average length of hospital stay figures and hence total cost calculations.

Keywords: cost-analysis, choledocholithiasis, risk stratification tool, general surgery

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Authors: Fikremariam Beyene, Getachew Bekele

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Ethiopia is currently on the move with various projects to raise the amount of power generated in the country. The progress observed in recent years indicates this fact clearly and indisputably. The rural electrification program, the modernization of the power transmission system, the development of wind farm is some of the main accomplishments worth mentioning. As it is well known, currently, wind power is globally embraced as one of the most important sources of energy mainly for its environmentally friendly characteristics, and also that once it is installed, it is a source available free of charge. However, integration of wind power plant with an existing network has many challenges that need to be given serious attention. In Ethiopia, a number of wind farms are either installed or are under construction. A series of wind farm is planned to be installed in the near future. Ashegoda Wind farm (13.2°, 39.6°), which is the subject of this study, is the first large scale wind farm under construction with the capacity of 120 MW. The first phase of 120 MW (30 MW) has been completed and is expected to be connected to the grid soon. This paper is concerned with the investigation of the wind farm interaction with the national grid under transient operating condition. The main concern is the fault ride through (FRT) capability of the system when the grid voltage drops to exceedingly low values because of short circuit fault and also the active and reactive power behavior of wind turbines after the fault is cleared. On the wind turbine side, a detailed dynamic modelling of variable speed wind turbine of a 1 MW capacity running with a squirrel cage induction generator and full-scale power electronics converters is done and analyzed using simulation software DIgSILENT PowerFactory. On the Ethiopian electric power corporation side, after having collected sufficient data for the analysis, the grid network is modeled. In the model, a fault ride-through (FRT) capability of the plant is studied by applying 3-phase short circuit on the grid terminal near the wind farm. The results show that the Ashegoda wind farm can ride from voltage deep within a short time and the active and reactive power performance of the wind farm is also promising.

Keywords: squirrel cage induction generator, active and reactive power, DIgSILENT PowerFactory, fault ride-through capability, 3-phase short circuit

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Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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Authors: Koryukaeva Ksenia, Jinfeng Sun

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Europe has been a traditional importer of Russian natural gas for more than 50 years. In 2021, Russian state-owned company Gazprom supplied about a third of all gas consumed in Europe. The Russia-Europe mutual dependence in terms of natural gas supplies has been causing many concerns about the energy security of the two sides for a long period of time. These days the issue has become more urgent than ever considering recent Russian invasion in Ukraine followed by increased large-scale geopolitical conflicts, making the future of Russian natural gas supplies and global gas markets as well highly uncertain. Hence, the main purpose of this study is to get insight into the possible futures of Russian pipeline natural gas exports by a scenario planning method based on Monte-Carlo simulation within LUSS model framework, and propose Russian pipeline natural gas export strategies based on the obtained scenario planning results. The scenario analysis revealed that recent geopolitical disputes disturbed the traditional, longstanding model of Russian pipeline gas exports, and, as a result, the prospects and the pathways for Russian pipeline gas on the world markets will differ significantly from those before 2022. Specifically, our main findings show, that (i) the events of 2022 generated many uncertainties for the long-term future of Russian pipeline gas export perspectives on both western and eastern supply directions, including geopolitical, regulatory, economic, infrastructure and other uncertainties; (ii) according to scenario modelling results, Russian pipeline exports will face many challenges in the future, both on western and eastern directions. A decrease in pipeline gas exports will inevitably affect country’s natural gas production and significantly reduce fossil fuel export revenues, jeopardizing the energy security of the country; (iii) according to proposed strategies, in order to ensure the long-term stable export supplies in the changing environment, Russia may need to adjust its traditional export strategy by performing export flows and product diversification, entering new markets, adapting its contracting mechanism, increasing competitiveness and gaining a reputation of a reliable gas supplier.

Keywords: Russian natural gas, Pipeline natural gas, Uncertainty, Scenario simulation, Export strategy

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Authors: Aldona Kluczek

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Energy efficient process have become a pressing research field in manufacturing. The arguments for having an effective industrial energy efficiency processes are interacted with factors: economic and environmental impact, and energy security. Improvements in energy efficiency are most often achieved by implementation of more efficient technology or manufacturing process. Current processes of electricity production represents the biggest consumption of energy and the greatest amount of emissions to the environment. The goal of this study is to improve the potential energy-savings and reduce greenhouse emissions related to improvement scenarios for the treatment of hardwood lumber produced by an industrial plant operating in the U.S. through the application of green balancing procedure, in order to find the preferable efficient technology. The green procedure for energy is based on analysis of energy efficiency data. Three alternative scenarios of the cogeneration systems plant (CHP) construction are considered: generation of fresh steam, the purchase of a new boiler with the operating pressure 300 pounds per square inch gauge (PSIG), an installation of a new boiler with a 600 PSIG pressure. In this paper, the application of a bottom-down modelling for energy flow to devise a streamlined Energy and Emission Flow Analyze method for the technology of producing electricity is illustrated. It will identify efficiency or technology of a given process to be reached, through the effective use of energy, or energy management. Results have shown that the third scenario seem to be the efficient alternative scenario considered from the environmental and economic concerns for treating hardwood lumber. The energy conservation evaluation options could save an estimated 6,215.78 MMBtu/yr in each year, which represents 9.5% of the total annual energy usage. The total annual potential cost savings from all recommendations is $143,523/yr, which represents 30.1% of the total annual energy costs. Estimation have presented that energy cost savings are possible up to 43% (US$ 143,337.85), representing 18.6% of the total annual energy costs.

Keywords: alternative scenario improvements, cogeneration system, energy and emission flow analyze, energy balancing, green procedure, hardwood lumber manufacturing process

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Authors: Leo Nnamdi Ozurumba-Dwight

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Single-cell genomic analytical systems have proved to be a platform to isolate bulk cells into selected single cells for genomic, proteomic, and related metabolomic studies. This is enabling systematic investigations of the level of heterogeneity in a diverse and wide pool of cell populations. Single cell technologies, embracing techniques such as high parameter flow cytometry, single-cell sequencing, and high-resolution images are playing vital roles in these investigations on messenger ribonucleic acid (mRNA) molecules and related gene expressions in tracking the nature and course of disease conditions. This entails targeted molecular investigations on unit cells that help us understand cell behavoiur and expressions, which can be examined for their health implications on the health state of patients. One of the vital good sides of single-cell RNA sequencing (scRNA seq) is its probing capacity to detect deranged or abnormal cell populations present within homogenously perceived pooled cells, which would have evaded cursory screening on the pooled cell populations of biological samples obtained as part of diagnostic procedures. Despite conduction of just single-cell transcriptome analysis, scRNAseq now permits comparison of the transcriptome of the individual cells, which can be evaluated for gene expressional patterns that depict areas of heterogeneity with pharmaceutical drug discovery and clinical treatment applications. It is vital to strictly work through the tools of investigations from wet lab to bioinformatics and computational tooled analyses. In the precise steps for scRNAseq, it is critical to do thorough and effective isolation of viable single cells from the tissues of interest using dependable techniques (such as FACS) before proceeding to lysis, as this enhances the appropriate picking of quality mRNA molecules for subsequent sequencing (such as by the use of Polymerase Chain Reaction machine). Interestingly, scRNAseq can be deployed to analyze various types of biological samples such as embryos, nervous systems, tumour cells, stem cells, lymphocytes, and haematopoietic cells. In haematopoietic cells, it can be used to stratify acute myeloid leukemia patterns in patients, sorting them out into cohorts that enable re-modeling of treatment regimens based on stratified presentations. In immunotherapy, it can furnish specialist clinician-immunologist with tools to re-model treatment for each patient, an attribute of precision medicine. Finally, the good predictive attribute of scRNAseq can help reduce the cost of treatment for patients, thus attracting more patients who would have otherwise been discouraged from seeking quality clinical consultation help due to perceived high cost. This is a positive paradigm shift for patients’ attitudes primed towards seeking treatment.

Keywords: immunotherapy, transcriptome, re-modeling, mRNA, scRNA-seq

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Authors: Shashi Sharma, V. K. Katiyar, Uaday Singh

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The ability to manipulate magnetic particles in fluid flows by means of inhomogeneous magnetic fields is used in a wide range of biomedical applications including magnetic drug targeting (MDT). In MDT, magnetic carrier particles bounded with drug molecules are injected into the vascular system up-stream from the malignant tissue and attracted or retained at the specific region in the body with the help of an external magnetic field. Although the concept of MDT has been around for many years, however, wide spread acceptance of the technique is still looming despite the fact that it has shown some promise in both in vivo and clinical studies. This is because traditional MDT has some inherent limitations. Typically, the magnetic force is not very strong and it is also very short ranged. Since the magnetic force must overcome rather large hydrodynamic forces in the body, MDT applications have been limited to sites located close to the surface of the skin. Even in this most favorable situation, studies have shown that it is difficult to collect appreciable amounts of the MDCPs at the target site. To overcome these limitations of the traditional MDT approach, Ritter and co-workers reported the implant assisted magnetic drug targeting (IA-MDT). In IA-MDT, the magnetic implants are placed strategically at the target site to greatly and locally increase the magnetic force on MDCPs and help to attract and retain the MDCPs at the targeted region. In the present work, we develop a mathematical model to study the capturing of magnetic nanoparticles flowing in a fluid in an implant assisted cylindrical channel under the magnetic field. A coil of ferromagnetic SS 430 has been implanted inside the cylindrical channel to enhance the capturing of magnetic nanoparticles under the magnetic field. The dominant magnetic and drag forces, which significantly affect the capturing of nanoparticles, are incorporated in the model. It is observed through model results that capture efficiency increases from 23 to 51 % as we increase the magnetic field from 0.1 to 0.5 T, respectively. The increase in capture efficiency by increase in magnetic field is because as the magnetic field increases, the magnetization force, which is attractive in nature and responsible to attract or capture the magnetic particles, increases and results the capturing of large number of magnetic particles due to high strength of attractive magnetic force.

Keywords: capture efficiency, implant assisted-magnetic drug targeting (IA-MDT), magnetic nanoparticles, modelling

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Authors: Stefan Andersson, Balram Panjwani, Bernd Wittgens, Jan Erik Olsen

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Polycyclic Aromatic hydrocarbons are organic compounds consisting of only hydrogen and carbon aromatic rings. PAH are neutral, non-polar molecules that are produced due to incomplete combustion of organic matter. These compounds are carcinogenic and interact with biological nucleophiles to inhibit the normal metabolic functions of the cells. Norways, the most important sources of PAH pollution is considered to be aluminum plants, the metallurgical industry, offshore oil activity, transport, and wood burning. Stricter governmental regulations regarding emissions to the outer and internal environment combined with increased awareness of the potential health effects have motivated Norwegian metal industries to increase their efforts to reduce emissions considerably. One of the objective of the ongoing industry and Norwegian research council supported "SCORE" project is to reduce potential PAH emissions from an off gas stream of a ferroalloy furnace through controlled combustion. In a dedicated combustion chamber. The sizing and configuration of the combustion chamber depends on the combined properties of the bulk gas stream and the properties of the PAH itself. In order to achieve efficient and complete combustion the residence time and minimum temperature need to be optimized. For this design approach reliable kinetic data of the individual PAH-species and/or groups thereof are necessary. However, kinetic data on the combustion of PAH are difficult to obtain and there is only a limited number of studies. The paper presents an evaluation of the kinetic data for some of the PAH obtained from literature. In the present study, the oxidation is modelled for pure PAH and also for PAH mixed with process gas. Using a perfectly stirred reactor modelling approach the oxidation is modelled including advanced reaction kinetics to study influence of residence time and temperature on the conversion of PAH to CO2 and water. A Chemical Reactor Network (CRN) approach is developed to understand the oxidation of PAH inside the combustion chamber. Chemical reactor network modeling has been found to be a valuable tool in the evaluation of oxidation behavior of PAH under various conditions.

Keywords: PAH, PSR, energy recovery, ferro alloy furnace

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Authors: Gondrexon, Gonon, Mendil-Jakani, Mareau

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Proton Exchange Membrane Fuel Cells (PEMFCs) seems to be a promising device used for converting hydrogen into electricity. PEMFC is made of a Membrane Electrode Assembly (MEA) composed of a Proton Exchange Membrane (PEM) sandwiched by two catalytic layers. Nowadays, specific performances are targeted in order to ensure the long-term expansion of this technology. Current polymers used (perfluorinated as Nafion®) are unsuitable (loss of mechanical properties) for the high-temperature range. To overcome this issue, sulfonated polyaromatic polymers appear to be a good alternative since it has very good thermomechanical properties. However, their proton conductivity and chemical stability (oxidative resistance to H2O2 formed during fuel cell (FC) operating) are very low. In our team, we patented an original concept of hybrid membranes able to fulfill the specific requirements for PEMFC. This idea is based on the improvement of commercialized polymer membrane via an easy and processable stabilization thanks to sol-gel (SG) chemistry with judicious embeded chemical functions. This strategy is thus breaking up with traditional approaches (design of new copolymers, use of inorganic charges/additives). In 2020, we presented the elaboration and functional properties of a 1st generation of hybrid membranes with promising performances and durability. The latter was made by self-condensing a SG phase with 3(mercaptopropyl)trimethoxysilane (MPTMS) inside a commercial sPEEK host membrane. The successful in-situ condensation reactions of the MPTMS was demonstrated by measures of mass uptakes, FTIR spectroscopy (presence of C-Haliphatics) and solid state NMR 29Si (T2 & T3 signals of self-condensation products). The ability of the SG phase to prevent the oxidative degradation of the sPEEK phase (thanks to thiol chemical functions) was then proved with H2O2 accelerating tests and FC operating tests. A 2nd generation made of thiourea functionalized SG precursors (named HTU & TTU) was made after. By analysing in depth the morphologies of these different hybrids by direct space analysis (AFM/SEM/TEM) and reciprocal space analysis (SANS/SAXS/WAXS), we highlighted that both SG phase morphology and its localisation into the host has a huge impact on the PEM functional properties observed. This relationship is also dependent on the chemical function embedded. The hybrids obtained have shown very good chemical resistance during aging test (exposed to H2O2) compared to the commercial sPEEK. But the chemical function used is considered as “sacrificial” and cannot react indefinitely with H2O2. Thus, we are now working on a 3rd generation made of both sacrificial/regenerative chemical functions which are expected to inhibit the chemical aging of sPEEK more efficiently. With this work, we are confident to reach a predictive approach of the key parameters governing the final properties.

Keywords: fuel cells, ionomers, membranes, sPEEK, chemical stability

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Authors: Mohammad R. Jalali, Mohammad M. Jalali

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The earliest theories of sloshing waves and solitary waves based on potential theory idealisations and irrotational flow have been extended to be applicable to more realistic domains. To this end, the computational fluid dynamics (CFD) methods are widely used. Three-dimensional CFD methods such as Navier-Stokes solvers with volume of fluid treatment of the free surface and Navier-Stokes solvers with mappings of the free surface inherently impose high computational expense; therefore, considerable effort has gone into developing depth-averaged approaches. Examples of such approaches include Green–Naghdi (GN) equations. In Cartesian system, GN velocity profile depends on horizontal directions, x-direction and y-direction. The effect of vertical direction (z-direction) is also taken into consideration by applying weighting function in approximation. GN theory considers the effect of vertical acceleration and the consequent non-hydrostatic pressure. Moreover, in GN theory, the flow is rotational. The present study illustrates the application of GN equations to propagation of sloshing waves and solitary waves. For this purpose, GN equations solver is verified for the benchmark tests of Gaussian hump sloshing and solitary wave propagation in shallow basins. Analysis of the free surface sloshing of even harmonic components of an initial Gaussian hump demonstrates that the GN model gives predictions in satisfactory agreement with the linear analytical solutions. Discrepancies between the GN predictions and the linear analytical solutions arise from the effect of wave nonlinearities arising from the wave amplitude itself and wave-wave interactions. Numerically predicted solitary wave propagation indicates that the GN model produces simulations in good agreement with the analytical solution of the linearised wave theory. Comparison between the GN model numerical prediction and the result from perturbation analysis confirms that nonlinear interaction between solitary wave and a solid wall is satisfactorilly modelled. Moreover, solitary wave propagation at an angle to the x-axis and the interaction of solitary waves with each other are conducted to validate the developed model.

Keywords: Green–Naghdi equations, nonlinearity, numerical prediction, sloshing waves, solitary waves

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Authors: Nazlı Çetindağ, Pelin Yılmaz Çetiner, Metin Mert İlgün, Emine Birci, Gizemnur Yıldız Uysal, Özcan Hatipoğlu, Ehsan Tuzcuoğlu, Gökhan Sır

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Stressing the importance of water conservation, emphasizing the need for efficient management of household water, and underlining the significance of alternative solutions are important. In this context, advanced solutions based on technologies such as the advanced oxidation process have emerged as promising methods for treating household wastewater. Evaluating household water usage holds critical importance for the sustainability of water resources. Researchers and experts are examining various technological approaches to effectively treat and reclaim water for reuse. In this framework, the advanced oxidation process has proven to be an effective method for the removal of various organic and inorganic pollutants in the treatment of household wastewater. In this study, performance will be evaluated by comparing it with the reference case. This international criterion simulates the washing of home textile products, determining various performance parameters. The specially designed stain strips, including sebum, carbon black, blood, cocoa, and red wine, used in experiments, represent various household stains. These stain types were carefully selected to represent challenging stain scenarios, ensuring a realistic assessment of washing performance. Experiments conducted under different temperatures and program conditions successfully demonstrate the practical applicability of the advanced oxidation process for treating household wastewater. It is important to note that both adherence to standards and the use of real-life stain types contribute to the broad applicability of the findings. In conclusion, this study strongly supports the effectiveness of treating household wastewater with the advanced oxidation process in terms of washing performance under both standard and practical application conditions. The study underlines the importance of alternative solutions for sustainable water resource management and highlights the potential of the advanced oxidation process in the treatment of household water, contributing significantly to optimizing water usage and developing sustainable water management solutions.

Keywords: advanced oxidation process, household water usage, household appliance waste water, modelling, water reuse

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Authors: Mir Ahmad Lashteh Neshaei, Hamed Afsoos Biria, Ata Ghabraei, Mir Abdolhamid Mehrdad

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Awareness of effective land using issues in coastal area including protection of natural ecosystems and coastal environment due to the increasing of human life along the coast is of great importance. There are numerous valuable structures and heritages which are located in defence sites and waterfront area. Marine structures such as groins, sea walls and detached breakwaters are constructed in coast to improve the coast stability against bed erosion due to changing wave and climate pattern. Marine mechanisms and interaction with the shore protection structures need to be intensively studied. Groins are one of the most prominent structures that are used in shore protection to create a safe environment for coastal area by maintaining the land against progressive coastal erosion. The main structural function of a groin is to control the long shore current and littoral sediment transport. This structure can be submerged and provide the necessary beach protection without negative environmental impact. However, for submerged structures adopted for beach protection, the shoreline response to these structures is not well understood at present. Nowadays, modelling and computer simulation are used to assess beach morphology in the vicinity of marine structures to reduce their environmental impact. The objective of this study is to predict the beach morphology in the vicinity of submerged groins and comparison with non-submerged groins with focus on a part of the coast located in Dahane sar Sefidrood, Guilan province, Iran where serious coast erosion has occurred recently. The simulations were obtained using a one-line model which can be used as a first approximation of shoreline prediction in the vicinity of groins. The results of the proposed model are compared with field measurements to determine the shape of the coast. Finally, the results of the present study show that using submerged groins can have a good efficiency to control the beach erosion without causing severe environmental impact to the coast. The important outcome from this study can be employed in optimum designing of defence sites in the coastal cities to improve their efficiency in terms of re-using the heritage lands.

Keywords: submerged structures, groin, shore protective structures, coastal cities

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Authors: Sameh Shahin, Nannang Arrys

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Optimizing pit slope stability and reducing strip ratio of a mining operation are two key tasks in geotechnical engineering. With a growing demand for minerals and an increasing cost associated with extraction, companies are constantly re-evaluating the viability of mineral deposits and challenging their geological understanding. Within Rio Tinto Iron Ore, the Structural Geology (SG) team investigate and collect critical data, such as point based orientations, mapping and geological inferences from adjacent pits to re-model deposits where previous interpretations have failed to account for structurally controlled slope failures. Utilizing innovative data collection methods and data-driven investigation, SG aims to address the root causes of slope instability. Committing to a resource grid drill campaign as the primary source of data collection will often bias data collection to a specific orientation and significantly reduce the capability to identify and qualify complexity. Consequently, these limitations make it difficult to construct a realistic and coherent structural model that identifies adverse structural domains. Without the consideration of complexity and the capability of capturing these structural domains, mining operations run the risk of inadequately designed slopes that may fail and potentially harm people. Regional structural trends have been considered in conjunction with surface and in-pit mapping data to model multi-batter fold structures that were absent from previous iterations of the structural model. The risk is evident in newly identified dip-slope and rock-mass controlled sectors of the geotechnical design rather than a ubiquitous dip-slope sector across the pit. The reward is two-fold: 1) providing sectors of rock-mass controlled design in previously interpreted structurally controlled domains and 2) the opportunity to optimize the slope angle for mineral recovery and reduced strip ratio. Furthermore, a resulting high confidence model with structures and geometries that can account for historic slope instabilities in structurally controlled domains where design assumptions failed.

Keywords: structural geology, geotechnical design, optimization, slope stability, risk mitigation

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Authors: Mustafa Metin Donma

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Metabolic syndrome (MetS) is characterized by a series of biochemical, physiological and anthropometric indicators and is a life-threatening health problem due to its close association with chronic diseases such as diabetes mellitus, hypertension, cancer and cardiovascular diseases. The syndrome deserves great interest both in adults and children. Central obesity is the indispensable component of MetS. Particularly, children, who are morbidly obese have a great tendency to develop the disease, because they are under the threat in their future lives. Preventive measures at this stage should be considered. For this, investigators seek for an informative scale or an index for the purpose. So far, several, but not many suggestions come into the stage. However, the diagnostic decision is not so easy and may not be complete particularly in the pediatric population. The aim of the study was to develop a MetS index capable of predicting MetS, while children are at the morbid obesity stage. This study was performed on morbid obese (MO) children, which were divided into two groups. Morbid obese children, who do not possess MetS criteria comprised the first group (n=44). The second group was composed of children (n=42) with MetS diagnosis. Parents were informed about the signed consent forms, which are required for the participation of their children in the study. The approval of the study protocol was taken from the institutional ethics committee of Tekirdag Namik Kemal University. Helsinki Declaration was accepted prior to and during the study. Anthropometric measurements including weight, height, waist circumference (WC), hip C, head C, neck C, biochemical tests including fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein cholesterol (HDL-C) and blood pressure measurements (systolic (SBP) and diastolic (DBP)) were performed. Body fat percentage (BFP) values were determined by TANITA’s Bioelectrical Impedance Analysis technology. Body mass index and MetS indices were calculated. The equations for MetS index (MetSI) and advanced Donma MetS index (ADMI) were [(INS/FBG)/(HDL-C/TRG)]*100 and MetSI*[(SBP+DBP/Height)], respectively. Descriptive statistics including median values, compare means tests, correlation-regression analysis were performed within the scope of data evaluation using the statistical package program, SPSS. Statistically significant mean differences were determined by a p value smaller than 0.05. Median values for MetSI and ADMI in MO (MetS-) and MO (MetS+) groups were calculated as (25.9 and 36.5) and (74.0 and 106.1), respectively. Corresponding mean±SD values for BFPs were 35.9±7.1 and 38.2±7.7 in groups. Correlation analysis of these two indices with corresponding general BFP values exhibited significant association with ADMI, close to significance with MetSI in MO group. Any significant correlation was found with neither of the indices in MetS group. In conclusion, important associations observed with MetS indices in MO group were quite meaningful. The presence of these associations in MO group was important for showing the tendency towards the development of MetS in MO (MetS-) participants. The other index, ADMI, was more helpful for predictive purpose.

Keywords: body fat percentage, child, index, metabolic syndrome, obesity

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Authors: Raj Chandran, Saul Datwyler, Jaime Marino, Daniel West, Karla Grasso, Adam Buss, Hina Syed, Zina Al Sahouri, Jennifer Yen, Krista Caudle, Beth McQuiston

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The Alinity i TBI test is Therapeutic Goods Administration (TGA) registered and is a panel of in vitro diagnostic chemiluminescent microparticle immunoassays for the measurement of glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase L1 (UCH-L1) in plasma and serum. The Alinity i TBI performance was evaluated in a multi-center pivotal study to demonstrate the capability to assist in determining the need for a CT scan of the head in adult subjects (age 18+) presenting with suspected mild TBI (traumatic brain injury) with a Glasgow Coma Scale score of 13 to 15. TBI has been recognized as an important cause of death and disability and is a growing public health problem. An estimated 69 million people globally experience a TBI annually1. Blood-based biomarkers such as glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase L1 (UCH-L1) have shown utility to predict acute traumatic intracranial injury on head CT scans after TBI. A pivotal study using prospectively collected archived (frozen) plasma specimens was conducted to establish the clinical performance of the TBI test on the Alinity i system. The specimens were originally collected in a prospective, multi-center clinical study. Testing of the specimens was performed at three clinical sites in the United States. Performance characteristics such as detection limits, imprecision, linearity, measuring interval, expected values, and interferences were established following Clinical and Laboratory Standards Institute (CLSI) guidance. Of the 1899 mild TBI subjects, 120 had positive head CT scan results; 116 of the 120 specimens had a positive TBI interpretation (Sensitivity 96.7%; 95% CI: 91.7%, 98.7%). Of the 1779 subjects with negative CT scan results, 713 had a negative TBI interpretation (Specificity 40.1%; 95% CI: 37.8, 42.4). The negative predictive value (NPV) of the test was 99.4% (713/717, 95% CI: 98.6%, 99.8%). The analytical measuring interval (AMI) extends from the limit of quantitation (LoQ) to the upper LoQ and is determined by the range that demonstrates acceptable performance for linearity, imprecision, and bias. The AMI is 6.1 to 42,000 pg/mL for GFAP and 26.3 to 25,000 pg/mL for UCH-L1. Overall, within-laboratory imprecision (20 day) ranged from 3.7 to 5.9% CV for GFAP and 3.0 to 6.0% CV for UCH-L1, when including lot and instrument variances. The Alinity i TBI clinical performance results demonstrated high sensitivity and high NPV, supporting the utility to assist in determining the need for a head CT scan in subjects presenting to the emergency department with suspected mild TBI. The GFAP and UCH-L1 assays show robust analytical performance across a broad concentration range of GFAP and UCH-L1 and may serve as a valuable tool to help evaluate TBI patients across the spectrum of mild to severe injury.

Keywords: biomarker, diagnostic, neurology, TBI

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Authors: Shehu Usman Rano Aliyu

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Despite the significance of finance as a major trade lubricant, evidence in the literature alludes to its scarcity and increasing cost, especially in developing countries where small and medium-scale enterprises are worst affected. The creation of the African Continental Free Trade Area (AFCFTA) in 2018, an organ of the African Union (AU), was meant to serve as a beacon for deepening economic integration through the removal of trade barriers inhibiting intra-African trade and movement of persons, among others. Hence, this research explores the role Islamic trade finance (ITF) could play in spurring intra- and inter-African trade. The study involves six countries; Egypt, Kenya, Malaysia, Morocco, Nigeria, and Saudi Arabia, and employs survey research, a total of 430 sample data, and SmartPLS Structural Equation Modelling (SEM) techniques in its analyses. We find strong evidence that Shari’ah, legal and regulatory compliance issues of the ITF institutions rhythm with the internal, national, and international compliance requirements equally as the unique instruments applied in ITF. In addition, ITF was found to be largely driven by global economic and political stability, socially responsible finance, ethical and moral considerations, risk-sharing, and resilience of the global Islamic finance industry. Further, SMEs, Governments, and Importers are the major beneficiary sectors. By and large, AfCFTA’s protocols align with the principles of ITF and are therefore suited for the proliferation of Islamic finance in the continent. And, while AML/KYC and BASEL requirements, compliance to AAOIFI and IFSB standards, paucity of Shari'ah experts, threats to global security, and increasing global economic uncertainty pose as major impediments, the future of ITF would be shaped by a greater need for institutional and policy support, global economic cum political stability, robust regulatory framework, and digital technology/fintech. The study calls for the licensing of more ITF institutions in the continent, participation of multilateral institutions in ITF, and harmonization of Shariah standards.

Keywords: AfCFTA, islamic trade finance, murabaha, letter of credit, forwarding

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Authors: Liliana Rusu

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The goal of the proposed work is to provide a more comprehensive picture of the wind and wave climate in the Romanian nearshore, using the results provided by numerical models. The Romanian coastal environment is located in the western side of the Black Sea, the more energetic part of the sea, an area with heavy maritime traffic and various offshore operations. Information about the wind and wave climate in the Romanian waters is mainly based on observations at Gloria drilling platform (70 km from the coast). As regards the waves, the measurements of the wave characteristics are not so accurate due to the method used, being also available for a limited period. For this reason, the wave simulations that cover large temporal and spatial scales represent an option to describe better the wave climate. To assess the wind climate in the target area spanning 1992–2016, data provided by the NCEP-CFSR (U.S. National Centers for Environmental Prediction - Climate Forecast System Reanalysis) and consisting in wind fields at 10m above the sea level are used. The high spatial and temporal resolution of the wind fields is good enough to represent the wind variability over the area. For the same 25-year period, as considered for the wind climate, this study characterizes the wave climate from a wave hindcast data set that uses NCEP-CFSR winds as input for a model system SWAN (Simulating WAves Nearshore) based. The wave simulation results with a two-level modelling scale have been validated against both in situ measurements and remotely sensed data. The second level of the system, with a higher resolution in the geographical space (0.02°×0.02°), is focused on the Romanian coastal environment. The main wave parameters simulated at this level are used to analyse the wave climate. The spatial distributions of the wind speed, wind direction and the mean significant wave height have been computed as the average of the total data. As resulted from the amount of data, the target area presents a generally moderate wave climate that is affected by the storm events developed in the Black Sea basin. Both wind and wave climate presents high seasonal variability. All the results are computed as maps that help to find the more dangerous areas. A local analysis has been also employed in some key locations corresponding to highly sensitive areas, as for example the main Romanian harbors.

Keywords: numerical simulations, Romanian nearshore, waves, wind

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Authors: Mina Rouhollahi, J. Boland

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Changes in cities’ heat balance due to rapid urbanization and the urban heat island (UHI) have increased energy demands for space cooling and have resulted in uncomfortable living conditions for urban residents. Climate resilience and comfortable living spaces can be addressed through well-designed urban development. The sustainable housing can be more effective in controlling high levels of urban heat. In Australia, to mitigate the effects of UHIs and summer heat waves, one solution to sustainable housing has been the trend to compact housing design and the construction of energy efficient dwellings. This paper analyses whether current housing configurations and orientations are effective in avoiding increased demands for air conditioning and having an energy efficient residential neighborhood. A significant amount of energy is consumed to ensure thermal comfort in houses. This paper reports on the modelling of heat transfer within the homes using the measurements of radiation, convection and conduction between exterior/interior wall surfaces and outdoor/indoor environment respectively. The simulation was tested on selected 7.5-star energy efficient houses constructed of typical material elements and insulation in Adelaide, Australia. The chosen design dwellings were analyzed in extremely hot weather through one year. The data were obtained via a thermal circuit to accurately model the fundamental heat transfer mechanisms on both boundaries of the house and through the multi-layered wall configurations. The formulation of the Lumped capacitance model was considered in discrete time steps by adopting a non-linear model method. The simulation results focused on the effects of orientation of the solar radiation on the dynamic thermal characteristics of the houses orientations. A high star rating did not necessarily coincide with a decrease in peak demands for cooling. A more effective approach to avoid increasing the demands for air conditioning and energy may be to integrate solar–climatic data to evaluate the performance of energy efficient houses.

Keywords: energy-efficient residential building, heat transfer, neighborhood orientation, solar–climatic data

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Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

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The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

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Authors: Epameinondas Xanthakis, Erik Kaunisto, Alain Le-Bail, Lilia Ahrné

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Fruits and vegetables are characterized as perishable food matrices due to their short shelf life as several deterioration mechanisms are being involved. Prior to the common preservation methods like freezing or canning, fruits and vegetables are being blanched in order to inactivate deteriorative enzymes. Both conventional blanching pretreatments and conventional freezing methods hide drawbacks behind their beneficial impacts on the preservation of those matrices. Conventional blanching methods may require longer processing times, leaching of minerals and nutrients due to the contact with the warm water which in turn leads to effluent production with large BOD. An important issue of freezing technologies is the size of the formed ice crystals which is also critical for the final quality of the frozen food as it can cause irreversible damage to the cellular structure and subsequently to degrade the texture and the colour of the product. Herein, the developed microwave blanching methodology and the results regarding quality aspects and enzyme inactivation will be presented. Moreover, heat transfer phenomena, mass balance, temperature distribution, and enzyme inactivation (such as Pectin Methyl Esterase and Ascorbic Acid Oxidase) of our microwave blanching approach will be evaluated based on measurements and computer modelling. The present work is part of the COLDμWAVE project which aims to the development of an innovative environmentally sustainable process for blanching and freezing of fruits and vegetables with improved textural and nutritional quality. In this context, COLDµWAVE will develop tailored equipment for MW blanching of vegetables that has very high energy efficiency and no water consumption. Furthermore, the next steps of this project regarding the development of innovative pathways in MW assisted freezing to improve the quality of frozen vegetables, by exploring in depth previous results acquired by the authors, will be presented. The application of MW assisted freezing process on fruits and vegetables it is expected to lead to improved quality characteristics compared to the conventional freezing. Acknowledgments: COLDμWAVE has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grand agreement No 660067.

Keywords: blanching, freezing, fruits, microwave blanching, microwave

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Authors: Ludivine Gueho, Sylvain Fleury, Eric Jamet

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Driver distraction is known to be a major contributing factor of car accidents. Since many years, constructors have been designing embedded technologies to face this problem and reduce distraction. Being able to predict user acceptance would further be helpful in the development process to build appropriate systems. The present research aims at modelling the acceptability of a specific system, an innovative personalized and contextualized embedded radio, through an online survey of 202 people in France that assessed the psychological variables determining intentions to use the system. The questionnaire instantiated the dimensions of the extended version of the UTAUT acceptability model. Because of the specific features of the system assessed, we added 4 dimensions: perceived security, anxiety, trust and privacy concerns. Results showed that hedonic motivation, i.e., the fun or pleasure derived from using a technology, and performance expectancy, i.e., the degree to which individuals believe that the characteristics of the system meet their needs, are the most important dimensions in determining behavioral intentions about the innovative radio. To a lesser extent, social influence, i.e., the degree to which individuals think they can use the system while respecting their social group’s norms and while giving a positive image of themselves, had an effect on behavioral intentions. Moreover, trust, that is, the positive belief about the perceived reliability of, dependability of, and confidence in a person, object or process, had a significant effect, mediated by performance expectancy. In an applicative way, the present research reveals that, to be accepted, in-car embedded new technology has to address individual needs, for instance by facilitating the driving activity or by providing useful information. If it shows hedonic qualities by being entertaining, pretty or comfortable, this may improve the intentions to use it. Therefore, it is clearly important to include reflection about user experience in the design process. Finally, the users have to be reassured on the system’s reliability. For example, improving the transparency of the system by providing information about the system functioning, could improve trust. These results bring some highlights on determinant of acceptance of an in-vehicle technology and are useful for constructors to design acceptable systems.

Keywords: acceptability, innovative embedded radio, structural equation, user-centric evaluation, UTAUT

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Authors: Anna-Lisa Osvalder, Jonas Borell

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There are several reasons behind the use, non-use, or inadequate use of personal protective equipment (PPE) in the construction industry. Comfort and accurate size support proper use, while discomfort, misfit, and difficulties to understand how the PPEs should be handled inhibit correct usage. The need for several protective equipments simultaneously might also create problems. The purpose of this study was to analyse the correct usage, comfort, and fit of different types of PPEs used for construction work. Correct usage was analysed as guessability, i.e., human perceptions of how to don, adjust, use, and doff the equipment, and if used as intended. The PPEs tested individually or in combinations were a helmet, ear protectors, goggles, respiratory masks, gloves, protective cloths, and safety harnesses. First, an analytical evaluation was performed with ECW (enhanced cognitive walkthrough) and PUEA (predictive use error analysis) to search for usability problems and use errors during handling and use. Then usability tests were conducted to evaluate guessability, comfort, and fit with 10 test subjects of different heights and body constitutions. The tests included observations during donning, five different outdoor work tasks, and doffing. The think-aloud method, short interviews, and subjective estimations were performed. The analytical evaluation showed that some usability problems and use errors arise during donning and doffing, but with minor severity, mostly causing discomfort. A few use errors and usability problems arose for the safety harness, especially for novices, where some could lead to a high risk of severe incidents. The usability tests showed that discomfort arose for all test subjects when using a combination of PPEs, increasing over time. For instance, goggles, together with the face mask, caused pressure, chafing at the nose, and heat rash on the face. This combination also limited sight of vision. The helmet, in combination with the goggles and ear protectors, did not fit well and caused uncomfortable pressure at the temples. No major problems were found with the individual fit of the PPEs. The ear protectors, goggles, and face masks could be adjusted for different head sizes. The guessability for how to don and wear the combination of PPE was moderate, but it took some time to adjust them for a good fit. The guessability was poor for the safety harness; few clues in the design showed how it should be donned, adjusted, or worn on the skeletal bones. Discomfort occurred when the straps were tightened too much. All straps could not be adjusted for somebody's constitutions leading to non-optimal safety. To conclude, if several types of PPEs are used together, discomfort leading to pain is likely to occur over time, which can lead to misuse, non-use, or reduced performance. If people who are not regular users should wear a safety harness correctly, the design needs to be improved for easier interpretation, correct position of the straps, and increased possibilities for individual adjustments. The results from this study can be a base for re-design ideas for PPE, especially when they should be used in combinations.

Keywords: construction work, PPE, personal protective equipment, misuse, guessability, usability

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