Search results for: academic speed and accuracy

Authors: Jutta Ransmayr

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The digital age has long arrived at Austrian schools, so both society and educationalists demand that digital means should be integrated accordingly to day-to-day school routines. Therefore, the Austrian school-leaving exam (A-levels) can now be written either by hand or by using a computer. However, the choice of writing medium (pen and paper or computer) for written examination papers, which are considered 'high-stakes' exams, raises a number of questions that have not yet been adequately investigated and answered until recently, such as: What effects do the different conditions of text production in the written German A-levels have on the component of normative linguistic accuracy? How do the spelling skills of German A-level papers written with a pen differ from those that the students wrote on the computer? And how is the teacher's assessment related to this? Which practical desiderata for German didactics can be derived from this? In a trilateral pilot project of the Austrian Center for Digital Humanities (ACDH) of the Austrian Academy of Sciences and the University of Vienna in cooperation with the Austrian Ministry of Education and the Council for German Orthography, these questions were investigated. A representative Austrian learner corpus, consisting of around 530 German A-level papers from all over Austria (pen and computer written), was set up in order to subject it to a quantitative (corpus-linguistic and statistical) and qualitative investigation with regard to the spelling and punctuation performance of the high school graduates and the differences between pen- and computer-written papers and their assessments. Relevant studies are currently available mainly from the Anglophone world. These have shown that writing on the computer increases the motivation to write, has positive effects on the length of the text, and, in some cases, also on the quality of the text. Depending on the writing situation and other technical aids, better results in terms of spelling and punctuation could also be found in the computer-written texts as compared to the handwritten ones. Studies also point towards a tendency among teachers to rate handwritten texts better than computer-written texts. In this paper, the first comparable results from the German-speaking area are to be presented. Research results have shown that, on the one hand, there are significant differences between handwritten and computer-written work with regard to performance in orthography and punctuation. On the other hand, the corpus linguistic investigation and the subsequent statistical analysis made it clear that not only the teachers' assessments of the students’ spelling performance vary enormously but also the overall assessments of the exam papers – the factor of the production medium (pen and paper or computer) also seems to play a decisive role.

Keywords: exam paper assessment, pen and paper or computer, learner corpora, linguistics

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Authors: W. Meron Mebrahtu, R. Absi

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Velocity distribution in turbulent open-channel flows is organized in a complex manner. This is due to the large spatial and temporal variability of fluid motion resulting from the free-surface turbulent flow condition. This phenomenon is complicated further due to the complex geometry of channels and the presence of solids transported. Thus, several efforts were made to understand the phenomenon and obtain accurate mathematical models that are suitable for engineering applications. However, predictions are inaccurate because oversimplified assumptions are involved in modeling this complex phenomenon. Therefore, the aim of this work is to study velocity distribution profiles and obtain simple, more accurate, and predictive mathematical models. Particular focus will be made on the acceptable simplification of the general transport equations and an accurate representation of eddy viscosity. Wide rectangular open-channel seems suitable to begin the study; other assumptions are smooth-wall, and sediment-free flow under steady and uniform flow conditions. These assumptions will allow examining the effect of the bottom wall and the free surface only, which is a necessary step before dealing with more complex flow scenarios. For this flow condition, two ordinary differential equations are obtained for velocity profiles; from the Reynolds-averaged Navier-Stokes (RANS) equation and equilibrium consideration between turbulent kinetic energy (TKE) production and dissipation. Then different analytic models for eddy viscosity, TKE, and mixing length were assessed. Computation results for velocity profiles were compared to experimental data for different flow conditions and the well-known linear, log, and log-wake laws. Results show that the model based on the RANS equation provides more accurate velocity profiles. In the viscous sublayer and buffer layer, the method based on Prandtl’s eddy viscosity model and Van Driest mixing length give a more precise result. For the log layer and outer region, a mixing length equation derived from Von Karman’s similarity hypothesis provides the best agreement with measured data except near the free surface where an additional correction based on a damping function for eddy viscosity is used. This method allows more accurate velocity profiles with the same value of the damping coefficient that is valid under different flow conditions. This work continues with investigating narrow channels, complex geometries, and the effect of solids transported in sewers.

Keywords: accuracy, eddy viscosity, sewers, velocity profile

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Authors: Irina-Emily Hansen, Ola Jon Mork

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The European economic growth strategy and supporting it framework for research and innovation highlight the importance of nurturing new open innovation in order to strengthen Europe’s competitiveness. One of the main approaches to enhance innovation in European society is the Triple Helix model that centres on science- industry collaboration where the universities are assigned the managerial role. In spite of the defined collaboration strategy, the collaboration between academics and in-dustry in Europe has still many challenges. Many of them are explained by culture difference: academic culture aims towards scientific knowledge, while businesses are oriented towards pro-duction and profitable results; also execution of collaborative projects is seen differently by part-ners involved. That proves that traditional management strategies applied to collaboration between researchers and businesses are not effective. There is a need for dynamic strategies that can support the interaction between researchers and industry intensifying knowledge co-creation and contributing to development of national innovation system (NIS) by incorporating individual, organizational and inter-organizational learning. In order to find a good subject to follow, the researchers of a given paper have investigated one of the most rapidly developing knowledge-based, innovation society, Singapore. Singapore does not dispose much land- or sea- resources that normally provide income for any country. Therefore, Singapore was forced to think differently and build society on resources that are available: talented people and knowledge. Singapore has during the last twenty years developed attracting high rated university camps, research institutions and leading industrial companies from all over the world. This article elucidates and elaborates Singapore’s national innovation strategies from Knowledge Management perspective. The research is done on the variety of organizations that enable and support knowledge development in this state: governmental research and development (R&D) centers in universities, private talent incubators for entrepreneurs, and industrial companies with own R&D departments. The research methods are based on presentations, documents, and visits at a number of universities, research institutes, innovation parks, governmental institutions, industrial companies and innovation exhibitions in Singapore. In addition, a literature review of science articles is made regarding the topic. The first finding is that objectives of collaboration between researchers, entrepreneurs and industry in Singapore correspond primary goals of the state: knowledge- and economy growth. There are common objectives for all stakeholders on all national levels. The second finding is that Singapore has enabled system on a national level that supports innovation the entire way from fostering or capturing the new knowledge, providing knowledge exchange and co-creation to application of it in real-life. The conclusion is that innovation means not only new idea, but also the enabling mechanism for its execution and the marked-oriented approach in order that new knowledge can be absorbed in society. The future research can be done with regards to application of Singapore knowledge management strategy in innovation to European countries.

Keywords: knowledge management strategy, national innovation system, research industry and business collaboration, knowledge enabling

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Authors: Eliane G. Tótoli, Hérida Regina N. Salgado

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Daptomycin is an important antimicrobial agent used in clinical practice nowadays, since it is very active against some Gram-positive bacteria that are particularly challenges for the medicine, such as methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE). The importance of environmental preservation has receiving special attention since last years. Considering the evident need to protect the natural environment and the introduction of strict quality requirements regarding analytical procedures used in pharmaceutical analysis, the industries must seek environmentally friendly alternatives in relation to the analytical methods and other processes that they follow in their routine. In view of these factors, green analytical chemistry is prevalent and encouraged nowadays. In this context, infrared spectroscopy stands out. This is a method that does not use organic solvents and, although it is formally accepted for the identification of individual compounds, also allows the quantitation of substances. Considering that there are few green analytical methods described in literature for the analysis of daptomycin, the aim of this work was the development and validation of a green analytical method for the quantification of this drug in lyophilized powder for injectable solution, by Fourier-transform infrared spectroscopy (FT-IR). Method: Translucent potassium bromide pellets containing predetermined amounts of the drug were prepared and subjected to spectrophotometric analysis in the mid-infrared region. After obtaining the infrared spectrum and with the assistance of the IR Solution software, quantitative analysis was carried out in the spectral region between 1575 and 1700 cm-1, related to a carbonyl band of the daptomycin molecule, and this band had its height analyzed in terms of absorbance. The method was validated according to ICH guidelines regarding linearity, precision (repeatability and intermediate precision), accuracy and robustness. Results and discussion: The method showed to be linear (r = 0.9999), precise (RSD% < 2.0), accurate and robust, over a concentration range from 0.2 to 0.6 mg/pellet. In addition, this technique does not use organic solvents, which is one great advantage over the most common analytical methods. This fact contributes to minimize the generation of organic solvent waste by the industry and thereby reduces the impact of its activities on the environment. Conclusion: The validated method proved to be adequate to quantify daptomycin in lyophilized powder for injectable solution and can be used for its routine analysis in quality control. In addition, the proposed method is environmentally friendly, which is in line with the global trend.

Keywords: daptomycin, Fourier-transform infrared spectroscopy, green analytical chemistry, quality control, spectrometry in IR region

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Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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Authors: Jun Won Kim

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Objective: Theta-phase gamma-amplitude coupling (TGC) was used as a novel evidence-based tool to reflect the dysfunctional cortico-thalamic interaction in patients with schizophrenia. However, to our best knowledge, no studies have reported the diagnostic utility of the TGC in the resting-state electroencephalographic (EEG) of neuroleptic-naive patients with schizophrenia compared to healthy controls. Thus, the purpose of this EEG study was to understand the underlying mechanisms in patients with schizophrenia by comparing the TGC at rest between two groups and to evaluate the diagnostic utility of TGC. Method: The subjects included 90 patients with schizophrenia and 90 healthy controls. All patients were diagnosed with schizophrenia according to the criteria of Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) by two independent psychiatrists using semi-structured clinical interviews. Because patients were either drug-naïve (first episode) or had not been taking psychoactive drugs for one month before the study, we could exclude the influence of medications. Five frequency bands were defined for spectral analyses: delta (1–4 Hz), theta (4–8 Hz), slow alpha (8–10 Hz), fast alpha (10–13.5 Hz), beta (13.5–30 Hz), and gamma (30-80 Hz). The spectral power of the EEG data was calculated with fast Fourier Transformation using the 'spectrogram.m' function of the signal processing toolbox in Matlab. An analysis of covariance (ANCOVA) was performed to compare the TGC results between the groups, which were adjusted using a Bonferroni correction (P < 0.05/19 = 0.0026). Receiver operator characteristic (ROC) analysis was conducted to examine the discriminating ability of the TGC data for schizophrenia diagnosis. Results: The patients with schizophrenia showed a significant increase in the resting-state TGC at all electrodes. The delta, theta, slow alpha, fast alpha, and beta powers showed low accuracies of 62.2%, 58.4%, 56.9%, 60.9%, and 59.0%, respectively, in discriminating the patients with schizophrenia from the healthy controls. The ROC analysis performed on the TGC data generated the most accurate result among the EEG measures, displaying an overall classification accuracy of 92.5%. Conclusion: As TGC includes phase, which contains information about neuronal interactions from the EEG recording, TGC is expected to be useful for understanding the mechanisms the dysfunctional cortico-thalamic interaction in patients with schizophrenia. The resting-state TGC value was increased in the patients with schizophrenia compared to that in the healthy controls and had a higher discriminating ability than the other parameters. These findings may be related to the compensatory hyper-arousal patterns of the dysfunctional default-mode network (DMN) in schizophrenia. Further research exploring the association between TGC and medical or psychiatric conditions that may confound EEG signals will help clarify the potential utility of TGC.

Keywords: quantitative electroencephalography (QEEG), theta-phase gamma-amplitude coupling (TGC), schizophrenia, diagnostic utility

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Authors: Ibtissem Hosni, Lilia Bennaceur Farah, Saber Mohamed Naceur

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In order to assess the water availability in the soil, it is crucial to have information about soil distributed moisture content; this parameter helps to understand the effect of humidity on the exchange between soil, plant cover and atmosphere in addition to fully understanding the surface processes and the hydrological cycle. On the other hand, aerodynamic roughness length is a surface parameter that scales the vertical profile of the horizontal component of the wind speed and characterizes the surface ability to absorb the momentum of the airflow. In numerous applications of the surface hydrology and meteorology, aerodynamic roughness length is an important parameter for estimating momentum, heat and mass exchange between the soil surface and atmosphere. It is important on this side, to consider the atmosphere factors impact in general, and the natural erosion in particular, in the process of soil evolution and its characterization and prediction of its physical parameters. The study of the induced movements by the wind over soil vegetated surface, either spaced plants or plant cover, is motivated by significant research efforts in agronomy and biology. The known major problem in this side concerns crop damage by wind, which presents a booming field of research. Obviously, most models of soil surface require information about the aerodynamic roughness length and its temporal and spatial variability. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. We have introduced multi-layer aspect of the humidity of the soil surface, to take into account a volume component in the problem of backscattering radar signal. As humidity increases, the dielectric constant of the soil-water mixture increases and this change is detected by microwave sensors. Nevertheless, many existing models in the field of radar imagery, cannot be applied directly on areas covered with vegetation due to the vegetation backscattering. Thus, the radar response corresponds to the combined signature of the vegetation layer and the layer of soil surface. Therefore, the key issue of the numerical estimation of soil moisture is to separate the two contributions and calculate both scattering behaviors of the two layers by defining the scattering of the vegetation and the soil blow. This paper presents a synergistic methodology, and it is for estimating roughness and soil moisture from C-band radar measurements. The methodology adequately represents a microwave/optical model which has been used to calculate the scattering behavior of the aerodynamic vegetation-covered area by defining the scattering of the vegetation and the soil below.

Keywords: aerodynamic, bi-dimensional, vegetation, synergistic

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Authors: Bruno Biagianti, Angela Tseng, Kathy Wannaviroj, Allison Corlett, Megan DuBois, Kyu Lee, Suma Jacob

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Background: ASD is characterized by pervasive Sensory Processing Abnormalities (SPA) and social cognitive deficits that persist throughout the course of the illness and have been linked to functional abnormalities in specific neural systems that underlie the perception, processing, and representation of sensory information. SPA and social cognitive deficits are associated with difficulties in interpersonal relationships, poor development of social skills, reduced social interactions and lower academic performance. Importantly, they can hamper the effects of established evidence-based psychological treatments—including PEERS (Program for the Education and Enrichment of Relationship Skills), a parent/caregiver-assisted, 16-weeks social skills intervention—which nonetheless requires a functional brain capable of assimilating and retaining information and skills. As a matter of fact, some adolescents benefit from PEERS more than others, calling for strategies to increase treatment response rates. Objective: We will present interim data on CICADAS (Care Improving Cognition for ADolescents on the Autism Spectrum)—a clinician-assisted, closed-loop technology mobile application for adolescents with ASD. Via ten mobile assessments, CICADAS captures data on sensory processing abnormalities and associated cognitive deficits. These data populate a machine learning algorithm that tailors the delivery of ten neuroplasticity-based social cognitive training (NB-SCT) exercises targeting sensory processing abnormalities. Methods: In collaboration with the Autism Spectrum and Neurodevelopmental Disorders Clinic at the University of Minnesota, we conducted a fully remote, three-arm, randomized crossover trial with adolescents with ASD to document the acceptability of CICADAS and evaluate its potential as a stand-alone treatment or as a treatment enhancer of PEERS. Twenty-four adolescents with ASD (ages 11-18) have been initially randomized to 16 weeks of PEERS + CICADAS (Arm A) vs. 16 weeks of PEERS + computer games vs. 16 weeks of CICADAS alone (Arm C). After 16 weeks, the full battery of assessments has been remotely administered. Results: We have evaluated the acceptability of CICADAS by examining adherence rates, engagement patterns, and exit survey data. We found that: 1) CICADAS is able to serve as a treatment enhancer for PEERS, inducing greater improvements in sensory processing, cognition, symptom reduction, social skills and behaviors, as well as the quality of life compared to computer games; 2) the concurrent delivery of PEERS and CICADAS induces greater improvements in study outcomes compared to CICADAS only. Conclusion: While preliminary, our results indicate that the individualized assessment and treatment approach designed in CICADAS seems effective in inducing adaptive long-term learning about social-emotional events. CICADAS-induced enhancement of processing and cognition facilitates the application of PEERS skills in the environment of adolescents with ASD, thus improving their real-world functioning.

Keywords: ASD, social skills, cognitive training, mobile app

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Authors: Sarah Reker, Christiane H. Kellner

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From the perspective of people with disabilities, inequalities can also emerge from spatial segregation, the lack of social contacts or limited economic resources. In order to reduce or even eliminate these disadvantages and increase general well-being, community-based participation as well as decentralisation efforts within exclusively residential homes is essential. Therefore, the new research project “Index for participation development and quality of life for persons with disabilities”(TeLe-Index, 2014-2016), which is anchored at the Technische Universität München in Munich and at a large residential complex and service provider for persons with disabilities in the outskirts of Munich aims to assist the development of community-based living environments. People with disabilities should be able to participate in social life beyond the confines of the institution. Since a diverse society is a society in which different individual needs and wishes can emerge and be catered to, the ultimate goal of the project is to create an environment for all citizens–regardless of disability, age or ethnic background–that accommodates their daily activities and requirements. The UN-Convention on the Rights of Persons with Disabilities, which Germany also ratified, postulates the necessity of user-centered design, especially when it comes to evaluating the individual needs and wishes of all citizens. Therefore, a multidimensional approach is required. Based on this insight, the structure of the town-like center will be remodeled to open up the community to all people. This strategy should lead to more equal opportunities and open the way for a much more diverse community. Therefore, macro-level research questions were inspired by quality of life theory and were formulated as follows for different dimensions: •The user dimension: what needs and necessities can we identify? Are needs person-related? Are there any options to choose from? What type of quality of life can we identify? The economic dimension: what resources (both material and staff-related) are available in the region? (How) are they used? What costs (can) arise and what effects do they entail? •The environment dimension: what “environmental factors” such as access (mobility and absence of barriers) prove beneficial or impedimental? In this context, we have provided academic supervision and support for three projects (the construction of a new school, inclusive housing for children and teenagers with disabilities and the professionalization of employees with person-centered thinking). Since we cannot present all the issues of the umbrella-project within the conference framework, we will be focusing on one project more in-depth, namely “Outpatient Housing Options for Children and Teenagers with Disabilities”. The insights we have obtained until now will enable us to present the intermediary results of our evaluation. The most central questions pertaining to this part of the research were the following: •How have the existing network relations been designed? •What meaning (or significance) does the existing service offers and structures have for the everyday life of an external residential group? These issues underpinned the environmental analyses as well as the qualitative guided interviews and qualitative network analyses we carried out.

Keywords: decentralisation, environmental analyses, outpatient housing options for children and teenagers with disabilities, qualitative network analyses

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Authors: Ciara Pienaar, J. W. Odendaal, J. Joubert, J. C. Smit

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Radar cross section (RCS) of dielectric objects play an important role in many applications, such as low observability technology development, drone detection, and monitoring as well as coastal surveillance. Various materials are used to construct the targets of interest such as metal, wood, composite materials, radar absorbent materials, and other dielectrics. Since simulated datasets are increasingly being used to supplement infield measurements, as it is more cost effective and a larger variety of targets can be simulated, it is important to have a high level of confidence in the predicted results. Confidence can be attained through validation. Various computational electromagnetic (CEM) methods are capable of predicting the RCS of dielectric targets. This study will extend previous studies by validating full-wave and asymptotic RCS simulations of dielectric targets with measured data. The paper will provide measured RCS data of a number of canonical dielectric targets exhibiting different material properties. As stated previously, these measurements are used to validate numerous CEM methods. The dielectric properties are accurately characterized to reduce the uncertainties in the simulations. Finally, an analysis of the sensitivity of oblique and normal incidence scattering predictions to material characteristics is also presented. In this paper, the ability of several CEM methods, including method of moments (MoM), and physical optics (PO), to calculate the RCS of dielectrics were validated with measured data. A few dielectrics, exhibiting different material properties, were selected and several canonical targets, such as flat plates and cylinders, were manufactured. The RCS of these dielectric targets were measured in a compact range at the University of Pretoria, South Africa, over a frequency range of 2 to 18 GHz and a 360° azimuth angle sweep. This study also investigated the effect of slight variations in the material properties on the calculated RCS results, by varying the material properties within a realistic tolerance range and comparing the calculated RCS results. Interesting measured and simulated results have been obtained. Large discrepancies were observed between the different methods as well as the measured data. It was also observed that the accuracy of the RCS data of the dielectrics can be frequency and angle dependent. The simulated RCS for some of these materials also exhibit high sensitivity to variations in the material properties. Comparison graphs between the measured and simulation RCS datasets will be presented and the validation thereof will be discussed. Finally, the effect that small tolerances in the material properties have on the calculated RCS results will be shown. Thus the importance of accurate dielectric material properties for validation purposes will be discussed.

Keywords: asymptotic, CEM, dielectric scattering, full-wave, measurements, radar cross section, validation

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Authors: Alaa Abdellatif, Gabrièle Breda

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Background. Advanced therapy medicinal products (ATMPs) are innovative therapies that mainly target orphan diseases and high unmet medical needs. ATMP includes gene therapy medicinal products (GTMP), somatic cell therapy medicinal products (CTMP), and tissue-engineered therapies (TEP). Since legislation opened the way in 2007, 25 ATMPs have been approved in the EU, which is about the same amount as the U.S. Food and Drug Administration. However, not all of the ATMPs that have been approved have successfully reached the market and retained their approval. Objectives. We aim to understand all the factors limiting the market access to very promising therapies in a systemic approach, to be able to overcome these problems, in the future, with scientific, regulatory and commercial innovations. Further to recent reviews that focus either on specific countries, products, or dimensions, we will address all the challenges faced by ATMP development today. Methodology. We used mixed methods and a multi-level approach for data collection. First, we performed an updated academic literature review on ATMP development and their scientific and market access challenges (papers published between 2018 and April 2023). Second, we analyzed industry feedback from cell and gene therapy webinars and white papers published by providers and pharmaceutical industries. Finally, we established a comparative analysis of the regulatory guidelines published by EMA and the FDA for ATMP approval. Results: The main challenges in bringing these therapies to market are the high development costs. Developing ATMPs is expensive due to the need for specialized manufacturing processes. Furthermore, the regulatory pathways for ATMPs are often complex and can vary between countries, making it challenging to obtain approval and ensure compliance with different regulations. As a result of the high costs associated with ATMPs, challenges in obtaining reimbursement from healthcare payers lead to limited patient access to these treatments. ATMPs are often developed for orphan diseases, which means that the patient population is limited for clinical trials which can make it challenging to demonstrate their safety and efficacy. In addition, the complex manufacturing processes required for ATMPs can make it challenging to scale up production to meet demand, which can limit their availability and increase costs. Finally, ATMPs face safety and efficacy challenges: dangerous adverse events of these therapies like toxicity related to the use of viral vectors or cell therapy, starting material and donor-related aspects. Conclusion. As a result of our mixed method analysis, we found that ATMPs face a number of challenges in their development, regulatory approval, and commercialization and that addressing these challenges requires collaboration between industry, regulators, healthcare providers, and patient groups. This first analysis will help us to address, for each challenge, proper and innovative solution(s) in order to increase the number of ATMPs approved and reach the patients

Keywords: advanced therapy medicinal products (ATMPs), product development, market access, innovation

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Authors: Neeti Nayak, Khalid Duri

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Despite the many advances made in transportation planning, the number of injuries and fatalities in the United States which involve motorized vehicles near intersections remain largely unchanged year over year. Data from the National Highway Traffic Safety Administration for 2018 indicates accidents involving motorized vehicles at traffic intersections accounted for 8,245 deaths and 914,811 injuries. Furthermore, collisions involving pedal cyclists killed 861 people (38% at intersections) and injured 46,295 (68% at intersections), while accidents involving pedestrians claimed 6,247 lives (25% at intersections) and injured 71,887 (56% at intersections)- the highest tallies registered in nearly 20 years. Some of the causes attributed to the rising number of accidents relate to increasing populations and the associated changes in land and traffic usage patterns, insufficient visibility conditions, and inadequate applications of traffic controls. Intersections that were initially designed with a particular land use pattern in mind may be rendered obsolete by subsequent developments. Many accidents involving pedestrians are accounted for by locations which should have been designed for safe crosswalks. Conventional solutions for evaluating intersection safety often require costly deployment of engineering surveys and analysis, which limit the capacity of resource-constrained administrations to satisfy their community’s needs for safe roadways adequately, effectively relegating mitigation efforts for high-risk areas to post-incident responses. This paper demonstrates how geospatial technology can identify high-risk locations and evaluate the viability of specific intersection management techniques. GIS is used to simulate relevant real-world conditions- the presence of traffic controls, zoning records, locations of interest for human activity, design speed of roadways, topographic details and immovable structures. The proposed methodology provides a low-cost mechanism for empowering urban planners to reduce the risks of accidents using 2-dimensional data representing multi-modal street networks, parcels, crosswalks and demographic information alongside 3-dimensional models of buildings, elevation, slope and aspect surfaces to evaluate visibility and lighting conditions and estimate probabilities for jaywalking and risks posed by blind or uncontrolled intersections. The proposed tools were developed using sample areas of Southern California, but the model will scale to other cities which conform to similar transportation standards given the availability of relevant GIS data.

Keywords: crosswalks, cyclist safety, geotechnology, GIS, intersection safety, pedestrian safety, roadway safety, transportation planning, urban design

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Authors: Jihong Liang, Huiling Feng, Linqing Ma, Tianjiao Qi

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Confucius is the first sage in Chinese culture. Confucianism, the theories represented by Confucius, has long been at the core of Chinese traditional society, as the dominating political ideology of centralized feudal monarchy for more than two thousand years. Confucius Worship Ceremony held in the Confucian Temple in Qufu (Confucius’s birthplace), which is dedicated to commemorate Confucius and other 170 elites in Confucianism with a whole set of formal rites, pertains to “Auspicious Rites”, which worship heaven and earth, humans and ghosts. It was first a medium-scaled ritual activity but then upgraded to the supreme one at national level in the Qing Dynasty. As a national event, it was celebrated by Emperor as well as common intellectuals in traditional China. The Ceremony can be solemn and respectful, with prescribed and complicated procedures, well-prepared utensil and matched offerings operated in rhythm with music and dances. Each participant has his place, and everyone follows the specified rules. This magnificent ritual Ceremony, while embedded with rich culture connotation, actually symbolizes the social acknowledgment for orthodox culture represented by Confucianism. Rites reflected in this Ceremony, is one of the most important features of Chinese culture, serving as the key bond in the identification and continuation of Chinese culture. These rites and ritual ceremonies, as culture memories themselves, are not only treasures of China, but of the whole world. However, while the ancient Chinese Rite has been one of the thorniest and most complicated topics for academics, the more regrettable is that due to their interruption in practice and historical changes, these rites and ritual ceremonies have already become a vague language in today’s academic discourse and strange terms of the past for common people. Luckily, we, today, by virtue of modern digital technology, may be able to reproduce these ritual ceremonies, as most of them can still be found in ancient manuscripts, through which Chinese ancestors tell the beauty and gravity of their dignified rites and more importantly, their spiritual pursuits with vivid language and lively pictures. This research, based on review and interpretation of the ancient literature, intends to construct the ancient ritual ceremonies, with the Confucius Worship Ceremony as a case and by use of digital technology. Using 3D technology, the spatial scenes in the Confucian Temple can be reconstructed by virtual reality; the memorial tablet exhibited in the temple by GIS and different rites in the ceremonies by animation technology. With reference to the lyrics, melodies and lively pictures recorded in ancient scripts, it is also possible to reproduce the live dancing site. Also, image rendering technology can help to show the life experience and accomplishments of Confucius. Finally, lining up all the elements in a multimedia narrative form, a complete digitalized Confucius Worship Ceremony can be reproduced, which will provide an excellent virtual experience that goes beyond time and space by bringing its audience back to that specific historical time. This digital project, once completed, will play an important role in the inheritance and dissemination of cultural heritage.

Keywords: Confucius worship ceremony, multimedia narrative form, GIS, visual representation

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

Procedia PDF Downloads 235

Authors: Ali Aqa Mohammad Jawad

Abstract:

Taking a relational approach, this paper analyzes the causal mechanisms associated with successful mobilization and rapid demobilization of the Enlightening Movement in post-2001 Afghanistan. The movement emerged after the state-owned Da Afghan Bereshna Sherkat (DABS) decided to divert the route for the Turkmenistan-Uzbekistan-Tajikistan-Afghanistan-Pakistan (TUTAP) electricity project. The grid was initially planned to go through the Hazara-inhabited province of Bamiyan, according to Afghanistan’s Power Sector Master Plan. The reroute served as an aide-mémoire of historical subordination to other ethno-religious groups for the Hazara community. It was also perceived as deprivation from post-2001 development projects, financed by international aid. This torched the accumulated grievances, which then gave birth to the Enlightening Movement. The movement had a successful mobilization. However, it demobilized after losing much of its mobilizing capabilities through an amalgamation of external and internal relational factors. The successful mobilization yet rapid demobilization constitutes the puzzle of this paper. From the theoretical perspective, this paper is significant as it establishes the applicability of contentious politics theory to protest mobilizations that occurred in Afghanistan, a context-specific, characterized by ethnic politics. Both primary and secondary data are utilized to address the puzzle. As for the primary resources, media coverage, interviews, reports, public media statements of the movement, involved in contentious performances, and data from Social Networking Services (SNS) are used. The covered period is from 2001-2018. As for the secondary resources, published academic articles and books are used to give a historical account of contentious politics. For data analysis, a qualitative comparative historical method is utilized to uncover the causal mechanisms associated with successful mobilization and rapid demobilization of the Movement. In this pursuit, both mobilization and demobilization are considered as larger political processes that could be decomposed to constituent mechanisms. Enlightening Movement’s framing and campaigns are first studied to uncover the associated mechanisms. Then, to avoid introducing some ad hoc mechanisms, the recurrence of mechanisms is checked against another case. Mechanisms qualify as robust if they are “recurrent” in different episodes of contention. Checking the recurrence of causal mechanisms is vital as past contentious events tend to reinforce future events. The findings of this paper suggest that the public sphere in Afghanistan is drastically different from Western democracies known as the birthplace of social movements. In Western democracies, when institutional politics did not respond, movement organizers occupied the public sphere, undermining the legitimacy of the government. In Afghanistan, the public sphere is ethicized. Considering the inter- and intra-relational dynamics of ethnic groups in Afghanistan, the movement reduced to an erosive inter- and intra-ethnic conflict. This undermined the cohesiveness of the movement, which then kicked-off its demobilization process.

Keywords: enlightening movement, contentious politics, mobilization, demobilization

Procedia PDF Downloads 198

Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

Abstract:

Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

Procedia PDF Downloads 94

Authors: Pooria Norouzi, Nicholas Tsang, Adam van der Goes, Joseph Yu, Douglas Zheng, Sirine Maleej

Abstract:

In this study, virtual meters will be designed and used for energy balance measurements of an air handling unit (AHU). The method aims to replace traditional physical sensors in heating, ventilation, and air conditioning (HVAC) systems with simulated virtual meters. Due to the inability to manage and monitor these systems, many HVAC systems have a high level of inefficiency and energy wastage. Virtual meters are implemented and applied in an actual HVAC system, and the result confirms the practicality of mathematical sensors for alternative energy measurement. While most residential buildings and offices are commonly not equipped with advanced sensors, adding, exploiting, and monitoring sensors and measurement devices in the existing systems can cost thousands of dollars. The first purpose of this study is to provide an energy consumption rate based on available sensors and without any physical energy meters. It proves the performance of virtual meters in HVAC systems as reliable measurement devices. To demonstrate this concept, mathematical models are created for AHU-07, located in building NE01 of the British Columbia Institute of Technology (BCIT) Burnaby campus. The models will be created and integrated with the system’s historical data and physical spot measurements. The actual measurements will be investigated to prove the models' accuracy. Based on preliminary analysis, the resulting mathematical models are successful in plotting energy consumption patterns, and it is concluded confidently that the results of the virtual meter will be close to the results that physical meters could achieve. In the second part of this study, the use of virtual meters is further assisted by artificial intelligence (AI) in the HVAC systems of building to improve energy management and efficiency. By the data mining approach, virtual meters’ data is recorded as historical data, and HVAC system energy consumption prediction is also implemented in order to harness great energy savings and manage the demand and supply chain effectively. Energy prediction can lead to energy-saving strategies and considerations that can open a window in predictive control in order to reach lower energy consumption. To solve these challenges, the energy prediction could optimize the HVAC system and automates energy consumption to capture savings. This study also investigates AI solutions possibility for autonomous HVAC efficiency that will allow quick and efficient response to energy consumption and cost spikes in the energy market.

Keywords: virtual meters, HVAC, artificial intelligence, energy consumption prediction

Procedia PDF Downloads 112

Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

Abstract:

To develop a machine learning model to predict diabetes (DM) prevalence in the U.S. population using demographic characteristics, physical indicators, and lifestyle habits, and to analyze how these factors contribute to the likelihood of diabetes. We analyzed data from 23,546 participants aged 20 and older, who were non-pregnant, from the 2009-2018 National Health and Nutrition Examination Survey (NHANES). The dataset included key demographic (age, sex, ethnicity), physical (BMI, leg length, total cholesterol [TCHOL], fasting plasma glucose), and lifestyle indicators (smoking habits). A weighted sample was used to account for NHANES survey design features such as stratification and clustering. A classification machine learning model was trained to predict diabetes status. The target variable was binary (diabetes or non-diabetes) based on fasting plasma glucose measurements. The following models were evaluated: Logistic Regression (baseline), Random Forest Classifier, Gradient Boosting Machine (GBM), Support Vector Machine (SVM). Model performance was assessed using accuracy, F1-score, AUC-ROC, and precision-recall metrics. Feature importance was analyzed using SHAP values to interpret the contributions of variables such as age, BMI, ethnicity, and smoking status. The Gradient Boosting Machine (GBM) model outperformed other classifiers with an AUC-ROC score of 0.85. Feature importance analysis revealed the following key predictors: Age: The most significant predictor, with diabetes prevalence increasing with age, peaking around the 60s for males and 70s for females. BMI: Higher BMI was strongly associated with a higher risk of diabetes. Ethnicity: Black participants had the highest predicted prevalence of diabetes (14.6%), followed by Mexican-Americans (13.5%) and Whites (10.6%). TCHOL: Diabetics had lower total cholesterol levels, particularly among White participants (mean decline of 23.6 mg/dL). Smoking: Smoking showed a slight increase in diabetes risk among Whites (0.2%) but had a limited effect in other ethnic groups. Using machine learning models, we identified key demographic, physical, and lifestyle predictors of diabetes in the U.S. population. The results confirm that diabetes prevalence varies significantly across age, BMI, and ethnic groups, with lifestyle factors such as smoking contributing differently by ethnicity. These findings provide a basis for more targeted public health interventions and resource allocation for diabetes management.

Keywords: diabetes, NHANES, random forest, gradient boosting machine, support vector machine

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Authors: Muhammad Kashif Fida

Abstract:

In the bank, teller’s job (cash officer) is highly important and critical as at one end it requires soft and brisk customer services and on the other side, handling cash with integrity. It is always challenging for recruiters to hire competent and trustworthy tellers. According to author’s knowledge, there is no comprehensive test available that may provide assistance in recruitment in Pakistan. So there is a dire need of a psychometric battery that could provide support in recruitment of potential candidates for the teller’ position. So, the aim of the present study was to construct ABL-Teller Aptitude Test (ABL-TApT). Three major phases have been designed by following American Psychological Association’s guidelines. The first phase was qualitative, indicators of the test have been explored by content analysis of the a) teller’s job descriptions (n=3), b) interview with senior tellers (n=6) and c) interview with HR personals (n=4). Content analysis of above yielded three border constructs; i). Personality, ii). Integrity/honesty, iii). Professional Work Aptitude. Identified indicators operationalized and statements (k=170) were generated using verbatim. It was then forwarded to the five experts for review of content validity. They finalized 156 items. In the second phase; ABL-TApT (k=156) administered on 323 participants through a computer application. The overall reliability of the test shows significant alpha coefficient (α=.81). Reliability of subscales have also significant alpha coefficients. Confirmatory Factor Analysis (CFA) performed to estimate the construct validity, confirms four main factors comprising of eight personality traits (Confidence, Organized, Compliance, Goal-oriented, Persistent, Forecasting, Patience, Caution), one Integrity/honesty factor, four factors of professional work aptitude (basic numerical ability and perceptual accuracy of letters, numbers and signature) and two factors for customer services (customer services, emotional maturity). Values of GFI, AGFI, NNFI, CFI, RFI and RMSEA are in recommended range depicting significant model fit. In third phase concurrent validity evidences have been pursued. Personality and integrity part of this scale has significant correlations with ‘conscientiousness’ factor of NEO-PI-R, reflecting strong concurrent validity. Customer services and emotional maturity have significant correlations with ‘Bar-On EQI’ showing another evidence of strong concurrent validity. It is concluded that ABL-TAPT is significantly reliable and valid battery of tests, will assist in objective recruitment of tellers and help recruiters in finding a more suitable human resource.

Keywords: concurrent validity, construct validity, content validity, reliability, teller aptitude test, objective recruitment

Procedia PDF Downloads 232

Authors: Paramita Banerjee, K. R. S. Chandrakumar, G. P. Das

Abstract:

Bulk MgH2 has drawn much attention for the purpose of hydrogen storage because of its high hydrogen storage capacity (~7.7 wt %) as well as low cost and abundant availability. However, its practical usage has been hindered because of its high hydrogen desorption enthalpy (~0.8 eV/H2 molecule), which results in an undesirable desorption temperature of 3000C at 1 bar H2 pressure. To surmount the limitations of bulk MgH2 for the purpose of hydrogen storage, a detailed first-principles density functional theory (DFT) based study on the structure and stability of neutral (Mgm) and positively charged (Mgm+) Mg nanoclusters of different sizes (m = 2, 4, 8 and 12), as well as their interaction with molecular hydrogen (H2), is reported here. It has been found that due to the absence of d-electrons within the Mg atoms, hydrogen remained in molecular form even after its interaction with neutral and charged Mg nanoclusters. Interestingly, the H2 molecules do not enter into the interstitial positions of the nanoclusters. Rather, they remain on the surface by ornamenting these nanoclusters and forming new structures with a gravimetric density higher than 15 wt %. Our observation is that the inclusion of Grimme’s DFT-D3 dispersion correction in this weakly interacting system has a significant effect on binding of the H2 molecules with these nanoclusters. The dispersion corrected interaction energy (IE) values (0.1-0.14 eV/H2 molecule) fall in the right energy window, that is ideal for hydrogen storage. These IE values are further verified by using high-level coupled-cluster calculations with non-iterative triples corrections i.e. CCSD(T), (which has been considered to be a highly accurate quantum chemical method) and thereby confirming the accuracy of our ‘dispersion correction’ incorporated DFT calculations. The significance of the polarization and dispersion energy in binding of the H2 molecules are confirmed by performing energy decomposition analysis (EDA). A total of 16, 24, 32 and 36 H2 molecules can be attached to the neutral and charged nanoclusters of size m = 2, 4, 8 and 12 respectively. Ab-initio molecular dynamics (AIMD) simulation shows that the outermost H2 molecules are desorbed at a rather low temperature viz. 150 K (-1230C) which is expected. However, complete dehydrogenation of these nanoclusters occur at around 1000C. Most importantly, the host nanoclusters remain stable up to ~500 K (2270C). All these results on the adsorption and desorption of molecular hydrogen with neutral and charged Mg nanocluster systems indicate towards the possibility of reducing the dehydrogenation temperature of bulk MgH2 by designing new Mg-based nano materials which will be able to adsorb molecular hydrogen via this weak Mg-H2 interaction, rather than the strong Mg-H bonding. Notwithstanding the fact that in practical applications, these interactions will be further complicated by the effect of substrates as well as interactions with other clusters, the present study has implications on our fundamental understanding to this problem.

Keywords: density functional theory, DFT, hydrogen storage, molecular dynamics, molecular hydrogen adsorption, nanoclusters, physisorption

Procedia PDF Downloads 417

Authors: Angela T. H. Kwan, Saman Arfaie, Joseph Therriault, Zahra Azizi, Firoza Z. Lussier, Cecile Tissot, Mira Chamoun, Gleb Bezgin, Stijn Servaes, Jenna Stevenon, Nesrine Rahmouni, Vanessa Pallen, Serge Gauthier, Pedro Rosa-Neto

Abstract:

Alzheimer’s disease (AD) can be detected in living people using in vivo biomarkers of amyloid-β (Aβ) and tau, even in the absence of cognitive impairment during the preclinical phase. [¹⁸F]-MK-6420 is a high affinity positron emission tomography (PET) tracer that quantifies tau neurofibrillary tangles, but its ability to predict cognitive changes associated with early AD symptoms, such as memory decline, is unclear. Here, we assess the prognostic accuracy of baseline [18F]-MK-6420 tau PET for predicting longitudinal memory decline in asymptomatic elderly individuals. In a longitudinal observational study, we evaluated a cohort of cognitively normal elderly participants (n = 111) from the Translational Biomarkers in Aging and Dementia (TRIAD) study (data collected between October 2017 and July 2020, with a follow-up period of 12 months). All participants underwent tau PET with [¹⁸F]-MK-6420 and Aβ PET with [¹⁸F]-AZD-4694. The exclusion criteria included the presence of head trauma, stroke, or other neurological disorders. There were 111 eligible participants who were chosen based on the availability of Aβ PET, tau PET, magnetic resonance imaging (MRI), and APOEε4 genotyping. Among these participants, the mean (SD) age was 70.1 (8.6) years; 20 (18%) were tau PET positive, and 71 of 111 (63.9%) were women. A significant association between baseline Braak I-II [¹⁸F]-MK-6240 SUVR positivity and change in composite memory score was observed at the 12-month follow-up, after correcting for age, sex, and years of education (Logical Memory and RAVLT, standardized beta = -0.52 (-0.82-0.21), p < 0.001, for dichotomized tau PET and -1.22 (-1.84-(-0.61)), p < 0.0001, for continuous tau PET). Moderate cognitive decline was observed for A+T+ over the follow-up period, whereas no significant change was observed for A-T+, A+T-, and A-T-, though it should be noted that the A-T+ group was small.Our results indicate that baseline tau neurofibrillary tangle pathology is associated with longitudinal changes in memory function, supporting the use of [¹⁸F]-MK-6420 PET to predict the likelihood of asymptomatic elderly individuals experiencing future memory decline. Overall, [¹⁸F]-MK-6420 PET is a promising tool for predicting memory decline in older adults without cognitive impairment at baseline. This is of critical relevance as the field is shifting towards a biological model of AD defined by the aggregation of pathologic tau. Therefore, early detection of tau pathology using [¹⁸F]-MK-6420 PET provides us with the hope that living patients with AD may be diagnosed during the preclinical phase before it is too late.

Keywords: alzheimer’s disease, braak I-II, in vivo biomarkers, memory, PET, tau

Procedia PDF Downloads 83

Authors: Sonia A. Stoica, Lexi Frankel, Amalia Ardeljan, Selena Rashid, Ali Yasback, Omar Rashid

Abstract:

Introduction Enterococcus is a vast genus of lactic acid bacteria, gram-positivecocci species. They are common commensal organisms in the intestines of humans: E. faecalis (90–95%) and E. faecium (5–10%). Rare groups of infections can occur with other species, including E. casseliflavus, E. gallinarum, and E. raffinosus. The most common infections caused by Enterococcus include urinary tract infections, biliary tract infections, subacute endocarditis, diverticulitis, meningitis, septicemia, and spontaneous bacterial peritonitis. The treatment for sensitive strains of these bacteria includes ampicillin, penicillin, cephalosporins, or vancomycin, while the treatment for resistant strains includes daptomycin, linezolid, tygecycline, or streptogramine. Enterococcus faecalis CECT7121 is an encouraging nominee for being considered as a probiotic strain. E. faecalis CECT7121 enhances and skews the profile of cytokines to the Th1 phenotype in situations such as vaccination, anti-tumoral immunity, and allergic reactions. It also enhances the secretion of high levels of IL-12, IL-6, TNF alpha, and IL-10. Cytokines have been previously associated with the development of cancer. The intention of this study was to therefore evaluate the correlation between Enterococcus infections and incidence of bone carcinoma. Methods A retrospective cohort study (2010-2019) was conducted through a Health Insurance Portability and Accountability Act (HIPAA) compliant national database and conducted using International Classification of Disease (ICD) 9th and 10th codes for bone carcinoma diagnosis in a previously Enterococcus infected population. Patients were matched for age range and Charlson Comorbidity Index (CCI). Access to the database was granted by Holy Cross Health for academic research. Chi-squared test was used to assess statistical significance. Results A total number of 17,056 patients was obtained in Enterococcus infected group as well as in the control population (matched by Age range and CCI score). Subsequent bone carcinoma development was seen at a rate of 1.07% (184) in the Enterococcal infectious group and 3.42% (584) in the control group, respectively. The difference was statistically significant by p= 2.2x10-¹⁶, Odds Ratio = 0.355 (95% CI 0.311 - 0.404) Treatment for enterococcus infection was analyzed and controlled for in both enterococcus infected and noninfected populations. 78 out of 6,624 (1.17%) patients with a prior enterococcus infection and treated with antibiotics were compared to 202 out of 6,624 (3.04%) patients with no history of enterococcus infection (control) and received antibiotic treatment. Both populations subsequently developed bone carcinoma. Results remained statistically significant (p<2.2x10-), Odds Ratio=0.456 (95% CI 0.396-0.525). Conclusion This study shows a statistically significant correlation between Enterococcus infection and a decreased incidence of bone carcinoma. The immunologic response of the organism to Enterococcus infection may exert a protecting mechanism from developing bone carcinoma. Further exploration is needed to identify the potential mechanism of Enterococcus in reducing bone carcinoma incidence.

Keywords: anti-tumoral immunity, bone carcinoma, enterococcus, immunologic response

Procedia PDF Downloads 184

Authors: Ebenezer Joseph

Abstract:

Chess is a useful tool to enhance general and specific cognitive functioning in children. The present study aims to assess the impact of chess on cognitive in children and to measure the differential impact of socio-demographic factors like age and gender of the child on the effectiveness of the chess intervention.This research study used an experimental design to study the impact of the Training in Chess on the intelligence of children. The Pre-test Post-test Control Group Design was utilized. The research design involved two groups of children: an experimental group and a control group. The experimental group consisted of children who participated in the one-year Chess Training Intervention, while the control group participated in extra-curricular activities in school. The main independent variable was training in chess. Other independent variables were gender and age of the child. The dependent variable was the cognitive functioning of the child (as measured by IQ, working memory index, processing speed index, perceptual reasoning index, verbal comprehension index, numerical reasoning, verbal reasoning, non-verbal reasoning, social intelligence, language, conceptual thinking, memory, visual motor and creativity). The sample consisted of 200 children studying in Government and Private schools. Random sampling was utilized. The sample included both boys and girls falling in the age range 6 to 16 years. The experimental group consisted of 100 children (50 from Government schools and 50 from Private schools) with an equal representation of boys and girls. The control group similarly consisted of 100 children. The dependent variables were assessed using Binet-Kamat Test of Intelligence, Wechsler Intelligence Scale for Children - IV (India) and Wallach Kogan Creativity Test. The training methodology comprised Winning Moves Chess Learning Program - Episodes 1–22, lectures with the demonstration board, on-the-board playing and training, chess exercise through workbooks (Chess school 1A, Chess school 2, and tactics) and working with chess software. Further students games were mapped using chess software and the brain patterns of the child were understood. They were taught the ideas behind chess openings and exposure to classical games were also given. The children participated in mock as well as regular tournaments. Preliminary analysis carried out using independent t tests with 50 children indicates that chess training has led to significant increases in the intelligent quotient. Children in the experimental group have shown significant increases in composite scores like working memory and perceptual reasoning. Chess training has significantly enhanced the total creativity scores, line drawing and pattern meaning subscale scores. Systematically learning chess as part of school activities appears to have a broad spectrum of positive outcomes.

Keywords: chess, intelligence, creativity, children

Procedia PDF Downloads 260

Authors: Chieh-Ning Lan, Tzu-Shin Lin, Kun-Hao Lin

Abstract:

Chinese handwriting skill is one of the basic skills of school-age children in Taiwan, which helps them to learn most academic subjects. Differ from the alphabetic language system, Chinese written language is a logographic script with a complicated 2-dimensional character structure as a morpheme. Visuospatial ability places a great role in Chinese handwriting to maintain good proportion and alignment of these interwoven strokes. In Taiwan, school-age students faced the challenge to recognize and write down Chinese characters, especially in children with written expression difficulties (CWWDs). In this study, we developed an instructional app to help CWWDs practice Chinese handwriting skills, and we aimed to apply the mobile assisted language learning (MALL) system in clinical writing strategies. To understand the feasibility and satisfaction of this auxiliary instructional writing app, we investigated the perceive and value both from school-age students and the clinic therapists, who were the target users and the experts. A group of 8 elementary school children, as well as 8 clinic therapists, were recruited. The school-age students were asked to go through a paper-based instruction and were asked to score the visual expression based on their graphic preference; the clinic therapists were asked to watch an introductive video of this instructional app and complete the online formative questionnaire. In the results of our study, from the perspective of user interface design, school-age students were more attracted to cartoon-liked pictures rather than line drawings or vivid photos. Moreover, compared to text, pictures which have higher semantic transparency were more commonly chosen by children. In terms of the quantitative survey from clinic therapists, they were highly satisfied with this auxiliary instructional writing app, including the concepts such as visual design, teaching contents, and positive reinforcement system. Furthermore, the qualitative results also suggested comprehensive positive feedbacks on the teaching contents and the feasibility of integrating the app into clinical treatments. Interestingly, we found that clinic therapists showed high agreement in approving CWWDs’ writing ability with using orthographic knowledge; however, in the qualitative section, clinic therapists pointed out that CWWDs usually have relative insufficient background knowledge in Chinese character orthographic rules, which because it is not a key-point in conventional handwriting instruction. Also, previous studies indicated that conventional Chinese reading and writing instructions were lacked of utilizing visual-spatial arrangement strategies. Based on the sharing experiences from all participants, we concluded several interesting topics that are worth to dedicate to in the future. In this undergoing app system, improvement and revision will be applied into the system design, and will establish a better and more useful instructional system for CWWDs within their treatments; enlightened by the opinions related to learning content, the importance of orthographic knowledge in Chinese character recognition should be well discussed and involved in CWWDs’ intervention in the future.

Keywords: auxiliary instructional app, children with writing difficulties, Chinese handwriting, orthographic knowledge

Procedia PDF Downloads 177

Authors: Amor Jnifene, Cedric Cocaud

Abstract:

One of the most constraining problems facing the development of autonomous vehicles is the limitations of current technologies. Guidance and navigation controllers need to be faster and more robust. Communication data links need to be more reliable and secure. For an Unmanned Aerial Vehicles (UAV) to be useful, and fully autonomous, one important feature that needs to be an integral part of the navigation system is autonomous trajectory planning. The work discussed in this paper presents a method for on-line trajectory planning for UAV’s. This method takes into account various constraints of different types including specific vectors of approach close to target points, multiple objectives, and other constraints related to speed, altitude, and obstacle avoidance. The trajectory produced by the proposed method ensures a smooth transition between different segments, satisfies the minimum curvature imposed by the dynamics of the UAV, and finds the optimum velocity based on available atmospheric conditions. Given a set of objective points and waypoints a skeleton of the trajectory is constructed first by linking all waypoints with straight segments based on the order in which they are encountered in the path. Secondly, vectors of approach (VoA) are assigned to objective waypoints and their preceding transitional waypoint if any. Thirdly, the straight segments are replaced by 3D curvilinear trajectories taking into account the aircraft dynamics. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircrafts, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircraft, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers.

Keywords: trajectory planning, unmanned autonomous air vehicle, vector of approach, waypoints

Procedia PDF Downloads 412

Authors: Blanca A. Pichardo, Victor H. Lopez, Melchor Salazar, Rafael Garcia, Alberto Ruiz

Abstract:

Clad pipes in comparison to plain carbon steel pipes offer the oil and gas industry high corrosion resistance, reduction in economic losses due to pipeline failures and maintenance, lower labor risk, prevent pollution and environmental damage due to hydrocarbons spills caused by deteriorated pipelines. In this context, it is paramount to establish reliable welding procedures to join bimetallic plates or pipes. Thus, the aim of this work is to study the microstructure and mechanical behavior of clad plates welded by the gas metal arc welding (GMAW) process. A clad of 316L stainless steel was deposited onto API 5L X-60 plates by overlay welding with the GMAW process. Welding parameters were, 22.5 V, 271 A, heat input 1,25 kJ/mm, shielding gas 98% Ar + 2% O₂, reverse polarity, torch displacement speed 3.6 mm/s, feed rate 120 mm/s, electrode diameter 1.2 mm and application of an electromagnetic field of 3.5 mT. The overlay welds were subjected to macro-structural and microstructural characterization. After manufacturing the clad plates, a single V groove joint was machined with a 60° bevel and 1 mm root face. GMA welding of the bimetallic plates was performed in four passes with ER316L-Si filler for the root pass and an ER70s-6 electrode for the subsequent welding passes. For joining the clad plates, an electromagnetic field was applied with 2 purposes; to improve the microstructural characteristics and to assist the stability of the electric arc during welding in order to avoid magnetic arc blow. The welds were macro and microstructurally characterized and the mechanical properties were also evaluated. Vickers microhardness (100 g load for 10 s) measurements were made across the welded joints at three levels. The first profile, at the 316L stainless steel cladding, was quite even with a value of approximately 230 HV. The second microhardness profile showed high values in the weld metal, ~400 HV, this was due to the formation of a martensitic microstructure by dilution of the first welding pass with the second. The third profile crossed the third and fourth welding passes and an average value of 240 HV was measured. In the tensile tests, yield strength was between 400 to 450 MPa with a tensile strength of ~512 MPa. In the Charpy impact tests, the results were 86 and 96 J for specimens with the notch in the face and in the root of the weld bead, respectively. The results of the mechanical properties were in the range of the API 5L X-60 base material. The overlap welding process used for cladding is not suitable for large components, however, it guarantees a metallurgical bond, unlike the most commonly used processes such as thermal expansion. For welding bimetallic plates, control of the temperature gradients is key to avoid distortions. Besides, the dissimilar nature of the bimetallic plates gives rise to the formation of a martensitic microstructure during welding.

Keywords: clad pipe, dissimilar welding, gas metal arc welding, magnetic fields

Procedia PDF Downloads 154

Authors: Marlin Mubarak

Abstract:

Background: Endometriosis is a complex disabling disease affecting young females in the reproductive period mainly. The aim of this project is to generate a diagnostic model to predict severity and stage of endometriosis prior to Laparoscopic surgery. This will help to improve the pre-operative diagnostic accuracy of stage 3 & 4 endometriosis and as a result, refer relevant women to a specialist centre for complex Laparoscopic surgery. The model is based on the British Society of Gynaecological Endoscopy (BSGE) pain questionnaire, clinical examination and ultrasound scan. Design: This is a prospective, observational, study, in which women completed the BSGE pain questionnaire, a BSGE requirement. Also, as part of the routine preoperative assessment patient had a routine ultrasound scan and when recto-vaginal and deep infiltrating endometriosis was suspected an MRI was performed. Setting: Luton & Dunstable University Hospital. Patients: Symptomatic women (n = 56) scheduled for laparoscopy due to pelvic pain. The age ranged between 17 – 52 years of age (mean 33.8 years, SD 8.7 years). Interventions: None outside the recognised and established endometriosis centre protocol set up by BSGE. Main Outcome Measure(s): Sensitivity and specificity of endometriosis diagnosis predicted by symptoms based on BSGE pain questionnaire, clinical examinations and imaging. Findings: The prevalence of diagnosed endometriosis was calculated to be 76.8% and the prevalence of advanced stage was 55.4%. Deep infiltrating endometriosis in various locations was diagnosed in 32/56 women (57.1%) and some had DIE involving several locations. Logistic regression analysis was performed on 36 clinical variables to create a simple clinical prediction model. After creating the scoring system using variables with P < 0.05, the model was applied to the whole dataset. The sensitivity was 83.87% and specificity 96%. The positive likelihood ratio was 20.97 and the negative likelihood ratio was 0.17, indicating that the model has a good predictive value and could be useful in predicting advanced stage endometriosis. Conclusions: This is a hypothesis-generating project with one operator, but future proposed research would provide validation of the model and establish its usefulness in the general setting. Predictive tools based on such model could help organise the appropriate investigation in clinical practice, reduce risks associated with surgery and improve outcome. It could be of value for future research to standardise the assessment of women presenting with pelvic pain. The model needs further testing in a general setting to assess if the initial results are reproducible.

Keywords: deep endometriosis, endometriosis, minimally invasive, MRI, ultrasound.

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Authors: Wendy De Gomez

Abstract:

The University of Waterloo is situated in central Canada in the Province of Ontario- one hour from the metropolitan city of Toronto. For over 30 years, it has held Canada’s top spot as the most innovative university; and has been consistently ranked in the top 25 computer science and top 50 engineering schools in the world. Waterloo benefits from the federal government’s over 100 domestic innovation policies which have assisted in the country’s 15th place global ranking in the World Intellectual Property Organization’s (WIPO) 2022 Global Innovation Index. Yet undoubtedly, the University of Waterloo’s unique characteristics are what propels its innovative creativeness forward. This paper will provide a contextual definition of innovation in higher education and then demonstrate the five operational attributes that contribute to the University of Waterloo’s innovative reputation. The methodology is based on statistical analyses obtained from ranking bodies such as the QS World University Rankings, a secondary literature review related to higher education innovation in Canada, and case studies that exhibit the operationalization of the attributes outlined below. The first attribute is geography. Specifically, the paper investigates the network structure effect of the Toronto-Waterloo high-tech corridor and the resultant industrial relationships built there. The second attribute is University Policy 73-Intellectal Property Rights. This creator-owned policy grants all ownership to the creator/inventor regardless of the use of the University of Waterloo property or funding. Essentially, through the incentivization of IP ownership by all researchers, further commercialization and entrepreneurship are formed. Third, this IP policy works hand in hand with world-renowned business incubators such as the Accelerator Centre in the dedicated research and technology park and velocity, a 14-year-old facility that equips and guides founders to build and scale companies. Communitech, a 25-year-old provincially backed facility in the region, also works closely with the University of Waterloo to build strong teams, access capital, and commercialize products. Fourth, Waterloo’s co-operative education program contributes 31% of all co-op participants to the Canadian economy. Home to the world’s largest co-operative education program, data shows that over 7,000 from around the world recruit Waterloo students for short- and long-term placements- directly contributing to the student’s ability to learn and optimize essential employment skills when they graduate. Finally, the students themselves at Waterloo are exceptional. The entrance average ranges from the low 80s to the mid-90s depending on the program. In computer, electrical, mechanical, mechatronics, and systems design engineering, to have a 66% chance of acceptance, the applicant’s average must be 95% or above. Singularly, none of these five attributes could lead to the university’s outstanding track record of innovative creativity, but when bundled up into a 1000 acre- 100 building main campus with 6 academic faculties, 40,000+ students, and over 1300 world-class faculty, the recipe for success becomes quite evident.

Keywords: IP policy, higher education, economy, innovation

Procedia PDF Downloads 72

Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

Abstract:

Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

Procedia PDF Downloads 94

Authors: Chaitanya H. Acharya, Pavan Kumar P., Gopalakrishna Narayana

Abstract:

In the realm of aerodynamics, numerous vehicles incorporate moving components to enhance their performance. For instance, airliners deploy hydraulically operated flaps and ailerons during take-off and landing, while Formula 1 racing cars utilize hydraulic tubes and actuators for various components, including the Drag Reduction System (DRS). The DRS, consisting of a rear wing and adjustable flaps, plays a crucial role in overtaking manoeuvres. The DRS has two positions: the default position with the flaps down, providing high downforce, and the lifted position, which reduces drag, allowing for increased speed and aiding in overtaking. Swift deployment of the DRS during races is essential for overtaking competitors. The fluid flow over the rear wing flap becomes intricate during deployment, involving flow reversal and operational changes, leading to unsteady flow physics that significantly influence aerodynamic characteristics. Understanding the drag and downforce during DRS deployment is crucial for determining race outcomes. While experiments can yield accurate aerodynamic data, they can be expensive and challenging to conduct across varying speeds. Computational Fluid Dynamics (CFD) emerges as a cost-effective solution to predict drag and downforce across a range of speeds, especially with the rapid deployment of the DRS. This study employs the finite volume-based solver Ansys Fluent, incorporating dynamic mesh motions and a turbulent model to capture the complex flow phenomena associated with the moving rear wing flap. A dedicated section for the rare wing-flap is considered in the present simulations, and the aerodynamics of these sections closely resemble S1223 aerofoils. Before delving into the simulations of the rare wing-flap aerofoil, numerical results undergo validation using experimental data from an NLR flap aerofoil case, encompassing different flap angles at two distinct angles of attack was carried out. The increase in flap angle as increase in lift and drag is observed for a given angle of attack. The simulation methodology for the rare-wing-flap aerofoil case involves specific time durations before lifting the flap. During this period, drag and downforce values are determined as 330 N and 1800N, respectively. Following the flap lift, a noteworthy reduction in drag to 55 % and a decrease in downforce to 17 % are observed. This understanding is critical for making instantaneous decisions regarding the deployment of the Drag Reduction System (DRS) at specific speeds, thereby influencing the overall performance of the Formula 1 racing car. Hence, this work emphasizes the utilization of dynamic mesh motion methodology to predict the aerodynamic characteristics during the deployment of the DRS in a Formula 1 racing car.

Keywords: DRS, CFD, drag, downforce, dynamics mesh motion

Procedia PDF Downloads 98