Search results for: automated early warning score

Authors: Solaine Hachem, Frédéric Bourquin, Dominique Siegert

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The brutal collapse of bridges is mainly due to scour. Indeed, the soil erosion in the riverbed around a pier modifies the embedding conditions of the structure, reduces its overall stiffness and threatens its stability. Hence, finding an efficient technique that allows early scour detection becomes mandatory. Vibration analysis is an indirect method for scour detection that relies on real-time monitoring of the bridge. It tends to indicate the presence of a scour based on its consequences on the stability of the structure and its dynamic response. Most of the research in this field has focused on the dynamic behavior of a single pile and has examined the depth of the scour. In this paper, a bridge is fully modeled with all piles and spans and the scour is represented by a reduction in the foundation's stiffnesses. This work aims to identify the vibration modes sensitive to the rigidity’s loss in the foundations so that their variations can be considered as a scour indicator: the decrease in soil-structure interaction rigidity leads to a decrease in the natural frequencies’ values. By using the first-order perturbation method, the expression of sensitivity, which depends only on the selected vibration modes, is established to determine the deficiency of foundations stiffnesses. The solutions are obtained by using the singular value decomposition method for the regularization of the inverse problem. The propagation of uncertainties is also calculated to verify the efficiency of the inverse problem method. Numerical simulations describing different scenarios of scour are investigated on a simplified model of a real composite steel-concrete bridge located in France. The results of the modal analysis show that the modes corresponding to in-plane and out-of-plane piers vibrations are sensitive to the loss of foundation stiffness. While the deck bending modes are not affected by this damage.

Keywords: bridge’s piers, inverse problems, modal sensitivity, scour detection, vibration analysis

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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Authors: Meral Huri, Sedef Şahin

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Post-traumatic stress disorder (PTSD) is characterized by psychiatric symptoms and triggered by a terrifying experience which may immediately effect cognitive, affective, behavioral and social skills of the individual. One of the most common noncutaneous cancer among men is prostate cancer. The incidence of psychological stress is quite common in men with prostate cancer. The aim of the study was to explore the PTSD frequency among prostate cancer and define the relationship between occupational participation, coping skills and level of perceived social support among patients with prostate cancer. Forty patients diagnosed with prostate cancer were included in the study. After dividing the patients into two groups ( study/ control) according to type of tumor, we recorded their characteristics and evaluations differences. We evaluated the demographic information form, Structured Clinical Interview for DSM-IV (SCID- I)- Clinical Version for PTSD, Multidimensional Scale of Perceived Social Support, Styles of Coping Inventory and Canadian Occupational Performance Measure (COPM) before and after 1 month from surgery. The mean age of the study group (n:18) was 65.85.6 years (range: 61-79 years). The mean age of the control group (n: 22) was a little bit higher than the study group with mean age 71.3±6.9 years (range: 60-85 years). There was no statistically significant difference between the groups for age and the other characteristics. According to the results of the study, statistically significant difference was found between the level of PTSD of study and the control group. 22% of study group showed PTSD while 13% of the control group showed PTSD (r: 0.02, p<0.001). The scores of study group and control group showed statistically significant difference in five sub-categories of Styles of Coping Inventory. Patients with prostate cancer showed decreased scores in optimistic, seeking social supports and self-confident approach, while increased scores in helpless and submissive sub-categories than the control group (p<0.001). The scores of Multidimensional Scale of Perceived Social Supports of study group and control group showed statistically significant difference. The total perceived social supports score of the study group was 71.34 ± 0.75 while it was 75.34 ± 0.64 for the control group. Total and the sub-category scores of study group were statistically significant lower than the control group. According to COPM, mean scores of occupational participation of study group for occupational performance were 4.32±2.24 and 7.01±1.52 for the control group, respectively). Mean Satisfaction scores were 3,22±2.31 and 7.45±1.74 for the study and control group, respectively. The patients with prostate cancer and benign prostate hyperplasia (BPH) did not show any statistically difference in activity performance (r:0.87) while patients with prostate cancer showed statistically lower scores than the patients with BPH in activity satisfaction (r:0.02, p<0.001).Psycho-social occupational therapy interventions might help to decrease the prevalence of PTSD by increasing associated factors such as the social support perception, using coping skills and activity participation of patients with prostate cancer.

Keywords: activity performance, occupational therapy, posttraumatic stress disorder, prostate cancer

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Authors: Jonathan J. Burson

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With the rise of virtually costless, mobile-based trading platforms, stock market trading activity has increased significantly over the past decade, particularly for the millennial generation. This increased stock market attention, combined with the recent market turmoil due to the economic upset caused by COVID-19, make the topics of market-timing and forecasting particularly relevant. While the overall stock market saw an unprecedented, historically-long bull market from March 2009 to February 2020, the end of that bull market reignited a search by investors for a way to reduce risk and increase return. Similar searches for outperformance occurred in the early, and late 2000’s as the Dotcom bubble burst and the Great Recession led to years of negative returns for mean-variance, index investors. Extensive research has been conducted on fundamental analysis, technical analysis, macroeconomic indicators, microeconomic indicators, and other techniques—all using different methodologies and investment periods—in pursuit of higher returns with lower risk. The enormous variety of timeframes, data, and methodologies used by the diverse forecasting methods makes it difficult to compare the outcome of each method directly to other methods. This paper establishes a process to evaluate the market-timing methods in an apples-to-apples manner based on simplicity, performance, and feasibility. Preliminary findings show that certain technical analysis models provide a higher return with lower risk when compared to the buy-and-hold method and to other market-timing strategies. Furthermore, technical analysis models tend to be easier for individual investors both in terms of acquiring the data and in analyzing it, making technical analysis-based market-timing methods the preferred choice for retail investors.

Keywords: buy-and-hold, forecast, market-timing, probit, technical analysis

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Authors: J. Van der Walt, N. A. Plastow, M. Unger

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Gross and fine motor skill difficulties among children affect their ability to learn and progress in school. Research indicates that children in low socio-economic areas are at a higher risk of motor skill difficulties, while therapy resources are limited. The Hopscotch motor skill programme is a well-researched accessible in-school intervention developed by occupational and physiotherapists through complex intervention development. The development stage of the complex intervention development model firstly included a prevalence study in a low-resourced area in the West Coast of South Africa, indicating a high prevalence with significant motor skill difficulties among pre-school children at 14.5% with fine motor skill difficulties at 24.6%. A scoping review identifies motor skill interventions for pre-school children and a proposed a framework of fundamental concepts to consider when developing a motor skill intervention. a Delphi-study considered the framework and encouraged collaboration between therapists and educators to make the programme accessible, resource and cost effective, specifically geared towards a rural, low resourced area. The results from the Delphi study, together with the proposed framework from the scoping review was used to develop the Hopscotch programme, adopting a task-shifting approach. The eight-week small-group programme is facilitated by teachers with the support of therapists. The programme aims to improve the motor skills of pre-school aged children with motor skill difficulties to promote academic readiness through obstacle courses, ball skill games and fine motor games and crafts. A randomised controlled trial is planned as a next stage to determine the preliminary effect of the programme on the motor and early academic skills of pre-school children.

Keywords: accesible learning, motor skill intervention, school readiness, task shifting

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Authors: Jagannath P. Tegar

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The new National Education Policy (NEP) 2020 of Govt. of India has envisaged a major overhaul of the education system of India, in particular, the revamping of the Curriculum of Higher Education. In this process, the faculty members of the Indian universities and institutions have a challenging role in developing the curriculum, which is a shift from the traditional (content-based) curriculum to a student-centric- outcome-based Curriculum (SC-OBC) to be implemented in all of the Universities and institutions. The efforts and initiatives on the design and implementation of SC-OBC are remarkable in the engineering and technical education landscape of the country, but it is still in its early stages and many more steps are needed for the successful adaptation in every level of Higher Education. The premier institute of Govt. of India (NITTTR, Bhopal) has trained and developed the capacity and capability among the teachers of Polytechnics on the design and development of Student Centric - Outcome Based Curriculum and also providing academic consultancy for reforming curriculum in line of NEP- 2020 envisions for the states such as Chhattisgarh, Bihar and Maharashtra to make them responsibly ready for such a new shift in Higher Education. This research-based paper is on three main aspects: 1) the level of acceptance and preparedness of teachers /faculty towards NEP-2020 and student-centred outcome-based learning. 2) the extent of implementing NEP-2020 and student-centered outcome-based learning at Indian institutions/ universities and 3) the challenges of implementing NEP-2020 and student-centered outcome-based learning outcome-based education in the Indian context. The paper content will inspire curriculum designers and developers to prepare SC-OBC that meets the specific needs of industry and society at large, which is intended in the NEP-2020 of Govt. of India

Keywords: outcome based curriculum, student centric learning, national education policy -2020, implementation of nep-2020. outcome based learning, higher education curriculum

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Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

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The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

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Authors: Xiaoting Jing, Ling Huang

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After the reform and opening up, Chongqing has formed far more high-rise residential areas than other cities in its more than 40 years of urban construction. High-rise residential areas have become one of the main modern living models in Chongqing and an important carrier reflecting the city's high quality of life. Reviewing the construction process and renewal work helps understand the characteristics of high-rise residential areas in Chongqing at different stages, clarify current development demands, and look forward to the focus of future renewal work. Based on socio-economic development and policy background, the article sorts the construction process of high-rise residential areas in Chongqing into four stages: the early experimental construction period of high-rise residential areas (1978-1996), the rapid start-up period of high-rise commodity housing construction (1997-2006), the large-scale construction period of high-rise commodity housing and public rental housing (2007-2014), and the period of renewal and renovation of high-rise residential areas and step-by-step construction of quality commodity housing (2015-present). Based on the construction demands and main construction types of each stage, the article summarizes that the construction of high-rise residential areas in Chongqing features large scale, high speed, and high density. It points out that a large number of high-rise residential areas built after 2000 will become important objects of renewal and renovation in the future. Based on existing renewal work experience, it is urgent to explore a path for sustainable renewal and development in terms of policy mechanisms, digital supervision, and renewal and renovation models, leading the high-rise living in Chongqing toward high-quality development.

Keywords: high-rise residential areas, construction process, renewal and renovation, Chongqing

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Authors: Gleb Fomin, Kairat Tabynov, Nurkeldy Turebekov, Dinara Turegeldiyeva, Rinat Islamov

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The level of major cytokines in the blood of patients with COVID-19 varies greatly depending on age, gender, duration and severity of infection, and comorbidity. There are two clinically significant cytokines, IL-6 and TNF-α, which increase in levels in patients with severe COVID-19. However, in a model of COVID-19 in hamsters, TNF-α levels are unchanged or reduced, while the expression of other cytokines reflects the profile of cytokines found in patients’ plasma. The aim of our study was to evaluate the relationship between the level of cytokines in the blood, lungs, and lung damage in the model of the Syrian hamster (Mesocricetus auratus) infected with the SARS-CoV-2 strain. The study used outbred female and male Syrian hamsters (n=36, 4 groups) weighing 80-110 g and 5 months old (protocol IACUC, #4, 09/22/2020). Animals were infected intranasally with the hCoV-19/Kazakhstan/KazNAU-NSCEDI-481/2020 strain and euthanized at 3 d.p.i. The level of cytokines IL-6, TNF-α, IFN-α, and IFN-γ was determined by ELISA MyBioSourse (USA) for hamsters. Lung samples were subjected to histological processing. The presence of pathological changes in histological preparations was assessed on a 3-point scale. The work was carried out in the ABSL-3 laboratory. The data were analyzed in GraphPad Prism 6.00 (GraphPad Software, La Jolla, California, USA). The work was supported by the MES RK grant (AP09259865). In the blood, the level of TNF-α increased in males (p=0.0012) and IFN-γ in males and females (p=0.0001). On the contrary, IFN-α production decreased (p=0.0006). Only TNF-α level increased in lung tissues (p=0.0011). Correlation analysis showed a negative relationship between the level of IL-6 in the blood and lung damage in males (r -0.71, p=0.0001) and females (r-0.57, p=0.025). On the contrary, in males, the level of IL-6 in the lungs and score is positively correlated (r 0.80, p=0.01). The level of IFN-γ in the blood (r -0.64, p=0.035) and lungs (r-0.72, p=0.017) in males has a negative correlation with lung damage. No links were found for TNF-α and IFN-α. The study showed a positive association between lung injury and tissue levels of IL-6 in male hamsters. It is known that in humans, high concentrations of IL-6 in the lungs are associated with suppression of cellular immunity and, as a result, with an increase in the severity of COVID-19. TNF-α and IFN-γ play a key role in the pathogenesis of COVID-19 in hamsters. However, the mechanisms of their activity require more detailed study. IFN-α plays a lesser role in direct lung injury in a Syrian hamster model. We have shown the significance of tissue IL-6 and IFN-γ as predictors of the severity of lung damage in COVID-19 in the Syrian hamster model. Changes in the level of cytokines in the blood may not always reflect pathological processes in the lungs with COVID-19.

Keywords: syrian hamster, COVID-19, cytokines, biological model

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Authors: Enes Yasa, Guven Fidan

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Building Simulation tools need to better evaluate convective heat exchanges between external air and wall surfaces. Previous analysis demonstrated the significant effects of convective heat transfer coefficient values on the room energy balance. Some authors have pointed out that large discrepancies observed between widely used building thermal models can be attributed to the different correlations used to calculate or impose the value of the convective heat transfer coefficients. Moreover, numerous researchers have made sensitivity calculations and proved that the choice of Convective Heat Transfer Coefficient values can lead to differences from 20% to 40% of energy demands. The thermal losses to the ambient from a building surface or a roof mounted solar collector represent an important portion of the overall energy balance and depend heavily on the wind induced convection. In an effort to help designers make better use of the available correlations in the literature for the external convection coefficients due to the wind, a critical discussion and a suitable tabulation is presented, on the basis of algebraic form of the coefficients and their dependence upon characteristic length and wind direction, in addition to wind speed. Many research works have been conducted since early eighties focused on the convection heat transfer problems inside buildings. In this context, a Computational Fluid Dynamics (CFD) program has been used to predict external convective heat transfer coefficients at external building surfaces. For the building facades model, effects of wind speed and temperature differences between the surfaces and the external air have been analyzed, showing different heat transfer conditions and coefficients. In order to provide further information on external convective heat transfer coefficients, a numerical work is presented in this paper, using a Computational Fluid Dynamics (CFD) commercial package (CFX) to predict convective heat transfer coefficients at external building surface.

Keywords: CFD in buildings, external convective heat transfer coefficients, building facades, thermal modelling

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Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

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Authors: Emeshaw Damtew Zebene, Edom Seife, Hagos Tesfay, Gurja Belay

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Background: cancer incidence and mortality has grown rapidly throughout the world. Aging of the population, urbanization, physical inactivity, economic growth followed by smoking and drinking contributed a lot for the increased incidence of cancer all over the globe. Objective: the aim of this study was to assess a one-year trend of cancer patients who underwent curative/radical radiotherapy at radiotherapy center, Tikur Anbessa specialized hospital, Ethiopia. Methodology: We performed a prospective descriptive study of cancer patients treated with LINAC at Tikur Anbessa specialized hospital, Addis Ababa, Ethiopia, from April 2021- March 2022. A standardized questionnaire was used to collect sociodemographic and clinical characteristics of the patients. Descriptive statistics and chi-square results were generated using SPSS version 24. The level of significance was obtained at 0.05. Results: Sixty-four (64) curative/radical patients-44 females and 20 males were analyzed. Majority, 27(42.2%), of the patients age range from 45 to 64, and 45(70%) of them were urban residents where a group of higher gynecologic cancer was observed.78% of the patients were with locally advanced cancer, and 54(84.4%) of them had no awareness about cancer. Generally, head & neck cancer were found the most prevalent cancer 20(31.3%), and the leading cause of cancer among women was cervical cancer 17(38.6%), where about half 7(15.9%) of them were HIV positive. Conclusion: Our finding revealed that most of curative/radical patients presented at a locally advanced stage of the disease. Hence, maintaining the already available teletherapy machines and installing additional radiotherapy centers may help in treating the patients at the early stage of the disease. Since almost all of our study participants did not have information about cancer, awareness raising mechanisms should be done. Additionally, understanding differences in cancer incidence between urban and rural is important. Key words: Cancer, Curative/radical, Radiotherapy, Tikur Anbessa Specialized Hospital

Keywords: cancer, curative/radical, radiotherapy, tkur anbessa specialized hospital

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Authors: Anthony Khawaja, Jacques Prioux, Ghassan Maalouf, Rawad El Hage

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The regular practice of physical activities characterized by significant mechanical stresses stimulates bone formation and improves bone mineral density (BMD) in the most solicited sites. The purpose of this study was to explore the relationships between maximum power and bone variables in a group of young adult men. Identification of new determinants of BMD, bone mineral content (BMC) and hip geometric indices in young adult men, would allow screening and early management of future cases of osteopenia and osteoporosis. Fifty-three young adult men (18 – 35yr) voluntarily participated in this study. Weight and height were measured, and body mass index was calculated. Body composition, BMC and BMD were determined for each individual by Dual-energy X-ray absorptiometry (DXA; GE Healthcare, Madison, WI) at whole body (WB), lumbar spine (L1-L4), total hip (TH), and femoral neck (FN). FN cross-sectional area (CSA), strength index (SI), buckling ratio (BR), FN section modulus (Z), cross-sectional moment of inertia (CSMI) and L1-L4 TBS were also evaluated by DXA. The vertical jump was evaluated using a field test (sargent test). Two main parameters were retained: vertical jump performance (cm) and power (w). The subjects performed three jumps with 2 minutes of recovery between jumps. The highest vertical jump was selected. Maximum power (P max, in watts) was calculated. Maximum power was positively correlated to WB BMD (r = 0.41; p < 0.01), WB BMC (r = 0.65; p < 0.001), L1-L4 BMC (r = 0.54; p < 0.001), FN BMC (r = 0.35; p < 0.01), TH BMC (r = 0.50; p < 0.001), CSMI (r = 0.50; p < 0.001), CSA (r = 0.33; p < 0.05). Vertical jump was positively correlated to WB BMC (r = 0.31; p < 0.05), L1-L4 BMC (r = 0.40; p < 0.01), CSMI (r = 0.29; p < 0.05). The current study suggests that maximum power is a positive determinant of BMD, BMC and hip geometric indices in young adult men. In addition, it shows also that maximum power is a stronger positive determinant of bone variables than vertical jump in this population. Implementing strategies to increase maximum power in young adult men may be useful for preventing osteoporotic fractures later in life.

Keywords: bone variables, maximum power, osteopenia, osteoporosis, vertical jump, young adult men

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Authors: Wei Qu, Cassandra Agius, Nikki Varvazovsky, Angela Meade

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The goals of the case study are to address the importance of early diagnosis of osmotic demyelination syndrome (ODS) and to analyse the types, duration, and intensities of the rehabilitation program to promote neurological and functional recovery. It can be associated with biphasic course of disease and severe neurological and neuropsychiatric symptoms. Although a few treatment modalities, such as plasmapheresis, immunoglobulin therapy, steroid, and thyrotrophin-releasing hormone, have been suggested, there is no effective treatment for ODS. The overall prognosis of established ODS is generally poor. A high proportion of patients have a severe permanent disability, which has led to social, economic, and emotional burdens to carers and societies. In this case, a 69-year-old retired pensioner with chronic alcoholism was admitted to the hospital with a reduced level of consciousness and tonic-clonic seizure. He had severe hyponatraemia (serum sodium 118 mmol/L) and hypokalemia (serum potassium 2.8 mmol/L). He was treated with anticonvulsants, 150ml 3% hypertonic saline over one hour, and 40 mmol potassium chloride over one hour, and his sodium was increased by 11 mmol/L in the first 24 hours. However, he had worsened neurological symptoms with quadriplegia, dysphagia, anarthria, and confusion, and the radiological features suggested the diagnosis of ODS. He had minimal neurological recovery during the first four weeks of hospital admission. He was treated with seven weeks of a multi-disciplinary intensive rehabilitation program. On discharge, he had made a significant cognitive and functional recovery and could mobilize independently without a walking aid. In conclusion, ODS can still occur despite correcting sodium following the current clinical guidelines. Patients with severe neurological deficits in the context of osmotic demyelination syndrome would benefit from intensive rehabilitation to facilitate their functional improvement and to promote their quality of life.

Keywords: osmotic demyelination syndrome, hyponatremia, central pontine and extrapontine myelinolysis, rehabilitation

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Authors: WonSun Chen, James Boylan, Erwin Muharemovic, Denny Meyer

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In Australia, drivers aged between 18 and 24 remained at high risk of road fatality over the last decade. Despite the successful implementation of the Graduated Licensing System (GLS) that supports young drivers in their early phases of driving, the road fatality statistics for these drivers remains high. In response to these statistics, studies conducted in Australia prior to the start of the COVID-19 pandemic have demonstrated the benefits of using telematics devices for improving driving behaviour, However, the impact of COVID-19 lockdown on young drivers’ driving behaviour has emerged as a global concern. Therefore, this naturalistic study aimed to evaluate and compare the driving behaviour(such as acceleration, braking, speeding, etc.) of young drivers with the adoption of in-vehicle telematics devices. Forty-two drivers aged between 18 and 30 and residing in the Australian state of Victoria participated in this study during the period of May to October 2022. All participants drove with the telematics devices during the first 30-day. At the start of the second 30-day, twenty-one participants were randomised to an intervention group where they were provided with an additional telematics ray device that provided visual feedback to the drivers, especially when they committed to aggressive driving behaviour. The remaining twenty-one participants remined their driving journeys without the extra telematics ray device (control group). Such trustworthy data enabled the assessment of changes in the driving behaviour of these young drivers using a machine learning approach in Python. Results are expected to show participants from the intervention group will show improvements in their driving behaviour compared to those from the control group.Furthermore, the telematics data enable the assessment and quantification of such improvements in driving behaviour. The findings from this study are anticipated to shed some light in guiding the development of customised campaigns and interventions to further address the high road fatality among young drivers in Australia.

Keywords: driving behaviour, naturalistic study, telematics data, young drivers

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Authors: Praveen Adusumilli, Meher Lakshmi Konatam, Sadashivudu Gundeti, Stalin Bala

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The invention of trastuzumab has changed the treatment of breast cancer and lives of many patients all over the world. Despite many patients getting benefitted from the drug, it is out of reach for most of the patients. There is very limited real world data regarding the epidemiology and clinical outcome of Her2neu positive breast cancer patients. Materials and Methods: This is a retrospective analysis of breast cancer patients presenting to a tertiary care cancer centre in Southern India from 2007 to2013. All early and locally advanced breast cancer patients, who were Her2neu 3+ on IHC are included in the study and evaluated in terms of epidemiology, 3-year disease free survival (DFS)and 5-year overall survival(OS). Chemotherapy regimens used were-FAC 6 cycles or AC 4 cycles followed by 12 cycles of weekly paclitaxel . Trastuzumab was given after 6 cycles of FAC or weekly with paclitaxel followed by 3weekly maintenance until 1 year. Results: Over the period of this study there were 885 newly diagnosed cases of carcinoma breast, of which 242 (27%) were Her2neu positive, 360(40%) were hormone receptor positive, and 212(24%) were triple negative. A total of 71(8%) were Her2neu equivocal of which only 10 patients got FISH test done. Of the 212 newly diagnosed patients, only 74 (29%) opted to have standard of care therapy with trastuzumab at our centre, out of which 52(24%), 8(3%), received under insurance, paying basis respectively. 14(9%) patients received the care as part of clinical trial program (ALTTO trial). 7 (9.72%) patients developed decrease of ejection fraction by greater than 10%, requiring stoppage of trastuzumab out of which 5 were restarted in 2 months. Patients receiving trastuzumab along with chemotherapy had longer 3year DFS 92% vs. 60% (p value<0.0001) when compared to chemotherapy alone. 5 year OS was 87% vs 44% (p-value <0.0001) compared to chemotherapy alone. Conclusion: Trastuzumab with chemotherapy improves the DFS and OS in Her2neu positive patients. The biggest constraint is the cost of the treatment and absence of universal health security net to treat all patients with this diagnosis.

Keywords: breast cancer, Her 2 neu positive, real world data, Trastuzumab

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Authors: Andrew Kanzunguze, Sopani Sichinga, Paston Simkoko, George Nxumayo, Cosmas, V. B. Dambo

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Early detection of plant invasions is a necessary prerequisite for effective invasive plant management in protected areas. This study was conducted to determine the distribution and abundance of alien invasive trees in Nyika National Park (NNP). Data on species' presence and abundance were collected from belt transects (n=31) in a 100 square kilometer area on the central plateau. The data were tested for normality using the Shapiro-Wilk test; Mann-Whitney test was carried out to compare frequencies and abundances between the species, and geographical information systems were used for spatial analyses. Results revealed that Black Wattle (Acacia mearnsii), Mexican Pine (Pinus patula) and Himalayan Raspberry (Rubus ellipticus) were the main alien invasive trees on the plateau. A. mearnsii was localized in the areas where it was first introduced, whereas P. patula and R. ellipticus were spread out beyond original points of introduction. R. ellipticus occurred as dense, extensive (up to 50 meters) thickets on the margins of forest patches and pine stands, whilst P. patula trees were frequent in the valleys, occurring most densely (up to 39 stems per 100 square meters) south-west of Chelinda camp on the central plateau with high variation in tree heights. Additionally, there were no significant differences in abundance between R. ellipticus (48) and P. patula (48) in the study area (p > 0.05) It was concluded that R. ellipticus and P. patula require more attention as compared to A. mearnsii. Howbeit, further studies into the invasion ecology of both P. patula and R. ellipticus on the Nyika plateau are highly recommended so as to assess the threat posed by the species on biodiversity, and recommend appropriate conservation measures in the national park.

Keywords: alien-invasive trees, Himalayan raspberry, Nyika National Park, Mexican pine

Procedia PDF Downloads 156

Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: Tamirat Solomon, Aberash Yohannis, Efrem Gulfo

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The plantation of trees, which harmonizes the agroecology of the environment, has been implemented in Ethiopia with great concern for a noticeably degraded environment. This study was designed to evaluate the effectiveness of green legacy, species selection and, the rate of survival, and the management status in the study areas. A systematic sampling method was employed to collect the required data from 144 quadrants measuring a 15m radius with an interval of 40m apart. Additionally, 244 sample households were selected for the socioeconomic study in addition to secondary data collected from office recordings. The data collected was analyzed using multivariate analysis, considering exposure and outcome variables. The findings of this study indicated that four exotic tree species, namely; A. salgina, C. fistula, A. indica, and G. robusta, were commonly selected tree species for degraded land restoration in the study areas. Among the seedlings planted at the four study sites, a total of 79.9% survived, and A. salgina was the dominant and best performed species, A. indica was the least survived species in the entire study area. The age of the seedling before planting significantly (p = 0.05) affected the survival potential of most seedlings of species, and the majority (82%) of local communities expressed their positive attitudes and willingness to manage the restoration works in the study areas. It was recommended to consider the inclusion of native species in the restoration effort and evaluate the co-existence of native flora with exotic and its competition for nutrients, water, and light in addition to the invading potentials in the ecosystem. In general, before embarking on degraded land restoration, species selection, adequate preparation of seedlings, and species diversity composition that exactly fit the socioeconomic and ecological demands of the areas must get the attention for the success of the restoration.

Keywords: plantation forest, degraded land, forest restoration, plantation survival, species selection

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Authors: Yaxin Bi, Peter Nicholl

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The rapid advancement of Information and communication technologies (ICT) is extremely influencing every aspect of Higher Education. It has transformed traditional teaching, learning, assessment and feedback into a new era of Digital Education. This also introduces many challenges in capturing and understanding student engagement with their studies in Higher Education. The School of Computing at Ulster University has developed a Feedback And Notification (FAN) Online tool that has been used to send students links to personalized feedback on their submitted assessments and record students’ frequency of review of the shared feedback as well as the speed of collection. The feedback that the students initially receive is via a personal email directing them through to the feedback via a URL link that maps to the feedback created by the academic marker. This feedback is typically a Word or PDF report including comments and the final mark for the work submitted approximately three weeks before. When the student clicks on the link, the student’s personal feedback is viewable in the browser and they can view the contents. The FAN tool provides the academic marker with a report that includes when and how often a student viewed the feedback via the link. This paper presents an investigation into student engagement through analyzing the interaction timestamps and frequency of review by the student. We have proposed an approach to modeling interaction timestamps and use sentiment classification techniques to analyze the data collected over the last five years for a set of modules. The data studied is across a number of final years and second-year modules in the School of Computing. The paper presents the details of quantitative analysis methods and describes further their interactions with the feedback overtime on each module studied. We have projected the students into different groups of engagement based on sentiment analysis results and then provide a suggestion of early targeted intervention for the set of students seen to be under-performing via our proposed model.

Keywords: feedback, engagement, interaction modelling, sentiment analysis

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Authors: Andriy Fedorenko

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Background Early closure of the open abdomen is a priority after damage control laparotomy to prevent retraction of fascial layers and prevent hernia formation that requires definitive repair at a later stage. This substantially reduces the complications associated with ventral hernia formation for up to a year after initial surgery. TopClosure® is an innovative method that employs stress-relaxation and mechanical creep for skin stretching. Its use enables the primary closure of large abdominal wall defects and mitigates large ventral hernia formation. Materials and Methods A 7-year-old girl presented with severe blast injury. She underwent initial laparotomy in a facility within the conflict zone and was transferred in a state of septic shock to our facility for further care. Her abdominal injuries included liver lacerations, multiple perforations of the transverse colon and ileum, and a 8x16cm oblique abdominal wall defect. Further damage control laparotomy was performed with primary suture of the colon and ileum and temporary closure of the abdomen using a Bagota bag. Twelve hours later, negative pressure wound therapy (NPWT) was applied to the abdominal wound after relook laparotomy. Five days later, TopClosure® was applied to the lower part of the wound incorporating NPWT to the upper wound. Results The patient suffered leak from the colonic suture line and required relaparotomy. TopClosure® abdominal closure was achieved after every laparotomy. Conclusion TopClosure® utilizes the viscoelastic properties of the skin achieving full closure of the abdominal wall (including the fascia and skin),eliminating the need for prolonged NPWT, skin graft, and delayed ventral hernia repair surgery.

Keywords: topclosure, abdominal wall defect, hernia, damage control

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Authors: Hong Li, Haiyang Yu, Shiqing Cheng, Nai Cao, Zhiliang Shi

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Unconventional resources have gradually become the main direction for oil and gas exploration and development. However, the productivity of gas wells, the level of water production, and the seepage law in tight fractured gas reservoirs are very different. These are the reasons why production prediction is so difficult. Firstly, a three-dimensional multi-scale fracture and multiphase mathematical model based on an embedded discrete fracture model (EDFM) is established. And the material balance method is used to calculate the water body multiple according to the production performance characteristics of water-producing gas well. This will help construct a 'virtual water body'. Based on these, this paper presents a numerical simulation process that can adapt to different production modes of gas wells. The research results show that fractures have a double-sided effect. The positive side is that it can increase the initial production capacity, but the negative side is that it can connect to the water body, which will lead to the gas production drop and the water production rise both rapidly, showing a 'scissor-like' characteristic. It is worth noting that fractures with different angles have different abilities to connect with the water body. The higher the angle of gas well development, the earlier the water maybe break through. When the reservoir is a single layer, there may be a stable production period without water before the fractures connect with the water body. Once connected, a 'scissors shape' will appear. If the reservoir has multiple layers, the gas and water will produce at the same time. The above gas-water relationship can be matched with the gas well production date of the Xujiahe gas reservoir in the Sichuan Basin. This method is used to predict the productivity of a well with hydraulic fractures in this gas reservoir, and the prediction results are in agreement with on-site production data by more than 90%. It shows that this research idea has great potential in the productivity prediction of water-producing gas wells. Early prediction results are of great significance to guide the design of development plans.

Keywords: EDFM, multiphase, multilayer, water body

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Authors: Dipankar Saha, J. P. Singh, C. B. Pandey

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Indian Thar desert being the seventh largest in the world is the main hot sand desert occupies nearly 385,000km2 and about 9% of the area of the country harbours several species likely the flora of 682 species (63 introduced species) belonging to 352 genera and 87 families. The degree of endemism of plant species in the Thar desert is 6.4 percent, which is relatively higher than the degree of endemism in the Sahara desert which is very significant for the conservationist to envisage. The advent and development of computer technology for digitization and data base management coupled with the rapidly increasing importance of biodiversity conservation resulted in the invention of biodiversity informatics as discipline of basic sciences with multiple applications. Aichi Target 19 as an outcome of Convention of Biological Diversity (CBD) specifically mandates the development of an advanced and shared biodiversity knowledge base. Information on species distributions in space is the crux of effective management of biodiversity in the rapidly changing world. The efficiency of biodiversity management is being increased rapidly by various stakeholders like researchers, policymakers, and funding agencies with the knowledge and application of biodiversity informatics. Herbarium specimens being a vital repository for biodiversity conservation especially in climate change scenario the digitization process usually aims to improve access and to preserve delicate specimens and in doing so creating large sets of images as a part of the existing repository as arid plant information facility for long-term future usage. As the leaf characters are important for describing taxa and distinguishing between them and they can be measured from herbarium specimens as well. As a part of this activity, laminar characterization (leaves being the most important characters in assessing climate change impact) initially resulted in classification of more than thousands collections belonging to ten families like Acanthaceae, Aizoaceae, Amaranthaceae, Asclepiadaceae, Anacardeaceae, Apocynaceae, Asteraceae, Aristolochiaceae, Berseraceae and Bignoniaceae etc. Taxonomic diversity indices has also been worked out being one of the important domain of biodiversity informatics approaches. The digitization process also encompasses workflows which incorporate automated systems to enable us to expand and speed up the digitisation process. The digitisation workflows used to be on a modular system which has the potential to be scaled up. As they are being developed with a geo-referencing tool and additional quality control elements and finally placing specimen images and data into a fully searchable, web-accessible database. Our effort in this paper is to elucidate the role of BIs, present effort of database development of the existing botanical collection of institute repository. This effort is expected to be considered as a part of various global initiatives having an effective biodiversity information facility. This will enable access to plant biodiversity data that are fit-for-use by scientists and decision makers working on biodiversity conservation and sustainable development in the region and iso-climatic situation of the world.

Keywords: biodiversity informatics, climate change, digitization, herbarium, laminar characters, web accessible interface

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Authors: A. M. Taleb, A. G. Tail, A. F. Kara, B. B. Djedouani, C. T. Moussa

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Forensic entomology is the use of insects to aid legal investigations. The main purpose of forensic entomology is to establish the postmortem interval (PMI). In order to estimate the PMI, a forensic entomologist compares the case data with certain reference information relevant to the particular location and time of year. This reference information, including the local distribution of species, are not available in Algeria. Therefore, experiments need to be conducted to provide references for entomological evidence. The objective of this study was to identify the necrophagous flies species which arrive first to carrion using liver baits in Ghardaia, South Algeria. The study was carried out during the spring season in the palmeral of Beni Isguen, Ghardaia which is well known by its hot arid climate. The experiment site (32°28’0’’ N, 3°42’0’’ E), is situated at an altitude of about 526 metres above mean sea level. On April the 4th, 2014, a number of three replicates of liver baited traps were placed in the shade and other three baits were exposed to the sun. Flying insects and larvae were captured and identified. After few minutes, flies invaded the traps which were exposed to the sun. In contrast, no flies were observed in the other traps. A total number of fourty five (45) adult specimens belonging to three taxa were identified: Calliphora vicina (Robineau-Desvoidy, 1830) (Diptera, Calliphoridae) (51.11 %), Lucilia sericata (Meigen, 1826) (Diptera, Calliphoridae) (33.33 %) and Sarcophaga africa (Wiedemann, 1824) (Diptera: Sarcophagidae) (15.55 %). Six hundred and three (603) maggots belonging to two taxa were identified: Calliphora vicina (76.28 %) and Lucilia sericata (23.71 %). The data obtained from this study provides baseline information regarding the carrion fauna of this area. It will also form a basis for similar studies in different geographical and climatological regions of Algeria.

Keywords: forensic entomology, liver baits, necrophagous fly, Ghardaia, South Algeria

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Authors: Duduzile Dlamini-Boemah, Haretsebe Manwa, Lisebo Tseane-Gumbi

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The demands and expectations of twenty-first century tourists have changed, and they continue to have an impact on tour guiding in cultural and natural tourist attractions. The traditional communicative role of the tour guide as a mere presenter is not sufficient anymore; instead, there are expectations from the tourists of guides who provide effective interpretive guiding. It is always questionable if tour guides in South Africa are equipped with the skills for effective interpretation, yet limited research has been conducted to investigate the continuing professional education of tour guides in South Africa. Instead, much attention has been given to aspects of registration and certification of tour guides in South Africa. Concerns have been raised about tour guiding and have led to the development of a strategy by the Department of Tourism to professionalise tourists guiding that includes training. However, the necessity for tourism training in tour guiding in South Africa was raised as early as in the 1980s, the paper argues that there is a further need to emphasise continuing professional education in interpretive guiding in South Africa. In this study, continuing education and training are considered to involve the upgrading of the skills and knowledge of interpretation of those who are already working as tour guides at the cultural and natural attractions. The study is guided by the empowerment theory. The aim of this paper is to present issues of effective interpretive guiding and continuing professional education in interpretive guiding in South Africa. This study is based on the literature survey of secondary sources such as academic journal articles, government documents, and reports and books. The conclusions indicate that there is a need for training in interpretive delivery techniques in South Africa. The need for interpretive training in interpretive delivery techniques is attributed by the call to allow people to use indigenous knowledge, rather than formal education as a basis for becoming a field guide as well as affording the previously disadvantaged individuals to access training opportunities as tourist guides.

Keywords: continuing education, interpretive delivery skills, interpretive guiding, tour guide

Procedia PDF Downloads 137

Authors: Mark Andrew

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Geopolitical tensions are at a thirty-year high, and the pace of technological innovation is driving asymmetry in force capabilities between nation states and between non-state actors. Technology futures are a vital component of defence capability growth, and investments in technology futures need to be informed by accurate and reliable forecasts of the options for ‘systems of systems’ innovation, development, and deployment. This paper describes a method for forecasting technology futures developed through an analysis of four key systems’ development stages, namely: technology domain categorisation, scanning results examining novel systems’ signals and signs, potential system-of systems’ implications in warfare theatres, and political ramifications in terms of funding and development priorities. The method has been applied to several technology domains, including physical systems (e.g., nano weapons, loitering munitions, inflight charging, and hypersonic missiles), biological systems (e.g., molecular virus weaponry, genetic engineering, brain-computer interfaces, and trans-human augmentation), and information systems (e.g., sensor technologies supporting situation awareness, cyber-driven social attacks, and goal-specification challenges to proliferation and alliance testing). Although the current application of the method has been team-centred using paper-based rapid prototyping and iteration, the application of autonomous language models (such as GPT-3) is anticipated as a next-stage operating platform. The importance of forecasting accuracy and reliability is considered a vital element in guiding technology development to afford stronger contingencies as ideological changes are forecast to expand threats to ecology and earth systems, possibly eclipsing the traditional vulnerabilities of nation states. The early results from the method will be subjected to ground truthing using longitudinal investigation.

Keywords: forecasting, technology futures, uncertainty, complexity

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Authors: Grzegorz Szaciłowski, Marta Konop, Małgorzata Dymecka, Jakub Ośko

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In 1996, the European Council Directive 96/29/EURATOM pointed phosphate fertilizers to have a potentially negative influence on the environment from the radiation protection point of view. Fertilizers along with irrigation and crop rotation were the milestones that allowed to increase agricultural productivity. Firstly based on natural materials such as compost, manure, fish processing waste, etc., and since the 19th century created synthetically, fertilizers caused a boom in crop yield and helped to propel global food production, especially after World War II. In this work the concentrations of ²¹⁰Po, ²²⁶Ra, ²³²Th, ⁴⁰K, and ¹³⁷Cs in selected fertilizers and soil samples were determined. The results were used to calculate the annual addition of natural radionuclides and increment of the external radiation exposure caused by the use of studied fertilizers. Soils intended for different types of crops were sampled in early spring when no vegetation had occurred yet. Analysed fertilizers were those with which the soil was previously fertilized. For gamma radionuclides, a high purity germanium detector GX3520 from Canberra was used. The polonium concentration was determined by radiochemical separation followed by measurement by means of alpha spectrometry. The spectrometer used in this study was equipped with 450 cm² PIPS detector from Canberra. Obtained results showed significant differences in radionuclide composition between phosphate and nitrogenous fertilizers (e.g. the radium equivalent activity for phosphate fertilizer was 207.7 Bq/kg in comparison to <5.6 Bq/kg for nitrogenous fertilizer). The calculated increase of external radiation exposure due to use of phosphate fertilizer ranged between 3.4 and 5.4 nG/h, which represents up to 10% of the polish average outdoor exposure due to terrestrial gamma radiation (45 nGy/h).

Keywords: ²¹⁰Po, alpha spectrometry, exposure, gamma spectrometry, phosphate fertilizer, soil

Procedia PDF Downloads 273

Authors: Vongsathorn Ngampuak, Yutachai Chookaew, Wipawee Dejtisakdi

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Dunaliella salina has great potential as a system for generating commercially valuable products, including beta-carotene, pharmaceuticals, and biofuels. Our goal is to improve this potential by enhancing growth rate and other properties of D. salina under optimal growth conditions. We used ethyl methane sulfonate (EMS) to generate random mutants in D. salina KU11, a strain classified in Thailand. In a preliminary experiment, we first treated D. salina cells with 0%, 0.8%, 1.0%, 1.2%, 1.44% and 1.66% EMS to generate a killing curve. After that, we randomly picked 30 candidates from approximately 300 isolated survivor colonies from the 1.44% EMS treatment (which permitted 30% survival) as an initial test of the mutant screen. Among the 30 survivor lines, we found that 2 strains (mutant #17 and #24) had significantly improved growth rates and cell number accumulation at stationary phase approximately up to 1.8 and 1.45 fold, respectively, 2 strains (mutant #6 and #23) had significantly decreased growth rates and cell number accumulation at stationary phase approximately down to 1.4 and 1.35 fold, respectively, while 26 of 30 lines had similar growth rates compared with the wild type control. We also analyzed cell size for each strain and found there was no significant difference comparing all mutants with the wild type. In addition, mutant #24 had shown an increase of biomass accumulation approximately 1.65 fold compared with the wild type strain on day 5 that was entering early stationary phase. From these preliminary results, it could be feasible to identify D. salina mutants with significant improved growth rate, cell accumulation and biomass production compared to the wild type for the further study; this makes it possible to improve this microorganism as a platform for biotechnology application.

Keywords: Dunaliella salina, ethyl methyl sulfonate, growth rate, biomass

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Authors: Tina Sleiman

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In the early 1970s, a graphics revolution - in quantity and quality - marked the youth publications sector in France. The increased interest in youth publications was supported with the emergence of youth libraries and major publishing houses. In parallel, the 'Agence de Cooperation Culturelle et Technique' (currently the International Organization of the Francophonie) was created, and several Arab countries had joined as members. In spite of political turmoil in the Middle East, French schools in Arab countries were still functioning and some even flourishing. This is a testament that French culture was, and still is, a major export to the region. This study focuses on the aesthetic value of the graphic styles that characterize French children’s books from the 1970s, and their personal value to Francophone people who have consumed these artifacts, in the Middle East. The first part of the study looks at the artifact itself: starting from the context of creation and consumption of these books, and continuing to the preservation and remaining collections. The aesthetic value is studied and compared to similar types of visuals of juxtaposed time periods. The second part examines the audience’s response to the visuals in terms of style recognition or identification, along with emotional significance or associations, and the personal value the artifacts might hold to their consumers. The methods of investigation consist of a literature review, a survey of book collections, and a visual questionnaire, supported by personal interviews. As an outcome, visual patterns will be identified: elements from 1970s children’s books reborn in contemporary youth-based publications. Results of the study shall inform us directly on the aesthetic and personal value of illustrated French children’s books in the Middle East, and indirectly on the capacity of youth-targeted design to create a long-term emotional response from its audience.

Keywords: children’s books, French visual culture, graphic style, publication design, revival

Procedia PDF Downloads 140

Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

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Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

Procedia PDF Downloads 326