Search results for: optimal transport

Authors: M. Reza Hashemi, Chris Small, Scott Hayward

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The Northeast Coast of the US faces damaging effects of coastal flooding and winds due to Atlantic tropical and extratropical storms each year. Historically, several large storm events have produced substantial levels of damage to the region; most notably of which were the Great Atlantic Hurricane of 1938, Hurricane Carol, Hurricane Bob, and recently Hurricane Sandy (2012). The objective of this study was to develop an integrated modeling system that could be used as a forecasting/hindcasting tool to evaluate and communicate the risk coastal communities face from these coastal storms. This modeling system utilizes the ADvanced CIRCulation (ADCIRC) model for storm surge predictions and the Simulating Waves Nearshore (SWAN) model for the wave environment. These models were coupled, passing information to each other and computing over the same unstructured domain, allowing for the most accurate representation of the physical storm processes. The coupled SWAN-ADCIRC model was validated and has been set up to perform real-time forecast simulations (as well as hindcast). Modeled storm parameters were then passed to a coastal risk assessment tool. This tool, which is generic and universally applicable, generates spatial structural damage estimate maps on an individual structure basis for an area of interest. The required inputs for the coastal risk model included a detailed information about the individual structures, inundation levels, and wave heights for the selected region. Additionally, calculation of wind damage to structures was incorporated. The integrated coastal risk assessment system was then tested and applied to Charlestown, a small vulnerable coastal town along the southern shore of Rhode Island. The modeling system was applied to Hurricane Sandy and a synthetic storm. In both storm cases, effect of natural dunes on coastal risk was investigated. The resulting damage maps for the area (Charlestown) clearly showed that the dune eroded scenarios affected more structures, and increased the estimated damage. The system was also tested in forecast mode for a large Nor’Easters: Stella (March 2017). The results showed a good performance of the coupled model in forecast mode when compared to observations. Finally, a nearshore model XBeach was then nested within this regional grid (ADCIRC-SWAN) to simulate nearshore sediment transport processes and coastal erosion. Hurricane Irene (2011) was used to validate XBeach, on the basis of a unique beach profile dataset at the region. XBeach showed a relatively good performance, being able to estimate eroded volumes along the beach transects with a mean error of 16%. The validated model was then used to analyze the effectiveness of several erosion mitigation methods that were recommended in a recent study of coastal erosion in New England: beach nourishment, coastal bank (engineered core), and submerged breakwater as well as artificial surfing reef. It was shown that beach nourishment and coastal banks perform better to mitigate shoreline retreat and coastal erosion.

Keywords: ADCIRC, coastal flooding, storm surge, coastal risk assessment, living shorelines

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Authors: Roberta Martino, Viviana Ventre

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Empirical evidence has, over time, confirmed that the behavior of individuals is inconsistent with the descriptions provided by the Discounted Utility Model, an essential reference for calculating the utility of intertemporal prospects. The model assumes that individuals calculate the utility of intertemporal prospectuses by adding up the values of all outcomes obtained by multiplying the cardinal utility of the outcome by the discount function estimated at the time the outcome is received. The trend of the discount function is crucial for the preferences of the decision maker because it represents the perception of the future, and its trend causes temporally consistent or temporally inconsistent preferences. In particular, because different formulations of the discount function lead to various conclusions in predicting choice, the descriptive ability of models with a hyperbolic trend is greater than linear or exponential models. Suboptimal choices from any time point of view are the consequence of this mechanism, the psychological factors of which are encapsulated in the discount rate trend. In addition, analyzing the decision-making process from a psychological perspective, there is an equivalence between the selection of dominated prospects and a degree of impatience that decreases over time. The first part of the paper describes and investigates the anomalies of the discounted utility model by relating the cognitive distortions of the decision-maker to the emotional factors that are generated during the evaluation and selection of alternatives. Specifically, by studying the degree to which impatience decreases, it’s possible to quantify how the psychological and emotional mechanisms of the decision-maker result in a lack of decision persistence. In addition, this description presents inconsistency as the consequence of an inconsistent attitude towards time-delayed choices. The second part of the paper presents an experimental phase in which we show the relationship between inconsistency and impatience in different contexts. Analysis of the degree to which impatience decreases confirms the influence of the decision maker's emotional impulses for each anomaly in the utility model discussed in the first part of the paper. This work provides an application in the field of personalized behavioral finance. Indeed, the numerous behavioral diversities, evident even in the degrees of decrease in impatience in the experimental phase, support the idea that optimal strategies may not satisfy individuals in the same way. With the aim of homogenizing the categories of investors and to provide a personalized approach to advice, the results proven in the experimental phase are used in a complementary way with the information in the field of behavioral finance to implement the Analytical Hierarchy Process model in intertemporal choices, useful for strategic personalization. In the construction of the Analytic Hierarchy Process, the degree of decrease in impatience is understood as reflecting irrationality in decision-making and is therefore used for the construction of weights between anomalies and behavioral traits.

Keywords: analytic hierarchy process, behavioral finance, financial anomalies, impatience, time inconsistency

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Authors: Pedro M. Rodrigues, Claudia Raposo, Denise Schrama, Marco Cerqueira

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Farmed fish welfare is a very recent concept, widely discussed among the scientific community. Consumers’ interest regarding farmed animal welfare standards has significantly increased in the last years posing a huge challenge to producers in order to maintain an equilibrium between good welfare principles and productivity, while simultaneously achieve public acceptance. The major bottleneck of standard aquaculture is to impair considerably fish welfare throughout the production cycle and with this, the quality of fish protein. Welfare assessment in farmed fish is undertaken through the evaluation of fish stress responses. Primary and secondary stress responses include release of cortisol and glucose and lactate to the blood stream, respectively, which are currently the most commonly used indicators of stress exposure. However, the reliability of these indicators is highly dubious, due to a high variability of fish responses to an acute stress and the adaptation of the animal to a repetitive chronic stress. Our objective is to use comparative proteomics to identify and validate a fingerprint of proteins that can present an more reliable alternative to the already established welfare indicators. In this way, the culture conditions will improve and there will be a higher perception of mechanisms and metabolic pathway involved in the produced organism’s welfare. Due to its high economical importance in Portuguese aquaculture Gilthead seabream will be the elected species for this study. Protein extracts from Gilthead Seabream fish muscle, liver and plasma, reared for a 3 month period under optimized culture conditions (control) and induced stress conditions (Handling, high densities, and Hipoxia) are collected and used to identify a putative fish welfare protein markers fingerprint using a proteomics approach. Three tanks per condition and 3 biological replicates per tank are used for each analisys. Briefly, proteins from target tissue/fluid are extracted using standard established protocols. Protein extracts are then separated using 2D-DIGE (Difference gel electrophoresis). Proteins differentially expressed between control and induced stress conditions will be identified by mass spectrometry (LC-Ms/Ms) using NCBInr (taxonomic level - Actinopterygii) databank and Mascot search engine. The statistical analysis is performed using the R software environment, having used a one-tailed Mann-Whitney U-test (p < 0.05) to assess which proteins were differentially expressed in a statistically significant way. Validation of these proteins will be done by comparison of the RT-qPCR (Quantitative reverse transcription polymerase chain reaction) expressed genes pattern with the proteomic profile. Cortisol, glucose, and lactate are also measured in order to confirm or refute the reliability of these indicators. The identified liver proteins under handling and high densities induced stress conditions are responsible and involved in several metabolic pathways like primary metabolism (i.e. glycolysis, gluconeogenesis), ammonia metabolism, cytoskeleton proteins, signalizing proteins, lipid transport. Validition of these proteins as well as identical analysis in muscle and plasma are underway. Proteomics is a promising high-throughput technique that can be successfully applied to identify putative welfare protein biomarkers in farmed fish.

Keywords: aquaculture, fish welfare, proteomics, welfare biomarkers

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Authors: L. Raczynski, P. Moskal, P. Kowalski, W. Wislicki, T. Bednarski, P. Bialas, E. Czerwinski, A. Gajos, L. Kaplon, A. Kochanowski, G. Korcyl, J. Kowal, T. Kozik, W. Krzemien, E. Kubicz, Sz. Niedzwiecki, M. Palka, Z. Rudy, O. Rundel, P. Salabura, N.G. Sharma, M. Silarski, A. Slomski, J. Smyrski, A. Strzelecki, A. Wieczorek, M. Zielinski, N. Zon

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The J-PET scanner, which allows for single bed imaging of the whole human body, is currently under development at the Jagiellonian University. The J-PET detector improves the TOF resolution due to the use of fast plastic scintillators. Since registration of the waveform of signals with duration times of few nanoseconds is not feasible, a novel front-end electronics allowing for sampling in a voltage domain at four thresholds was developed. To take fully advantage of these fast signals a novel scheme of recovery of the waveform of the signal, based on ideas from the Tikhonov regularization (TR) and Compressive Sensing methods, is presented. The prior distribution of sparse representation is evaluated based on the linear transformation of the training set of waveform of the signals by using the Principal Component Analysis (PCA) decomposition. Beside the advantage of including the additional information from training signals, a further benefit of the TR approach is that the problem of signal recovery has an optimal solution which can be determined explicitly. Moreover, from the Bayes theory the properties of regularized solution, especially its covariance matrix, may be easily derived. This step is crucial to introduce and prove the formula for calculations of the signal recovery error. It has been proven that an average recovery error is approximately inversely proportional to the number of samples at voltage levels. The method is tested using signals registered by means of the single detection module of the J-PET detector built out from the 30 cm long BC-420 plastic scintillator strip. It is demonstrated that the experimental and theoretical functions describing the recovery errors in the J-PET scenario are largely consistent. The specificity and limitations of the signal recovery method in this application are discussed. It is shown that the PCA basis offers high level of information compression and an accurate recovery with just eight samples, from four voltage levels, for each signal waveform. Moreover, it is demonstrated that using the recovered waveform of the signals, instead of samples at four voltage levels alone, improves the spatial resolution of the hit position reconstruction. The experiment shows that spatial resolution evaluated based on information from four voltage levels, without a recovery of the waveform of the signal, is equal to 1.05 cm. After the application of an information from four voltage levels to the recovery of the signal waveform, the spatial resolution is improved to 0.94 cm. Moreover, the obtained result is only slightly worse than the one evaluated using the original raw-signal. The spatial resolution calculated under these conditions is equal to 0.93 cm. It is very important information since, limiting the number of threshold levels in the electronic devices to four, leads to significant reduction of the overall cost of the scanner. The developed recovery scheme is general and may be incorporated in any other investigation where a prior knowledge about the signals of interest may be utilized.

Keywords: plastic scintillators, positron emission tomography, statistical analysis, tikhonov regularization

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Authors: D. Pugazhenthi, B. Sree Vidya

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Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

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Authors: Corentin Jankowiak, Aggelos Zacharopoulos, Caterina Brandoni

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In a context of increasing stress put on the electricity network by the decarbonization of many sectors, energy storage is likely to be the key mitigating element, by acting as a buffer between production and demand. In particular, the highest potential for storage is when connected closer to the loads. Yet, low voltage storage struggles to penetrate the market at a large scale due to the novelty and complexity of the solution, and the competitive advantage of fossil fuel-based technologies regarding regulations. Strong and reliable numerical simulations are required to show the benefits of storage located near loads and promote its development. The present study was restrained from excluding aggregated control of storage: it is assumed that the storage units operate independently to one another without exchanging information – as is currently mostly the case. A computationally light battery model is presented in detail and validated by direct comparison with a domestic battery operating in real conditions. This model is then used to develop Peak-Shaving (PS) control strategies as it is the decentralized service from which beneficial impacts are most likely to emerge. The aggregation of flatter, peak- shaved consumption profiles is likely to lead to flatter and arbitraged profile at higher voltage layers. Furthermore, voltage fluctuations can be expected to decrease if spikes of individual consumption are reduced. The crucial part to achieve PS lies in the charging pattern: peaks depend on the switching on and off of appliances in the dwelling by the occupants and are therefore impossible to predict accurately. A performant PS strategy must, therefore, include a smart charge recovery algorithm that can ensure enough energy is present in the battery in case it is needed without generating new peaks by charging the unit. Three categories of PS algorithms are introduced in detail. First, using a constant threshold or power rate for charge recovery, followed by algorithms using the State Of Charge (SOC) as a decision variable. Finally, using a load forecast – of which the impact of the accuracy is discussed – to generate PS. A performance metrics was defined in order to quantitatively evaluate their operating regarding peak reduction, total energy consumption, and self-consumption of domestic photovoltaic generation. The algorithms were tested on load profiles with a 1-minute granularity over a 1-year period, and their performance was assessed regarding these metrics. The results show that constant charging threshold or power are far from optimal: a certain value is not likely to fit the variability of a residential profile. As could be expected, forecast-based algorithms show the highest performance. However, these depend on the accuracy of the forecast. On the other hand, SOC based algorithms also present satisfying performance, making them a strong alternative when the reliable forecast is not available.

Keywords: decentralised control, domestic integrated batteries, electricity network performance, peak-shaving algorithm

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Authors: Adrian Szczyrba, Aneta Halka-Grysinska, Tomasz Baj, Tadeusz H. Dzido

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Since prehistory, plants were constituted as an essential source of biologically active substances in folk medicine. One of the examples of medicinal plants is Ruta graveolens L. For a long time, Ruta g. herb has been famous for its spasmolytic, diuretic, or anti-inflammatory therapeutic effects. The wide spectrum of secondary metabolites produced by Ruta g. includes flavonoids (eg. rutin, quercetin), coumarins (eg. bergapten, umbelliferone) phenolic acids (eg. rosmarinic acid, chlorogenic acid), and limonoids. Unfortunately, the presence of produced substances is highly dependent on environmental factors like temperature, humidity, or soil acidity; therefore standardization is necessary. There were many attempts of characterization of various phytochemical groups (eg. coumarins) of Ruta graveolens using the normal – phase thin-layer chromatography (TLC). However, due to the so-called general elution problem, usually, some components remained unseparated near the start or finish line. Therefore Ruta graveolens is a very good model plant. Methanol and petroleum ether extract from its aerial parts were used to demonstrate the capabilities of the new device for gradient thin-layer chromatogram development. The development of gradient thin-layer chromatograms in the reversed-phase system in conventional horizontal chambers can be disrupted by problems associated with an excessive flux of the mobile phase to the surface of the adsorbent layer. This phenomenon is most likely caused by significant differences between the surface tension of the subsequent fractions of the mobile phase. An excessive flux of the mobile phase onto the surface of the adsorbent layer distorts the flow of the mobile phase. The described effect produces unreliable, and unrepeatable results, causing blurring and deformation of the substance zones. In the prototype device, the mobile phase solution is delivered onto the surface of the adsorbent layer with controlled velocity (by moving pipette driven by 3D machine). The delivery of the solvent to the adsorbent layer is equal to or lower than that of conventional development. Therefore chromatograms can be developed with optimal linear mobile phase velocity. Furthermore, under such conditions, there is no excess of eluent solution on the surface of the adsorbent layer so the higher performance of the chromatographic system can be obtained. Directly feeding the adsorbent layer with eluent also enables to perform convenient continuous gradient elution practically without the so-called gradient delay. In the study, unique fingerprints of methanol and petroleum ether extracts of Ruta graveolens aerial parts were obtained with stepwise gradient reversed-phase thin-layer chromatography. Obtained fingerprints under different chromatographic conditions will be compared. The advantages and disadvantages of the proposed approach to chromatogram development with controlled solvent velocity will be discussed.

Keywords: fingerprints, gradient thin-layer chromatography, reversed-phase TLC, Ruta graveolens

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Authors: Lily Ranjbar, Haori Yang

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Online education has been around for several decades, but the importance of online education became evident after the COVID-19 pandemic. Eventhough the online delivery approach works well for knowledge building through delivering content and oversight processes, it has limitations in developing hands-on laboratory skills, especially in the STEM field. During the pandemic, many education institutions faced numerous challenges in delivering lab-based courses, especially in the STEM field. Also, many students worldwide were unable to practice working with lab equipment due to social distancing or the significant cost of highly specialized equipment. The laboratory plays a crucial role in nuclear science and engineering education. It can engage students and improve their learning outcomes. In addition, online education and virtual labs have gained substantial popularity in engineering and science education. Therefore, developing virtual labs is vital for institutions to deliver high-class education to their students, including their online students. The School of Nuclear Science and Engineering (NSE) at Oregon State University, in partnership with SpectralLabs company, has developed an Advanced Virtual Radiation Detection and Measurement Lab (AVR-DML) to offer a fully online Master of Health Physics program. It was essential for us to use a system that could simulate nuclear modules that accurately replicate the underlying physics, the nature of radiation and radiation transport, and the mechanics of the instrumentations used in the real radiation detection lab. It was all accomplished using a Realistic, Adaptive, Interactive Learning System (RAILS). RAILS is a comprehensive software simulation-based learning system for use in training. It is comprised of a web-based learning management system that is located on a central server, as well as a 3D-simulation package that is downloaded locally to user machines. Users will find that the graphics, animations, and sounds in RAILS create a realistic, immersive environment to practice detecting different radiation sources. These features allow students to coexist, interact and engage with a real STEM lab in all its dimensions. It enables them to feel like they are in a real lab environment and to see the same system they would in a lab. Unique interactive interfaces were designed and developed by integrating all the tools and equipment needed to run each lab. These interfaces provide students full functionality for data collection, changing the experimental setup, and live data collection with real-time updates for each experiment. Students can manually do all experimental setups and parameter changes in this lab. Experimental results can then be tracked and analyzed in an oscilloscope, a multi-channel analyzer, or a single-channel analyzer (SCA). The advanced virtual radiation detection and measurement laboratory developed in this study enabled the NSE school to offer a fully online MHP program. This flexibility of course modality helped us to attract more non-traditional students, including international students. It is a valuable educational tool as students can walk around the virtual lab, make mistakes, and learn from them. They have an unlimited amount of time to repeat and engage in experiments. This lab will also help us speed up training in nuclear science and engineering.

Keywords: advanced radiation detection and measurement, virtual laboratory, realistic adaptive interactive learning system (rails), online education in stem fields, student engagement, stem online education, stem laboratory, online engineering education

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Authors: Salvatore Luongo, Carlo Luongo

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This paper discusses the implementation solutions to reduce the computational load for the Traffic Situational Awareness with Alerts (TSAA) application, based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology. In 2008, there were 23 total mid-air collisions involving general aviation fixed-wing aircraft, 6 of which were fatal leading to 21 fatalities. These collisions occurred during visual meteorological conditions, indicating the limitations of the see-and-avoid concept for mid-air collision avoidance as defined in the Federal Aviation Administration’s (FAA). The commercial aviation aircraft are already equipped with collision avoidance system called TCAS, which is based on classic transponder technology. This system dramatically reduced the number of mid-air collisions involving air transport aircraft. In general aviation, the same reduction in mid-air collisions has not occurred, so this reduction is the main objective of the TSAA application. The major difference between the original conflict detection application and the TSAA application is that the conflict detection is focused on preventing loss of separation in en-route environments. Instead TSAA is devoted to reducing the probability of mid-air collision in all phases of flight. The TSAA application increases the flight crew traffic situation awareness providing alerts of traffic that are detected in conflict with ownship in support of the see-and-avoid responsibility. The relevant effort has been spent in the design process and the code generation in order to maximize the efficiency and performances in terms of computational load and memory consumption reduction. The TSAA architecture is divided into two high-level systems: the “Threats database” and the “Conflict detector”. The first one receives the traffic data from ADS-B device and provides the memorization of the target’s data history. Conflict detector module estimates ownship and targets trajectories in order to perform the detection of possible future loss of separation between ownship and each target. Finally, the alerts are verified by additional conflict verification logic, in order to prevent possible undesirable behaviors of the alert flag. In order to reduce the computational load, a pre-check evaluation module is used. This pre-check is only a computational optimization, so the performances of the conflict detector system are not modified in terms of number of alerts detected. The pre-check module uses analytical trajectories propagation for both target and ownship. This allows major accuracy and avoids the step-by-step propagation, which requests major computational load. Furthermore, the pre-check permits to exclude the target that is certainly not a threat, using an analytical and efficient geometrical approach, in order to decrease the computational load for the following modules. This software improvement is not suggested by FAA documents, and so it is the main innovation of this work. The efficiency and efficacy of this enhancement are verified using fast-time and real-time simulations and by the execution on a real device in several FAA scenarios. The final implementation also permits the FAA software certification in compliance with DO-178B standard. The computational load reduction allows the installation of TSAA application also on devices with multiple applications and/or low capacity in terms of available memory and computational capabilities

Keywords: traffic situation awareness, general aviation, aircraft conflict detection, computational load reduction, implementation solutions, software certification

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Authors: A. Arshad, M. Lehtonen. M. Humayun

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With the increasing Distributed Generation (DG) penetration, distribution systems are advancing towards the smart grid technology for least latency in tackling voltage control problem in a distributed manner. This paper proposes a Multi-agent based distributed voltage level control. In this method a flat architecture of agents is used and agents involved in the whole controlling procedure are On Load Tap Changer Agent (OLTCA), Static VAR Compensator Agent (SVCA), and the agents associated with DGs and loads at their locations. The objectives of the proposed voltage control model are to minimize network losses and DG curtailments while maintaining voltage value within statutory limits as close as possible to the nominal. The total loss cost is the sum of network losses cost, DG curtailment costs, and voltage damage cost (which is based on penalty function implementation). The total cost is iteratively calculated for various stricter limits by plotting voltage damage cost and losses cost against varying voltage limit band. The method provides the optimal limits closer to nominal value with minimum total loss cost. In order to achieve the objective of voltage control, the whole network is divided into multiple control regions; downstream from the controlling device. The OLTCA behaves as a supervisory agent and performs all the optimizations. At first, a token is generated by OLTCA on each time step and it transfers from node to node until the node with voltage violation is detected. Upon detection of such a node, the token grants permission to Load Agent (LA) for initiation of possible remedial actions. LA will contact the respective controlling devices dependent on the vicinity of the violated node. If the violated node does not lie in the vicinity of the controller or the controlling capabilities of all the downstream control devices are at their limits then OLTC is considered as a last resort. For a realistic study, simulations are performed for a typical Finnish residential medium-voltage distribution system using Matlab ®. These simulations are executed for two cases; simple Distributed Voltage Control (DVC) and DVC with optimized loss cost (DVC + Penalty Function). A sensitivity analysis is performed based on DG penetration. The results indicate that costs of losses and DG curtailments are directly proportional to the DG penetration, while in case 2 there is a significant reduction in total loss. For lower DG penetration, losses are reduced more or less 50%, while for higher DG penetration, loss reduction is not very significant. Another observation is that the newer stricter limits calculated by cost optimization moves towards the statutory limits of ±10% of the nominal with the increasing DG penetration as for 25, 45 and 65% limits calculated are ±5, ±6.25 and 8.75% respectively. Observed results conclude that the novel voltage control algorithm proposed in case 1 is able to deal with the voltage control problem instantly but with higher losses. In contrast, case 2 make sure to reduce the network losses through proposed iterative method of loss cost optimization by OLTCA, slowly with time.

Keywords: distributed voltage control, distribution system, multi-agent systems, smart grids

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Authors: João Coutinho-Rodrigues, Nuno Sousa, Luís Alçada-Almeida

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Transportation infrastructure systems are fundamental in modern society and economy. However, they need modernizing, maintaining, and reinforcing interventions which require large investments. In many countries, accumulated intervention delays arise from aging and intense use, being magnified by financial constraints of the past. The decision problem of managing the renewal of large backlogs is common to several types of important transportation infrastructures (e.g., railways, roads). This problem requires considering financial aspects as well as operational constraints under a multidimensional framework. The present research introduces a linear programming multiobjective model for managing railway infrastructure asset renewal. The model aims at minimizing three objectives: (i) yearly investment peak, by evenly spreading investment throughout multiple years; (ii) total cost, which includes extra maintenance costs incurred from renewal backlogs; (iii) priority delays related to work start postponements on the higher priority railway sections. Operational constraints ensure that passenger and freight services are not excessively delayed from having railway line sections under intervention. Achieving a balanced annual investment plan, without compromising the total financial effort or excessively postponing the execution of the priority works, was the motivation for pursuing the research which is now presented. The methodology, inspired by a real case study and tested with real data, reflects aspects of the practice of an infrastructure management company and is generalizable to different types of infrastructure (e.g., railways, highways). It was conceived for treating renewal interventions in infrastructure assets, which is a railway network may be rails, ballasts, sleepers, etc.; while a section is under intervention, trains must run at reduced speed, causing delays in services. The model cannot, therefore, allow for an accumulation of works on the same line, which may cause excessively large delays. Similarly, the lines do not all have the same socio-economic importance or service intensity, making it is necessary to prioritize the sections to be renewed. The model takes these issues into account, and its output is an optimized works schedule for the renewal project translatable in Gantt charts The infrastructure management company provided all the data for the first test case study and validated the parameterization. This case consists of several sections to be renewed, over 5 years and belonging to 17 lines. A large instance was also generated, reflecting a problem of a size similar to the USA railway network (considered the largest one in the world), so it is not expected that considerably larger problems appear in real life; an average of 25 years backlog and ten years of project horizon was considered. Despite the very large increase in the number of decision variables (200 times as large), the computational time cost did not increase very significantly. It is thus expectable that just about any real-life problem can be treated in a modern computer, regardless of size. The trade-off analysis shows that if the decision maker allows some increase in max yearly investment (i.e., degradation of objective ii), solutions improve considerably in the remaining two objectives.

Keywords: transport infrastructure, asset renewal, railway maintenance, multiobjective modeling

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Authors: Eszter Repasi, Akos Koller

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Our genetic information determines our look, physiology, sports performance and all our features. Maximizing the performances of athletes have adopted a science-based approach to the nutritional support. Nowadays genetics studies have blended with nutritional sciences, and a dynamically evolving, new research field have appeared. Nutritional genomics is needed to be used by nutritional experts. This is a recent field of nutritional science, which can provide a solution to reach the best sport performance using correlations between the athlete’s genome, nutritions, molecules, included human microbiome (links between food, microbiome and epigenetics), nutrigenomics and nutrigenetics. Nutritional genomics has a tremendous potential to change the future of dietary guidelines and personal recommendations. Experts need to use new technology to get information about the athletes, like nutritional genomics profile (included the determination of the oral and gut microbiome and DNA coded reaction for food components), which can modify the preparation term and sports performance. The influence of nutrients on the genes expression is called Nutrigenomics. The heterogeneous response of gene variants to nutrients, dietary components is called Nutrigenetics. The human microbiome plays a critical role in the state of health and well-being, and there are more links between food or nutrition and the human microbiome composition, which can develop diseases and epigenetic changes as well. A nutritional genomics-based profile of athletes can be the best technic for a dietitian to make a unique sports nutrition diet plan. Using functional food and the right food components can be effected on health state, thus sports performance. Scientists need to determine the best response, due to the effect of nutrients on health, through altering genome promote metabolites and result changes in physiology. Nutritional biochemistry explains why polymorphisms in genes for the absorption, circulation, or metabolism of essential nutrients (such as n-3 polyunsaturated fatty acids or epigallocatechin-3-gallate), would affect the efficacy of that nutrient. Controlled nutritional deficiencies and failures, prevented the change of health state or a newly discovered food intolerance are observed by a proper medical team, can support better sports performance. It is important that the dietetics profession informed on gene-diet interactions, that may be leading to optimal health, reduced risk of injury or disease. A special medical application for documentation and monitoring of data of health state and risk factors can uphold and warn the medical team for an early action and help to be able to do a proper health service in time. This model can set up a personalized nutrition advice from the status control, through the recovery, to the monitoring. But more studies are needed to understand the mechanisms and to be able to change the composition of the microbiome, environmental and genetic risk factors in cases of athletes.

Keywords: gene-diet interaction, multidisciplinary team, microbiome, diet plan

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Authors: Emine Umran Topcu

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In both urban design and architecture, the primary goal is considered to be looking for ways in which people feel and think about space and place. Humans, in general, see a place as security and space as freedom and feel attached to place and long for space. Contemporary urban design manifests itself by addressing basic physical and psychological human needs. Not much attention is paid to transcendence. There seems to be a gap in the hierarchy of human needs. Usually, social aspects of public space are addressed through urban design. More personal and intimately scaled needs of an individual are neglected. How does built form contribute to an individual’s growth, contemplation, and exploration? In other words, a greater meaning in the immediate environment. Architects love to talk about meaning, poetics, attachment and other ethereal aspects of space that are not visible attributes of places. This paper aims at describing spirituality through built form with a personal experience of Kamppi Chapel of Helsinki. Experience covers various modes through which a person unfolds or constructs reality. Perception, sensation, emotion, and thought can be counted as for these modes. To experience is to get to know. What can be known is a construct of experience. Feelings and thoughts about space and place are very complex in human beings. They grow out of life experiences. The author had the chance of visiting Kamppi Chapel in April 2017, out of which the experience grew. The Kamppi Chapel is located on the South side of the busy Narinnka Square in central Helsinki. It offers a place to quiet down and compose oneself in a most lively urban space. With its curved wooden facade, the small building looks more like a museum than a chapel. It can be called a museum for contemplation. With its gently shaped interior, it embraces visitors and shields them from the hustle bustle of the city outside. Places of worship in all faiths signify sacred power. The author, having origins in a part of the world where domes and minarets dominate the cityscape, was impressed by the size and the architectural visibility of the Chapel. Anyone born and trained in such a tradition shares the inherent values and psychological mechanisms of spirituality, sacredness and the modest realities of their environment. Spirituality in all cultural traditions has not been analyzed and reinterpreted in new conceptual frameworks. Fundamentalists may reject this positivist attitude, but Kamppi Chapel as it stands does not look like it has a say like “I’m a model to be followed”. It just faces the task of representing a religious facility in an urban setting largely shaped by modern urban planning, which seems to the author as looking for a new definition of individual status. The quest between the established and the new is the demand for modern efficiency versus dogmatic rigidity. The architecture here has played a very promising and rewarding role for spirituality. The designers have been the translators for human desire for better life and aesthetic environment for an optimal satisfaction of local citizens and the visitors alike.

Keywords: architecture, Kamppi Chapel, spirituality, urban

Procedia PDF Downloads 182

Authors: Vita Krungleviciute, Rasa Zelvyte, Ingrida Monkeviciene, Jone Kantautaite, Rolandas Stankevicius, Modestas Ruzauskas, Elena Bartkiene

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The environmental impact of agricultural bioproducts from the processing of food crops is an increasing concern worldwide. Currently, cereal bran has been used as a low-value ingredient for both human consumption and animal feed. The most popular bioprocessing technologies for cereal bran nutritional and technological functionality increasing are enzymatic processing and fermentation, and the most popular starters in fermented feed production are lactic acid bacteria (LAB) including pediococci. However, the ruminant digestive system is unique, there are billions of microorganisms which help the cow to digest and utilize nutrients in the feed. To achieve efficient feed utilization and high milk yield, the microorganisms must have optimal conditions, and the disbalance of this system is highly undesirable. Pediococcus strains Pediococcus acidilactici BaltBio01 and Pediococcus pentosaceus BaltBio02 from spontaneous fermented rye were isolated (by rep – PCR method), identified, and characterized by their growth (by Thermo Bioscreen C automatic turbidometer), acidification rate (2 hours in 2.5 pH), gas production (Durham method), and carbohydrate metabolism (by API 50 CH test ). Antimicrobial activities of isolated pediococcus against variety of pathogenic and opportunistic bacterial strains previously isolated from diseased cattle, and their resistance to antibiotics were evaluated (EFSA-FEEDAP method). The isolated pediococcus strains were cultivated in barley/wheat bran (90 / 10, m / m) substrate, and developed supplements, with high content of valuable pediococcus, were used for Lithuanian black and white dairy cows feeding. In addition, the influence of supplements on milk production and composition was determined. Milk composition was evaluated by the LactoScope FTIR” FT1.0. 2001 (Delta Instruments, Holland). P. acidilactici BaltBio01 and P. pentosaceus BaltBio02 demonstrated versatile carbohydrate metabolism, grown at 30°C and 37°C temperatures, and acidic tolerance. Isolated pediococcus strains showed to be non resistant to antibiotics, and having antimicrobial activity against undesirable microorganisms. By barley/wheat bran utilisation using fermentation with selected pediococcus strains, it is possible to produce safer (reduced Enterobacteriaceae, total aerobic bacteria, yeast and mold count) feed stock with high content of pediococcus. Significantly higher milk yield (after 33 days) by using pediococcus supplements mix for dairy cows feeding could be obtained, while similar effect by using separate strains after 66 days of feeding could be achieved. It can be stated that barley/wheat bran could be used for higher value feed production in order to increase milk production. Therefore, further research is needed to identify what is the main mechanism of the positive action.

Keywords: barley/wheat bran, dairy cattle, fermented feed, milk, pediococcus

Procedia PDF Downloads 307

Authors: V. Schmidt, L. Janovák, N. Wiegand, B. Patczai, K. Turzó

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Large bone defects are not able to heal spontaneously. Bioactive glasses seem to be appropriate (bio)materials for bone reconstruction. Bioactive glasses are osteoconductive and osteoinductive, therefore, play a useful role in bony regeneration and repair. Because of their not optimal mechanical properties (e.g., brittleness, low bending strength, and fracture toughness), their applications are limited. Bioactive glass can be used as a coating material applied on metal surfaces. In this way -when using them as implants- the excellent mechanical properties of metals and the biocompatibility and bioactivity of glasses will be utilized. Furthermore, ion release effects of bioactive glasses regarding osteogenic and angiogenic responses have been shown. Silicate bioactive glasses (45S5 Bioglass) induce the release and exchange of soluble Si, Ca, P, and Na ions on the material surface. This will lead to special cellular responses inducing bone formation, which is favorable in the biointegration of the orthopedic prosthesis. The incorporation of other additional elements in the silicate network such as fluorine, magnesium, iron, silver, potassium, or zinc has been shown, as the local delivery of these ions is able to enhance specific cell functions. Although hip and knee prostheses present a high success rate, bacterial infections -mainly implant associated- are serious and frequent complications. Infection can also develop after implantation of hip prostheses, the elimination of which means more surgeries for the patient and additional costs for the clinic. Prosthesis-related infection is a severe complication of orthopedic surgery, which often causes prolonged illness, pain, and functional loss. While international efforts are made to reduce the risk of these infections, orthopedic surgical infections (SSIs) continue to occur in high numbers. It is currently estimated that up to 2.5% of primary hip and knee surgeries and up to 20% of revision arthroplasties are complicated by periprosthetic joint infection (PJIs). According to some authors, these numbers are underestimated, and they are also increasing. Staphylococcus aureus is the leading cause of both SSIs and PJIs, and the prevalence of methicillin-resistant S. aureus (MRSA) is on the rise, particularly in the United States. These deep infections lead to implant removal and consequently increase morbidity and mortality. The study targets this clinical problem using our experience so far with the Ag-doped polymer coatings on Titanium implants. Non-modified or modified (e.g., doped with antibacterial agents, like Ag) bioactive glasses could play a role in the prevention of infections or the therapy of infected tissues. Bioactive glasses have excellent biocompatibility, proved by in vitro cell culture studies of human osteoblast-like MG-63 cells. Ag-doped bioactive glass-scaffold has a good antibacterial ability against Escherichia coli and other bacteria. It may be concluded that these scaffolds have great potential in the prevention and therapy of implant-associated bone infection.

Keywords: antibacterial agents, bioactive glass, hip and knee prosthesis, medical implants

Procedia PDF Downloads 193

Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

Procedia PDF Downloads 292

Authors: K. Ghosh, S. N. Tripathi, Manish Joshi, Y. S. Mayya, Arshad Khan, B. K. Sapra

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We have developed a CFD coupled aerosol microphysics model in the context of aerosol generation from a glowing wire. The governing equations can be solved implicitly for mass, momentum, energy transfer along with aerosol dynamics. The computationally efficient framework can simulate temporal behavior of total number concentration and number size distribution. This formulation uniquely couples standard K-Epsilon scheme with boundary layer model with detailed aerosol dynamics through residence time. This model uses measured temperatures (wire surface and axial/radial surroundings) and wire compositional data apart from other usual inputs for simulations. The model predictions show that bulk fluid motion and local heat distribution can significantly affect the aerosol behavior when the buoyancy effect in momentum transfer is considered. Buoyancy generated turbulence was found to be affecting parameters related to aerosol dynamics and transport as well. The model was validated by comparing simulated predictions with results obtained from six controlled experiments performed with a laboratory-made hot wire nanoparticle generator. Condensation particle counter (CPC) and scanning mobility particle sizer (SMPS) were used for measurement of total number concentration and number size distribution at the outlet of reactor cell during these experiments. Our model-predicted results were found to be in reasonable agreement with observed values. The developed model is fast (fully implicit) and numerically stable. It can be used specifically for applications in the context of the behavior of aerosol particles generated from glowing wire technique and in general for other similar large scale domains. Incorporation of CFD in aerosol microphysics framework provides a realistic platform to study natural convection driven systems/ applications. Aerosol dynamics sub-modules (nucleation, coagulation, wall deposition) have been coupled with Navier Stokes equations modified to include buoyancy coupled K-Epsilon turbulence model. Coupled flow-aerosol dynamics equation was solved numerically and in the implicit scheme. Wire composition and temperature (wire surface and cell domain) were obtained/measured, to be used as input for the model simulations. Model simulations showed a significant effect of fluid properties on the dynamics of aerosol particles. The role of buoyancy was highlighted by observation and interpretation of nucleation zones in the planes above the wire axis. The model was validated against measured temporal evolution, total number concentration and size distribution at the outlet of hot wire generator cell. Experimentally averaged and simulated total number concentrations were found to match closely, barring values at initial times. Steady-state number size distribution matched very well for sub 10 nm particle diameters while reasonable differences were noticed for higher size ranges. Although tuned specifically for the present context (i.e., aerosol generation from hotwire generator), the model can also be used for diverse applications, e.g., emission of particles from hot zones (chimneys, exhaust), fires and atmospheric cloud dynamics.

Keywords: nanoparticles, k-epsilon model, buoyancy, CFD, hot wire generator, aerosol dynamics

Procedia PDF Downloads 142

Authors: Ben Morrow, Patrick O'Hara, Natalie Ban, Tunai Marques, Molly Fraser, Christopher Bone

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Relative to commercial fisheries, recreational fisheries are often poorly understood and pose various challenges for monitoring frameworks. In British Columbia (BC), Canada, Pacific salmon are heavily targeted by recreational fishers while also being a key source of nutrient flow and crucial prey for a variety of marine and terrestrial fauna, including endangered Southern Resident killer whales (Orcinus orca). Although commercial fisheries were historically responsible for the majority of salmon retention, recreational fishing now comprises both greater effort and retention. The current monitoring scheme for recreational salmon fisheries involves aerial-roving creel surveys. However, this method has been identified as costly and having low predictive power as it is often limited to sampling fragments of fluid and temporally dynamic fisheries. This study used imagery from two shore-based autonomous cameras in a highly active recreational fishery around Sooke, BC, and evaluated their efficacy in supplementing existing aerial-roving surveys for monitoring a recreational salmon fishery. This study involved continuous monitoring and high temporal resolution (over one million images analyzed in a single fishing season), using a deep learning-based vessel detection algorithm and a custom image annotation tool to efficiently thin datasets. This allowed for the quantification of peak-season effort from a busy harbour, species-specific retention estimates, high levels of detected fishing events at a nearby popular fishing location, as well as the proportion of the fishery management area represented by cameras. Then, this study demonstrated how it could substantially enhance the temporal resolution of a fishery through diel activity pattern analyses, scaled monthly to visualize clusters of activity. This work also highlighted considerable off-season fishing detection, currently unaccounted for in the existing monitoring framework. These results demonstrate several distinct applications of autonomous cameras for providing enhanced detail currently unavailable in the current monitoring framework, each of which has important considerations for the managerial allocation of resources. Further, the approach and methodology can benefit other studies that apply shore-based camera monitoring, supplement aerial-roving creel surveys to improve fine-scale temporal understanding, inform the optimal timing of creel surveys, and improve the predictive power of recreational stock assessments to preserve important and endangered fish species.

Keywords: cameras, monitoring, recreational fishing, stock assessment

Procedia PDF Downloads 122

Authors: Marina Passero, Tianhua Zhai, Zuyi (Jacky) Huang

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Alzheimer’s disease has become a major public health issue, as indicated by the increasing populations of Americans living with Alzheimer’s disease. After decades of extensive research in Alzheimer’s disease, only seven drugs have been approved by Food and Drug Administration (FDA) to treat Alzheimer’s disease. Five of these drugs were designed to treat the dementia symptoms, and only two drugs (i.e., Aducanumab and Lecanemab) target the progression of Alzheimer’s disease, especially the accumulation of amyloid-b plaques. However, controversial comments were raised for the accelerated approvals of either Aducanumab or Lecanemab, especially with concerns on safety and side effects of these two drugs. There is still an urgent need for further drug discovery to target the biological processes involved in the progression of Alzheimer’s disease. Excessive cholesterol has been found to accumulate in the brain of those with Alzheimer’s disease. Cholesterol can be synthesized in both the blood and the brain, but the majority of biosynthesis in the adult brain takes place in astrocytes and is then transported to the neurons via ApoE. The blood brain barrier separates cholesterol metabolism in the brain from the rest of the body. Various proteins contribute to the metabolism of cholesterol in the brain, which offer potential targets for Alzheimer’s treatment. In the astrocytes, SREBP cleavage-activating protein (SCAP) binds to Sterol Regulatory Element-binding Protein 2 (SREBP2) in order to transport the complex from the endoplasmic reticulum to the Golgi apparatus. Cholesterol is secreted out of the astrocytes by ATP-Binding Cassette A1 (ABCA1) transporter. Lipoprotein receptors such as triggering receptor expressed on myeloid cells 2 (TREM2) internalize cholesterol into the microglia, while lipoprotein receptors such as Low-density lipoprotein receptor-related protein 1 (LRP1) internalize cholesterol into the neuron. Cytochrome P450 Family 46 Subfamily A Member 1 (CYP46A1) converts excess cholesterol to 24S-hydroxycholesterol (24S-OHC). Cholesterol has been approved for its direct effect on the production of amyloid-beta and tau proteins. The addition of cholesterol to the brain promotes the activity of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), secretase, and amyloid precursor protein (APP), which all aid in amyloid-beta production. The reduction of cholesterol esters in the brain have been found to reduce phosphorylated tau levels in mice. In this work, a computational pipeline was developed to identify the protein targets involved in cholesterol regulation in brain and further to identify chemical compounds as the inhibitors of a selected protein target. Since extensive evidence shows the strong correlation between brain cholesterol regulation and Alzheimer’s disease, a detailed literature review on genes or pathways related to the brain cholesterol synthesis and regulation was first conducted in this work. An interaction network was then built for those genes so that the top gene targets were identified. The involvement of these genes in Alzheimer’s disease progression was discussed, which was followed by the investigation of existing clinical trials for those targets. A ligand-protein docking program was finally developed to screen 1.5 million chemical compounds for the selected protein target. A machine learning program was developed to evaluate and predict the binding interaction between chemical compounds and the protein target. The results from this work pave the way for further drug discovery to regulate brain cholesterol to combat Alzheimer’s disease.

Keywords: Alzheimer’s disease, drug discovery, ligand-protein docking, gene-network analysis, cholesterol regulation

Procedia PDF Downloads 74

Authors: Kelly Jaunzems

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Social media is a powerful instrument of communication, enabling the presentation of information in multiple forms and modes, amplifying the interactions between people, organisations, and stakeholders, and increasing the range of communication channels available. Younger generations are highly engaged with social media and more likely to use this channel than any other to seek information. Given this, it may appear extraordinary that occupational safety and health professionals have yet to seriously engage with social media for communicating safety messages to younger audiences who, in many industries, might be statistically more likely to encounter more workplace harm or injury. Millennials, defined as those born between 1981-2000, have distinctive characteristics that also impact their interaction patterns rendering many traditional occupational safety and health communication channels sub-optimal or near obsolete. Used to immediate responses, 280-character communication, shares, likes, and visual imagery, millennials struggle to take seriously the low-tech, top-down communication channels such as safety noticeboards, toolbox meetings, and passive tick-box online inductions favoured by traditional OSH professionals. This paper draws upon well-established communication findings, which argue that it is important to know a target audience and reach them using their preferred communication pathways, particularly if the aim is to impact attitudes and behaviours. Health practitioners have adopted social media as a communication channel with great success, yet safety practitioners have failed to follow this lead. Using a digital ethnography approach, this paper examines seven organisations’ Facebook posts from two one-month periods one year apart, one in 2018 and one in 2019. Each of the years informs organisation-based case studies. Comparing, contrasting, and drawing upon these case studies, the paper discusses and evaluates the (non) use of social media communication of safety information in terms of user engagement, shareability, and overall appeal. The success of health practitioners’ use of social media provides a compelling template for the implementation of social media into organisations’ safety communication strategies. Highly visible content such as that found on social media allows an organization to become more responsive and engage in two-way conversations with their audience, creating more engaged and participatory conversations around safety. Further, using social media to address younger audiences with a range of tonal qualities (for example, the use of humour) can achieve cut through in a way that grim statistics fail to do. On the basis of 18 months of interviews, filed work, and data analysis, the paper concludes with recommendations for communicating safety information via social media. It proposes exploration of the social media communication formula that, when utilised by safety practitioners, may create an effective social media presence. It is anticipated that such social media use will increase engagement, expand the number of followers and reduce the likelihood and severity of safety-related incidents. The tools offered may provide a path for safety practitioners to reach a disengaged generation of workers to build a cohesive and inclusive conversation around ways to keep people safe at work.

Keywords: social media, workplace safety, communication strategies, young workers

Procedia PDF Downloads 115

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

Procedia PDF Downloads 87

Authors: Jovina Concepcion Bachynski, Lenora Duhn, Idevania G. Costa, Pilar Camargo-Plazas

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Kidney failure is a life-limiting condition for which treatment, such as dialysis (hemodialysis and peritoneal dialysis), can exact a tremendously high physical and psychosocial symptom burden. Kidney failure can be severe enough to require a palliative approach to care. The term supportive care can be used in lieu of palliative care to avoid the misunderstanding that palliative care is synonymous with end-of-life or hospice care. Kidney supportive care, encompassing advance care planning, is an approach to care that improves the quality of life for people receiving dialysis through early identification and treatment of symptoms throughout the disease trajectory. Advanced care planning involves ongoing conversations about the values, goals, and preferences for future care between individuals and their healthcare teams. Kidney supportive care is underutilized and often initiated late in this population. There is evidence to indicate nurses are not providing the necessary elements of supportive kidney care. Dialysis nurses’ delay or lack of engagement in supportive care until close to the end of life may result in people dying without receiving optimal palliative care services. Using Charmaz’s constructivist grounded theory, the purpose of this doctoral study is to develop a substantive theory that explains the process of engagement in supportive care by nurses working in dialysis settings in Canada. Through initial purposeful and subsequent theoretical sampling, 23 nurses with current or recent work experience in outpatient hemodialysis, home hemodialysis, and peritoneal dialysis settings drawn from across Canada were recruited to participate in two intensive interviews using the Zoom© teleconferencing platform. Concurrent data collection and data analysis, constant comparative analysis of initial and focused codes until the attainment of theoretical saturation, and memo-writing, as well as researcher reflexivity, have been undertaken to aid the emergence of concepts, categories, and, ultimately, the constructed theory. At the time of abstract submission, data analysis is currently at the second level of coding (i.e., focused coding stage) of the research study. Preliminary categories include: (a) focusing on biomedical care; (b) multi-dimensional challenges to having the conversation; (c) connecting and setting boundaries with patients; (d) difficulty articulating kidney-supportive care; and (e) unwittingly practising kidney-supportive care. For the conference, the resulting theory will be presented. Nurses working in dialysis are well-positioned to ensure the delivery of quality kidney-supportive care. This study will help to determine the process and the factors enabling and impeding nurse engagement in supportive care in dialysis to effect change for normalizing advance care planning conversations in the clinical setting. This improved practice will have substantive beneficial implications for the many individuals living with kidney failure and their supporting loved ones.

Keywords: dialysis, kidney failure, nursing, supportive care

Procedia PDF Downloads 102

Authors: Leslie Raphael de M. Ferraz, Salvana Priscylla M. Costa, Tarcyla de A. Gomes, Giovanna Christinne R. M. Schver, Cristóvão R. da Silva, Magaly Andreza M. de Lyra, Danilo Augusto F. Fontes, Larissa A. Rolim, Amanda Carla Q. M. Vieira, Miracy M. de Albuquerque, Pedro J. Rolim-Neto

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Efavirenz (EFV) is a drug used as first-line treatment of AIDS. However, it has poor aqueous solubility and wettability, presenting problems in the gastrointestinal tract absorption and bioavailability. One of the most promising strategies to improve the solubility is the use of solid dispersions (SD). Therefore, this study aimed to characterize SD EFZ with the polymers: PVP-K30, PVPVA 64 and SOLUPLUS in order to find an optimal formulation to compose a future pharmaceutical product for AIDS therapy. Initially, Physical Mixtures (PM) and SD with the polymers were obtained containing 10, 20, 50 and 80% of drug (w/w) by the solvent method. The best formulation obtained between the SD was selected by in vitro dissolution test. Finally, the drug-carrier system chosen, in all ratios obtained, were analyzed by the following techniques: Differential Scanning Calorimetry (DSC), polarization microscopy, Scanning Electron Microscopy (SEM) and spectrophotometry of absorption in the region of infrared (IR). From the dissolution profiles of EFV, PM and SD, the values of area Under The Curve (AUC) were calculated. The data showed that the AUC of all PM is greater than the isolated EFV, this result is derived from the hydrophilic properties of the polymers thus favoring a decrease in surface tension between the drug and the dissolution medium. In adittion, this ensures an increasing of wettability of the drug. In parallel, it was found that SD whom had higher AUC values, were those who have the greatest amount of polymer (with only 10% drug). As the amount of drug increases, it was noticed that these results either decrease or are statistically similar. The AUC values of the SD using the three different polymers, followed this decreasing order: SD PVPVA 64-EFV 10% > SD PVP-K30-EFV 10% > SD Soluplus®-EFV 10%. The DSC curves of SD’s did not show the characteristic endothermic event of drug melt process, suggesting that the EFV was converted to its amorphous state. The analysis of polarized light microscopy showed significant birefringence of the PM’s, but this was not observed in films of SD’s, thus suggesting the conversion of the drug from the crystalline to the amorphous state. In electron micrographs of all PM, independently of the percentage of the drug, the crystal structure of EFV was clearly detectable. Moreover, electron micrographs of the SD with the two polymers in different ratios investigated, we observed the presence of particles with irregular size and morphology, also occurring an extensive change in the appearance of the polymer, not being possible to differentiate the two components. IR spectra of PM corresponds to the overlapping of polymer and EFV bands indicating thereby that there is no interaction between them, unlike the spectra of all SD that showed complete disappearance of the band related to the axial deformation of the NH group of EFV. Therefore, this study was able to obtain a suitable formulation to overcome the solubility limitations of the EFV, since SD PVPVA 64-EFZ 10% was chosen as the best system in delay crystallization of the prototype, reaching higher levels of super saturation.

Keywords: characterization, dissolution, Efavirenz, solid dispersions

Procedia PDF Downloads 631

Authors: F. Infante, W. Kaal, S. Perfetto, S. Herold

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In the last decade the demand of wireless sensors and low-power electric devices for condition monitoring in mechanical structures has been strongly increased. Networks of wireless sensors can potentially be applied in a huge variety of applications. Due to the reduction of both size and power consumption of the electric components and the increasing complexity of mechanical systems, the interest of creating dense nodes sensor networks has become very salient. Nevertheless, with the development of large sensor networks with numerous nodes, the critical problem of powering them is drawing more and more attention. Batteries are not a valid alternative for consideration regarding lifetime, size and effort in replacing them. Between possible alternative solutions for durable power sources useable in mechanical components, vibrations represent a suitable source for the amount of power required to feed a wireless sensor network. For this purpose, energy harvesting from structural vibrations has received much attention in the past few years. Suitable vibrations can be found in numerous mechanical environments including automotive moving structures, household applications, but also civil engineering structures like buildings and bridges. Similarly, a dynamic vibration absorber (DVA) is one of the most used devices to mitigate unwanted vibration of structures. This device is used to transfer the primary structural vibration to the auxiliary system. Thus, the related energy is effectively localized in the secondary less sensitive structure. Then, the additional benefit of harvesting part of the energy can be obtained by implementing dedicated components. This paper describes the design process of an energy harvesting tuned vibration absorber (EHTVA) for rotating systems using piezoelectric elements. The energy of the vibration is converted into electricity rather than dissipated. The device proposed is indeed designed to mitigate torsional vibrations as with a conventional rotational TVA, while harvesting energy as a power source for immediate use or storage. The resultant rotational multi degree of freedom (MDOF) system is initially reduced in an equivalent single degree of freedom (SDOF) system. The Den Hartog’s theory is used for evaluating the optimal mechanical parameters of the initial DVA for the SDOF systems defined. The performance of the TVA is operationally assessed and the vibration reduction at the original resonance frequency is measured. Then, the design is modified for the integration of active piezoelectric patches without detuning the TVA. In order to estimate the real power generated, a complex storage circuit is implemented. A DC-DC step-down converter is connected to the device through a rectifier to return a fixed output voltage. Introducing a big capacitor, the energy stored is measured at different frequencies. Finally, the electromechanical prototype is tested and validated achieving simultaneously reduction and harvesting functions.

Keywords: energy harvesting, piezoelectricity, torsional vibration, vibration absorber

Procedia PDF Downloads 147

Authors: Jolanta Jonak, Sylvia Tolczyk

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Educational systems are tasked with preparing students for future success in academic or work environments. Schools strive to achieve this goal, but often it is challenging as conventional teaching approaches are often ineffective in increasingly diverse educational systems. In today’s ever-increasing global society, educational systems become increasingly diverse in terms of cultural and linguistic differences, learning preferences and styles, ability and disability. Through increased understanding of disabilities and improved identification processes, students having some form of disabilities tend to be identified earlier than in the past, meaning that more students with identified disabilities are being supported in our classrooms. Also, a large majority of students with disabilities are educated in general education environments. Due to cognitive makeup and life experiences, students have varying learning styles and preferences impacting how they receive and express what they are learning. Many students come from bi or multilingual households and with varying proficiencies in the English language, further impacting their learning. All these factors need to be seriously considered when developing learning opportunities for student's. Educators try to adjust their teaching practices as they discover that conventional methods are often ineffective in reaching each student’s potential. Many teachers do not have the necessary educational background or training to know how to teach students whose learning needs are more unique and may vary from the norm. This is further complicated by the fact that many classrooms lack consistent access to interventionists/coaches that are adequately trained in evidence-based approaches to meet the needs of all students, regardless of what their academic needs may be. One evidence-based way for providing successful education for all students is by incorporating cognitive approaches and strategies that tap into affective, recognition, and strategic networks in the student's brain. This can be done through Differentiated Instruction (DI). Differentiated Instruction is increasingly recognized model that is established on the basic principles of Universal Design for Learning. This form of support ensures that regardless of the students’ learning preferences and cognitive learning profiles, they have opportunities to learn through approaches that are suitable to their needs. This approach improves the educational outcomes of students with special needs and it benefits other students as it accommodates learning styles as well as the scope of unique learning needs that are evident in the typical classroom setting. Differentiated Instruction also is recognized as an evidence-based best practice in education and is highly effective when it is implemented within the tiered system of the Response to Intervention (RTI) model. Recognition of DI becomes more common; however, there is still limited understanding of the effective implementation and use of strategies that can create unique learning environments for each student within the same setting. Through employing knowledge of a variety of instructional strategies, general and special education teachers can facilitate optimal learning for all students, with and without a disability. A desired byproduct of DI is that it can eliminate inaccurate perceptions about the students’ learning abilities, unnecessary referrals for special education evaluations, and inaccurate decisions about the presence of a disability.

Keywords: differentiated instruction, universal design for learning, special education, diversity

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Authors: Farhan A. Alenizi

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Digital watermarking has evolved in the past years as an important means for data authentication and ownership protection. The images and video watermarking was well known in the field of multimedia processing; however, 3D objects' watermarking techniques have emerged as an important means for the same purposes, as 3D mesh models are in increasing use in different areas of scientific, industrial, and medical applications. Like the image watermarking techniques, 3D watermarking can take place in either space or transform domains. Unlike images and video watermarking, where the frames have regular structures in both space and temporal domains, 3D objects are represented in different ways as meshes that are basically irregular samplings of surfaces; moreover, meshes can undergo a large variety of alterations which may be hard to tackle. This makes the watermarking process more challenging. While the transform domain watermarking is preferable in images and videos, they are still difficult to implement in 3d meshes due to the huge number of vertices involved and the complicated topology and geometry, and hence the difficulty to perform the spectral decomposition, even though significant work was done in the field. Spatial domain watermarking has attracted significant attention in the past years; they can either act on the topology or on the geometry of the model. Exploiting the statistical characteristics in the 3D mesh models from both geometrical and topological aspects was useful in hiding data. However, doing that with minimal surface distortions to the mesh attracted significant research in the field. A 3D mesh blind watermarking technique is proposed in this research. The watermarking method depends on modifying the vertices' positions with respect to the center of the object. An optimal method will be developed to reduce the errors, minimizing the distortions that the 3d object may experience due to the watermarking process, and reducing the computational complexity due to the iterations and other factors. The technique relies on the displacement process of the vertices' locations depending on the modification of the variances of the vertices’ norms. Statistical analyses were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduced in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. To evaluate the algorithm's robustness against other common geometry and connectivity attacks, the watermarked objects were subjected to uniform noise, Laplacian smoothing, vertices quantization, simplification, and cropping. Experimental results showed that the approach is robust in terms of both perceptual and quantitative qualities. It was also robust against both geometry and connectivity attacks. Moreover, the probability of true positive detection versus the probability of false-positive detection was evaluated. To validate the accuracy of the test cases, the receiver operating characteristics (ROC) curves were drawn, and they’ve shown robustness from this aspect. 3D watermarking is still a new field but still a promising one.

Keywords: watermarking, mesh objects, local roughness, Laplacian Smoothing

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Authors: Pedram Saadati, Zahra Nazari

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Anticipating and identifying future opportunities and challenges facing industry activists for the emergence and entry of new knowledge and technologies of personal financial planning, and providing practical solutions is one of the goals of this research. For this purpose, a future research tool based on receiving opinions from the main players of the insurance industry has been used. The research method in this study was in 4 stages; including 1- a survey of the specialist salesforce of life insurance in order to identify the variables 2- the ranking of the variables by experts selected by a researcher-made questionnaire 3- holding a panel of experts with the aim of understanding the mutual effects of the variables and 4- statistical analyzes of the mutual effects matrix in Mick Mac software is done. The integrated analysis of influencing variables in the future has been done with the method of Structural Analysis, which is one of the efficient and innovative methods of future research. A list of opportunities and challenges was identified through a survey of best-selling life insurance representatives who were selected by snowball sampling. In order to prioritize and identify the most important issues, all the issues raised were sent to selected experts who were selected theoretically through a researcher-made questionnaire. The respondents determined the importance of 36 variables through scoring, so that the prioritization of opportunity and challenge variables can be determined. 8 of the variables identified in the first stage were removed by selected experts, and finally, the number of variables that could be examined in the third stage became 28 variables, which, in order to facilitate the examination, were divided into 6 categories, respectively, 11 variables of organization and management. Marketing and sales 7 cases, social and cultural 6 cases, technological 2 cases, rebranding 1 case and insurance 1 case were divided. The reliability of the researcher-made questionnaire was confirmed with the Cronbach's alpha test value of 0.96. In the third stage, by forming a panel consisting of 5 insurance industry experts, the consensus of their opinions about the influence of factors on each other and the ranking of variables was entered into the matrix. The matrix included the interrelationships of 28 variables, which were investigated using the structural analysis method. By analyzing the data obtained from the matrix by Mic Mac software, the findings of the research indicate that the categories of "correct training in the use of the software, the weakness of the technology of insurance companies in personalizing products, using the approach of equipping the customer, and honesty in declaring no need Customer to Insurance", the most important challenges of the influencer and the categories of "salesforce equipping approach, product personalization based on customer needs assessment, customer's pleasant experience of being consulted with consulting robots, business improvement of the insurance company due to the use of these tools, increasing the efficiency of the issuance process and optimal customer purchase" were identified as the most important opportunities for influence.

Keywords: personal financial planning, wealth management, advisor robots, life insurance, digital transformation

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Authors: B. M. Vishal, Monamie Basu, Gopinath M., Rose Havilah Pulla

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Though there are several methods of synthesizing silver nano particles, Green synthesis always has its own dignity. Ranging from the cost-effectiveness to the ease of synthesis, the process is simplified in the best possible way and is one of the most explored topics. This study of extracting secondary metabolites from Perilla frutescens and using them for therapeutic additives has its own significance. Unlike the other researches that have been done so far, this study aims to synthesize Silver nano particles from Perilla frutescens using three available forms of the plant: leaves, seed, and commercial leaf extract powder. Perilla frutescens, commonly known as 'Beefsteak Plant', is a perennial plant and belongs to the mint family. The plant has two varieties classed within itself. They are frutescens crispa and frutescens frutescens. The species, frutescens crispa (commonly known as 'Shisho' in Japanese), is generally used for edible purposes. Its leaves occur in two forms, varying on the colors. It is found in two different colors of red with purple streaks and green with crinkly pattern on it. This species is aromatic due to the presence of two major compounds: polyphenols and perillaldehyde. The red (purple streak) variety of this plant is due to the presence of a pigment, Perilla anthocyanin. The species, frutescens frutescens (commonly known as 'Egoma' in Japanese), is the main source for perilla oil. This species is also aromatic, but in this case, the major compound which gives the aroma is Perilla ketone or egoma ketone. Shisho grows short as compared with Wild Sesame and both produce seeds. The seeds of Wild Sesame are large and soft whereas that of Shisho is small and hard. The seeds have a large proportion of lipids, ranging about 38-45 percent. Excluding those, the seeds have a large quantity of Omega-3 fatty acids, linoleic acid, and an Omega-6 fatty acid. Other than these, Perilla leaf extract has gold and silver nano particles in it. The yield comparison in all the cases have been done, and the process’ optimal conditions were modified, keeping in mind the efficiencies. The characterization of secondary metabolites includes GC-MS and FTIR which can be used to identify the components of purpose that actually helps in synthesizing silver nano particles. The analysis of silver was done through a series of characterization tests that include XRD, UV-Vis, EDAX, and SEM. After the synthesis, for being used as therapeutic additives, the toxin analysis was done, and the results were tabulated. The synthesis of silver nano particles was done in a series of multiple cycles of extraction from leaves, seeds and commercially purchased leaf extract. The yield and efficiency comparison were done to bring out the best and the cheapest possible way of synthesizing silver nano particles using Perilla frutescens. The synthesized nano particles can be used in therapeutic drugs, which has a wide range of application from burn treatment to cancer treatment. This will, in turn, replace the traditional processes of synthesizing nano particles, as this method will prove effective in terms of cost and the environmental implications.

Keywords: nanoparticles, green synthesis, Perilla frutescens, characterisation, toxin analysis

Procedia PDF Downloads 233

Authors: Pengzhou Lu, Liming Xin, Payam Tavakoli, Zhonghua Lin, Roberto V. P. Ribeiro, Mitesh V. Badiwala

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Ex vivo Heart Perfusion (EVHP) has been developed as an alternative strategy to expand cardiac donation by enabling resuscitation and functional assessment of hearts donated from marginal donors, which were previously not accepted. EVHP parameters, such as perfusion flow (PF) and perfusion pressure (PP) are crucial for optimal organ preservation. However, with the heart’s constant physiological changes during EVHP, such as coronary vascular resistance, manual control of these parameters is rendered imprecise and cumbersome for the operator. Additionally, low control precision and the long adjusting time may lead to irreversible damage to the myocardial tissue. To solve this problem, an automatic heart perfusion system was developed by applying a Human-Machine Interface (HMI) and a Programmable-Logic-Controller (PLC)-based circuit to control PF and PP. The PLC-based control system collects the data of PF and PP through flow probes and pressure transducers. It has two control modes: the RPM-flow mode and the pressure mode. The RPM-flow control mode is an open-loop system. It influences PF through providing and maintaining the desired speed inputted through the HMI to the centrifugal pump with a maximum error of 20 rpm. The pressure control mode is a closed-loop system where the operator selects a target Mean Arterial Pressure (MAP) to control PP. The inputs of the pressure control mode are the target MAP, received through the HMI, and the real MAP, received from the pressure transducer. A PID algorithm is applied to maintain the real MAP at the target value with a maximum error of 1mmHg. The precision and control speed of the RPM-flow control mode were examined by comparing the PLC-based system to an experienced operator (EO) across seven RPM adjustment ranges (500, 1000, 2000 and random RPM changes; 8 trials per range) tested in a random order. System’s PID algorithm performance in pressure control was assessed during 10 EVHP experiments using porcine hearts. Precision was examined through monitoring the steady-state pressure error throughout perfusion period, and stabilizing speed was tested by performing two MAP adjustment changes (4 trials per change) of 15 and 20mmHg. A total of 56 trials were performed to validate the RPM-flow control mode. Overall, the PLC-based system demonstrated the significantly faster speed than the EO in all trials (PLC 1.21±0.03, EO 3.69±0.23 seconds; p < 0.001) and greater precision to reach the desired RPM (PLC 10±0.7, EO 33±2.7 mean RPM error; p < 0.001). Regarding pressure control, the PLC-based system has the median precision of ±1mmHg error and the median stabilizing times in changing 15 and 20mmHg of MAP are 15 and 19.5 seconds respectively. The novel PLC-based control system was 3 times faster with 60% less error than the EO for RPM-flow control. In pressure control mode, it demonstrates a high precision and fast stabilizing speed. In summary, this novel system successfully controlled perfusion flow and pressure with high precision, stability and a fast response time through a user-friendly interface. This design may provide a viable technique for future development of novel heart preservation and assessment strategies during EVHP.

Keywords: automatic control system, biomedical engineering, ex-vivo heart perfusion, human-machine interface, programmable logic controller

Procedia PDF Downloads 175

Authors: Tristance Kee

Abstract:

With the unprecedented increase in elderly population globally, it is critical to search for new sustainable housing and urban development alternatives to traditional housing options. This research examines concepts of elderly migration pattern in the context of a high density city in Hong Kong to Mainland China. The research objectives are to: 1) explore the relationships between soon-to-be-old elderly and their intentions to move to Mainland upon retirement and their demographic characteristics; and 2) What are the desired amenities, locational factors and activities that are expected in the soon-to-be-old generation’s retirement housing environment? Primary data was collected through questionnaire survey conducted using random sampling method with respondents aged between 45-64 years old. The face-to-face survey was completed by 500 respondents. The survey was divided into four sections. The first section focused on respondent’s demographic information such as gender, age, education attainment, monthly income, housing tenure type and their visits to Mainland China. The second section focused on their retirement plans in terms of intended retirement age, prospective retirement funding and retirement housing options. The third section focused on the respondent’s attitudes toward retiring in Mainland for housing. It asked about their intentions to migrate retire into Mainland and incentives to retire in Hong Kong. The fourth section focused on respondent’s ideal housing environment including preferred housing amenities, desired living environment and retirement activities. The dependent variable in this study was ‘respondent’s consideration to move to Mainland China upon retirement’. Eight primary independent variables were integrated into the study to identify the correlations between them and retirement migration plan. The independent variables include: gender, age, marital status, monthly income, present housing tenure type, property ownership in Hong Kong, relationship with Mainland and the frequency of visiting Mainland China. In addition to the above independent variables, respondents were asked to indicate their retirement plans (retirement age, funding sources and retirement housing options), incentives to migrate to retire (choices included: property ownership, family relations, cost of living, living environment, medical facilities, government welfare benefits, etc.), perceived ideal retirement life qualities including desired amenities (sports, medical and leisure facilities etc.), desired locational qualities (green open space, convenient transport options and accessibility to urban settings etc.) and desired retirement activities (home-based leisure, elderly friendly sports, cultural activities, child care, social activities, etc.). The finding shows correlations between the used independent variables and consideration to migrate for housing options. The two independent variables indicated a possible correlation were gender and the frequency of visiting Mainland at present. When considering the increasing property prices across the border and strong social relationships, potential retirement migration is a very subjective decision that could vary from person to person. This research adds knowledge to housing research and migration study. Although the research is based in Mainland, most of the characteristics identified including better medical services, government welfare and sound urban amenities are shared qualities for all sustainable urban development and housing strategies.

Keywords: elderly migration, housing alternative, soon-to-be-old, sustainable environment

Procedia PDF Downloads 211