Search results for: business model environment

Authors: Shelley Y. Hawkins

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Introduction/Background: As technology has grown exponentially in healthcare, nurse educators must prepare Advanced Practice Registered Nurse (APRN) graduates with the knowledge and skills in information systems/technology to support and improve patient care and health care systems. APRN’s are expected to lead in caring for populations who lack accessibility and availability through the use of technology, specifically telehealth. The capacity to effectively and efficiently use technology in patient care delivery is clearly delineated in the American Association of Colleges of Nursing (AACN) Doctor of Nursing Practice (DNP) and Master of Science in Nursing (MSN) Essentials. However, APRN’s have minimal, or no, exposure to formalized telehealth education and lack necessary technical skills needed to incorporate telehealth into their patient care. APRN’s must successfully master the technology using telehealth/telemedicine, electronic health records, health information technology, and clinical decision support systems to advance health. Furthermore, APRN’s must be prepared to lead the coordination and collaboration with other healthcare providers in their use and application. Aim/Goal/Purpose: The purpose of this presentation is to establish and operationalize telehealth-focused educational partnerships between one University School of Nursing and two health care systems in order to enhance the preparation of APRN NP students for practice, teaching, and/or scholarly endeavors. Methods: The proposed project was initially presented by the project director to selected multidisciplinary stakeholders including leadership, home telehealth personnel, primary care providers, and decision support systems within two major health care systems to garner their support for acceptance and implementation. Concurrently, backing was obtained from key university-affiliated colleagues including the Director of Simulation and Innovative Learning Lab and Coordinator of the Health Care Informatics Program. Technology experts skilled in design and production in web applications and electronic modules were secured from two local based technology companies. Results: Two telehealth-focused APRN Program academic/practice partnerships have been established. Students have opportunities to engage in clinically based telehealth experiences focused on: (1) providing patient care while incorporating various technology with a specific emphasis on telehealth; (2) conducting research and/or evidence-based practice projects in order to further develop the scientific foundation regarding incorporation of telehealth with patient care; and (3) participating in the production of patient-level educational materials related to specific topical areas. Conclusions: Evidence-based APRN student telehealth clinical experiences will assist in preparing graduates who can effectively incorporate telehealth into their clinical practice. Greater access for diverse populations will be available as a result of the telehealth service model as well as better care and better outcomes at lower costs. Furthermore, APRN’s will provide the necessary leadership and coordination through interprofessional practice by transforming health care through new innovative care models using information systems and technology.

Keywords: academic/practice partnerships, advanced practice nursing, nursing education, telehealth

Procedia PDF Downloads 218

Authors: Jiri Cecrdle

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This paper describes the concept of the W-WING whirl flutter aeroelastic demonstrator. Whirl flutter is the specific case of flutter that accounts for the additional dynamic and aerodynamic influences of the engine rotating parts. The instability is driven by motion-induced unsteady aerodynamic propeller forces and moments acting in the propeller plane. Whirl flutter instability is a serious problem that may cause the unstable vibration of a propeller mounting, leading to the failure of an engine installation or an entire wing. The complicated physical principle of whirl flutter required the experimental validation of the analytically gained results. W-WING aeroelastic demonstrator has been designed and developed at Czech Aerospace Research Centre (VZLU) Prague, Czechia. The demonstrator represents the wing and engine of the twin turboprop commuter aircraft. Contrary to the most of past demonstrators, it includes a powered motor and thrusting propeller. It allows the changes of the main structural parameters influencing the whirl flutter stability characteristics. Propeller blades are adjustable at standstill. The demonstrator is instrumented by strain gauges, accelerometers, revolution-counting impulse sensor, sensor of airflow velocity, and the thrust measurement unit. Measurement is supported by the in house program providing the data storage and real-time depiction in the time domain as well as pre-processing into the form of the power spectral densities. The engine is linked with a servo-drive unit, which enables maintaining of the propeller revolutions (constant or controlled rate ramp) and monitoring of immediate revolutions and power. Furthermore, the program manages the aerodynamic excitation of the demonstrator by the aileron flapping (constant, sweep, impulse). Finally, it provides the safety guard to prevent any structural failure of the demonstrator hardware. In addition, LMS TestLab system is used for the measurement of the structure response and for the data assessment by means of the FFT- and OMA-based methods. The demonstrator is intended for the experimental investigations in the VZLU 3m-diameter low-speed wind tunnel. The measurement variant of the model is defined by the structural parameters: pitch and yaw attachment stiffness, pitch and yaw hinge stations, balance weight station, propeller type (duralumin or steel blades), and finally, angle of attack of the propeller blade 75% section (). The excitation is provided either by the airflow turbulence or by means of the aerodynamic excitation by the aileron flapping using a frequency harmonic sweep. The experimental results are planned to be utilized for validation of analytical methods and software tools in the frame of development of the new complex multi-blade twin-rotor propulsion system for the new generation regional aircraft. Experimental campaigns will include measurements of aerodynamic derivatives and measurements of stability boundaries for various configurations of the demonstrator.

Keywords: aeroelasticity, flutter, whirl flutter, W WING demonstrator

Procedia PDF Downloads 59

Authors: R. Yuan, S. Sivasankaran, N. Dutta, K. Ebrahimi

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This paper investigates the software capability and computer-aided engineering (CAE) method of modelling transient heat transfer process occurred in the vehicle underhood region during vehicle thermal soak phase. The heat retention from the soak period will be beneficial to the cold start with reduced friction loss for the second 14°C worldwide harmonized light-duty vehicle test procedure (WLTP) cycle, therefore provides benefits on both CO₂ emission reduction and fuel economy. When vehicle undergoes soak stage, the airflow and the associated convective heat transfer around and inside the engine bay is driven by the buoyancy effect. This effect along with thermal radiation and conduction are the key factors to the thermal simulation of the engine bay to obtain the accurate fluids and metal temperature cool-down trajectories and to predict the temperatures at the end of the soak period. Method development has been investigated in this study on a light-duty passenger vehicle using coupled aerodynamic-heat transfer thermal transient modelling method for the full vehicle under 9 hours of thermal soak. The 3D underhood flow dynamics were solved inherently transient by the Lattice-Boltzmann Method (LBM) method using the PowerFlow software. This was further coupled with heat transfer modelling using the PowerTHERM software provided by Exa Corporation. The particle-based LBM method was capable of accurately handling extremely complicated transient flow behavior on complex surface geometries. The detailed thermal modelling, including heat conduction, radiation, and buoyancy-driven heat convection, were integrated solved by PowerTHERM. The 9 hours cool-down period was simulated and compared with the vehicle testing data of the key fluid (coolant, oil) and metal temperatures. The developed CAE method was able to predict the cool-down behaviour of the key fluids and components in agreement with the experimental data and also visualised the air leakage paths and thermal retention around the engine bay. The cool-down trajectories of the key components obtained for the 9 hours thermal soak period provide vital information and a basis for the further development of reduced-order modelling studies in future work. This allows a fast-running model to be developed and be further imbedded with the holistic study of vehicle energy modelling and thermal management. It is also found that the buoyancy effect plays an important part at the first stage of the 9 hours soak and the flow development during this stage is vital to accurately predict the heat transfer coefficients for the heat retention modelling. The developed method has demonstrated the software integration for simulating buoyancy-driven heat transfer in a vehicle underhood region during thermal soak with satisfying accuracy and efficient computing time. The CAE method developed will allow integration of the design of engine encapsulations for improving fuel consumption and reducing CO₂ emissions in a timely and robust manner, aiding the development of low-carbon transport technologies.

Keywords: ATCT/WLTC driving cycle, buoyancy-driven heat transfer, CAE method, heat retention, underhood modeling, vehicle thermal soak

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Authors: James Cairns, Marco Vezza, Richard Green, Donald MacVicar

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Significant legislative changes are set to revolutionise the commercial shipping industry. Upcoming emissions restrictions will force operators to look at technologies that can improve the efficiency of their vessels -reducing fuel consumption and emissions. A device which may help in this challenge is the Ship Wind-Assisted Propulsion system (SWAP), an actively controlled aerofoil mounted vertically on the deck of a ship. The device functions in a similar manner to a sail on a yacht, whereby the aerodynamic forces generated by the sail reach an equilibrium with the hydrodynamic forces on the hull and a forward velocity results. Numerical and experimental testing of the SWAP device is presented in this study. Circulation control takes the form of a co-flow jet aerofoil, utilising both blowing from the leading edge and suction from the trailing edge. A jet at the leading edge uses the Coanda effect to energise the boundary layer in order to delay flow separation and create high lift with low drag. The SWAP concept has been originated by the research and development team at SMAR Azure Ltd. The device will be retrofitted to existing ships so that a component of the aerodynamic forces acts forward and partially reduces the reliance on existing propulsion systems. Wind tunnel tests have been carried out at the de Havilland wind tunnel at the University of Glasgow on a 1:20 scale model of this system. The tests aim to understand the airflow characteristics around the aerofoil and investigate the approximate lift and drag coefficients that an early iteration of the SWAP device may produce. The data exhibits clear trends of increasing lift as injection momentum increases, with critical flow attachment points being identified at specific combinations of jet momentum coefficient, Cµ, and angle of attack, AOA. Various combinations of flow conditions were tested, with the jet momentum coefficient ranging from 0 to 0.7 and the AOA ranging from 0° to 35°. The Reynolds number across the tested conditions ranged from 80,000 to 240,000. Comparisons between 2D computational fluid dynamics (CFD) simulations and the experimental data are presented for multiple Reynolds-Averaged Navier-Stokes (RANS) turbulence models in the form of normalised surface pressure comparisons. These show good agreement for most of the tested cases. However, certain simulation conditions exhibited a well-documented shortcoming of RANS-based turbulence models for circulation control flows and over-predicted surface pressures and lift coefficient for fully attached flow cases. Work must be continued in finding an all-encompassing modelling approach which predicts surface pressures well for all combinations of jet injection momentum and AOA.

Keywords: CFD, circulation control, Coanda, turbo wing sail, wind tunnel

Procedia PDF Downloads 111

Authors: Jana Abu Ahmada, Zaineb Mohamed, Ilyasse Aksikas

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The linear quadratic control system of hyperbolic first order partial differential equations (PDEs) are presented. The aim of this research is to control chemical reactions. This is achieved by converting the PDEs system to ordinary differential equations (ODEs) using the method of characteristics to reduce the system to control it by using the integral reinforcement learning. The designed controller is applied to a catalytic cracking reactor. Background—Transport-Reaction systems cover a large chemical and bio-chemical processes. They are best described by nonlinear PDEs derived from mass and energy balances. As a main application to be considered in this work is the catalytic cracking reactor. Indeed, the cracking reactor is widely used to convert high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils into more valuable gasoline, olefinic gases, and others. On the other hand, control of PDEs systems is an important and rich area of research. One of the main control techniques is feedback control. This type of control utilizes information coming from the system to correct its trajectories and drive it to a desired state. Moreover, feedback control rejects disturbances and reduces the variation effects on the plant parameters. Linear-quadratic control is a feedback control since the developed optimal input is expressed as feedback on the system state to exponentially stabilize and drive a linear plant to the steady-state while minimizing a cost criterion. The integral reinforcement learning policy iteration technique is a strong method that solves the linear quadratic regulator problem for continuous-time systems online in real time, using only partial information about the system dynamics (i.e. the drift dynamics A of the system need not be known), and without requiring measurements of the state derivative. This is, in effect, a direct (i.e. no system identification procedure is employed) adaptive control scheme for partially unknown linear systems that converges to the optimal control solution. Contribution—The goal of this research is to Develop a characteristics-based optimal controller for a class of hyperbolic PDEs and apply the developed controller to a catalytic cracking reactor model. In the first part, developing an algorithm to control a class of hyperbolic PDEs system will be investigated. The method of characteristics will be employed to convert the PDEs system into a system of ODEs. Then, the control problem will be solved along the characteristic curves. The reinforcement technique is implemented to find the state-feedback matrix. In the other half, applying the developed algorithm to the important application of a catalytic cracking reactor. The main objective is to use the inlet fraction of gas oil as a manipulated variable to drive the process state towards desired trajectories. The outcome of this challenging research would yield the potential to provide a significant technological innovation for the gas industries since the catalytic cracking reactor is one of the most important conversion processes in petroleum refineries.

Keywords: PDEs, reinforcement iteration, method of characteristics, riccati equation, cracking reactor

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Authors: Kiana Taheri

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Rural tourism has garnered significant attention as a catalyst for rural development and sustainability, particularly in regions like Tuscany, Italy, where the convergence of cultural heritage, picturesque landscapes, and agricultural traditions provides a fertile ground for tourism activities. This paper investigates the pivotal role of women entrepreneurs in driving sustainable rural tourism development, with a specific focus on Tuscany. Drawing upon a synthesis of literature on rural tourism, entrepreneurship, and gender studies, this research offers insights into how women entrepreneurs contribute to the economic, social, and environmental dimensions of rural tourism in Tuscany. The conceptual framework of this study is rooted in the evolving landscape of rural development, shaped by shifting paradigms in agricultural policies, such as the Common Agricultural Policy (CAP) of the European Union. This framework underscores the transition from traditional agrarian economies to dynamic rural tourism destinations characterized by a consumer-centric approach and a focus on sustainable development. Against this backdrop, the study delves into the multifaceted contributions of women entrepreneurs within the rural tourism sector. Central to the analysis is the recognition of rural tourism as a nexus of social, cultural, economic, and environmental interactions, wherein women entrepreneurs play a pivotal role in leveraging local resources, preserving cultural heritage, and fostering community engagement. By capitalizing on their unique perspectives, skills, and networks, women entrepreneurs drive innovation, diversification, and inclusivity within the tourism sector, thereby enhancing its resilience and long-term viability. Moreover, the study highlights the symbiotic relationship between rural tourism development and women's empowerment, as evidenced by the increasing prominence of women entrepreneurs in Tuscany's rural economy. Through their leadership roles in small and medium enterprises (SMEs) and agritourism ventures, women entrepreneurs not only contribute to economic growth but also challenge traditional gender norms and empower local communities. A key empirical focus of this research is a comprehensive case study of Tuscany, renowned for its successful rural tourism model and vibrant entrepreneurial ecosystem. Through qualitative interviews, surveys, and archival analysis, the study elucidates the strategies, challenges, and impacts of women entrepreneurs on sustainable rural tourism development in Tuscany. By examining the experiences of women entrepreneurs across diverse sectors of rural tourism, including hospitality, gastronomy, and cultural heritage, the study offers nuanced insights into their contributions to regional development and empowerment. In conclusion, this research contributes to the burgeoning scholarship on rural tourism, entrepreneurship, and gender studies by shedding light on the transformative role of women entrepreneurs in driving sustainable development agendas in rural areas. By elucidating the interplay between gender dynamics, entrepreneurial activities, and tourism development, this study seeks to inform policy interventions and strategic initiatives aimed at fostering inclusive and sustainable rural tourism ecosystems.

Keywords: rural tourism, women empowerment, entrepreneurship, sustainable development, small and medium-sized enterprises (SMEs)

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Authors: Cynthia Sau Chun Yip, Richard Fielding

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High meat and especially red meat intakes are significantly and positively associated with a multiple burden of diseases and also high greenhouse gas (GHG) emissions. This study investigated population meat intake patterns in Hong Kong. It quantified the burden of disease and GHG emission outcomes by modeling to adjust Hong Kong population meat intakes to recommended healthy levels. It compared age- and sex-specific population meat, fruit and vegetable intakes obtained from a population survey among adults aged 20 years and over in Hong Kong in 2005-2007, against intake recommendations suggested in the Modelling System to Inform the Revision of the Australian Guide to Healthy Eating (AGHE-2011-MS) technical document. This study found that meat and meat alternatives, especially red meat intakes among Hong Kong males aged 20+ years and over are significantly higher than recommended. Red meat intakes among females aged 50-69 years and other meat and alternatives intakes among aged 20-59 years are also higher than recommended. Taking the 2005-07 age- and sex-specific population meat intake as baselines, three counterfactual scenarios of adjusting Hong Kong adult population meat intakes to AGHE-2011-MS and Pre-2011 AGHE recommendations by the year 2030 were established. Consequent energy intake gaps were substituted with additional legume, fruit and vegetable intakes. To quantify the consequent GHG emission outcomes associated with Hong Kong meat intakes, Cradle-to-ready-to-eat lifecycle assessment emission outcome modelling was used. Comparative risk assessment of burden of disease model was used to quantify the health outcomes. This study found adjusting meat intakes to recommended levels could reduce Hong Kong GHG emission by 17%-44% when compared against baseline meat intake emissions, and prevent 2,519 to 7,012 premature deaths in males and 53 to 1,342 in females, as well as multiple burden of diseases when compared to the baseline meat intake scenario. Comparing lump sum meat intake reduction and outcome measures across the entire population, and using emission factors, and relative risks from individual studies in previous co-benefit studies, this study used age- and sex-specific input and output measures, emission factors and relative risks obtained from high quality meta-analysis and meta-review respectively, and has taken government dietary recommendations into account. Hence evaluations in this study are of better quality and more reflective of real life practices. Further to previous co-benefit studies, this study pinpointed age- and sex-specific population and meat-type-specific intervention points and leverages. When compared with similar studies in Australia, this study also showed that intervention points and leverages among populations in different geographic and cultural background could be different, and that globalization also globalizes meat consumption emission effects. More regional and cultural specific evaluations are recommended to promote more sustainable meat consumption and enhance global food security.

Keywords: burden of diseases, greenhouse gas emissions, Hong Kong diet, sustainable meat consumption

Procedia PDF Downloads 291

Authors: Vijayabhaskar Reddy Kandula, Peter Provost Taillac, Balasubramanya M. A., Ram Krishnan Nair, Gokul Toshnival, Vibhu Dhawan, Vijaya Karanam, Buffy Cramer

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Introduction: The lack of Emergency Care Services (ECS) is a cause of extensive and serious public health problems in low- and middle-income countries (LMIC), Many LMIC countries have ambulance services that allow timely transfer of ill patients but due to poor care during the ‘Golden Hour’ many deaths occur which are otherwise preventable. Lack of adequate training as evidenced by a study in India is a major reason for poor care during the ‘Golden Hour’. Adapting developed country models which includes staffing specialty-trained doctors in emergency care, is neither feasible nor guarantees cost-effective ECS. Methods: Based on our assessment and felt needs by first-line doctors providing emergency care in 2014, Rajiv Gandhi Health Sciences University’s JeevaRaksha Trust in partnership with the University of Utah, USA, designed, piloted and successfully implemented a 4-day Comprehensive-Emergency Care and Life Support course (C-ECLS) for allopathic doctors. 1730 doctors completed the 4-day course between June 2014 and December- 2020. Subsequently, we conducted a survey to investigate the utilization rates and usefulness of the training. 1662 were contacted but only 309 completed the survey. The respondents had the following designations: Senior faculty (33%), junior faculty (25), Resident (16%), Private-Practitioners (8%), Medical-Officer (16%) and not-working (11%). 51% were generalists (51%) and the rest were specialists (>30 specialties). Results: 97% (271/280) felt they are better doctors because of C-ECLS. 79% (244/309) reported that training helped to save life- specialists more likely than generalists (91% v/s 68%. P<0.05). 64% agreed that they were confident of managing COVID-19 symptomatic patients better because of C-ECLS. 27% (77) were neutral; 9% (24) disagreed. 66% agreed that training helps to be confident in managing COVID-19 critically ill patients. 26% (72) were neutral; 8% (23) disagreed. Frequency of use of C-ECLS skills: Hemorrhage-control (70%), Airway (67%), circulation skills (62%), Safe-transport and communication (60%), managing critically ill patients (58%), cardiac arrest (51%), Trauma (49%), poisoning/animal bites/stings (44%), neonatal-resuscitation (39%), breathing (36%), post-partum-hemorrhage and eclampsia (35%). Among those who used the skills, the majority (ranging from (88%-94%) reported that they were able to apply the skill more effectively because of ECLS training. Conclusion: JeevaRaksha’s C-ECLS is the world’s first comprehensive training. It improves the confidence of front-line doctors and enables them to provide quality care during the ‘Golden Hour’ of emergency. It also prepares doctors to manage unknown emergencies (e.g., COVID-19). C-ECLS was piloted in Morocco, and Uzbekistan and implemented countrywide in Bhutan. C-ECLS is relevant to most settings and offers a replicable model across LMIC.

Keywords: comprehensive emergency care and life support, training, capacity building, low- and middle-income countries, developing countries

Procedia PDF Downloads 39

Authors: Marcus Goh Tian Xi, Alicia Chua Si Wen, Eunice Gan Ghee Wu, Helen Bound, Lee Liang Ying, Albert Lee

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The Map of Dialogical Inquiry provides a conceptual look at the underlying nature of future-oriented skills. According to the Map, learning is learner-oriented, with conversational time shifted from teachers to learners, who play a strong role in deciding what and how they learn. For example, in courses operating on the principles of Dialogical Inquiry, learners were able to leave the classroom with a deeper understanding of the topic, broader exposure to differing perspectives, and stronger critical thinking capabilities, compared to traditional approaches to teaching. Despite its contributions to learning, the Map is grounded in a qualitative approach both in its development and its application for providing feedback to learners and educators. Studies hinge on openended responses by Map users, which can be time consuming and resource intensive. The present research is motivated by this gap in practicality by aiming to develop and validate a quantitative measure of the Map. In addition, a quantifiable measure may also strengthen applicability by making learning experiences trackable and comparable. The Map outlines eight learning aspects that learners should holistically engage. This research focuses on the Analysing aspect of learning. According to the Map, Analysing has four key components: liking or engaging in logic, using interpretative lenses, seeking patterns, and critiquing and deconstructing. Existing scales of constructs (e.g., critical thinking, rationality) related to these components were identified so that the current scale could adapt items from. Specifically, items were phrased beginning with an “I”, followed by an action phrase, to fulfil the purpose of assessing learners' engagement with Analysing either in general or in classroom contexts. Paralleling standard scale development procedure, the 26-item Analysing scale was administered to 330 participants alongside existing scales with varying levels of association to Analysing, to establish construct validity. Subsequently, the scale was refined and its dimensionality, reliability, and validity were determined. Confirmatory factor analysis (CFA) revealed if scale items loaded onto the four factors corresponding to the components of Analysing. To refine the scale, items were systematically removed via an iterative procedure, according to their factor loadings and results of likelihood ratio tests at each step. Eight items were removed this way. The Analysing scale is better conceptualised as unidimensional, rather than comprising the four components identified by the Map, for three reasons: 1) the covariance matrix of the model specified for the CFA was not positive definite, 2) correlations among the four factors were high, and 3) exploratory factor analyses did not yield an easily interpretable factor structure of Analysing. Regarding validity, since the Analysing scale had higher correlations with conceptually similar scales than conceptually distinct scales, with minor exceptions, construct validity was largely established. Overall, satisfactory reliability and validity of the scale suggest that the current procedure can result in a valid and easy-touse measure for each aspect of the Map.

Keywords: analytical thinking, dialogical inquiry, education, lifelong learning, pedagogy, scale development

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Authors: Gyu-Dong Kim, Wuk-Jae Yoo, Sang-Youl Lee

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Composite structures offer numerous advantages over conventional structural systems in the form of higher specific stiffness and strength, lower life-cycle costs, and benefits such as easy installation and improved safety. Recently, there has been a considerable increase in the use of composites in engineering applications and as wraps for seismic upgrading and repairs. However, these composites deteriorate with time because of outdated materials, excessive use, repetitive loading, climatic conditions, manufacturing errors, and deficiencies in inspection methods. In particular, damaged fibers in a composite result in significant degradation of structural performance. In order to reduce the failure probability of composites in service, techniques to assess the condition of the composites to prevent continual growth of fiber damage are required. Condition assessment technology and nondestructive evaluation (NDE) techniques have provided various solutions for the safety of structures by means of detecting damage or defects from static or dynamic responses induced by external loading. A variety of techniques based on detecting the changes in static or dynamic behavior of isotropic structures has been developed in the last two decades. These methods, based on analytical approaches, are limited in their capabilities in dealing with complex systems, primarily because of their limitations in handling different loading and boundary conditions. Recently, investigators have introduced direct search methods based on metaheuristics techniques and artificial intelligence, such as genetic algorithms (GA), simulated annealing (SA) methods, and neural networks (NN), and have promisingly applied these methods to the field of structural identification. Among them, GAs attract our attention because they do not require a considerable amount of data in advance in dealing with complex problems and can make a global solution search possible as opposed to classical gradient-based optimization techniques. In this study, we propose an alternative damage-detection technique that can determine the degraded stiffness distribution of vibrating laminated composites made of Glass Fiber-reinforced Polymer (GFRP). The proposed method uses a modified form of the bivariate Gaussian distribution function to detect degraded stiffness characteristics. In addition, this study presents a method to detect the fiber property variation of laminated composite plates from the micromechanical point of view. The finite element model is used to study free vibrations of laminated composite plates for fiber stiffness degradation. In order to solve the inverse problem using the combined method, this study uses only first mode shapes in a structure for the measured frequency data. In particular, this study focuses on the effect of the interaction among various parameters, such as fiber angles, layup sequences, and damage distributions, on fiber-stiffness damage detection.

Keywords: stiffness detection, fiber damage, genetic algorithm, layup sequences

Procedia PDF Downloads 239

Authors: Desmond Appiah, Fan Zhang, Shouqi Yuan, Wei Xueyuan, Stephen N. Asomani

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The side channel pump has distinctive hydraulic performance characteristics over other vane pumps because of its generation of high pressure heads in only one impeller revolution. Hence, there is soaring utilization and application in the fields of petrochemical, food processing fields, automotive and aerospace fuel pumping where high heads are required at low flows. The side channel pump is characterized by unstable flow because after fluid flows into the impeller passage, it moves into the side channel and comes back to the impeller again and then moves to the next circulation. Consequently, the flow leaves the side channel pump following a helical path. However, the pressure fluctuation exhibited in the flow greatly contributes to the unwanted noise and vibration which is associated with the flow. In this paper, a side channel pump prototype was examined thoroughly through numerical calculations based on SST k-ω turbulence model to ascertain the pressure fluctuation behavior. The pressure fluctuation intensity of the 3D unstable flow dynamics were carefully investigated under different working conditions 0.8QBEP, 1.0 QBEP and 1.2QBEP. The results showed that the pressure fluctuation distribution around the pressure side of the blade is greater than the suction side at the impeller and side channel interface (z=0) for all three operating conditions. Part-load condition 0.8QBEP recorded the highest pressure fluctuation distribution because of the high circulation velocity thus causing an intense exchanged flow between the impeller and side channel. Time and frequency domains spectra of the pressure fluctuation patterns in the impeller and the side channel were also analyzed under the best efficiency point value, QBEP using the solution from the numerical calculations. It was observed from the time-domain analysis that the pressure fluctuation characteristics in the impeller flow passage increased steadily until the flow reached the interrupter which separates low-pressure at the inflow from high pressure at the outflow. The pressure fluctuation amplitudes in the frequency domain spectrum at the different monitoring points depicted a gentle decreasing trend of the pressure amplitudes which was common among the operating conditions. The frequency domain also revealed that the main excitation frequencies occurred at 600Hz, 1200Hz, and 1800Hz and continued in the integers of the rotating shaft frequency. Also, the mass flow exchange plots indicated that the side channel pump is characterized with many vortex flows. Operating conditions 0.8QBEP, 1.0 QBEP depicted less and similar vortex flow while 1.2Q recorded many vortex flows around the inflow, middle and outflow regions. The results of the numerical calculations were finally verified experimentally. The performance characteristics curves from the simulated results showed that 0.8QBEP working condition recorded a head increase of 43.03% and efficiency decrease of 6.73% compared to 1.0QBEP. It can be concluded that for industrial applications where the high heads are mostly required, the side channel pump can be designed to operate at part-load conditions. This paper can serve as a source of information in order to optimize a reliable performance and widen the applications of the side channel pumps.

Keywords: exchanged flow, pressure fluctuation, numerical simulation, side channel pump

Procedia PDF Downloads 103

Authors: Dedjo Yao Simon, Takahiro Saito, Norikazu Inuzuka, Ikuo Sugiyama

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The megacity of Abidjan is a coastal urban area where the number of floods reported and the associated impacts are on a rapid increase due to climate change, an uncontrolled urbanization, a rapid population increase, a lack of flood disaster mitigation and citizens’ awareness. The objective of this research is to reduce in the short and long term period, the human and socio-economic impact of the flood. Hydrological simulation is applied on free of charge global spatial data (digital elevation model, satellite-based rainfall estimate, landuse) to identify the flood-prone area and to map the risk of flood. A direct interview to a sample residents is used to validate the simulation results. Then a mobile application (Flood Locator) is prototyped to disseminate the risk information to the citizen. In addition, a value capture strategy is proposed to mobilize financial resource for disaster risk reduction (DRRf) to reduce the impact of the flood. The town of Cocody in Abidjan is selected as a case study area to implement this research. The mapping of the flood risk reveals that population living in the study area is highly vulnerable. For a 5-year flood, more than 60% of the floodplain is affected by a water depth of at least 0.5 meters; and more than 1000 ha with at least 5000 buildings are directly exposed. The risk becomes higher for a 50 and 100-year floods. Also, the interview reveals that the majority of the citizen are not aware of the risk and severity of flooding in their community. This shortage of information is overcome by the Flood Locator and by an urban flood database we prototype for accumulate flood data. Flood Locator App allows the users to view floodplain and depth on a digital map; the user can activate the GPS sensor of the mobile to visualize his location on the map. Some more important additional features allow the citizen user to capture flood events and damage information that they can send remotely to the database. Also, the disclosure of the risk information could result to a decrement (-14%) of the value of properties locate inside floodplain and an increment (+19%) of the value of property in the suburb area. The tax increment due to the higher tax increment in the safer area should be captured to constitute the DRRf. The fund should be allocated to the reduction of flood risk for the benefit of people living in flood-prone areas. The flood prevention system discusses in this research will minimize in the short and long term the direct damages in the risky area due to effective awareness of citizen and the availability of DRRf. It will also contribute to the growth of the urban area in the safer zone and reduce human settlement in the risky area in the long term. Data accumulated in the urban flood database through the warning app will contribute to regenerate Abidjan towards the more resilient city by means of risk avoidable landuse in the master plan.

Keywords: abidjan, database, flood, geospatial techniques, risk communication, smartphone, value capture

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Authors: L. J. de Jager

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In the South African English school curriculum, one of the aims is to achieve communicative competence, the knowledge of using language competently and appropriately in a speech community. Communicatively competent speakers should not only produce grammatically correct sentences but also produce contextually appropriate sentences for various purposes and in different situations. As most speakers of English are non-native speakers, achieving communicative competence remains a complex challenge. Moreover, the changing needs of society necessitate not merely language proficiency, but also technological proficiency. One of the burning issues in the South African educational landscape is the replacement of the standardised literacy model by the pedagogy of multiliteracies that incorporate, by default, the exploration of technological text forms that are part of learners’ everyday lives. It foresees learners as decoders, encoders, and manufacturers of their own futures by exploiting technological possibilities to constantly create and recreate meaning. As such, 21st century learners will feel comfortable working with multimodal texts that are intrinsically part of their lives and by doing so, become authors of their own learning experiences while teachers may become agents supporting learners to discover their capacity to acquire new digital skills for the century of multiliteracies. The aim is transformed practice where learners use their skills, ideas, and knowledge in new contexts. This paper reports on a research project on the integration of technology for language learning, based on the technological pedagogical content knowledge framework, conceptually founded in the theory of multiliteracies, and which aims to achieve communicative competence. The qualitative study uses the community of inquiry framework to answer the research question: How does the integration of technology transform language teaching of preservice teachers? Pre-service teachers in the Postgraduate Certificate of Education Programme with English as methodology were purposively selected to source and evaluate apps for teaching and learning English. The participants collaborated online in a dedicated Blackboard module, using discussion threads to sift through applicable apps and develop interactive lessons using the Apps. The selected apps were entered on to a predesigned Qualtrics form. Data from the online discussions, focus group interviews, and reflective journals were thematically and inductively analysed to determine the participants’ perceptions and experiences when integrating technology in lesson design and the extent to which communicative competence was achieved when using these apps. Findings indicate transformed practice among participants and research team members alike with a better than average technology acceptance and integration. Participants found value in online collaboration to develop and improve their own teaching practice by experiencing directly the benefits of integrating e-learning into the teaching of languages. It could not, however, be clearly determined whether communicative competence was improved. The findings of the project may potentially inform future e-learning activities, thus supporting student learning and development in follow-up cycles of the project.

Keywords: apps, communicative competence, English teaching, technology integration, technological pedagogical content knowledge

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Authors: Valentina Dolmova

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What consumers choose to buy and who voters select on election days are two questions that have captivated the interest of both academics and practitioners for many decades. The importance of understanding what influences the behavior of those groups and whether or not we can predict or control it fuels a steady stream of research in a range of fields. By looking only at the past 40 years, more than 70 thousand scientific papers have been published in each field – consumer behavior and political psychology, respectively. From marketing, economics, and the science of persuasion to political and cognitive psychology - we have all remained heavily engaged. The ever-evolving technology, inevitable socio-cultural shifts, global economic conditions, and much more play an important role in choice-equations regardless of context. On one hand, this makes the research efforts always relevant and needed. On the other, the relatively low number of cross-field collaborations, which seem to be picking up only in more in recent years, makes the existing findings isolated into framed bubbles. By performing systematic research across both areas of psychology and building a parallel between theories and factors of influence, however, we find that there is not only a definitive common ground between the behaviors of consumers and voters but that we are moving towards a global model of choice. This means that the lines between contexts are fading which has a direct implication on what we should focus on when predicting or navigating buyers and voters’ behavior. Internal and external factors in four main categories determine the choices we make as consumers and as voters. Together, personal, psychological, social, and cultural create a holistic framework through which all stimuli in relation to a particular product or a political party get filtered. The analogy “consumer-voter” solidifies further. Leading academics suggest that this fundamental parallel is the key to managing successfully political and consumer brands alike. However, we distinguish additional four key stimuli that relate to those factor categories (1/ opportunity costs; 2/the memory of the past; 3/recognisable figures/faces and 4/conflict) arguing that the level of expertise a person has determines the prevalence of factors or specific stimuli. Our efforts take into account global trends such as the establishment of “celebrity politics” and the image of “ethically concerned consumer brands” which bridge the gap between contexts to an even greater extent. Scientists and practitioners are pushed to accept the transformative nature of both fields in social psychology. Existing blind spots as well as the limited number of research conducted outside the American and European societies open up space for more collaborative efforts in this highly demanding and lucrative field. A mixed method of research tests three main hypotheses, the first two of which are focused on the level of irrelevance of context when comparing voting or consumer behavior – both from the factors and stimuli lenses, the third on determining whether or not the level of expertise in any field skews the weight of what prism we are more likely to choose when evaluating options.

Keywords: buyers’ behaviour, decision-making, voters’ behaviour, social psychology

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Authors: Timothy Gray

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This paper will present work and discuss lessons learned during a semester-long travel study based in Southeast Asia, which was run in the Spring Semester of 2019 and again in the summer of 2023. The first travel group consisted of fifteen students, and the second group consisted of twelve students ranging from second-year to graduate level, student participants majoring in either architecture or planning. Students worked in interdisciplinary teams, each team beginning their travel study, living together in a separate small town for over a month in (relatively) remote conditions in rural Thailand. Students became intimately familiar with these towns, forged strong personal relationships, and built reservoirs of knowledge one conversation at a time. Rather than impose external ideas and solutions, students were asked to learn from and be open to lessons from the people and the place. The following design statement was used as a point of departure for their investigations: It is our shared premise that architecture exists in small villages and towns of Southeast Asia in the ingenuity of the people, that architecture exists in a shared language of making, modifying, and reusing. It is a modest but vibrant architecture, an architecture that is alive and evolving, an architecture that is small in scale, accessible, and one that emerges from the people. It is an architecture that can exist in a modified bicycle, a woven bamboo bridge, or a self-built community. Students were challenged to engage in existing conditions as design professionals, both empowering and lending coherence to the energies that already existed in the place. As one of the student teams noted in their design narrative: “During our field study, we had the unique opportunity to tour a number of informal settlements and meet and talk to residents through interpreters. We found that many of the residents work in nearby factories for dollars a day. Others find employment in self-generated informal economies such as hand carving and textiles. Despite extreme poverty, we found these places to be vibrant and full of life as people navigate these challenging conditions to live lives with purpose and dignity.” Students worked together with local community members and colleagues to develop a series of varied proposals that emerged from their interrogations of place and partnered with community members and professional colleagues in the development of these proposals. Project partners included faculty and student colleagues Yangon University, the mayor's Office, Planning Department Officials and religious leaders in Sawankhalok, Thailand, and community leaders in Natonchan, Thailand, to name a few. This paper will present a series of student community-based design projects that emerged from these conditions. The paper will also discuss this model of travel study as a way of building an architecture which uses social and cultural issues as a catalyst for design. The paper will discuss lessons relative to sustainable development that the Western students learned through their travels in Southeast Asia.

Keywords: travel study, CAPasia, architecture of empowerment, modular housing

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Authors: Betty Chiyangwa

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The subject of second-generation migrant youth is under-researched in the context of South Africa. Thus, their opinions and views have been marginalised in social science research. This paper addresses this gap by exploring the complexities of second-generation Mozambican migrant youth’s lived experiences in how they construct their identities and develop a sense of belonging in post-apartheid South Africa, specifically in Bushbuckridge. Bushbuckridge was among the earliest districts to accommodate Mozambican refugees to South Africa in the 1970s and remains associated with large numbers of Mozambicans. Drawing on Crenshaw’s (1989) intersectionality approach, the study contributes to knowledge on South-to-South migration by demonstrating how this approach is operationalised to understand the complex lived experiences of a disadvantaged group in life and possibly in death. In conceptualising the notion of identity among second-generation migrant youth, this paper explores the history and present of first and second-generation Mozambican migrants in South Africa to reveal how being born to migrant parents and raised in a hosting country poses life-long complications in one’s identity and sense of belonging. In the quest to form their identities and construct a sense of belonging, migrant youth employ precariously means to navigate the terrane. This is a case study informed by semi-structured interviews and narrative data gathered from 22 second-generation Mozambican migrant youth between 18 and 34 years who were born to at least one Mozambican parent living in Bushbuckridge and raised in South Africa. Views of two key informants from the South African Department of Home Affairs and the local tribal authority provided additional perspectives on second-generation migrant youth’s lived experiences in Bushbuckridge, which were explored thematically and narratively through Braun and Clarke’s (2012) six-step framework for analysing qualitative data. In exploring the interdependency and interconnectedness of social categories and social systems in Bushbuckridge, the findings revealed that participants’ experiences of identity formation and development of a sense of belonging were marginalised in complex, intersectional and precarious ways where they constantly (re)negotiated their daily experiences, which were largely shaped by their paradoxical migrant status in a host country. This study found that, in the quest for belonging, migrant youths were not a perfectly integrated category but evolved from almost daily lived experiences of creating a living that gave them an identity and a sense of belonging in South Africa. The majority of them shared feelings of living in limbo since childhood and fear of possibly dying in limbo with no clear (solid) sense of belonging to either South Africa or Mozambique. This study concludes that there is a strong association between feelings of identity, sense of belonging and levels of social integration. It recommends the development and adoption of a multilayer comprehensive model for understanding second-generation migrant youth identity and belonging in South Africa which encourages a collaborative effort among individual migrant youth, their family members, neighbours, society, and regional and national institutional structures for migrants to enhance and harness their capabilities and improve their wellbeing in South Africa.

Keywords: bushbuckridge, limbo, mozambican migrants, second-generation

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Authors: Marta Paszkiewicz, Justyna Łuczak, Martyna Marchelek, Adriana Zaleska-Medynska

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In recent years, photocatalytical processes have been intensively investigated for destruction of pollutants, hydrogen evolution, disinfection of water, air and surfaces, for the construction of self-cleaning materials (tiles, glass, fibres, etc.). Titanium dioxide (TiO2) is the most popular material used in heterogeneous photocatalysis due to its excellent properties, such as high stability, chemical inertness, non-toxicity and low cost. It is well known that morphology and microstructure of TiO2 significantly influence the photocatalytic activity. This characteristics as well as other physical and structural properties of photocatalysts, i.e., specific surface area or density of crystalline defects, could be controlled by preparation route. In this regard, TiO2 particles can be obtained by sol-gel, hydrothermal, sonochemical methods, chemical vapour deposition and alternatively, by ionothermal synthesis using ionic liquids (ILs). In the TiO2 particles synthesis ILs may play a role of a solvent, soft template, reagent, agent promoting reduction of the precursor or particles stabilizer during synthesis of inorganic materials. In this work, the effect of the ILs anion type on morphology and photoactivity of TiO2 is presented. The preparation of TiO2 microparticles with spherical structure was successfully achieved by solvothermal method, using tetra-tert-butyl orthotitatane (TBOT) as the precursor. The reaction process was assisted by an ionic liquids 1-butyl-3-methylimidazolium bromide [BMIM][Br], 1-butyl-3-methylimidazolium tetrafluoroborate [BMIM][BF4] and 1-butyl-3-methylimidazolium haxafluorophosphate [BMIM][PF6]. Various molar ratios of all ILs to TBOT (IL:TBOT) were chosen. For comparison, reference TiO2 was prepared using the same method without IL addition. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Brenauer-Emmett-Teller surface area (BET), NCHS analysis, and FTIR spectroscopy were used to characterize the surface properties of the samples. The photocatalytic activity was investigated by means of phenol photodegradation in the aqueous phase as a model pollutant, as well as formation of hydroxyl radicals based on detection of fluorescent product of coumarine hydroxylation. The analysis results showed that the TiO2 microspheres had spherical structure with the diameters ranging from 1 to 6 µm. The TEM micrographs gave a bright observation of the samples in which the particles were comprised of inter-aggregated crystals. It could be also observed that the IL-assisted TiO2 microspheres are not hollow, which provides additional information about possible formation mechanism. Application of the ILs results in rise of the photocatalytic activity as well as BET surface area of TiO2 as compared to pure TiO2. The results of the formation of 7-hydroxycoumarin indicated that the increased amount of ·OH produced at the surface of excited TiO2 for samples TiO2_ILs well correlated with more efficient degradation of phenol. NCHS analysis showed that ionic liquids remained on the TiO2 surface confirming structure directing role of that compounds.

Keywords: heterogeneous photocatalysis, IL-assisted synthesis, ionic liquids, TiO2

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Authors: Farideh Tabatabaee Yazdi, Fereshteh Falah, Alireza Vasiee

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Introduction: Gamma-aminobutyric acid (GABA) is a non-protein amino acid that is widely present in organisms. GABA is a kind of pharmacological and biological component and its application is wide and useful. Several important physiological functions of GABA have been characterized, such as neurotransmission and induction of hypotension. GABA is also a strong secretagogue of insulin from the pancreas and effectively inhibits small airway-derived lung adenocarcinoma and tranquilizer. Many microorganisms can produce GABA, and lactic acid bacteria have been a focus of research in recent years because lactic acid bacteria possess special physiological activities and are generally regarded as safe. Among them, the Lb. Brevis produced the highest amount of GABA. The major factors affecting GABA production have been characterized, including carbon sources and glutamate concentration. The use of food industry waste to produce valuable products such as amino acids seems to be a good way to reduce production costs and prevent the waste of food resources. In a dairy factory, a high volume of sludge is produced from a separator that contains useful compounds such as growth factors, carbon, nitrogen, and organic matter that can be used by different microorganisms such as Lb.brevis as carbon and nitrogen sources. Therefore, it is a good source of GABA production. GABA is primarily formed by the irreversible α-decarboxylation reaction of L-glutamic acid or its salts, catalysed by the GAD enzyme. In the present study, this aim was achieved for the fast-growing of Lb.brevis and producing GABA, using the dairy industry sludge as a suitable growth medium. Lactobacillus Brevis strains obtained from Microbial Type Culture Collection (MTCC) were used as model strains. In order to prepare dairy sludge as a medium, sterilization should be done at 121 ° C for 15 minutes. Lb. Brevis was inoculated to the sludge media at pH=6 and incubated for 120 hours at 30 ° C. After fermentation, the supernatant solution is centrifuged and then, the GABA produced was analyzed by the Thin Layer chromatography (TLC) method qualitatively and by the high-performance liquid chromatography (HPLC) method quantitatively. By increasing the percentage of dairy sludge in the culture medium, the amount of GABA increased. Also, evaluated the growth of bacteria in this medium showed the positive effect of dairy sludge on the growth of Lb.brevis, which resulted in the production of more GABA. GABA-producing LAB offers the opportunity of developing naturally fermented health-oriented products. Although some GABA-producing LAB has been isolated to find strains suitable for different fermentations, further screening of various GABA-producing strains from LAB, especially high-yielding strains, is necessary. The production of lactic acid, bacterial gamma-aminobutyric acid, is safe and eco-friendly. The use of dairy industry waste causes enhanced environmental safety. Also provides the possibility of producing valuable compounds such as GABA. In general, dairy sludge is a suitable medium for the growth of Lactic Acid Bacteria and produce this amino acid that can reduce the final cost of it by providing carbon and nitrogen source.

Keywords: GABA, Lactobacillus, HPLC, dairy sludge

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Authors: D. Norton

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This qualitative study focuses on the lived experience and displacement of young white-collar masculinities in Japan. In recent years, the salaryman lifestyle has undergone significant disruption - increased competition for regular employment, rise in non-regular structurings of labour across public/private sectors, and shifting role expectations within the home. Despite this, related scholarship hints at a continued reinforcement of the traditional male gender role - that the salaryman remains a key benchmark of Japanese masculine identity. For those in structural proximity to these more ‘normative’ performativities, interest lies their engagement with such narratives - how they make sense of their masculinity in response to stated changes. In light of the historical emphasis on labour and breadwinning logics, notions of respective security or precarity generated as a result remain unclear. Similarly, concern extends to developments within the private sphere - by what means young white-collar men construct ideas of singlehood and companionship according to traditional gender ideologies or more contemporary, flexible readings. The influence of these still-emergent status distinctions on the logics of the social group in question is yet to be explored in depth by gender scholars. This project, therefore, focuses on a salaryman archetype as hegemonic - its transformation amidst these changes and socialising mechanisms that continue to legitimate unequal gender hierarchies. For data collection, a series of ethnographic interviews were held over a period of 12 months with university-educated, white-collar male employees from both Osaka and the Greater Tokyo Area. Findings suggest a modern salaryman ideal reflecting both continuities and shifts within white-collar employment. Whilst receptive to more contemporary workplace practices, the narratives of those interviewed remain imbued with logics supporting patterns of internal hegemony. Regular/non-regular distinction emerged as the foremost variable for both material and discursive patterns of white-collar stratification, with variants of displacement for each social group. Despite the heightened valorisation of stable employment, regular workers articulated various concerns over a model of corporate masculinity seen to be incompatible with recent socioeconomic developments. Likewise, non-regular employees face detachment owing to a still-inflexible perception of their working masculinity as marginalized amidst economic precarity. In seeking to negotiate respective challenges, those interviewed demonstrated an engagement with various concurrent social changes that would often either accommodate, reinforce, or expand upon traditional role behaviours. Few of these narratives offered any notable transgression of said ideal, however, suggesting that within the spectre of white-collar employment in Japan for the near future, any substantive transformation of corporate masculinity remains dependant upon economic developments, less so the agency of those involved.

Keywords: gender ideologies, hegemonic masculinity, Japan, white-collar employment

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Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

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Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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Authors: Alena Semeradtova, Marcel Stofik, Lucie Mareckova, Petr Maly, Ondrej Stanek, Jan Maly

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Recently, novel strategies based on so-called molecular evolution were shown to be effective for the production of various peptide ligand libraries with high affinities to molecular targets of interest comparable or even better than monoclonal antibodies. The major advantage of these peptide scaffolds is mainly their prevailing low molecular weight and simple structure. This study describes a new high-affinity binding molecules based immunesensor using a simple optical system for human serum albumin (HSA) detection as a model molecule. We present a comparison of two variants of recombinant binders based on albumin binding domain of the protein G (ABD) performed on micropatterned glass chip. Binding domains may be tailored to any specific target of interest by molecular evolution. Micropatterened glass chips were prepared using UV-photolithography on chromium sputtered glasses. Glass surface was modified by (3-aminopropyl)trietoxysilane and biotin-PEG-acid using EDC/NHS chemistry. Two variants of high-affinity binding molecules were used to detect target molecule. Firstly, a variant is based on ABD domain fused with TolA chain. This molecule is in vivo biotinylated and each molecule contains one molecule of biotin and one ABD domain. Secondly, the variant is ABD domain based on streptavidin molecule and contains four gaps for biotin and four ABD domains. These high-affinity molecules were immobilized to the chip surface via biotin-streptavidin chemistry. To eliminate nonspecific binding 1% bovine serum albumin (BSA) or 6% fetal bovine serum (FBS) were used in every step. For both variants range of measured concentrations of fluorescently labelled HSA was 0 – 30 µg/ml. As a control, we performed a simultaneous assay without high-affinity binding molecules. Fluorescent signal was measured using inverse fluorescent microscope Olympus IX 70 with COOL LED pE 4000 as a light source, related filters, and camera Retiga 2000R as a detector. The fluorescent signal from non-modified areas was substracted from the signal of the fluorescent areas. Results were presented in graphs showing the dependence of measured grayscale value on the log-scale of HSA concentration. For the TolA variant the limit of detection (LOD) of the optical immunosensor proposed in this study is calculated to be 0,20 µg/ml for HSA detection in 1% BSA and 0,24 µg/ml in 6% FBS. In the case of streptavidin-based molecule, it was 0,04 µg/ml and 0,07 µg/ml respectively. The dynamical range of the immunosensor was possible to estimate just in the case of TolA variant and it was calculated to be 0,49 – 3,75 µg/ml and 0,73-1,88 µg/ml respectively. In the case of the streptavidin-based the variant we didn´t reach the surface saturation even with the 480 ug/ml concentration and the upper value of dynamical range was not estimated. Lower value was calculated to be 0,14 µg/ml and 0,17 µg/ml respectively. Based on the obtained results, it´s clear that both variants are useful for creating the bio-recognizing layer on immunosensors. For this particular system, it is obvious that the variant based on streptavidin molecule is more useful for biosensing on glass planar surfaces. Immunosensors based on this variant would exhibit better limit of detection and wide dynamical range.

Keywords: high affinity binding molecules, human serum albumin, optical immunosensor, protein G, UV-photolitography

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Amy Heaps, Amy Burns, Una McMahon-Beattie

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Shock and fear tactics have been used to encourage consumer behaviour change within the UK regarding lifestyle choices such as smoking and alcohol abuse, yet such measures have not been applied to food labels to encourage healthier purchasing decisions. Obesity levels are continuing to rise within the UK, despite efforts made by government and charitable bodies to encourage consumer behavioural changes, which will have a positive influence on their fat, salt, and sugar intake. We know that taking extreme measures to shock consumers into behavioural changes has worked previously; for example, the anti-smoking television adverts and new standardised cigarette and tobacco packaging have reduced the numbers of the UK adult population who smoke or encouraged those who are currently trying to quit. The USA has also introduced new front-of-pack labelling, which is clear, easy to read, and includes concise health warnings on products high in fat, salt, or sugar. This model has been successful, with consumers reducing purchases of products with these warning labels present. Therefore, investigating if shock labels would have an impact on UK consumer behaviour and purchasing decisions would help to fill the gap within this research field. This study aims to develop an understanding of consumer’s initial responses to shock advertising with an interest in the perceived impact of long-term effect shock advertising on consumer food purchasing decisions, behaviour, and attitudes and will achieve this through a mixed methodological approach taken with a sample size of 25 participants ages ranging from 22 and 60. Within this research, shock mock labels were developed, including a graphic image, health warning, and get-help information. These labels were made for products (available within the UK) with large market shares which were high in either fat, salt, or sugar. The use of online focus groups and mouse-tracking experiments results helped to develop an understanding of consumer’s initial responses to shock advertising with interest in the perceived impact of long-term effect shock advertising on consumer food purchasing decisions, behaviour, and attitudes. Preliminary results have shown that consumers believe that the use of graphic images, combined with a health warning, would encourage consumer behaviour change and influence their purchasing decisions regarding those products which are high in fat, salt and sugar. Preliminary main findings show that graphic mock shock labels may have an impact on consumer behaviour and purchasing decisions, which will, in turn, encourage healthier lifestyles. Focus group results show that 72% of participants indicated that these shock labels would have an impact on their purchasing decisions. During the mouse tracking trials, this increased to 80% of participants, showing that more exposure to shock labels may have a bigger impact on potential consumer behaviour and purchasing decision change. In conclusion, preliminary results indicate that graphic shock labels will impact consumer purchasing decisions. Findings allow for a deeper understanding of initial emotional responses to these graphic labels. However, more research is needed to test the longevity of these labels on consumer purchasing decisions, but this research exercise is demonstrably the foundation for future detailed work.

Keywords: consumer behavior, decision making, labelling legislation, purchasing decisions, shock advertising, shock labelling

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Authors: Alena Cejkova, Martina Paldrychova, Jana Michailidu, Olga Matatkova, Jan Masak

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Increasing the resistance of pathogenic microorganisms to many antibiotics is a serious threat to the treatment of infectious diseases and cleaning medical instruments. It should be added that the resistance of microbial populations growing in biofilms is often up to 1000 times higher compared to planktonic cells. Biofilm formation in a number of microorganisms is largely influenced by the quorum sensing regulatory mechanism. Finding external factors such as natural substances or physical processes that can interfere effectively with quorum sensing signal molecules should reduce the ability of the cell population to form biofilm and increase the effectiveness of antibiotics. The present work is devoted to the effect of chitosan as a representative of natural substances with anti-biofilm activity and non- thermal plasma (NTP) alone or in combination with polymyxin B on biofilm formation of Pseudomonas aeruginosa. Particular attention was paid to the influence of these agents on the level of quorum sensing signal molecules (acyl-homoserine lactones) during planktonic and biofilm cultivations. Opportunistic pathogenic strains of Pseudomonas aeruginosa (DBM 3081, DBM 3777, ATCC 10145, ATCC 15442) were used as model microorganisms. Cultivations of planktonic and biofilm populations in 96-well microtiter plates on horizontal shaker were used for determination of antibiotic and anti-biofilm activity of chitosan and polymyxin B. Biofilm-growing cells on titanium alloy, which is used for preparation of joint replacement, were exposed to non-thermal plasma generated by cometary corona with a metallic grid for 15 and 30 minutes. Cultivation followed in fresh LB medium with or without chitosan or polymyxin B for next 24 h. Biofilms were quantified by crystal violet assay. Metabolic activity of the cells in biofilm was measured using MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) colorimetric test based on the reduction of MTT into formazan by the dehydrogenase system of living cells. Activity of N-acyl homoserine lactones (AHLs) compounds involved in the regulation of biofilm formation was determined using Agrobacterium tumefaciens strain harboring a traG::lacZ/traR reporter gene responsive to AHLs. The experiments showed that both chitosan and non-thermal plasma reduce the AHLs level and thus the biofilm formation and stability. The effectiveness of both agents was somewhat strain dependent. During the eradication of P. aeruginosa DBM 3081 biofilm on titanium alloy induced by chitosan (45 mg / l) there was an 80% decrease in AHLs. Applying chitosan or NTP on the P. aeruginosa DBM 3777 biofilm did not cause a significant decrease in AHLs, however, in combination with both (chitosan 55 mg / l and NTP 30 min), resulted in a 70% decrease in AHLs. Combined application of NTP and polymyxin B allowed reduce antibiotic concentration to achieve the same level of AHLs inhibition in P. aeruginosa ATCC 15442. The results shown that non-thermal plasma and chitosan have considerable potential for the eradication of highly resistant P. aeruginosa biofilms, for example on medical instruments or joint implants.

Keywords: anti-biofilm activity, chitosan, non-thermal plasma, opportunistic pathogens

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Authors: Arti Singh, Carolyn Jenkins, Oyedunni S. Arulogun, Mayowa O. Owolabi, Fred S. Sarfo, Bruce Ovbiagele, Enzinne Sylvia

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Background: Stroke, the leading cause of adult-onset disability and the second leading cause of death, is a major public health concern particularly pertinent in Sub-Saharan Africa (SSA), where nearly 80% of all global stroke mortalities occur. The Stroke Investigative Research and Education Network (SIREN) seeks to comprehensively characterize the genomic, sociocultural, economic, and behavioral risk factors for stroke and to build effective teams for research to address and decrease the burden of stroke and other non communicable diseases in SSA. One of the first steps to address this goal was to effectively engage the communities that suffer the high burden of disease in SSA. This study describes how the SIREN project engaged six sites in Ghana and Nigeria over the past three years, describing the community engagement activities that have arisen since inception. Aim: The aim of community engagement (CE) within SIREN is to elucidate information about knowledge, attitudes, beliefs, and practices (KABP) about stroke and its risk factors from individuals of African ancestry in SSA, and to educate the community about stroke and ways to decrease disabilities and deaths from stroke using socioculturally appropriate messaging and messengers. Methods: Community Advisory Board (CABs), Focus Group Discussions (FGDs) and community outreach programs. Results: 27 FGDs with 168 participants including community heads, religious leaders, health professionals and individuals with stroke among others, were conducted, and over 60 CE outreaches have been conducted within the SIREN performance sites. Over 5,900 individuals have received education on cardiovascular risk factors and about 5,000 have been screened for cardiovascular risk factors during the outreaches. FGDs and outreach programs indicate that knowledge of stroke, as well as risk factors and follow-up evidence-based care is limited and often late. Other findings include: 1) Most recognize hypertension as a major risk factor for stroke. 2) About 50% report that stroke is hereditary and about 20% do not know organs affected by stroke. 3) More than 95% willing to participate in genetic testing research and about 85% willing to pay for testing and recommend the test to others. 4) Almost all indicated that genetic testing could help health providers better treat stroke and help scientists better understand the causes of stroke. The CABs provided stakeholder input into SIREN activities and facilitated collaborations among investigators, community members and stakeholders. Conclusion: The CE core within SIREN is a first-of-its kind public outreach engagement initiative to evaluate and address perceptions about stroke and genomics by patients, caregivers, and local leaders in SSA and has implications as a model for assessment in other high-stroke risk populations. SIREN’s CE program uses best practices to build capacity for community-engaged research, accelerate integration of research findings into practice and strengthen dynamic community-academic partnerships within our communities. CE has had several major successes over the past three years including our multi-site collaboration examining the KABP about stroke (symptoms, risk factors, burden) and genetic testing across SSA.

Keywords: community advisory board, community engagement, focus groups, outreach, SSA, stroke

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Authors: Adine Gericke, Jiri Militky, Mohanapriya Venkataraman

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Mohair, obtained from the Angora goat, is a luxury fiber and recognized as one of the best quality natural fibers. Expansion of the use of mohair into technical and functional textile products necessitates the need for a better understanding of how the use of mohair in fabrics will impact on its thermo-physiological comfort related properties. Despite its popularity, very little information is available on the quantification of the thermal and moisture management properties of mohair fabrics. This study investigated the effect of fibrous matter composition and fabric structural parameters on conductive and convective heat transfers to attain more information on the thermal comfort properties of mohair fabrics. Dry heat transfer through textiles may involve conduction through the fibrous phase, radiation through fabric interstices and convection of air within the structure. Factors that play a major role in heat transfer by conduction are fabric areal density (g/m2) and derived quantities such as cover factor and porosity. Convective heat transfer through fabrics is found in environmental conditions where there is wind-flow or the object is moving (e.g. running or walking). The thermal comfort properties of mohair fibers were objectively evaluated firstly in comparison with other textile fibers and secondly in a variety of fabric structures. Two sample sets were developed for this purpose, with fibre content, yarn structure and fabric design as main variables. SEM and microscopic images were obtained to closely examine the physical structures of the fibers and fabrics. Thermal comfort properties such as thermal resistance and thermal conductivity, as well as fabric thickness, were measured on the well-known Alambeta test instrument. Clothing insulation (clo) was calculated from the above. The thermal properties of fabrics under heat convection was evaluated using a laboratory model device developed at the Technical University of Liberec (referred to as the TP2-instrument). The effects of the different variables on fabric thermal comfort properties were analyzed statistically using TIBCO Statistica Software. The results showed that fabric structural properties, specifically sample thickness, played a significant role in determining the thermal comfort properties of the fabrics tested. It was found that regarding thermal resistance related to conductive heat flow, the effect of fiber type was not always statistically significant, probably as a result of the amount of trapped air within the fabric structure. The very low thermal conductivity of air, compared to that of the fibers, had a significant influence on the total conductivity and thermal resistance of the samples. This was confirmed by the high correlation of these factors with sample thickness. Regarding convective heat flow, the most important factor influencing the ability of the fabric to allow dry heat to move through the structure, was again fabric thickness. However, it would be wrong to totally disregard the effect of fiber composition on the thermal resistance of textile fabrics. In this study, the samples containing mohair or mohair/wool were consistently thicker than the others even though weaving parameters were kept constant. This can be ascribed to the physical properties of the mohair fibers that renders it exceptionally well towards trapping air among fibers (in a yarn) as well as among yarns (inside a fabric structure). The thicker structures trap more air to provide higher thermal insulation, but also prevent the free flow of air that allow thermal convection.

Keywords: mohair fabrics, convective heat transfer, thermal comfort properties, thermal resistance

Procedia PDF Downloads 123

Authors: Lesly Y Carmona-Sarabia, Luisa Barraza-Vergara, Vilmalí López-Mejías, Wandaliz Torres-García, Maribella Domenech-Garcia, Madeline Torres-Lugo

Abstract:

Biosensors are used in many applications providing real-time monitoring to treat long-term conditions. Thus, understanding the physicochemical properties and biological side effects on the skin of polymers (e. g., poly(methyl methacrylate), PMMA) employed in the fabrication of wearable biosensors is crucial for the selection of manufacturing materials within this field. The PMMA (hydrophobic and thermoplastic polymer) is commonly employed as a coating material or substrate in the fabrication of wearable devices. The cytotoxicityof PMMA (including residual monomers or degradation products) on the skin, in terms of cells and tissue, is required to prevent possible adverse effects (cell death, skin reactions, sensitization) on human health. Within this work, accelerated aging of PMMA (Mw ~ 15000) through thermal and photochemical degradation was under-taken. The accelerated aging of PMMA was carried out by thermal (200°C, 1h) and photochemical degradation (UV-Vis, 8-15d) adapted employing ISO protocols (ISO-10993-12, ISO-4892-1:2016, ISO-877-1:2009, ISO-188: 2011). In addition, in vitro cytotoxicity evaluation of PMMA degradation products was performed using NIH3T3 fibroblast cells to assess the response of skin tissues (in terms of cell viability) exposed with polymers utilized to manufacture wearable biosensors, such as PMMA. The PMMA (Mw ~ 15000) before and after accelerated aging experiments was characterized by thermal gravimetric analysis (TGA), differential scanning calorimetric (DSC), powder X-ray diffractogram (PXRD), and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) to determine and verify the successful degradation of this polymer under the specific conditions previously mention. The degradation products were characterized through nuclear magnetic resonance (NMR) to identify possible byproducts generated after the accelerated aging. Results demonstrated a percentage (%) weight loss between 1.5-2.2% (TGA thermographs) for PMMA after accelerated aging. The EDS elemental analysis reveals a 1.32 wt.% loss of carbon for PMMA after thermal degradation. These results might be associated with the amount (%) of PMMA degrade after the accelerated aging experiments. Furthermore, from the thermal degradation products was detected the presence of the monomer and methyl formate (low concentrations) and a low molecular weight radical (·COOCH3) in higher concentrations by NMR. In the photodegradation products, methyl formate was detected in higher concentrations. These results agree with the proposed thermal or photochemical degradation mechanisms found in the literature.1,2 Finally, significant cytotoxicity on the NIH3T3 cells was obtained for the thermal and photochemical degradation products. A decrease in cell viability by > 90% (stock solutions) was observed. It is proposed that the presence of byproducts (e.g. methyl formate or radicals such as ·COOCH₃) from the PMMA degradation might be responsible for the cytotoxicity observed in the NIH3T3 fibroblast cells. Additionally, experiments using skin models will be employed to compare with the NIH3T3 fibroblast cells model.

Keywords: biosensors, polymer, skin irritation, degradation products, cell viability

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Authors: Bronwen Wade

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Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

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Authors: D. Mokatsanyane, J. Jansen Van Rensburg

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This paper analyses the influence and impact of COVID-19 on major agricultural commodity prices in South Africa. According to a World Bank report, the agricultural sector in South Africa has been unable to reduce the domestic food crisis that has been occurring over the past years, hence the increased rate of poverty, which is currently at 55.5 percent as of April 2020. Despite the significance of this sector, empirical findings concluded that the agricultural sector now accounts for 1.88 percent of South Africa's gross domestic product (GDP). Suggesting that the agricultural sector's contribution to the economy has diminished. Despite the low contribution to GDP, this primary sector continues to play an essential role in the economy. Over the past years, multiple factors have contributed to the soaring commodities prices, namely, climate shocks, biofuel demand, demand and supply shocks, the exchange rate, speculation in commodity derivative markets, trade restrictions, and economic growth. The COVID-19 outbursts have currently disturbed the supply and demand of staple crops. To address the disruption, the government has exempted the agricultural sector from closure and restrictions on movement. The spread of COVID-19 has caused turmoil all around the world, but mostly in developing countries. According to Statistic South Africa, South Africa's economy decreased by seven percent in 2020. Consequently, this has arguably made the agricultural sector the most affected sector since slumped economic growth negatively impacts food security, trade, farm livelihood, and greenhouse gas emissions. South Africa is sensitive to the fruitfulness of global food chains. Restrictions in trade, reinforced sanitary control systems, and border controls have influenced food availability and prices internationally. The main objective of this study is to evaluate the behavior of agricultural commodity prices pre-and during-COVID to determine the impact of volatility drivers on these crops. Historical secondary data of spot prices for the top five major commodities, namely white maize, yellow maize, wheat, soybeans, and sunflower seeds, are analysed from 01 January 2017 to 1 September 2021. The timeframe was chosen to capture price fluctuations between pre-COVID-19 (01 January 2017 to 23 March 2020) and during-COVID-19 (24 March 2020 to 01 September 2021). The Generalised Autoregressive Conditional Heteroscedasticity (GARCH) statistical model will be used to measure the influence of price fluctuations. The results reveal that the commodity market has been experiencing volatility at different points. Extremely high volatility is represented during the first quarter of 2020. During this period, there was high uncertainty, and grain prices were very volatile. Despite the influence of COVID-19 on agricultural prices, the demand for these commodities is still existing and decent. During COVID-19, analysis indicates that prices were low and less volatile during the pandemic. The prices and returns of these commodities were low during COVID-19 because of the government's actions to respond to the virus's spread, which collapsed the market demand for food commodities.

Keywords: commodities market, commodity prices, generalised autoregressive conditional heteroscedasticity (GARCH), Price volatility, SAFEX

Procedia PDF Downloads 142

Authors: Aditya Sharma

Abstract:

Profits earned from relative strength strategy of zero-cost portfolio i.e. taking long position in winner stocks and short position in loser stocks from recent past are termed as momentum profits. In recent times, there has been lot of controversy and concern about sources of momentum profits, since the existence of these profits acts as an evidence of earning non-normal returns from publicly available information directly contradicting Efficient Market Hypothesis. Literature review reveals conflicting theories and differing evidences on sources of momentum profits. This paper aims at re-examining the sources of momentum profits in Indian capital markets. The study focuses on assessing the effect of fundamental as well as behavioral sources in order to understand the role of investor behavior in stock returns and suggest (if any) improvements to existing behavioral asset pricing models. This Paper adopts calendar time methodology to calculate momentum profits for 6 different strategies with and without skipping a month between ranking and holding period. For each J/K strategy, under this methodology, at the beginning of each month t stocks are ranked on past j month’s average returns and sorted in descending order. Stocks in upper decile are termed winners and bottom decile as losers. After ranking long and short positions are taken in winner and loser stocks respectively and both portfolios are held for next k months, in such manner that at any given point of time we have K overlapping long and short portfolios each, ranked from t-1 month to t-K month. At the end of period, returns of both long and short portfolios are calculated by taking equally weighted average across all months. Long minus short returns (LMS) are momentum profits for each strategy. Post testing for momentum profits, to study the role market risk plays in momentum profits, CAPM and Fama French three factor model adjusted LMS returns are calculated. In the final phase of studying sources, decomposing methodology has been used for breaking up the profits into unconditional means, serial correlations, and cross-serial correlations. This methodology is unbiased, can be used with the decile-based methodology and helps to test the effect of behavioral and fundamental sources altogether. From all the analysis, it was found that momentum profits do exist in Indian capital markets with market risk playing little role in defining them. Also, it was observed that though momentum profits have multiple sources (risk, serial correlations, and cross-serial correlations), cross-serial correlations plays a major role in defining these profits. The study revealed that momentum profits do have multiple sources however, cross-serial correlations i.e. the effect of returns of other stocks play a major role. This means that in addition to studying the investors` reactions to the information of the same firm it is also important to study how they react to the information of other firms. The analysis confirms that investor behavior does play an important role in stock returns and incorporating both the aspects of investors’ reactions in behavioral asset pricing models help make then better.

Keywords: investor behavior, momentum effect, sources of momentum, stock returns

Procedia PDF Downloads 282