Search results for: linear low density polyethylene

Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, a new set of metrics and measurement system is needed to better quantify the environmental, social and economic impacts of circular zero-waste design. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. Lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. In particular, the forestry-based plants which have been an invaluable outlet for woody biomass surplus, forest health improvement, timber production enhancement, and especially reduction of wildfire risk. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. It proposes not only models for integration of forestry, aquaculture, and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. Typically, life cycle analyses measure environmental impacts of different industrial production stages and are not integrated with indicators of material use circularity. This concept paper proposes the further development of a new set of metrics that would illustrate not only the typical life-cycle analysis (LCA), which shows the reduction in greenhouse gas (GHG) emissions, but also the zero-waste circularity measures of mass balance of the full value chain of the raw material and energy content/caloric value. These new measures quantify key impacts in making hyper-efficient use of natural resources and eliminating waste to landfills. The project utilized traditional LCA using the GREET model where the standalone biomass energy plant case was contrasted with the integration of a jet-fuel biorefinery. The methodology was then expanded to include combinations of co-hosts that optimize the life cycle of woody biomass from tree to energy, CO₂, heat and wood ash both from an energy/caloric value and for mass balance to include reuse of waste streams which are typically landfilled. The major findings of both a formal LCA study resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. If proven as a model, the expedited roll-out of these innovative scenarios can set a new standard for circular zero-waste projects that advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable bio-economy paradigm where waste streams become valuable inputs, supporting local and rural communities in simple, sustainable ways.

Keywords: bio-economy, biomass energy, financing, metrics

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Authors: Leonie Bradfield, Stephen Fityus, John Simmons

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

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

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Authors: Sree Bash Chandra Debnath, Didier Tonneau, Carole Fauquet, Agnes Tallet, Julien Darreon

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Purpose: Inorganic scintillating dosimetry is the most recent promising technique to solve several dosimetric issues and provide quality assurance in radiation therapy. Despite several advantages, the major issue of using scintillating detectors is the Cerenkov effect, typically induced in the visible emission range. In this context, the purpose of this research work is to evaluate the performance of a novel infrared inorganic scintillator detector (IR-ISD) in the radiation therapy treatment to ensure Cerenkov free signal and the best matches between the delivered and prescribed doses during treatment. Methods: A simple and small-scale infrared inorganic scintillating detector of 100 µm diameter with a sensitive scintillating volume of 2x10-6 mm3 was developed. A prototype of the dose verification system has been introduced based on PTIR1470/F (provided by Phosphor Technology®) material used in the proposed novel IR-ISD. The detector was tested on an Elekta LINAC system tuned at 6 MV/15MV and a brachytherapy source (Ir-192) used in the patient treatment protocol. The associated dose rate was measured in count rate (photons/s) using a highly sensitive photon counter (sensitivity ~20ph/s). Overall measurements were performed in IBATM water tank phantoms by following international Technical Reports series recommendations (TRS 381) for radiotherapy and TG43U1 recommendations for brachytherapy. The performance of the detector was tested through several dosimetric parameters such as PDD, beam profiling, Cerenkov measurement, dose linearity, dose rate linearity repeatability, and scintillator stability. Finally, a comparative study is also shown using a reference microdiamond dosimeter, Monte-Carlo (MC) simulation, and data from recent literature. Results: This study is highlighting the complete removal of the Cerenkov effect especially for small field radiation beam characterization. The detector provides an entire linear response with the dose in the 4cGy to 800 cGy range, independently of the field size selected from 5 x 5 cm² down to 0.5 x 0.5 cm². A perfect repeatability (0.2 % variation from average) with day-to-day reproducibility (0.3% variation) was observed. Measurements demonstrated that ISD has superlinear behavior with dose rate (R2=1) varying from 50 cGy/s to 1000 cGy/s. PDD profiles obtained in water present identical behavior with a build-up maximum depth dose at 15 mm for different small fields irradiation. A low dimension of 0.5 x 0.5 cm² field profiles have been characterized, and the field cross profile presents a Gaussian-like shape. The standard deviation (1σ) of the scintillating signal remains within 0.02% while having a very low convolution effect, thanks to lower sensitive volume. Finally, during brachytherapy, a comparison with MC simulations shows that considering energy dependency, measurement agrees within 0.8% till 0.2 cm source to detector distance. Conclusion: The proposed scintillating detector in this study shows no- Cerenkov radiation and efficient performance for several radiation therapy measurement parameters. Therefore, it is anticipated that the IR-ISD system can be promoted to validate with direct clinical investigations, such as appropriate dose verification and quality control in the Treatment Planning System (TPS).

Keywords: IR-Scintillating detector, dose measurement, micro-scintillators, Cerenkov effect

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Authors: Andrew Laming, John Hattie, Mark Wilson

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Nine Queensland Independent high schools provided deidentified student-matched ATAR and NAPLAN data for all 1217 ATAR graduates since 2020 who also sat NAPLAN at the school. Graduating cohorts from the nine schools contained a mean 100 ATAR graduates with previous NAPLAN data from their school. Excluded were vocational students (mean=27) and any ATAR graduates without NAPLAN data (mean=20). Based on Index of Community Socio-Educational Access (ICSEA) prediction, all schools had larger that predicted proportions of their students graduating with ATARs. There were an additional 173 students not releasing their ATARs to their school (14%), requiring this data to be inferred by schools. Gain was established by first converting each student’s strongest NAPLAN domain to a statewide percentile, then subtracting this result from final ATAR. The resulting ‘percentile shift’ was corrected for plausible ATAR participation at each NAPLAN level. Strongest NAPLAN domain had the highest correlation with ATAR (R2=0.58). RESULTS School mean NAPLAN scores fitted ICSEA closely (R2=0.97). Schools achieved a mean cohort gain of two ATAR rankings, but only 66% of students gained. This ranged from 46% of top-NAPLAN decile students gaining, rising to 75% achieving gains outside the top decile. The 54% of top-decile students whose ATAR fell short of prediction lost a mean 4.0 percentiles (or 6.2 percentiles prior to correction for regression to the mean). 71% of students in smaller schools gained, compared to 63% in larger schools. NAPLAN variability in each of the 13 ICSEA1100 cohorts was 17%, with both intra-school and inter-school variation of these values extremely low (0.3% to 1.8%). Mean ATAR change between years in each school was just 1.1 ATAR ranks. This suggests consecutive school cohorts and ICSEA-similar schools share very similar distributions and outcomes over time. Quantile analysis of the NAPLAN/ATAR revealed heteroscedasticity, but splines offered little additional benefit over simple linear regression. The NAPLAN/ATAR R2 was 0.33. DISCUSSION Standardised data like NAPLAN and ATAR offer educators a simple no-cost progression metric to analyse performance in conjunction with their internal test results. Change is expressed in percentiles, or ATAR shift per student, which is layperson intuitive. Findings may also reduce ATAR/vocational stream mismatch, reveal proportions of cohorts meeting or falling short of expectation and demonstrate by how much. Finally, ‘crashed’ ATARs well below expectation are revealed, which schools can reasonably work to minimise. The percentile shift method is neither value-add nor a growth percentile. In the absence of exit NAPLAN testing, this metric is unable to discriminate academic gain from legitimate ATAR-maximizing strategies. But by controlling for ICSEA, ATAR proportion variation and student mobility, it uncovers progression to ATAR metrics which are not currently publicly available. However achieved, ATAR maximisation is a sought-after private good. So long as standardised nationwide data is available, this analysis offers useful analytics for educators and reasonable predictivity when counselling subsequent cohorts about their ATAR prospects.  

Keywords: NAPLAN, ATAR, analytics, measurement, gain, performance, data, percentile, value-added, high school, numeracy, reading comprehension, variability, regression to the mean

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Helen S. Joyner (Melito), Mohammad Anvari

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Concentrated emulsions stabilized by proteins are systems of great importance in food, pharmaceutical and cosmetic products. Controlling emulsion rheology is critical for ensuring desired properties during formation, storage, and consumption of emulsion-based products. Studies on concentrated emulsions have focused on rheology of monodispersed systems. However, emulsions used for industrial applications are polydispersed in nature, and this polydispersity is regarded as an important parameter that also governs the rheology of the concentrated emulsions. Therefore, the objective of this study was to characterize rheological (small and large deformation behaviors) and microstructural properties of concentrated emulsions which were not truly monodispersed as usually encountered in food products such as margarines, mayonnaise, creams, spreads, and etc. The concentrated emulsions were prepared at different concentrations of fish gelatin (0.2, 0.4, 0.8% w/v in the whole emulsion system), oil-water ratio 80-20 (w/w), homogenization speed 10000 rpm, and 25oC. Confocal laser scanning microscopy (CLSM) was used to determine the microstructure of the emulsions. To prepare samples for CLSM analysis, FG solutions were stained by Fluorescein isothiocyanate dye. Emulsion viscosity profiles were determined using shear rate sweeps (0.01 to 100 1/s). The linear viscoelastic regions (LVRs) of the emulsions were determined using strain sweeps (0.01 to 100% strain) for each sample. Frequency sweeps were performed in the LVR (0.1% strain) from 0.6 to 100 rad/s. Large amplitude oscillatory shear (LAOS) testing was conducted by collecting raw waveform data at 0.05, 1, 10, and 100% strain at 4 different frequencies (0.5, 1, 10, and 100 rad/s). All measurements were performed in triplicate at 25oC. The CLSM results revealed that increased fish gelatin concentration resulted in more stable oil-in-water emulsions with homogeneous, finely dispersed oil droplets. Furthermore, the protein concentration had a significant effect on emulsion rheological properties. Apparent viscosity and dynamic moduli at small deformations increased with increasing fish gelatin concentration. These results were related to increased inter-droplet network connections caused by increased fish gelatin adsorption at the surface of oil droplets. Nevertheless, all samples showed shear-thinning and weak gel behaviors over shear rate and frequency sweeps, respectively. Lissajous plots, or plots of stress versus strain, and phase lag values were used to determine nonlinear behavior of the emulsions in LAOS testing. Greater distortion in the elliptical shape of the plots followed by higher phase lag values was observed at large strains and frequencies in all samples, indicating increased nonlinear behavior. Shifts from elastic-dominated to viscous dominated behavior were also observed. These shifts were attributed to damage to the sample microstructure (e.g. gel network disruption), which would lead to viscous-type behaviors such as permanent deformation and flow. Unlike the small deformation results, the LAOS behavior of the concentrated emulsions was not dependent on fish gelatin concentration. Systems with different microstructures showed similar nonlinear viscoelastic behaviors. The results of this study provided valuable information that can be used to incorporate concentrated emulsions in emulsion-based food formulations.

Keywords: concentrated emulsion, fish gelatin, microstructure, rheology

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Authors: Miguel Chen Austin, Denis Bruneau, Alain Sempey, Laurent Mora, Alain Sommier

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An experimental study in a Plus Energy House (PEH) prototype was conducted in August 2016. It aimed to highlight the energy charge and discharge of a concrete-slab floor submitted to the day-night-cycles heat exchanges in the southwestern part of France and to identify the heat transfer phenomena that take place in both processes: charge and discharge. The main features of this PEH, significant to this study, are the following: (i) a non-active slab covering the major part of the entire floor surface of the house, which include a concrete layer 68 mm thick as upper layer; (ii) solar window shades located on the north and south facades along with a large eave facing south, (iii) large double-glazed windows covering the majority of the south facade, (iv) a natural ventilation system (NVS) composed by ten automatized openings with different dimensions: four are located on the south facade, four on the north facade and two on the shed roof (north-oriented). To highlight the energy charge and discharge processes of the non-active slab, heat flux and temperature measurement techniques were implemented, along with airspeed measurements. Ten “measurement-poles” (MP) were distributed all over the concrete-floor surface. Each MP represented a zone of measurement, where air and surface temperatures, and convection and radiation heat fluxes, were intended to be measured. The airspeed was measured only at two points over the slab surface, near the south facade. To identify the heat transfer phenomena that take part in the charge and discharge process, some relevant dimensionless parameters were used, along with statistical analysis; heat transfer phenomena were identified based on this analysis. Experimental data, after processing, had shown that two periods could be identified at a glance: charge (heat gain, positive values) and discharge (heat losses, negative values). During the charge period, on the floor surface, radiation heat exchanges were significantly higher compared with convection. On the other hand, convection heat exchanges were significantly higher than radiation, in the discharge period. Spatially, both, convection and radiation heat exchanges are higher near the natural ventilation openings and smaller far from them, as expected. Experimental correlations have been determined using a linear regression model, showing the relation between the Nusselt number with relevant parameters: Peclet, Rayleigh, and Richardson numbers. This has led to the determination of the convective heat transfer coefficient and its comparison with the convective heat coefficient resulting from measurements. Results have shown that forced and natural convection coexists during the discharge period; more accurate correlations with the Peclet number than with the Rayleigh number, have been found. This may suggest that forced convection is stronger than natural convection. Yet, airspeed levels encountered suggest that it is natural convection that should take place rather than forced convection. Despite this, Richardson number values encountered indicate otherwise. During the charge period, air-velocity levels might indicate that none air motion occurs, which might lead to heat transfer by diffusion instead of convection.

Keywords: heat flux measurement, natural ventilation, non-active concrete slab, plus energy house

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Authors: Bijit Kalita, K. V. N. Surendra

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The pulley works under both compressive loading due to contacting belt in tension and central torque due to cause rotation. In a power transmission system, the belt pulley assemblies offer a contact problem in the form of two mating cylindrical parts. In this work, we modeled a pulley as a heavy two-dimensional circular disk. Stress analysis due to contact loading in the pulley mechanism is performed. Finite element analysis (FEA) is conducted for a pulley to investigate the stresses experienced on its inner and outer periphery. In most of the heavy-duty applications, most frequently used mechanisms to transmit power in applications such as automotive engines, industrial machines, etc. is Belt Drive. Usually, very heavy circular disks are used as pulleys. A pulley could be entitled as a drum and may have a groove between two flanges around the circumference. A rope, belt, cable or chain can be the driving element of a pulley system that runs over the pulley inside the groove. A pulley is experienced by normal and shear tractions on its contact region in the process of motion transmission. The region may be belt-pulley contact surface or pulley-shaft contact surface. In 1895, Hertz solved the elastic contact problem for point contact and line contact of an ideal smooth object. Afterward, this hypothesis is generally utilized for computing the actual contact zone. Detailed stress analysis in such contact region of such pulleys is quite necessary to prevent early failure. In this paper, the results of the finite element analyses carried out on the compressed disk of a belt pulley arrangement using fracture mechanics concepts are shown. Based on the literature on contact stress problem induced in the wide field of applications, generated stress distribution on the shaft-pulley and belt-pulley interfaces due to the application of high-tension and torque was evaluated in this study using FEA concepts. Finally, the results obtained from ANSYS (APDL) were compared with the Hertzian contact theory. The study is mainly focused on the fatigue life estimation of a rotating part as a component of an engine assembly using the most famous Paris equation. Digital Image Correlation (DIC) analyses have been performed using the open-source software. From the displacement computed using the images acquired at a minimum and maximum force, displacement field amplitude is computed. From these fields, the crack path is defined and stress intensity factors and crack tip position are extracted. A non-linear least-squares projection is used for the purpose of the estimation of fatigue crack growth. Further study will be extended for the various application of rotating machinery such as rotating flywheel disk, jet engine, compressor disk, roller disk cutter etc., where Stress Intensity Factor (SIF) calculation plays a significant role on the accuracy and reliability of a safe design. Additionally, this study will be progressed to predict crack propagation in the pulley using maximum tangential stress (MTS) criteria for mixed mode fracture.

Keywords: crack-tip deformations, contact stress, stress concentration, stress intensity factor

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Authors: Stephen Tullis, M. David DiDonato, Hong Sung Park

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Rowing boats (shells) are often steered by a small rudder operated by one of the backward-facing rowers; the attention required of that athlete then slightly decreases the power that that athlete can provide. Reducing the steering distraction would then increase the overall boat speed. Races are straight 2000 m courses with each boat in a 13.5 m wide lane marked by small (~15 cm) widely-spaced (~10 m) buoys, and the boat trajectory is affected by both cross-currents and winds. An optical buoy recognition and tracking system has been developed that provides the boat’s location and orientation with respect to the lane edges. This information is provided to the steering athlete as either: a simple overlay on a video display, or fed to a simplified autopilot system giving steering directions to the athlete or directly controlling the rudder. The system is then effectively a “lane-assist” device but with small, widely-spaced lane markers viewed from a very shallow angle due to constraints on camera height. The image is captured with a lightweight 1080p webcam, and most of the image analysis is done in OpenCV. The colour RGB-image is converted to a grayscale using the difference of the red and blue channels, which provides good contrast between the red/yellow buoys and the water, sky, land background and white reflections and noise. Buoy detection is done with thresholding within a tight mask applied to the image. Robust linear regression using Tukey’s biweight estimator of the previously detected buoy locations is used to develop the mask; this avoids the false detection of noise such as waves (reflections) and, in particular, buoys in other lanes. The robust regression also provides the current lane edges in the camera frame that are used to calculate the displacement of the boat from the lane centre (lane location), and its yaw angle. The interception of the detected lane edges provides a lane vanishing point, and yaw angle can be calculated simply based on the displacement of this vanishing point from the camera axis and the image plane distance. Lane location is simply based on the lateral displacement of the vanishing point from any horizontal cut through the lane edges. The boat lane position and yaw are currently fed what is essentially a stripped down marine auto-pilot system. Currently, only the lane location is used in a PID controller of a rudder actuator with integrator anti-windup to deal with saturation of the rudder angle. Low Kp and Kd values decrease unnecessarily fast return to lane centrelines and response to noise, and limiters can be used to avoid lane departure and disqualification. Yaw is not used as a control input, as cross-winds and currents can cause a straight course with considerable yaw or crab angle. Mapping of the controller with rudder angle “overall effectiveness” has not been finalized - very large rudder angles stall and have decreased turning moments, but at less extreme angles the increased rudder drag slows the boat and upsets boat balance. The full system has many features similar to automotive lane-assist systems, but with the added constraints of the lane markers, camera positioning, control response and noise increasing the challenge.

Keywords: auto-pilot, lane-assist, marine, optical, rowing

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Authors: Kavitha Madhu, Karthik K. Srinivasan, R. Sivanandan

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Indian traffic can be considered as mixed and heterogeneous due to the presence of various types of vehicles that operate with weak lane discipline. Consequently, vehicles can position themselves anywhere in the traffic stream depending on availability of gaps. The choice of lateral positioning is an important component in representing and characterizing mixed traffic. The field data provides evidence that the trajectory of vehicles in Indian urban roads have significantly varying longitudinal and lateral components. Further, the notion of headway which is widely used for homogeneous traffic simulation is not well defined in conditions lacking lane discipline. From field data it is clear that following is not strict as in homogeneous and lane disciplined conditions and neighbouring vehicles ahead of a given vehicle and those adjacent to it could also influence the subject vehicles choice of position, speed and acceleration. Given these empirical features, the suitability of using headway distributions to characterize mixed traffic in Indian cities is questionable, and needs to be modified appropriately. To address these issues, this paper attempts to analyze the time gap distribution between consecutive vehicles (in a time-sense) crossing a section of roadway. More specifically, to characterize the complex interactions noted above, the influence of composition, manoeuvre types, and lateral placement characteristics on time gap distribution is quantified in this paper. The developed model is used for evaluating various performance measures such as link speed, midblock delay and intersection delay which further helps to characterise the vehicular fuel consumption and emission on urban roads of India. Identifying and analyzing exact interactions between various classes of vehicles in the traffic stream is essential for increasing the accuracy and realism of microscopic traffic flow modelling. In this regard, this study aims to develop and analyze time gap distribution models and quantify it by lead lag pair, manoeuvre type and lateral position characteristics in heterogeneous non-lane based traffic. Once the modelling scheme is developed, this can be used for estimating the vehicle kilometres travelled for the entire traffic system which helps to determine the vehicular fuel consumption and emission. The approach to this objective involves: data collection, statistical modelling and parameter estimation, simulation using calibrated time-gap distribution and its validation, empirical analysis of simulation result and associated traffic flow parameters, and application to analyze illustrative traffic policies. In particular, video graphic methods are used for data extraction from urban mid-block sections in Chennai, where the data comprises of vehicle type, vehicle position (both longitudinal and lateral), speed and time gap. Statistical tests are carried out to compare the simulated data with the actual data and the model performance is evaluated. The effect of integration of above mentioned factors in vehicle generation is studied by comparing the performance measures like density, speed, flow, capacity, area occupancy etc under various traffic conditions and policies. The implications of the quantified distributions and simulation model for estimating the PCU (Passenger Car Units), capacity and level of service of the system are also discussed.

Keywords: lateral movement, mixed traffic condition, simulation modeling, vehicle following models

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Authors: Kuo Chieh Chao, Thishani Amarathunga, Sangam Shrestha

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Rainfall induced slope failures are one of the most damaging and disastrous natural hazards which occur frequently in the world. This type of sliding mainly occurs in the zone above the groundwater level in silty/sandy soils. When the rainwater begins to infiltrate into the vadose zone of the soil, the negative pore-water pressure tends to decrease and reduce the shear strength of soil material. Climate change has resulted in excessive and unpredictable rainfall in all around the world, resulting in landslides with dire consequences to human lives and infrastructure. Such problems could be overcome by examining in detail the causes for such slope failures and recommending effective repair plans for vulnerable locations by considering future climatic change. The selected area for this study is located in the road rehabilitation section from Maubara to Mota Ain road in Timor-Leste. Slope failures and cracks have occurred in 2013 and after repairs reoccurred again in 2017 subsequent to heavy rains. Both observed and future predicted climate data analyses were conducted to understand the severe precipitation conditions in past and future. Observed climate data were collected from NOAA global climate data portal. CORDEX data portal was used to collect Regional Climate Model (RCM) future predicted climate data. Both observed and RCM data were extracted to location-based data using ArcGIS Software. Linear scaling method was used for the bias correction of future data and bias corrected climate data were assigned to GeoStudio Software. Precipitations of wet seasons (December to March ) in 2007 to 2013 is higher than 2001-2006 period and it is more than nearly 40% higher precipitation than usual monthly average precipitation of 160mm.The results of seepage analyses which were carried out using SEEP/W model with observed climate, clearly demonstrated that the pore water pressure within the fill slope was significantly increased due to the increase of the infiltration during the wet season of 2013.One main Regional Climate Models (RCM) was analyzed in order to predict future climate variation under two Representative Concentration Pathways (RCPs).In the projected period of 76 years ahead from 2014, shows that the amount of precipitation is considerably getting higher in the future in both RCP 4.5 and RCP 8.5 emission scenarios. Critical pore water pressure conditions during 2014-2090 were used in order to recommend appropriate remediation methods. Results of slope stability analyses indicated that the factor of safety of the fill slopes was reduced from 1.226 to 0.793 during the dry season to wet season in 2013.Results of future slope stability which were obtained using SLOPE/W model for the RCP emissions scenarios depict that, the use of tieback anchors and geogrids in slope protection could be effective in increasing the stability of slopes to an acceptable level during the wet seasons. Moreover, methods and procedures like monitoring of slopes showing signs or susceptible for movement and installing surface protections could be used to increase the stability of slopes.

Keywords: climate change, precipitation, SEEP/W, SLOPE/W, unsaturated soil

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Authors: Rifilwe Victor Modiba, Stefan Hendric Foord

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Alien invasive plants (IAP’s) have considerable negative impacts on freshwater habitats and South Africa has implemented an innovative Work for Water (WfW) programme for the systematic removal of these plants aimed at, amongst other objectives, restoring biodiversity and ecosystem services in these threatened habitats. These restoration processes are expensive and have to be evidence-based. In this study in-stream macroinvertebrate and adult Odonata assemblages were used as indicators of restoration success by quantifying the response of biodiversity metrics for these two groups to the removal of IAP’s in a strategic water resource of South Africa that is extensively invaded by invasive alien plants (IAP’s). The study consisted of a replicated design that included 45 sampling units, viz. 15 invaded, 15 uninvaded and 15 cleared sites stratified across the upper reaches of six sub-catchments of the Luvuvhu river catchment, Limpopo Province. Cleared sites were only considered if they received at least two WfW treatments in the last 3 years. The Benthic macroinvertebrate and adult Odonate assemblages in each of these sampling were surveyed from between November and March, 2013/2014 and 2014/2015 respectively. Generalized Linear Models (GLM) with a log link function and Poisson error distribution were done for metrics (invaded, cleared, and uninvaded) whose residuals were not normally distributed or had unequal variance and for abundance. RDA was done for EPTO genera (Ephemeroptera, Plecoptera, Trichoptera and Odonata) and adult Odonata species abundance. GLM was done to for the abundance of Genera and Odonates that had the association with the RDA environmental factors. Sixty four benthic macroinvertebrate families, 57 EPTO genera, and 45 adult Odonata species were recorded across all 45 sampling units. There was no significant difference between the SASS5 total score, ASPT, and family richness of the three invasion classes. Although clearing only had a weak positive effect on the adult Odonate species richness it had a positive impact on DBI scores. These differences were mainly the result of significantly larger DBI scores in the cleared sites as compared to the invaded sites. Results suggest that water quality is positively impacted by repeated clearing pointing to the importance of follow up procedures after initial clearing. Adult Odonate diversity as measured by richness, endemicity, threat and distribution respond positively to all forms of the clearing. The clearing had a significant impact on Odonate assemblage structure but did not affect EPTO structure. Variation partitioning showed that 21.8% of the variation in EPTO assemblage can be explained by spatial and environmental variables, 16% of the variation in Odonate structure was explained by spatial and environmental variables. The response of the diversity metrics to clearing increased in significance at finer taxonomic resolutions, particularly of adult Odonates whose metrics significantly improved with clearing and whose structure responded to both invasion and clearing. The study recommends the use of DBI for surveying river health when hydraulic biotopes are poor.

Keywords: DBI, evidence-based conservation, EPTO, macroinvetebrates

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Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

Procedia PDF Downloads 119

Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

Procedia PDF Downloads 127

Authors: Carina Emminger, Umut D. Cakmak, Evrim Burkut, Rene Preuer, Ingrid Graz, Zoltan Major

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Damping accompanies us daily in everyday life and is used to protect (e.g., in shoes) and make our life more comfortable (damping of unwanted motion) and calm (noise reduction). In general, damping is the absorption of energy which is either stored in the material (vibration isolation systems) or changed into heat (vibration absorbers). In case of the last, the damping mechanism can be split in active, passive, as well as semi-active (a combination of active and passive). Active damping is required to enable an almost perfect damping over the whole application range and is used, for instance, in sport cars. In contrast, passive damping is a response of the material due to external loading. Consequently, the material composition has a huge influence on the damping behavior. For elastomers, the material behavior is inherent viscoelastic, temperature, and frequency dependent. However, passive damping is not adjustable during application. Therefore, it is of importance to understand the fundamental viscoelastic behavior and the dissipation capability due to external loading. The objective of this work is to assess the limitation and applicability of viscoelastic material damping for applications in which currently coil-over shock absorbers are utilized. Coil-over shock absorbers are usually made of various mechanical parts and incorporate fluids within the damper. These shock absorbers are well-known and studied in the industry, and when needed, they can be easily adjusted during their product lifetime. In contrary, dampers made of – ideally – a single material are more resource efficient, have an easier serviceability, and are easier manufactured. However, they lack of adaptability and adjustability in service. Therefore, a case study with a remote-controlled sport car was conducted. The original shock absorbers were redesigned, and the spring-dashpot system was replaced by both an elastomer and a thermoplastic-elastomer, respectively. Here, five different formulations of elastomers were used, including a pure and an iron-particle filled thermoplastic poly(urethan) (TPU) and blends of two different poly(dimethyl siloxane) (PDMS). In addition, the TPUs were investigated as full and hollow dampers to investigate the difference between solid and structured material. To get comparative results each material formulation was comprehensively characterized, by monotonic uniaxial compression tests, dynamic thermomechanical analysis (DTMA), and rebound resilience. Moreover, the new material-based shock absorbers were compared with spring-dashpot shock absorbers. The shock absorbers were analyzed under monotonic and cyclic loading. In addition, an impact loading was applied on the remote-controlled car to measure the damping properties in operation. A servo-hydraulic high-speed linear actuator was utilized to apply the loads. The acceleration of the car and the displacement of specific measurement points were recorded while testing by a sensor and high-speed camera, respectively. The results prove that elastomers are suitable in damping applications, but they are temperature and frequency dependent. This is a limitation in applicability of viscous material damper. Feasible fields of application may be in the case of micromobility, like bicycles, e-scooters, and e-skateboards. Furthermore, the viscous material damping could be used to increase the inherent damping of a whole structure, e.g., in bicycle-frames.

Keywords: damper structures, material damping, PDMS, TPU

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Authors: John Lachapelle

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Introduction: Neural stimulation is increasingly targeted toward treatment of back pain, PTSD, Parkinson’s disease, and for sensory perception. Sensory recording during stimulation is important in order to examine neural response to stimulation. Most neural amplifiers (headstages) focus on noise efficiency factor (NEF). Conversely, neural headstages need to handle artifacts from several sources including power lines, movement (EMG), and neural stimulation itself. In this work a layered approach to artifact rejection is used to reduce corruption of the neural ENG signal by 60dBv, resulting in recovery of sensory signals in rats and primates that would previously not be possible. Methods: The approach combines analog techniques to reduce and handle unwanted signal amplitudes. The methods include optimized (1) sensory electrode placement, (2) amplifier configuration, and (3) artifact blanking when necessary. The techniques together are like concentric moats protecting a castle; only the wanted neural signal can penetrate. There are two conditions in which the headstage operates: unwanted artifact < 50mV, linear operation, and artifact > 50mV, fast-settle gain reduction signal limiting (covered in more detail in a separate paper). Unwanted Signals at the headstage input: Consider: (a) EMG signals are by nature < 10mV. (b) 60 Hz power line signals may be > 50mV with poor electrode cable conditions; with careful routing much of the signal is common to both reference and active electrode and rejected in the differential amplifier with <50mV remaining. (c) An unwanted (to the neural recorder) stimulation signal is attenuated from stimulation to sensory electrode. The voltage seen at the sensory electrode can be modeled Φ_m=I_o/4πσr. For a 1 mA stimulation signal, with 1 cm spacing between electrodes, the signal is <20mV at the headstage. Headstage ASIC design: The front end ASIC design is designed to produce < 1% THD at 50mV input; 50 times higher than typical headstage ASICs, with no increase in noise floor. This requires careful balance of amplifier stages in the headstage ASIC, as well as consideration of the electrodes effect on noise. The ASIC is designed to allow extremely small signal extraction on low impedance (< 10kohm) electrodes with configuration of the headstage ASIC noise floor to < 700nV/rt-Hz. Smaller high impedance electrodes (> 100kohm) are typically located closer to neural sources and transduce higher amplitude signals (> 10uV); the ASIC low-power mode conserves power with 2uV/rt-Hz noise. Findings: The enhanced neural processing ASIC has been compared with a commercial neural recording amplifier IC. Chronically implanted primates at MGH demonstrated the presence of commercial neural amplifier saturation as a result of large environmental artifacts. The enhanced artifact suppression headstage ASIC, in the same setup, was able to recover and process the wanted neural signal separately from the suppressed unwanted artifacts. Separately, the enhanced artifact suppression headstage ASIC was able to separate sensory neural signals from unwanted artifacts in mouse-implanted peripheral intrafascicular electrodes. Conclusion: Optimizing headstage ASICs allow observation of neural signals in the presence of large artifacts that will be present in real-life implanted applications, and are targeted toward human implantation in the DARPA HAPTIX program.

Keywords: ASIC, biosensors, biomedical signal processing, biomedical sensors

Procedia PDF Downloads 316

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

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

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

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Authors: Jérémy Philippe, Lucien Baldas, Batoul Attar, Jean-Charles Mare

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The proposed communication deals with the research and development of a rotary direct-drive servo valve for aerospace applications. A key challenge of the project is to downsize the electromagnetic torque motor by reducing the torque required to drive the rotary spool. It is intended to optimize the spool and the sleeve geometries by combining a Computational Fluid Dynamics (CFD) approach with commercial optimization software. The present communication addresses an important phase of the project, which consists firstly of gaining confidence in the simulation results. It is well known that the force needed to pilot a sliding spool valve comes from several physical effects: hydraulic forces, friction and inertia/mass of the moving assembly. Among them, the flow force is usually a major contributor to the steady-state (or Root Mean Square) driving torque. In recent decades, CFD has gradually become a standard simulation tool for studying fluid-structure interactions. However, in the particular case of high-pressure valve design, the authors have experienced that the calculated overall hydraulic force depends on the parameterization and options used to build and run the CFD model. To solve this issue, the authors have selected the standard case of the linear spool valve, which is addressed in detail in numerous scientific references (analytical models, experiments, CFD simulations). The first CFD simulations run by the authors have shown that the evolution of the equivalent discharge coefficient vs. Reynolds number at the metering orifice corresponds well to the values that can be predicted by the classical analytical models. Oppositely, the simulated flow force was found to be quite different from the value calculated analytically. This drove the authors to investigate minutely the influence of the studied domain and the setting of the CFD simulation. It was firstly shown that the flow recirculates in the inlet and outlet channels if their length is not sufficient regarding their hydraulic diameter. The dead volume on the uncontrolled orifice side also plays a significant role. These examples highlight the influence of the geometry of the fluid domain considered. The second action was to investigate the influence of the type of mesh, the turbulence models and near-wall approaches, and the numerical solver and discretization scheme order. Two approaches were used to determine the overall hydraulic force acting on the moving spool. First, the force was deduced from the momentum balance on a control domain delimited by the valve inlet and outlet and the spool walls. Second, the overall hydraulic force was calculated from the integral of pressure and shear forces acting at the boundaries of the fluid domain. This underlined the significant contribution of the viscous forces acting on the spool between the inlet and outlet orifices, which are generally not considered in the literature. This also emphasized the influence of the choices made for the implementation of CFD calculation and results analysis. With the step-by-step process adopted to increase confidence in the CFD simulations, the authors propose a set of best practices and recommendations for the efficient use of CFD to design high-pressure spool valves.

Keywords: computational fluid dynamics, hydraulic forces, servovalve, rotary servovalve

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Authors: Vivek Garg, Brajendra S. Sengar, Gaurav Siddharth, Nisheka Anadkat, Amitesh Kumar, Shailendra Kumar, Shaibal Mukherjee

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CuInGaSe (CIGSe) is the dominant thin film solar cell technology. The band alignment of Buffer/CIGSe interface is one of the most crucial parameters for solar cell performance. In this article, the valence band offset (VBOff) and conduction band offset (CBOff) values of Cu(In0.70Ga0.30)Se/ 1 at.% Ga: Mg0.25Zn0.75O (GMZO) heterojunction, grown by dual ion beam sputtering system (DIBS), are calculated to understand the carrier transport mechanism at the heterojunction for the realization of all sputtered buffer-less solar cells. To determine the valence band offset (VBOff), ∆E_V at GMZO/CIGSe heterojunction interface, the standard method based on core-level photoemission is utilized. The value of ∆E_V can be evaluated by considering common core-level peaks. In our study, the values of (Valence band onset)VBOn, obtained by linear extrapolation method for GMZO and CIGSe films are calculated to be 2.86 and 0.76 eV. In the UPS spectra peak positions of Se 3d is observed in UPS spectra at 54.82 and 54.7 eV for CIGSe film and GMZO/CIGSe interface respectively, while the peak position of Mg 2p is observed at 50.09 and 50.12 eV for GMZO and GMZO/CIGSe interface respectively. The optical band gap of CIGSe and GMZO are obtained from absorption spectra procured from spectroscopic ellipsometry are 1.26 and 3.84 eV respectively. The calculated average values of ∆E_v and ∆E_C are estimated to be 2.37 and 0.21 eV, respectively, at room temperature. The calculated positive conduction band offset termed as a spike at the absorber junction is the required criterion for the high-efficiency solar cells for the efficient charge extraction from the junction. So we can conclude that the above study confirms GMZO thin films grown by the dual ion beam sputtering system are the suitable candidate for the CIGSe thin films based ultra-thin buffer-less solar cells. We investigated the band-offset properties at the GMZO/CIGSe heterojunction to verify the suitability of the GMZO for the realization of the buffer-less solar cells. The calculated average values of ∆E_V and ∆E_C are estimated to be 2.37 and 0.21 eV, respectively, at room temperature. The calculated positive conduction band offset termed as a spike at the absorber junction is the required criterion for the high-efficiency solar cells for the efficient charge extraction from the junction. So we can conclude that the above study confirms GMZO thin films grown by the dual ion beam sputtering system are the suitable candidate for the CIGSe thin films based ultra-thin buffer-less solar cells. Acknowledgment: We are thankful to DIBS, EDX, and XRD facility equipped at Sophisticated Instrument Centre (SIC) at IIT Indore. The authors B.S.S and A.K acknowledge CSIR and V.G acknowledge UGC, India for their fellowships. B.S.S is thankful to DST and IUSSTF for BASE Internship Award. Prof. Shaibal Mukherjee is thankful to DST and IUSSTF for BASE Fellowship and MEITY YFRF award. This work is partially supported by DAE BRNS, DST CERI, and DST-RFBR Project under India-Russia Programme of Cooperation in Science and Technology. We are thankful to Mukul Gupta for SIMS facility equipped at UGC-DAE Indore.

Keywords: CIGSe, DIBS, GMZO, solar cells, UPS

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Authors: Kanokwan Chancharoenchai

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Economic growth can be considered as an important element of countries’ development process. For developing countries, like Thailand, to ensure the continuous growth of the economy, the Thai government usually implements various policies to stimulate economic growth. They may take the form of fiscal, monetary, trade, and other policies. Because of these different aspects, understanding factors relating to economic growth could allow the government to introduce the proper plan for the future economic stimulating scheme. Consequently, this issue has caught interest of not only policymakers but also academics. This study, therefore, investigates explanatory variables for economic growth in Thailand from 2005 to 2017 with a total of 52 quarters. The findings would contribute to the field of economic growth and become helpful information to policymakers. The investigation is estimated throughout the production function with non-linear Cobb-Douglas equation. The rate of growth is indicated by the change of GDP in the natural logarithmic form. The relevant factors included in the estimation cover three traditional means of production and implicit effects, such as human capital, international activity and technological transfer from developed countries. Besides, this investigation takes the internal and external instabilities into account as proxied by the unobserved inflation estimation and the real effective exchange rate (REER) of the Thai baht, respectively. The unobserved inflation series are obtained from the AR(1)-ARCH(1) model, while the unobserved REER of Thai baht is gathered from naive OLS-GARCH(1,1) model. According to empirical results, the AR(|2|) equation which includes seven significant variables, namely capital stock, labor, the imports of capital goods, trade openness, the REER of Thai baht uncertainty, one previous GDP, and the world financial crisis in 2009 dummy, presents the most suitable model. The autoregressive model is assumed constant estimator that would somehow cause the unbias. However, this is not the case of the recursive coefficient model from the state space model that allows the transition of coefficients. With the powerful state space model, it provides the productivity or effect of each significant factor more in detail. The state coefficients are estimated based on the AR(|2|) with the exception of the one previous GDP and the 2009 world financial crisis dummy. The findings shed the light that those factors seem to be stable through time since the occurrence of the world financial crisis together with the political situation in Thailand. These two events could lower the confidence in the Thai economy. Moreover, state coefficients highlight the sluggish rate of machinery replacement and quite low technology of capital goods imported from abroad. The Thai government should apply proactive policies via taxation and specific credit policy to improve technological advancement, for instance. Another interesting evidence is the issue of trade openness which shows the negative transition effect along the sample period. This could be explained by the loss of price competitiveness to imported goods, especially under the widespread implementation of free trade agreement. The Thai government should carefully handle with regulations and the investment incentive policy by focusing on strengthening small and medium enterprises.

Keywords: autoregressive model, economic growth, state space model, Thailand

Procedia PDF Downloads 136

Authors: Jing Jin

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The incorporation of artificial intelligence (AI) and machine learning (ML) in aircraft manufacturing and aerospace supply chains leads to the generation of a substantial amount of data among various tiers of suppliers and OEMs. Identifying the high-quality information challenges decision-makers. The application of AI/ML models necessitates access to 'high-quality' information to yield desired outputs. However, the process of information sharing introduces complexities, including distortion through various communication channels and biases introduced by both human and AI entities. This phenomenon significantly influences the quality of information, impacting decision-makers engaged in configuring supply chain systems. Traditionally, distorted information is categorized as 'low-quality'; however, this study challenges this perception, positing that distorted information, contributing to stakeholder goals, can be deemed high-quality within supply chains. The main aim of this study is to identify and evaluate the dimensions of information quality crucial to the UK aerospace supply chain. Guided by a central research question, "What information quality dimensions are considered when defining information quality in the UK aerospace supply chain?" the study delves into the intricate dynamics of information quality in the aerospace industry. Additionally, the research explores the nuanced impact of information distortion on stakeholders' decision-making processes, addressing the question, "How does the information distortion phenomenon influence stakeholders’ decisions regarding information quality in the UK aerospace supply chain system?" This study employs deductive methodologies rooted in positivism, utilizing a cross-sectional approach and a mono-quantitative method -a questionnaire survey. Data is systematically collected from diverse tiers of supply chain stakeholders, encompassing end-customers, OEMs, Tier 0.5, Tier 1, and Tier 2 suppliers. Employing robust statistical data analysis methods, including mean values, mode values, standard deviation, one-way analysis of variance (ANOVA), and Pearson’s correlation analysis, the study interprets and extracts meaningful insights from the gathered data. Initial analyses challenge conventional notions, revealing that information distortion positively influences the definition of information quality, disrupting the established perception of distorted information as inherently low-quality. Further exploration through correlation analysis unveils the varied perspectives of different stakeholder tiers on the impact of information distortion on specific information quality dimensions. For instance, Tier 2 suppliers demonstrate strong positive correlations between information distortion and dimensions like access security, accuracy, interpretability, and timeliness. Conversely, Tier 1 suppliers emphasise strong negative influences on the security of accessing information and negligible impact on information timeliness. Tier 0.5 suppliers showcase very strong positive correlations with dimensions like conciseness and completeness, while OEMs exhibit limited interest in considering information distortion within the supply chain. Introducing social network analysis (SNA) provides a structural understanding of the relationships between information distortion and quality dimensions. The moderately high density of ‘information distortion-by-information quality’ underscores the interconnected nature of these factors. In conclusion, this study offers a nuanced exploration of information quality dimensions in the UK aerospace supply chain, highlighting the significance of individual perspectives across different tiers. The positive influence of information distortion challenges prevailing assumptions, fostering a more nuanced understanding of information's role in the Industry 4.0 landscape.

Keywords: information distortion, information quality, supply chain configuration, UK aerospace industry

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Authors: Stephanie J. Sedberry, William J. Gerace, Ian D. Beatty, Michael J. Kane

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Increasing the number of US university students who attain degrees in STEM and enter the STEM workforce is a national priority. Demographic groups vary in their rates of participation in STEM, and the US produces just 10% of the world’s science and engineering degrees (2014 figures). To address these gaps, we have developed and tested a practical, 30-minute, single-session classroom-based intervention to improve students’ self-efficacy and academic performance in University STEM courses. Self-efficacy is a psychosocial construct that strongly correlates with academic success. Self-efficacy is a construct that is internal and relates to the social, emotional, and psychological aspects of student motivation and performance. A compelling body of research demonstrates that university students’ self-efficacy beliefs are strongly related to their selection of STEM as a major, aspirations for STEM-related careers, and persistence in science. The development of an intervention to increase students’ self-efficacy is motivated by research showing that short, social-psychological interventions in education can lead to large gains in student achievement. Our intervention addresses STEM self-efficacy via two strong, but previously separate, lines of research into attitudinal/affect variables that influence student success. The first is ‘attributional retraining,’ in which students learn to attribute their successes and failures to internal rather than external factors. The second is ‘mindset’ about fixed vs. growable intelligence, in which students learn that the brain remains plastic throughout life and that they can, with conscious effort and attention to thinking skills and strategies, become smarter. Extant interventions for both of these constructs have significantly increased academic performance in the classroom. We developed a 34-item questionnaire (Likert scale) to measure STEM Self-efficacy, Perceived Academic Control, and Growth Mindset in a University STEM context, and validated it with exploratory factor analysis, Rasch analysis, and multi-trait multi-method comparison to coded interviews. Four iterations of our 42-week research protocol were conducted across two academic years (2017-2018) at three different Universities in North Carolina, USA (UNC-G, NC A&T SU, and NCSU) with varied student demographics. We utilized a quasi-experimental prospective multiple-group time series research design with both experimental and control groups, and we are employing linear modeling to estimate the impact of the intervention on Self-Efficacy,wth-Mindset, Perceived Academic Control, and final course grades (performance measure). Preliminary results indicate statistically significant effects of treatment vs. control on Self-Efficacy, Growth-Mindset, Perceived Academic Control. Analyses are ongoing and final results pending. This intervention may have the potential to increase student success in the STEM classroom—and ownership of that success—to continue in a STEM career. Additionally, we have learned a great deal about the complex components and dynamics of self-efficacy, their link to performance, and the ways they can be impacted to improve students’ academic performance.

Keywords: academic performance, affect variables, growth mindset, intervention, perceived academic control, psycho-social variables, self-efficacy, STEM, university classrooms

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Authors: A.Cifarelli, L. Boggioni, F. Bertini, L. Magon, M. Pitalieri, S. Losio

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Nowadays, the growing environmental awareness and the dwindling of fossil resources stimulate the polyurethane (PU) industry towards renewable polymers with low carbon footprint to replace the feed stocks from petroleum sources. The main challenge in this field consists in replacing high-performance products from fossil-fuel with novel synthetic polymers derived from 'green monomers'. The bio-polyols from plant oils have attracted significant industrial interest and major attention in scientific research due to their availability and biodegradability. Triglycerides rich in unsaturated fatty acids, such as soybean oil (SBO) and linseed oil (ELO), are particularly interesting because their structures and functionalities are tunable by chemical modification in order to obtain polymeric materials with expected final properties. Unfortunately, their use is still limited for processing or performance problems because a high functionality, as well as OH number of the polyols will result in an increase in cross-linking densities of the resulting PUs. The main aim of this study is to evaluate soy and linseed-based polyols as precursors to prepare prepolymers for the production of polyurethane foams (PUFs) or waterborne-polyurethanes (WPU) used as coatings. An effective reaction route is employed for its simplicity and economic impact. Indeed, bio-polyols were synthesized by a two-step method: epoxidation of the double bonds in vegetable oils and solvent-free ring-opening reaction of the oxirane with organic acids. No organic solvents have been used. Acids with different moieties (aliphatic or aromatics) and different length of hydrocarbon backbones can be used to customize polyols with different functionalities. The ring-opening reaction requires a fine tuning of the experimental conditions (time, temperature, molar ratio of carboxylic acid and epoxy group) to control the acidity value of end-product as well as the amount of residual starting materials. Besides, a Lewis base catalyst is used to favor the ring opening reaction of internal epoxy groups of the epoxidized oil and minimize the formation of cross-linked structures in order to achieve less viscous and more processable polyols with narrower polydispersity indices (molecular weight lower than 2000 g/mol⁻¹). The functionality of optimized polyols is tuned from 2 to 4 per molecule. The obtained polyols are characterized by means of GPC, NMR (¹H, ¹³C) and FT-IR spectroscopy to evaluate molecular masses, molecular mass distributions, microstructures and linkage pathways. Several polyurethane foams have been prepared by prepolymer method blending conventional synthetic polyols with new bio-polyols from soybean and linseed oils without using organic solvents. The compatibility of such bio-polyols with commercial polyols and diisocyanates is demonstrated. The influence of the bio-polyols on the foam morphology (cellular structure, interconnectivity), density, mechanical and thermal properties has been studied. Moreover, bio-based WPUs have been synthesized by well-established processing technology. In this synthesis, a portion of commercial polyols is substituted by the new bio-polyols and the properties of the coatings on leather substrates have been evaluated to determine coating hardness, abrasion resistance, impact resistance, gloss, chemical resistance, flammability, durability, and adhesive strength.

Keywords: bio-polyols, polyurethane foams, solvent free synthesis, waterborne-polyurethanes

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Authors: Alberto Fina, Samuele Colonna, Maria del Mar Bernal, Orietta Monticelli, Mauro Tortello, Renato Gonnelli, Julio Gomez, Chiara Novara, Guido Saracco

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Thermally conductive polymer nanocomposites are of high interest for several applications including low-temperature heat recovery, heat exchangers in a corrosive environment and heat management in electronics and flexible electronics. In this paper, the preparation of thermally conductive nanocomposites exploiting graphene-related materials is addressed, along with their thermal characterization. In particular, correlations between 1- chemical and physical features of the nanoflakes and 2- processing conditions with the heat conduction properties of nanocomposites is studied. Polymers are heat insulators; therefore, the inclusion of conductive particles is the typical solution to obtain a sufficient thermal conductivity. In addition to traditional microparticles such as graphite and ceramics, several nanoparticles have been proposed, including carbon nanotubes and graphene, for the use in polymer nanocomposites. Indeed, thermal conductivities for both carbon nanotubes and graphenes were reported in the wide range of about 1500 to 6000 W/mK, despite such property may decrease dramatically as a function of the size, number of layers, the density of topological defects, re-hybridization defects as well as on the presence of impurities. Different synthetic techniques have been developed, including mechanical cleavage of graphite, epitaxial growth on SiC, chemical vapor deposition, and liquid phase exfoliation. However, the industrial scale-up of graphene, defined as an individual, single-atom-thick sheet of hexagonally arranged sp2-bonded carbons still remains very challenging. For large scale bulk applications in polymer nanocomposites, some graphene-related materials such as multilayer graphenes (MLG), reduced graphene oxide (rGO) or graphite nanoplatelets (GNP) are currently the most interesting graphene-based materials. In this paper, different types of graphene-related materials were characterized for their chemical/physical as well as for thermal properties of individual flakes. Two selected rGOs were annealed at 1700°C in vacuum for 1 h to reduce defectiveness of the carbon structure. Thermal conductivity increase of individual GNP with annealing was assessed via scanning thermal microscopy. Graphene nano papers were prepared from both conventional RGO and annealed RGO flakes. Characterization of the nanopapers evidenced a five-fold increase in the thermal diffusivity on the nano paper plane for annealed nanoflakes, compared to pristine ones, demonstrating the importance of structural defectiveness reduction to maximize the heat dissipation performance. Both pristine and annealed RGO were used to prepare polymer nanocomposites, by melt reactive extrusion. Thermal conductivity showed two- to three-fold increase in the thermal conductivity of the nanocomposite was observed for high temperature treated RGO compared to untreated RGO, evidencing the importance of using low defectivity nanoflakes. Furthermore, the study of different processing paremeters (time, temperature, shear rate) during the preparation of poly (butylene terephthalate) nanocomposites evidenced a clear correlation with the dispersion and fragmentation of the GNP nanoflakes; which in turn affected the thermal conductivity performance. Thermal conductivity of about 1.7 W/mK, i.e. one order of magnitude higher than for pristine polymer, was obtained with 10%wt of annealed GNPs, which is in line with state of the art nanocomposites prepared by more complex and less upscalable in situ polymerization processes.

Keywords: graphene, graphene-related materials, scanning thermal microscopy, thermally conductive polymer nanocomposites

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Authors: Abdullah Nurus Salam Khan, Farhana Karim, Mohiuddin Ahsanul Kabir Chowdhury, S. Masum Billah, Nabila Zaka, Alexander Manu, Shams El Arifeen

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Globally, pre-eclampsia (PE) and ante-partum haemorrhage (APH) are two major causes of maternal mortality. Prompt identification and management of these conditions depend on competency of the birth attendants. Since these conditions are infrequent to be observed, clinical vignette based assessment could identify the extent of health worker’s competence in managing emergency obstetric care (EmOC). During June-August 2016, competence of 39 medical officers (MO) and 95 nurses working in obstetric ward of 15 government health facilities (3 district hospital, 12 sub-district hospital) was measured using clinical vignettes on PE and APH. The vignettes resulted in three outcome measures: total vignette scores, scores for diagnosis component, and scores for management component. T-test was conducted to compare mean vignette scores and linear regression was conducted to measure the strength and association of vignette scores with different cadres of health workers, facility’s readiness for EmOC and average annual utilization of normal deliveries after adjusting for type of health facility, health workers’ work experience, training status on managing maternal complication. For each of the seven component of EmOC items (administration of injectable antibiotics, oxytocic and anticonvulsant; manual removal of retained placenta, retained products of conception; blood transfusion and caesarean delivery), if any was practised in the facility within last 6 months, a point was added and cumulative EmOC readiness score (range: 0-7) was generated for each facility. The yearly utilization of delivery cases were identified by taking the average of all normal deliveries conducted during three years (2013-2015) preceding the survey. About 31% of MO and all nurses were female. Mean ( ± sd) age of the nurses were higher than the MO (40.0 ± 6.9 vs. 32.2 ± 6.1 years) and also longer mean( ± sd) working experience (8.9 ± 7.9 vs. 1.9 ± 3.9 years). About 80% health workers received any training on managing maternal complication, however, only 7% received any refresher’s training within last 12 months. The overall vignette score was 8.8 (range: 0-19), which was significantly higher among MO than nurses (10.7 vs. 8.1, p < 0.001) and the score was not associated with health facility types, training status and years of experience of the providers. Vignette score for management component (range: 0-9) increased with higher annual average number of deliveries in their respective working facility (adjusted β-coefficient 0.16, CI 0.03-0.28, p=0.01) and increased with each unit increase in EmOC readiness score (adjusted β-coefficient 0.44, CI 0.04-0.8, p=0.03). The diagnosis component of vignette score was not associated with any of the factors except it was higher among the MO than the nurses (adjusted β-coefficient 1.2, CI 0.13-2.18, p=0.03). Lack of competence in diagnosing and managing obstetric complication by the nurses than the MO is of concern especially when majority of normal deliveries are conducted by the nurses. Better EmOC preparedness of the facility and higher utilization of normal deliveries resulted in higher vignette score for the management component; implying the impact of experiential learning through higher case management. Focus should be given on improving the facility readiness for EmOC and providing the health workers periodic refresher’s training to make them more competent in managing obstetric cases.

Keywords: Bangladesh, emergency obstetric care, clinical vignette, competence of health workers

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Authors: Peter Falanga

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During the process of de-Stalinization that began in 1956 with the Twentieth Congress of the Soviet Communist Party, many filmmakers in Hungary chose to explore their country’s political discomforts by using Socialist Realism as a negative model against which they could react to the dominating ideology. A renewed national film industry and a more permissive political regime would allow filmmakers to take to task the plight of the preceding generation who had experienced the fatal political turmoil of both World Wars and the purges of Stalin. What follows is no longer the multigenerational unity found in Socialist Realism wherein both the old and the young embrace Stalin’s revolutionary optimism; instead, the protagonists are parentless, and thus their connection to the previous generation is partially severed. In these films, violent historical forces leave one generation to search for both a connection with their family’s past, and for moral guidance to direct their future. István Szabó’s Father (1966), Márta Mészáros Diary for My Children (1984), and Pál Gábor’s Angi Vera (1978) each consider the fraught relationship between successive generations through the lens of postwar youth. A characteristic each of their protagonist’s share is that they are all missing one or both parents, and cope with familial loss either through recalling memories of their parents in dream-like sequences, or, in the case of Angi Vera, through embracing the surrogate paternalism that the Communist Party promises to provide. This paper considers the argument these films present about the progress of Hungarian history, and how this topic is explored in more recent films that similarly focus on the transmission of generational values. Scholars such as László Strausz and John Cunningham have written on the continuous concern with the transmission of generational values in more recent films such as István Szabó’s Sunshine (1999), Béla Tarr’s Werckmeister Harmonies (2000), György Pálfi’s Taxidermia (2006), Ágnes Kocsis’ Pál Adrienn (2010), and Kornél Mundruczó’s Evolution (2021). These films, they argue, make intimate portrayals of the various sweeping political changes in Hungary’s history and question how these epochs or events have impacted Hungarian identities. If these films attempt to personalize historical shifts of Hungary, then what is the significance of featuring characters who have lost one or both parents? An attempt to understand this coherent trend in Hungarian cinema will profit from examining the earlier, celebrated films of Szabó, Mészáros, and Gábor, who inaugurated this preoccupation with generational values. The pervasive interplay of dreams and memory in their films invites an additional element to their argument concerning historical progression. This paper incorporates Richard Teniman’s notion of the “dialectics of memory” in which memory is in a constant process of negation and reinvention to explain why these Directors prefer to explore Hungarian identity through the disarranged form of psychological realism over the linear causality structure of historical realism.

Keywords: film theory, Eastern European Studies, film history, Eastern European History

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Authors: Tristance Kee

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

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

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Authors: Dilek Ozturk, Narin Ozturk, Zeliha Pala Kara, Engin Kaptan, Serap Sancar Bas, Nurten Ozsoy, Alper Okyar

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Most physiological processes oscillate in a rhythmic manner in mammals including metabolism and energy homeostasis, locomotor activity, hormone secretion, immune and endocrine system functions. Endocrine body rhythms are tightly regulated by the circadian timing system. The hypothalamic-pituitary-thyroid (HPT) axis is under circadian control at multiple levels from hypothalamus to thyroid gland. Since circadian timing system controls a variety of biological functions in mammals, circadian rhythms of biological functions may modify the drug tolerability/toxicity depending on the dosing time. Selective mTOR (mammalian target of rapamycin) inhibitor everolimus is an immunosuppressant and anticancer agent that is active against many cancers. It was also found to be active in medullary thyroid cancer. The aim of this study was to investigate the dosing time-dependent toxicity of everolimus on the thyroid gland and hormones in mice. Healthy C57BL/6J mice were synchronized with 12h:12h Light-Dark cycle (LD12:12, with Zeitgeber Time 0 – ZT0 – corresponding to Light onset). Everolimus was administered to male (5 mg/kg/day) and female mice (15 mg/kg/day) orally at ZT1-rest period- and ZT13-activity period- for 4 weeks; body weight loss, clinical signs and possible changes in serum thyroid hormone levels (TSH and free T4) were examined. Histological alterations in the thyroid gland were evaluated according to the following criteria: follicular size, colloid density and viscidity, height of the follicular epithelium and the presence of necrotic cells. The statistical significance between differences was analyzed with ANOVA. Study findings included everolimus-related diarrhea, decreased activity, decreased body weight gains, alterations in serum TSH levels, and histopathological changes in thyroid gland. Decreases in mean body weight gains were more evident in mice treated at ZT1 as compared to ZT13 (p < 0.001, for both sexes). Control tissue sections of thyroid glands exhibited well-organized histoarchitecture when compared to everolimus-treated groups. Everolimus caused histopathological alterations in thyroid glands in male (5 mg/kg, slightly) and female mice (15 mg/kg; p < 0.01 for both ZT as compared to their controls) irrespective of dosing-time. TSH levels were slightly decreased upon everolimus treatment at ZT13 in both males and females. Conversely, increases in TSH levels were observed when everolimus treated at ZT1 in both males (5 mg/kg; p < 0.05) and females (15 mg/kg; slightly). No statistically significant alterations in serum free T4 levels were observed. TSH and free T4 is clinically important thyroid hormones since a number of disease states have been linked to alterations in these hormones. Serum free T4 levels within the normal ranges in the presence of abnormal serum TSH levels in everolimus treated mice may suggest subclinical thyroid disease which may have repercussions on the cardiovascular system, as well as on other organs and systems. Our study has revealed the histological damage on thyroid gland induced by subacute everolimus administration, this effect was irrespective of dosing time. However, based on the body weight changes and clinical signs upon everolimus treatment, tolerability for the drug was best following dosing at ZT13 in both male and females. Yet, effects of everolimus on thyroid functions may deserve further studies regarding their clinical importance and chronotoxicity.

Keywords: circadian rhythm, chronotoxicity, everolimus, thyroid gland, thyroid hormones

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Authors: Piotr Jablonski, Krzysztof Mars, Wiktor Niemiec, Agnieszka Kyziol, Marek Hebda, Halina Krawiec, Karol Kyziol

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NiTi alloys, possessing unique mechanical properties such as pseudoelasticity and shape memory effect (SME), are suitable for many applications, including implanthology and biomedical devices. Additionally, these alloys have similar values of elastic modulus to those of human bones, what is very important in orthopedics. Unfortunately, the environment of physiological fluids in vivo causes unfavorable release of Ni ions, which in turn may lead to metalosis as well as allergic reactions and toxic effects in the body. For these reasons, the surface properties of NiTi alloys should be improved to increase corrosion resistance, taking into account biological properties, i.e. excellent biocompatibility. The prospective in this respect are layers based on DLC (Diamond-Like Carbon) structures, which are an attractive solution for many applications in implanthology. These coatings (DLC), usually obtained by PVD (Physical Vapour Deposition) and PA CVD (Plasma Activated Chemical Vapour Deposition) methods, can be also modified by doping with other elements like silicon, nitrogen, oxygen, fluorine, titanium and silver. These methods, in combination with a suitably designed structure of the layers, allow the possibility co-decide about physicochemical and biological properties of modified surfaces. Mentioned techniques provide specific physicochemical properties of substrates surface in a single technological process. In this work, the following types of layers based on DLC structures (incl. Si-DLC or Si/N-DLC) were proposed as prospective and attractive approach in surface functionalization of shape memory alloy. Nitinol substrates were modified in plasma conditions, using RF CVD (Radio Frequency Chemical Vapour Deposition). The influence of plasma treatment on the useful properties of modified substrates after deposition DLC layers doped with silica and/or nitrogen atoms, as well as only pre-treated in O2 NH3 plasma atmosphere in a RF reactor was determined. The microstructure and topography of the modified surfaces were characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM). Furthermore, the atomic structure of coatings was characterized by IR and Raman spectroscopy. The research also included the evaluation of surface wettability, surface energy as well as the characteristics of selected mechanical and biological properties of the layers. In addition, the corrosion properties of alloys after and before modification in the physiological saline were also investigated. In order to determine the corrosion resistance of NiTi in the Ringer solution, the potentiodynamic polarization curves (LSV – Linear Sweep Voltamperometry) were plotted. Furthermore, the evolution of corrosion potential versus immersion time of TiNi alloy in Ringer solution was performed. Based on all carried out research, the usefullness of proposed modifications of nitinol for medical applications was assessed. It was shown, inter alia, that the obtained Si-DLC layers on the surface of NiTi alloy exhibit a characteristic complex microstructure, increased surface development, which is an important aspect in improving the osteointegration of an implant. Furthermore, the modified alloy exhibits biocompatibility, the transfer of the metal (Ni, Ti) to Ringer’s solution is clearly limited.

Keywords: bioactive coatings, corrosion resistance, doped DLC structure, NiTi alloy, RF CVD

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Authors: Hongyan Chen, Megan Jobson, Andrew J. Masters, Maria Gonzalez-Miquel, Simon Halstead, Mayri Diaz de Rienzo

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Ionic liquids offer excellent advantages over conventional solvents for industrial extraction of metals from aqueous solutions, where such extraction processes bring opportunities for recovery, reuse, and recycling of valuable resources and more sustainable production pathways. Recent research on the use of ionic liquids for extraction confirms their high selectivity and low volatility, but there is relatively little focus on how their properties can be best exploited in practice. This work addresses gaps in research on process modelling and simulation, to support development, design, and optimisation of these processes, focusing on the separation of the highly similar transition metals, cobalt, and nickel. The study exploits published experimental results, as well as new experimental results, relating to the separation of Co and Ni using trihexyl (tetradecyl) phosphonium chloride. This extraction agent is attractive because it is cheaper, more stable and less toxic than fluorinated hydrophobic ionic liquids. This process modelling work concerns selection and/or development of suitable models for the physical properties, distribution coefficients, for mass transfer phenomena, of the extractor unit and of the multi-stage extraction flowsheet. The distribution coefficient model for cobalt and HCl represents an anion exchange mechanism, supported by the literature and COSMO-RS calculations. Parameters of the distribution coefficient models are estimated by fitting the model to published experimental extraction equilibrium results. The mass transfer model applies Newman’s hard sphere model. Diffusion coefficients in the aqueous phase are obtained from the literature, while diffusion coefficients in the ionic liquid phase are fitted to dynamic experimental results. The mass transfer area is calculated from the surface to mean diameter of liquid droplets of the dispersed phase, estimated from the Weber number inside the extractor. New experiments measure the interfacial tension between the aqueous and ionic phases. The empirical models for predicting the density and viscosity of solutions under different metal loadings are also fitted to new experimental data. The extractor is modelled as a continuous stirred tank reactor with mass transfer between the two phases and perfect phase separation of the outlet flows. A multistage separation flowsheet simulation is set up to replicate a published experiment and compare model predictions with the experimental results. This simulation model is implemented in gPROMS software for dynamic process simulation. The results of single stage and multi-stage flowsheet simulations are shown to be in good agreement with the published experimental results. The estimated diffusion coefficient of cobalt in the ionic liquid phase is in reasonable agreement with published data for the diffusion coefficients of various metals in this ionic liquid. A sensitivity study with this simulation model demonstrates the usefulness of the models for process design. The simulation approach has potential to be extended to account for other metals, acids, and solvents for process development, design, and optimisation of extraction processes applying ionic liquids for metals separations, although a lack of experimental data is currently limiting the accuracy of models within the whole framework. Future work will focus on process development more generally and on extractive separation of rare earths using ionic liquids.

Keywords: distribution coefficient, mass transfer, COSMO-RS, flowsheet simulation, phosphonium

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