Search results for: RNG model

Authors: Niloufar Yadgari

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GANs are a potent form of deep learning models that have found success in various fields. They are part of the larger group of generative techniques, which aim to produce authentic data using a probabilistic model that learns distributions from actual samples. In clinical settings, GANs have demonstrated improved abilities in capturing spatially intricate, nonlinear, and possibly subtle disease impacts in contrast to conventional generative techniques. This review critically evaluates the current research on how GANs are being used in imaging studies of different neurological conditions like Alzheimer's disease, brain tumors, aging of the brain, and multiple sclerosis. We offer a clear explanation of different GAN techniques for each use case in neuroimaging and delve into the key hurdles, unanswered queries, and potential advancements in utilizing GANs in this field. Our goal is to connect advanced deep learning techniques with neurology studies, showcasing how GANs can assist in clinical decision-making and enhance our comprehension of the structural and functional aspects of brain disorders.

Keywords: GAN, pathology, generative adversarial network, neuro imaging

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Authors: Murad Almadani, Khalil Abu-Hantash, Xinyu Wang, Herbert Jelinek, Kinda Khalaf

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Gait analysis is used by healthcare professionals as a tool to gain a better understanding of the movement impairment and track progress. In most circumstances, monitoring patients in their real-life environments with low-cost equipment such as cameras and wearable sensors is more important. Inertial sensors, on the other hand, cannot provide enough information on angular dynamics. This research offers a method for tracking 2D joint coordinates using cutting-edge vision algorithms and a single RGB camera. We provide an end-to-end comprehensive deep learning pipeline for marker-less gait parameter estimation, which, to our knowledge, has never been done before. To make our pipeline function in real-time for real-world applications, we leverage the AlphaPose human posture prediction model and a deep learning transformer. We tested our approach on the well-known GPJATK dataset, which produces promising results.

Keywords: gait analysis, human pose estimation, deep learning, real time gait estimation, AlphaPose, transformer

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Authors: Warren Jared, Bekker Jeremy, Salazar Guy, Jackman Katelyn, Linford Lauren

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Introduction: Positive Psychology research has burgeoned in the past 20 years; however, relatively few evidence-based resources to cultivate positive psychology skills are widely available to the general public. The positive psychology resources at www.mybestself101.org were developed to assist individuals in cultivating well-being using a variety of techniques, including gratitude, purpose, mindfulness, self-compassion, savoring, personal growth, and supportive relationships. These resources are empirically based and are built to be accessible to a broad audience. Key Objectives: This presentation highlights results from two recent randomized intervention studies of specific MBS101 learning modules. A key objective of this research is to empirically assess the efficacy and usability of these online resources. Another objective of this research is to encourage the broad dissemination of online positive psychology resources; thus, recommendations for further research and dissemination will be discussed. Methods: In both interventions, we recruited adult participants using social media advertisements. The participants completed several well-being and positive psychology construct-specific measures (savoring and self-compassion measures) at baseline and post-intervention. Participants in the experimental condition were also given a feedback questionnaire to gather qualitative data on how participants viewed the modules. Participants in the self-compassion study were randomly split between an experimental group, who received the treatment, and a control group, who were placed on a waitlist. There was no control group for the savoring study. Participants were instructed to read content on the module and practice savoring or self-compassion strategies listed in the module for a minimum of twenty minutes a day for 21 days. The intervention was semi-structured, as participants were free to choose which module activities they would complete from a menu of research-based strategies. Participants tracked which activities they completed and how long they spent on the modules each day. Results: In the savoring study, participants increased in savoring ability as indicated by multiple measures. In addition, participants increased in well-being from pre- to post-treatment. In the self-compassion study, repeated measures mixed model analyses revealed that compared to waitlist controls, participants who used the MBS101 self-compassion module experienced significant improvements in self-compassion, well-being, and body image with effect sizes ranging from medium to large. Attrition was 10.5% for the self-compassion study and 71% for the savoring study. Overall, participants indicated that the modules were generally helpful, and they particularly appreciated the specific strategy menus. Participants requested more structured course activities, more interactive content, and more practice activities overall. Recommendations: Mybestself101.org is an applied positive psychology research program that shows promise as a model for effectively disseminating evidence-based positive psychology resources that are both engaging and easily accessible. Considerable research is still needed, both to test the efficacy and usability of the modules currently available and to improve them based on participant feedback. Feedback received from participants in the randomized controlled trial led to the development of an expanded, 30-day online course called The Gift of Self-Compassion and an online mindfulness course currently in development called Mindfulness For Humans.

Keywords: positive psychology, intervention, online resources, self-compassion, dissemination, online curriculum

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Authors: Francesco Pandolfi, Georgios Baltzopoulos, Iunio Iervolino

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The impact of extreme winds on industrial assets and the built environment is gaining increasing attention from stakeholders, including the corporate insurance industry. This has led to a progressively more in-depth study of building vulnerability and fragility to wind. Wind vulnerability models are used in probabilistic risk assessment to relate a loss metric to an intensity measure of the natural event, usually a gust or a mean wind speed. In fact, vulnerability models can be integrated with the wind hazard, which consists of associating a probability to each intensity level in a time interval (e.g., by means of return periods) to provide an assessment of future losses due to extreme wind. This has also given impulse to the world- and regional-scale wind hazard studies.Another approach often adopted for the probabilistic description of building vulnerability to the wind is the use of fragility functions, which provide the conditional probability that selected building components will exceed certain damage states, given wind intensity. In fact, in wind engineering literature, it is more common to find structural system- or component-level fragility functions rather than wind vulnerability models for an entire building. Loss assessment based on component fragilities requires some logical combination rules that define the building’s damage state given the damage state of each component and the availability of a consequence model that provides the losses associated with each damage state. When risk calculations are based on numerical simulation of a structure’s behavior during extreme wind scenarios, the interaction of component fragilities is intertwined with the computational procedure. However, simulation-based approaches are usually computationally demanding and case-specific. In this context, the present work introduces the ExtReMe wind risk assESsment prototype Software, ERMESS, which is being developed at the University of Naples Federico II. ERMESS is a wind risk assessment tool for insurance applications to industrial facilities, collecting a wide assortment of available wind vulnerability models and fragility functions to facilitate their incorporation into risk calculations based on in-built or user-defined wind hazard data. This software implements an alternative method for building-specific risk assessment based on existing component-level fragility functions and on a number of simplifying assumptions for their interactions. The applicability of this alternative procedure is explored by means of an illustrative proof-of-concept example, which considers four main building components, namely: the roof covering, roof structure, envelope wall and envelope openings. The application shows that, despite the simplifying assumptions, the procedure can yield risk evaluations that are comparable to those obtained via more rigorous building-level simulation-based methods, at least in the considered example. The advantage of this approach is shown to lie in the fact that a database of building component fragility curves can be put to use for the development of new wind vulnerability models to cover building typologies not yet adequately covered by existing works and whose rigorous development is usually beyond the budget of portfolio-related industrial applications.

Keywords: component wind fragility, probabilistic risk assessment, vulnerability model, wind-induced losses

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Authors: Phawichsak Prapassornpitaya, Wanida Jinsart

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Daily monitoring PM₁₀ and PM₂.₅ data from 2007 to 2017 were analyzed to provide baseline data for prediction of the air pollution in Bangkok in the period of 2018 -2020. Two statistical models, Autoregressive Integrated Moving Average model (ARIMA) were used to evaluate the trends of pollutions. The prediction concentrations were tested by root means square error (RMSE) and index of agreement (IOA). This evaluation of the traffic PM₂.₅ and PM₁₀ were studied in association with the regulatory control and emission standard changes. The emission factors of particulate matter from diesel vehicles were decreased when applied higher number of euro standard. The trends of ambient air pollutions were expected to decrease. However, the Bangkok smog episode in February 2018 with temperature inversion caused high concentration of PM₂.₅ in the air environment of Bangkok. The impact of traffic pollutants was depended upon the emission sources, temperature variations, and metrological conditions.

Keywords: fine particulate matter, ARIMA, RMSE, Bangkok

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Authors: Andrea J. Alarcón, Maxime Daulat, Raydel Lorenzo, Renato P. Da Cunha, Pierre Breul

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Brazil has increased the use of renewable energy during the last years. Due to its sunshine and large surface area, photovoltaic panels founded in helical piles have been used to produce solar energy. Since Brazilian territory is mainly cover by highly porous structured tropical soils, when the helical piles are installed this structure is broken and its soil properties are modified. Considering the special characteristics of these soils, helical foundations behavior must be extensively studied. The first objective of this work is to determine the most suitable method to estimate the tensile capacity of helical piles in tropical soils. The second objective is to simulate the behavior of these piles in tropical soil. To obtain the rupture to assess load-displacement curves and the ultimate load, also a numerical modelling using Plaxis software was conducted. Lastly, the ultimate load and the load-displacements curves are compared with experimental values to validate the implemented model.

Keywords: finite element, helical piles, modelling, tropical soil, uplift capacity

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Authors: Sayed Kifayat Shah, Tang Zhongjun, Arfa Tanveer

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This study explores the significant heatwave effect on stock return and volatility. Using an ARCH/GARCH approach, it examines the relationship between the heatwave of Karachi, Islamabad, and Lahore on the KSE-100 index. It also explores the impact of heatwave on returns of the pharmaceutical and electronics industries. The empirical results confirm that that stock return is positively related to the heat waves of Karachi, negatively related to that of Islamabad, and is not affected by the heatwave of Lahore. Similarly, pharmaceutical and electronics indices are also positively related to heatwaves. These differences in results can be ascribed to the change in the behavior of the residents of that city. The outcomes are useful for understanding an investor's behavior reacting to weather and fluxes in stock price related to heatwave severity levels. The results can support investors in fixing biases in behavior.

Keywords: ARCH/GARCH model, heat wave, KSE-100 index, stock market return

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Authors: Jonathan Kissi, Baozhen Dai, Wisdom W. K. Pomegbe, Abdul-Basit Kassim

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Protecting patient’s digital information is a growing concern for healthcare institutions as people nowadays perpetually live their lives through telemedicine services. These telemedicine services have been confronted with several determinants that hinder their successful implementations, especially in developing countries. Identifying such determinants that influence the acceptance of telemedicine services is also a problem for healthcare professionals. Despite the tremendous increase in telemedicine services, its adoption, and use has been quite slow in some healthcare settings. Generally, it is accepted in today’s globalizing world that the success of telemedicine services relies on users’ satisfaction. Satisfying health professionals and patients are one of the crucial objectives of telemedicine success. This study seeks to investigate the determinants that influence health professionals’ intention to utilize telemedicine services in clinical activities in a sub-Saharan African country in West Africa (Ghana). A hybridized model comprising of health adoption models, including technology acceptance theory, diffusion of innovation theory, and protection of motivation theory, were used to investigate these quandaries. The study was carried out in four government health institutions that apply and regulate telemedicine services in their clinical activities. A structured questionnaire was developed and used for data collection. Purposive and convenience sampling methods were used in the selection of healthcare professionals from different medical fields for the study. The collected data were analyzed based on structural equation modeling (SEM) approach. All selected constructs showed a significant relationship with health professional’s behavioral intention in the direction expected from prior literature including perceived usefulness, perceived ease of use, management strategies, financial sustainability, communication channels, patients security threat, patients privacy risk, self efficacy, actual service use, user satisfaction, and telemedicine services systems securities threat. Surprisingly, user characteristics and response efficacy of health professionals were not significant in the hybridized model. The findings and insights from this research show that health professionals are pragmatic when making choices for technology applications and also their willingness to use telemedicine services. They are, however, anxious about its threats and coping appraisals. The identified significant constructs in the study may help to increase efficiency, quality of services, quality patient care delivery, and satisfactory user satisfaction among healthcare professionals. The implantation and effective utilization of telemedicine services in the selected hospitals will aid as a strategy to eradicate hardships in healthcare services delivery. The service will help attain universal health access coverage to all populace. This study contributes to empirical knowledge by identifying the vital factors influencing health professionals’ behavioral intentions to adopt telemedicine services. The study will also help stakeholders of healthcare to formulate better policies towards telemedicine service usage.

Keywords: telemedicine service, perceived usefulness, perceived ease of use, management strategies, security threats

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Authors: Roman Klas, František Pochylý, Pavel Rudolf

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This paper is focused on the CFD simulation of the radiaxial pump (i.e. mixed flow pump) with the aim to detect the reasons of Y-Q characteristic instability. The main reasons of pressure pulsations were detected by means of the analysis of velocity and pressure fields within the pump combined with the theoretical approach. Consequently, the modifications of spiral case and pump suction area were made based on the knowledge of flow conditions and the shape of dissipation function. The primary design of pump geometry was created as the base model serving for the comparison of individual modification influences. The basic experimental data are available for this geometry. This approach replaced the more complicated and with respect to convergence of all computational tasks more difficult calculation for the compressible liquid flow. The modification of primary pump consisted in inserting the three fins types. Subsequently, the evaluation of pressure pulsations, specific energy curves and visualization of velocity fields were chosen as the criterion for successful design.

Keywords: CFD, radiaxial pump, spiral case, stability

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Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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Authors: Ghada Mohammed, Mohamed Abdel Salam, Passent Tantawi

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The study aimed to investigate the impact of motives and barriers for Egyptian users to use Airbnb as a platform of peer-to-peer accommodation instead of hotels on overall attitude towards Airbnb. A sequential mixed-methods approach was adopted to this study and it proposed a comprehensive research model adapted from both literature and results of qualitative phase and then tested via an online questionnaire. The findings revealed that, motives, price, home benefits, privacy, and online reviews significantly explained overall attitude towards Airbnb, while the main barriers were respectively: perceived risk and distrust in which they can predict the overall attitude. While from the subjective norms, only social influence can predict behavioral intention to use Airbnb. The study may serve as a practical reference for practitioners as well as researchers when developing programs and strategies to manage Airbnb consumers' needs and decision process. Some of the main conclusions drawn from this study are that variety was one of the major things that users like about Airbnb and the most important motives are the functional ones like price rather than the experiential ones like authenticity.

Keywords: airbnb, barriers, disruptive innovation, motives, sharing economy

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Authors: Shuting Ji, Yueming Zhang, Jing Zhao

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The output error of the globoidal cam mechanism can be considered as a relevant indicator of mechanism performance, because it determines kinematic and dynamical behavior of mechanical transmission. Based on the differential geometry and the rigid body transformations, the mathematical model of surface geometry of the globoidal cam is established. Then we present the analytical expression of the output error (including the transmission error and the displacement error along the output axis) by considering different manufacture and assembly errors. The effects of the center distance error, the perpendicular error between input and output axes and the rotational angle error of the globoidal cam on the output error are systematically analyzed. A globoidal cam mechanism which is widely used in automatic tool changer of CNC machines is applied for illustration. Our results show that the perpendicular error and the rotational angle error have little effects on the transmission error but have great effects on the displacement error along the output axis. This study plays an important role in the design, manufacture and assembly of the globoidal cam mechanism.

Keywords: globoidal cam mechanism, manufacture error, transmission error, automatic tool changer

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Authors: Sudhir Kumar Tiwari

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The paper demonstrates a methodology that can be used at an early design stage of any conventional aircraft. This research activity assesses the feasibility derivation of methodology for aircraft loads estimation during the various phases of design for a transport category aircraft by utilizing potential of using commercial finite element analysis software, which may drive significant time saving. Early Design phase have limited data and quick changing configuration results in handling of large number of load cases. It is useful to idealize the aircraft as a connection of beams, which can be very accurately modelled using finite element analysis (beam elements). This research explores the correct approach towards idealizing an aircraft using beam elements. FEM Techniques like inertia relief were studied for implementation during course of work. The correct boundary condition technique envisaged for generation of shear force, bending moment and torque diagrams for the aircraft. The possible applications of this approach are the aircraft design process, which have been investigated.

Keywords: multi-disciplinary optimization, aircraft load, finite element analysis, stick model

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Authors: Daniel O'Shea, Mario M. Attard, David C. Kellermann

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In this paper, we propose a hyperelastic strain energy function that maps isotopic hyperelastic constitutive laws for the use of orthotropic materials without the use of structural tensors or any kind of fiber vector, or the use of standard invariants. In particular, we focus on neo-Hookean class of models and represent them using an invariant-free formulation. To achieve this, we revise the invariant-free formulation of isotropic hyperelasticity. The formulation uses quadruple contractions between fourth-order tensors, rather than scalar products of scalar invariants. We also propose a new decomposition of the orthotropic Hookean stiffness tensor into two fourth-order Lamé tensors that collapse down to the classic Lamé parameters for isotropic continua. The resulting orthotropic hyperelastic model naturally maintains all of the advanced properties of the isotropic counterparts, and similarly collapse back down to their isotropic form by nothing more than equality of parameters in all directions (isotropy). Comparisons are made with large strain experimental results for transversely isotropic rubber type materials under tension.

Keywords: finite strain, hyperelastic, invariants, orthotropic

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Authors: Suzan Anwar, Utkarsh Goyal

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Heart rate (HR) is a predictor of cardiovascular, cerebrovascular, and all-cause mortality in the general population, as well as in patients with cardio and cerebrovascular diseases. Machine learning (ML) significantly improves the accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment while avoiding unnecessary treatment of others. This research examines relationship between the individual's various heart health inputs like age, sex, cp, trestbps, thalach, oldpeaketc, and the likelihood of developing heart disease. Machine learning techniques like logistic regression and decision tree, and Python are used. The results of testing and evaluating the model using the Heart Failure Prediction Dataset show the chance of a person having a heart disease with variable accuracy. Logistic regression has yielded an accuracy of 80.48% without data handling. With data handling (normalization, standardscaler), the logistic regression resulted in improved accuracy of 87.80%, decision tree 100%, random forest 100%, and SVM 100%.

Keywords: heart rate, machine learning, SVM, decision tree, logistic regression, random forest

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Authors: Surinder Deswal, Mahesh Pal

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The paper investigates the potential of support vector machines based regression approach to model the mass transfer capacity of multiple plunging jets, both vertical (θ = 90°) and inclined (θ = 60°). The data set used in this study consists of four input parameters with a total of eighty eight cases. For testing, tenfold cross validation was used. Correlation coefficient values of 0.971 and 0.981 (root mean square error values of 0.0025 and 0.0020) were achieved by using polynomial and radial basis kernel functions based support vector regression respectively. Results suggest an improved performance by radial basis function in comparison to polynomial kernel based support vector machines. The estimated overall mass transfer coefficient, by both the kernel functions, is in good agreement with actual experimental values (within a scatter of ±15 %); thereby suggesting the utility of support vector machines based regression approach.

Keywords: mass transfer, multiple plunging jets, support vector machines, ecological sciences

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Authors: Yaser S. Kishawi, Sadi R. Ali

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Part of Palestine, Gaza Strip (365 km2 and 1.8 million inhabitants) is considered a semi-arid zone relies solely on the Coastal Aquifer. The coastal aquifer is only source of water with only 5-10% suitable for human use. This barely cover the domestic and agricultural needs of Gaza Strip. Palestinian Water Authority Strategy is finding non-conventional water resource from treated wastewater to cover agricultural requirements and serve the population. A new WWTP project is to replace the old-overloaded Biet Lahia WWTP. The project consists of three parts; phase A (pressure line & infiltration basins - IBs), phase B (a new WWTP) and phase C (Recovery and Reuse Scheme – RRS – to capture the spreading plume). Currently, only phase A is functioning. Nearly 23 Mm3 of partially treated wastewater were infiltrated into the aquifer. Phase B and phase C witnessed many delays and this forced a reassessment of the RRS original design. An Environmental Management Plan was conducted from Jul 2013 to Jun 2014 on 13 existing monitoring wells surrounding the project location. This is to measure the efficiency of the SAT system and the spread of the contamination plume with relation to the efficiency of the proposed RRS. Along with the proposed location of the 27 recovery wells as part of the proposed RRS. The results of monitored wells were assessed compared with PWA baseline data. This was put into a groundwater model to simulate the plume to propose the best suitable solution to the delays. The redesign mainly manipulated the pumping rate of wells, proposed locations and functioning schedules (including wells groupings). The proposed simulations were examined using visual MODFLOW V4.2 to simulate the results. The results of monitored wells were assessed based on the location of the monitoring wells related to the proposed recovery wells locations (200m, 500m and 750m away from the IBs). Near the 500m line (the first row of proposed recovery wells), an increase of nitrate (from 30 to 70mg/L) compare to a decrease in Chloride (1500 to below 900mg/L) was found during the monitoring period which indicated an expansion of plume to this distance. On this rate with the required time to construct the recovery scheme, keeping the original design the RRS will fail to capture the plume. Based on that many simulations were conducted leading into three main scenarios. The scenarios manipulated the starting dates, the pumping rate and the locations of recovery wells. A simulation of plume expansion and path-lines were extracted from the model monitoring how to prevent the expansion towards the nearby municipal wells. It was concluded that the location is the most important factor in determining the RRS efficiency. Scenario III was adopted and showed an effective results even with a reduced pumping rates. This scenario proposed adding two additional recovery wells in a location beyond the 750m line to compensate the delays and effectively capture the plume. A continuous monitoring program for current and future monitoring wells should be in place to support the proposed scenario and ensure maximum protection.

Keywords: soil aquifer treatment, recovery and reuse scheme, infiltration basins, north gaza

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Authors: Sana Fatima, Paul Sadler, Jon Cooper, David Mendel, Ayesha Jameel

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Background: Neurodiversity refers to intrinsic differences between human minds and encompasses dyspraxia, dyslexia, attention deficit hyperactivity disorder, dyscalculia, autism spectrum disorder, and Tourette syndrome. There is increasing recognition of neurodiversity in relation to disability/diversity in medical education and the associated impact on training, career progression, and personal and professional wellbeing. In addition, documented and anecdotal evidence suggests that medical educators and training providers in all four nations (UK) are increasingly concerned about understanding neurodiversity and identifying and providing support for neurodivergent trainees. Summary of Work: A national Neurodiversity Task and Finish group were established to survey Health Education England local office Professional Support teams about insights into infrastructure, training for educators, triggers for assessment, resources, and intervention protocols. This group drew from educational leadership, professional and personal neurodiverse expertise, occupational medicine, employer human resource, and trainees. An online, exploratory survey was conducted to gather insights from supervisors and trainers across England using the Professional Support Units' platform. Summary of Results: This survey highlighted marked heterogeneity in the identification, assessment, and approaches to support and management of neurodivergent trainees and highlighted a 'deficit' approach to neurodiversity. It also demonstrated a paucity of educational and protocol resources for educators and supervisors in supporting neurodivergent trainees. Discussions and Conclusions: In phase one, we focused on faculty development. An educational repository for all supervising trainees using a thematic approach was formalised. This was guided by our survey findings specific for neurodiversity and took a triple 'A' approach: awareness, assessment, and action. This is further supported by video material incorporating stories in training as well as mobile workshops for trainers for more immersive learning. The subtle theme from both the survey and Task and finish group suggested a move away from deficit-focused methods toward a positive holistic, interdisciplinary approach within a biopsychosocial framework. Contributions: 1. Faculty Knowledge and basic understanding of neurodiversity are key to supporting trainees with known or underlying Neurodiverse conditions. This is further complicated by challenges around non-disclosure, varied presentations, stigma, and intersectionality. 2. There is national (and international) inconsistency in the approach to how trainees are managed once a neurodiverse condition is suspected or diagnosed. 3. A carefully constituted and focussed Task and Finish group can rapidly identify national inconsistencies in neurodiversity and implement rapid educational interventions. 4. Nuanced findings from surveys and discussion can reframe the approach to neurodiversity; from a medical model to a more comprehensive, asset-based, biopsychosocial model of support, fostering a cultural shift, accepting 'diversity' in all its manifestations, visible and hidden.

Keywords: neurodiversity, professional support, human considerations, workplace wellbeing

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Authors: Armenuhi Ghazaryan, Qnarik Poghosyan, Tadevos Markosyan

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We have considered the high-order harmonic generation in-plane graphene quantum dots of hexagonal shape by the independent quasiparticle approximation-tight binding model. We have investigated how such a nonlinear effect is affected by a strong optical wave field, quantum dot typical band gap and lateral size, and dephasing processes. The equation of motion for the density matrix is solved by performing the time integration with the eight-order Runge-Kutta algorithm. If the optical wave frequency is much less than the quantum dot intrinsic band gap, the main aspects of multiphoton high harmonic emission in quantum dots are revealed. In such a case, the dependence of the cutoff photon energy on the strength of the optical pump wave is almost linear. But when the wave frequency is comparable to the bandgap of the quantum dot, the cutoff photon energy shows saturation behavior with an increase in the wave field strength.

Keywords: strong wave field, multiphoton, bandgap, wave field strength, nanostructure

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Authors: Provides Ng

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Platform economy is a peer-to-peer model of distributing resources facilitated by community-based digital platforms. In recent years, digital platforms are rapidly reconfiguring the public realm using hyper-personalisation techniques. This paper aims at investigating how urban planning can leapfrog into the digital age to help relieve the rising tension of the global issue of labour flow; it discusses the means to transfer techniques of hyper-personalisation into urban planning for plasticity using platform technologies. This research first denotes the limitations of the current system of urban residency, where the system maintains itself on the circulation of documents, which are data on paper. Then, this paper tabulates how some of the institutions around the world, both public and private, digitise data, and streamline communications between a network of systems and citizens using platform technologies. Subsequently, this paper proposes ways in which hyper-personalisation can be utilised to form a digital planning platform. Finally, this paper concludes by reviewing how the proposed strategy may help to open up new ways of thinking about how we affiliate ourselves with cities.

Keywords: platform urbanism, hyper-personalisation, digital inventory, urban accessibility

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Authors: Azza A. Ali, Doaa M. Abd El-Latif, Amany M. Gad, Yasser M. A. Elnahas, Karema Abu-Elfotuh

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Background: Exposure to Aluminium (Al) has been increased recently. It is found in food products, food additives, drinking water, cosmetics and medicines. Chronic consumption of Al causes oxidative stress and has been implicated in several chronic disorders. Liver is considered as the major site for detoxification while kidney is involved in the elimination of toxic substances and is a target organ of metal toxicity. Social isolation (SI) or protein malnutrition (PM) also causes oxidative stress and has negative impact on Al-induced nephrotoxicity as well as hepatotoxicity. Coenzyme Q10 (CoQ10) is a powerful intracellular antioxidant with mitochondrial membrane stabilizing ability while wheat grass is a natural product with antioxidant, anti-inflammatory and different protective activities, cocoa is also potent antioxidants and can protect against many diseases. They provide different degrees of protection from the impact of oxidative stress. Objective: To study the impact of social isolation together with Protein malnutrition on nephro- and hepato-toxicity induced by chronic Al exposure in rats as well as to investigate the postulated protection using a combination of Co Q10, wheat grass and cocoa. Methods: Eight groups of rats were used; four served as protected groups and four as un-protected. Each of them received daily for five weeks AlCl3 (70 mg/kg, IP) for Al-toxicity model groups except one group served as control. Al-toxicity model groups were divided to Al-toxicity alone, SI- associated PM (10% casein diet) and Al- associated SI&PM groups. Protection was induced by oral co-administration of CoQ10 (200mg/kg), wheat grass (100mg/kg) and cocoa powder (24mg/kg) combination together with Al. Biochemical changes in total bilirubin, lipids, cholesterol, triglycerides, glucose, proteins, creatinine and urea as well as alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), lactate deshydrogenase (LDH) were measured in serum of all groups. Specimens of kidney and liver were used for assessment of oxidative parameters (MDA, SOD, TAC, NO), inflammatory mediators (TNF-α, IL-6β, nuclear factor kappa B (NF-κB), Caspase-3) and DNA fragmentation in addition to evaluation of histopathological changes. Results: SI together with PM severely enhanced nephro- and hepato-toxicity induced by chronic Al exposure. Co Q10, wheat grass and cocoa combination showed clear protection against hazards of Al exposure either alone or when associated with SI&PM. Their protection were indicated by the significant decrease in Al-induced elevations in total bilirubin, lipids, cholesterol, triglycerides, glucose, creatinine and urea levels as well as ALT, AST, ALP, LDH. Liver and kidney of the treated groups also showed significant decrease in MDA, NO, TNF-α, IL-6β, NF-κB, caspase-3 and DNA fragmentation, together with significant increase in total proteins, SOD and TAC. Biochemical results were confirmed by the histopathological examinations. Conclusion: SI together with PM represents a risk factor in enhancing nephro- and hepato-toxicity induced by Al in rats. CoQ10, wheat grass and cocoa combination provide clear protection against nephro- and hepatotoxicity as well as the consequent degenerations induced by chronic Al-exposure even when associated with the risk of SI together with PM.

Keywords: aluminum, nephrotoxicity, hepatotoxicity, isolation and protein malnutrition, coenzyme Q10, wheatgrass, cocoa, nutrients combinations

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Authors: Laura Brennan, Ram Balakumar

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ChatGPT has been developed by Open AI (Nov 2022) as a powerful artificial intelligence (AI) language model which has been designed to produce human-like text from user written prompts. To gain the most from the system, user written prompts must give context specific information. This article aims to give guidance on how to optimise the ChatGPT system in the context of education for otolaryngology. Otolaryngology is a specialist field which sees little time dedicated to providing education to both medical students and doctors. Additionally, otolaryngology trainees have seen a reduction in learning opportunities since the COVID-19 pandemic. In this article we look at these various barriers to medical education in Otolaryngology training and suggest ways that ChatGPT can overcome them and assist in simulation-based training. Examples provide how this can be achieved using the Authors’ experience to further highlight the practicalities. What this article has found is that while ChatGPT cannot replace traditional mentorship and practical surgical experience, it can serve as an invaluable supplementary resource to simulation based medical education in Otolaryngology.

Keywords: artificial intelligence, otolaryngology, surgical training, medical education

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Authors: Derrick Boakye Boadu, Zahra Fakhri

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Transformational leaders are the catalyst of change and focus more importantly on members or followers. Involvement of transformational leadership style in organizational structures can provide interesting nuances to the implementation and enhancement of citizen and customer participation mechanisms in an organization regardless of the time consuming, cost, and delaying process of analyzing the feedback of workers and citizens/customers which stifles good outcome of organization’s department performance. It posits that transformational leadership has a positive direct effect on organization-departmental performance and the intervening role of citizen and customer participation and internal communication. Using the NASP-IV 2007 data, the article finds support for the five hypotheses in a structural equation model, and the findings show that transformational leadership does have a direct impact on organizational-departmental performance a partial mediation effect of the relationship through the role of internal communication and citizen and customer participation.  

Keywords: transformational leaders, departmental performance, internal communication, citizen/customer participation

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Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

Abstract:

With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

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Authors: Elham Davoodi, Kylie King, Laura Jobson

Abstract:

Depression is one of the most common mental health disorders. Self-silencing theory adopts a socio-cultural lens to examine the development and maintenance of depression. Self-silencing can be a vulnerability factor in depression, and personality vulnerabilities (e.g., perfectionism) and moral emotions (e.g., guilt) are strongly related to self-silencing and depression. Yet, the relationships between all four variables among different cultural groups are not clear. We aimed to address this gap by examining whether perfectionism and depression are related indirectly through self-silencing and guilt and whether cultural group moderates these associations. Participants (N=288) from either European Australian or Iranian Australian cultural backgrounds completed an online survey assessing self-silencing, guilt, perfectionism, and depression. First, we found an indirect relationship between perfectionism and depression through self-silencing. Second, using a serial mediation model, we found an indirect association between perfectionism and depression through self-silencing and guilt. There was no evidence that cultural groups moderated these indirect relationships. Our findings leave an important question for future longitudinal studies to answer; that is, whether the association between self-silencing and depression is oversimplified and whether moral emotions in this relationship have been overlooked.

Keywords: perfectionism, depression, self-silencing, culture, guilt

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Authors: Adji Achmad Rinaldo Fernandes

Abstract:

The research was conducted to apply semiparametric SEM modeling to the timeliness of paying credit. Semiparametric SEM is structural modeling in which two combined approaches of parametric and nonparametric approaches are used. The analysis method in this research is semiparametric SEM with a nonparametric approach using a truncated spline. The data in the study were obtained through questionnaires distributed to Bank X mortgage debtors and are confidential. The study used 3 variables consisting of one exogenous variable, one intervening endogenous variable, and one endogenous variable. The results showed that (1) the effect of capacity and willingness to pay variables on timeliness of payment is significant, (2) modeling the capacity variable on willingness to pay also produces a significant estimate, (3) the effect of the capacity variable on the timeliness of payment variable is not influenced by the willingness to pay variable as an intervening variable, (4) the R^2 value of 0.763 or 76.33% indicates that the model has good predictive relevance.

Keywords: structural equation modeling semiparametric, credit bank, accuracy of payment time, willingness to pay

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Authors: Han Bai, Tong Zhang, Lemei Yu, Doudou Xie, Liang Zhao

Abstract:

Road transition design on freeway tunnel entrance and exit is one vital factor in realizing smooth transition and improving traveling safety for vehicles. The goal of this research is to develop a horizontal road transition design tool that considers the transition technology of traffic capacity consistency to explore its accommodation mechanism. The influencing factors of capacity are synthesized and a modified capacity calculation model focusing on the influence of road width and lateral clearance is developed based on the VISSIM simulation to calculate the width of road transition sections. To keep the traffic capacity consistency, the right side of the transition section of the tunnel entrance and exit is divided into three parts: front arc, an intermediate transition section, and end arc; an optimization design on each transition part is conducted to improve the capacity stability and horizontal alignment transition. A case study on the Panlong Tunnel in Ji-Qing freeway illustrates the application of the tool.

Keywords: traffic safety, road transition, freeway tunnel, traffic capacity

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Authors: Fariea Bakul, Chhanda Karmaker

Abstract:

The present study was designed to investigate the effects of parental bonding on adult’s cognitive emotion regulation and also to investigate gender differences in parental bonding and cognitive emotion regulation. Data were collected by using convenience sampling technique from 100 adult students (50 males and 50 females) of different universities of Dhaka city, ages between 20 to 25 years, using Bengali version of Parental Bonding Inventory and Bengali version of Cognitive Emotion Regulation Questionnaire. The obtained data were analyzed by using multiple regression analysis and independent samples t-test. The results revealed that fathers care (β =0.317, p < 0.05) was only significantly positively associated with adult’s cognitive emotion regulation. Adjusted R² indicated that the model explained 30% of the variance in adult’s adaptive cognitive emotion regulation. No significant association was found between parental bonding and less adaptive cognitive emotion regulations. Results from independent samples t-test also revealed that there was no significant gender difference in both parental bonding and cognitive emotion regulations.

Keywords: cognitive emotion regulation, parental bonding, parental care, parental over-protection

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Authors: Yasemin Kaya, Ahmet N. Eraslan

Abstract:

In this study, the thermoelastic behavior of a long tube is studied by taking into account the temperature dependency of all mechanical and thermal properties. As the tube is heated slowly, an uncoupled solution procedure is adopted under free and radially constrained boundary conditions. The nonlinear heat conduction equation is solved by a finite element collocation procedure and the corresponding distributions of stress and strain are computed by shooting iterations. The computational model is verified in comparison to the analytical solution by shutting down the temperature dependency of physical properties. In the analysis, experimental data available in the literature is used to describe the coefficient of thermal expansion $\alpha$, the thermal conductivity $k$, the modulus of rigidity $G$, the yield strength $\sigma_{0}$, and the Poisson's ratio $\nu$ of Nickel. Results of the analysis are presented in comparison to those having constant physical properties. As a result of the calculations, the temperature dependency of the material properties should be taken into account at higher temperature ranges.

Keywords: thermoelasticity, long tube, temperature-dependent properties, internal heating

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Authors: Jafar Razmi

Abstract:

Integral abutment bridges are bridges that do not have joints. If these bridges are subject to large seasonal and daily temperature variations, the expansion and contraction of the bridge slab is transferred to the piles. Since the piles are deep into the soil, displacement induced by slab can cause bending and stresses in piles. These stresses cause fatigue and failure of piles. A complex mechanical interaction exists between the slab, pile, soil and abutment. This complex interaction needs to be understood in order to calculate the stresses in piles. This paper uses a mechanical approach in developing analytical equations for the complex structure to determine the stresses in piles. The solution to these analytical solutions is developed and compared with finite element analysis results and experimental data. Our comparison shows that using analytical approach can accurately predict the displacement in piles. This approach offers a simplified technique that can be utilized without the need for computationally extensive finite element model.

Keywords: integral abutment bridges, piles, thermo-mechanical stress, stress and strains

Procedia PDF Downloads 240