Search results for: performance properties

Authors: Akinola Helen Olufunke, Soetan Olatunbosun Jonathan, Adeleye Oludamola

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Introduction: Antibiotic resistance has grown significantly, which is a major cause for concern. There have not been many significant developments in antibiotics over the past few decades, and practically all of the ones that are currently in use are losing effectiveness against pathogenic germs. Researchers are starting to focus more on the physiologically active compounds found in plants, particularly phytobiotics in poultry production. Consumption of chicken products is among the greatest in the country, but numerous nations, including Nigeria, use excessive amounts of necessary antibiotics in poultry farming, endangering the safety of such goods (through antimicrobial residues). Drug resistance has become a widespread issue as a result of the risky use of antibiotics in the chicken production industry. In order to replace antibiotics, biotic or natural products like phytobiotics (also known as botanicals or phytogenics) have drawn a lot of interest. Phytobiotics or their components are thought to be a relatively recent category of natural herbs that have acquired acceptance and favor among chicken farmers. The addition of several phytobiotic additions to poultry feed has demonstrated its capacity to improve both the broiler and layer populations' productivity. Design: Experimental research design and cross-sectional study was carried out at every 300 purposively selected farming household in the six-geopolitical zone in Nigeria. Data Analysis: A semi-structured questionnaire was administered to each farmer, and quantitative data were analyzed using Statistical Package for Social Science (SPSS) while the Chi-square test was used to analyze factors mitigating the use of Phytobiotics. Result: The result shows that the benefits associated with the use of phytobiotics are contributed to growth promotion in chickens and enhancement of productive performance of broiler and layer, which could be attributed to their antioxidant activity. The result further revealed that factors mitigating the use of phytobiotics were lack of knowledge in the use of phytobiotics, overdose or underdose usage, and seasonal availability of the phytobiotics. Others are the educational level of the farmers, intrinsic motivation, income poultry farming experience, price of phytobiotics based additives feeds, and intensity of extension agents in visiting them. Conclusion: The difficulties associated with using phytobiotics in chicken farms limit their willingness to boost productivity. The study found that most farmers were ignorant, which prevented them from handling this notion and turning their poultry into a viable enterprise while also allowing them to be creative. They believed that packing phytobiotics-based additive feed was expensive, and lastly, the seasonal availability of some phytobiotics. Recommendation: Further research in phytobiotics use in Nigeria should be carried out in order to establish its efficiency, safety, and awareness.

Keywords: mitigating, antibiotics, phytobiotics, poultry farming

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Anirudh Lahiri

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Neuromorphic computing, inspired by the intricate operations of biological neural networks, offers a revolutionary approach to overcoming the limitations of traditional computing architectures. This research proposes the integration of spintronics with neuromorphic systems, aiming to enhance computational performance, scalability, and energy efficiency. Traditional computing systems, based on the Von Neumann architecture, struggle with scalability and efficiency due to the segregation of memory and processing functions. In contrast, the human brain exemplifies high efficiency and adaptability, processing vast amounts of information with minimal energy consumption. This project explores the use of spintronics, which utilizes the electron's spin rather than its charge, to create more energy-efficient computing systems. Spintronic devices, such as magnetic tunnel junctions (MTJs) manipulated through spin-transfer torque (STT) and spin-orbit torque (SOT), offer a promising pathway to reducing power consumption and enhancing the speed of data processing. The integration of these devices within a neuromorphic framework aims to replicate the efficiency and adaptability of biological systems. The research is structured into three phases: an exhaustive literature review to build a theoretical foundation, laboratory experiments to test and optimize the theoretical models, and iterative refinements based on experimental results to finalize the system. The initial phase focuses on understanding the current state of neuromorphic and spintronic technologies. The second phase involves practical experimentation with spintronic devices and the development of neuromorphic systems that mimic synaptic plasticity and other biological processes. The final phase focuses on refining the systems based on feedback from the testing phase and preparing the findings for publication. The expected contributions of this research are twofold. Firstly, it aims to significantly reduce the energy consumption of computational systems while maintaining or increasing processing speed, addressing a critical need in the field of computing. Secondly, it seeks to enhance the learning capabilities of neuromorphic systems, allowing them to adapt more dynamically to changing environmental inputs, thus better mimicking the human brain's functionality. The integration of spintronics with neuromorphic computing could revolutionize how computational systems are designed, making them more efficient, faster, and more adaptable. This research aligns with the ongoing pursuit of energy-efficient and scalable computing solutions, marking a significant step forward in the field of computational technology.

Keywords: material science, biological engineering, mechanical engineering, neuromorphic computing, spintronics, energy efficiency, computational scalability, synaptic plasticity.

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Authors: Doni Dermawan

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Modern sports competition as a consequence of the increase in the value of the business and entertainment in the field of sport has been demanding athletes to always have excellent physical endurance performance. Physical exercise is done in a long time, and intensive may pose a risk of muscle tissue damage caused by the increase of the enzyme creatine kinase. Branched Chain Amino Acids (BCAA) is an essential amino acid that is composed of leucine, isoleucine, and valine which serves to maintain muscle tissue, keeping the immune system, and prevent further loss of coordination and muscle pain. Pea (Pisum sativum L.) is a kind of leguminous plants that are rich in Branched Chain Amino Acids (BCAA) where every one gram of protein pea contains 82.7 mg of leucine; 56.3 mg isoleucine; and 56.0 mg of valine. This research aims to develop Branched Chain Amino Acids (BCAA) from pea extract is applied in dosage forms Gel PVP Kinesio Tape technology using Ultrasound-assisted Extraction. The method used in the writing of this paper is the Cochrane Collaboration Review that includes literature studies, testing the quality of the study, the characteristics of the data collection, analysis, interpretation of results, and clinical trials as well as recommendations for further research. Extraction of BCAA in pea done using ultrasound-assisted extraction technology with optimization variables includes the type of solvent extraction (NaOH 0.1%), temperature (20-250C), time (15-30 minutes) power (80 watt) and ultrasonic frequency (35 KHz). The advantages of this extraction method are the level of penetration of the solvent into the membrane of the cell is high and can increase the transfer period so that the BCAA substance separation process more efficient. BCAA extraction results are then applied to the polymer PVP (Polyvinylpyrrolidone) Gel powder composed of PVP K30 and K100 HPMC dissolved in 10 mL of water-methanol (1: 1) v / v. Preparations Kinesio Tape Gel PVP is the BCAA in the gel are absorbed into the muscle tissue, and joints through tensile force then provides stimulation to the muscle circulation with variable pressure so that the muscle can increase the biomechanical movement and prevent damage to the muscle enzyme creatine kinase. Analysis and evaluation of test preparation include interaction, thickness, weight uniformity, humidity, water vapor permeability, the levels of the active substance, content uniformity, percentage elongation, stability testing, release profile, permeation in vitro and in vivo skin irritation testing.

Keywords: branched chain amino acid, BCAA, Kinesio tape, pea, PVP gel, ultrasound-assisted extraction

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Authors: Jianan Sun, Ziwen Ye

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Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

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Authors: Ocsana Opris, Ildiko Lung, Maria L. Soran, Alexandra Ciorita, Lucian Copolovici

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The effects assessment of environmental stress factors on both crop and wild plants of nutritional value are a very important research topic. Continuously worldwide consumption of drugs leads to significant environmental pollution, thus generating environmental stress. Understanding the effects of the important drugs on plant composition and ultrastructural modification is still limited, especially at environmentally relevant concentrations. The aim of the present work was to investigate the influence of three non-steroidal anti-inflammatory drugs (NSAIDs) on chlorophylls content, carotenoids content, total polyphenols content, antioxidant capacity, and ultrastructure of orache (Atriplex patula L.) and spinach (Spinacia oleracea L.). All green leafy vegetables selected for this study were grown in controlled conditions and treated with solutions of different concentrations (0.1‒1 mg L⁻¹) of diclofenac, ibuprofen, and naproxen. After eight weeks of exposure of the plants to NSAIDs, the chlorophylls and carotenoids content were analyzed by high-performance liquid chromatography coupled with photodiode array and mass spectrometer detectors, total polyphenols and antioxidant capacity by ultraviolet-visible spectroscopy. Also, the ultrastructural analyses of the vegetables were performed using transmission electron microscopy in order to assess the influence of the selected NSAIDs on cellular organisms, mainly photosynthetic organisms (chloroplasts), energy supply organisms (mitochondria) and nucleus as a cellular metabolism coordinator. In comparison with the control plants, decreases in the content of chlorophylls were observed in the case of the Atriplex patula L. plants treated with ibuprofen (11-34%) and naproxen (25-52%). Also, the chlorophylls content from Spinacia oleracea L. was affected, the lowest decrease (34%) being obtained in the case of the treatment with naproxen (1 mg L⁻¹). Diclofenac (1 mg L⁻¹) affected the total polyphenols content (a decrease of 45%) of Atriplex patula L. and ibuprofen (1 mg L⁻¹) affected the total polyphenols content (a decrease of 20%) of Spinacia oleracea L. The results obtained also indicate a moderate reduction of carotenoids and antioxidant capacity in the treated plants, in comparison with the controls. The investigations by transmission electron microscopy demonstrated that the green leafy vegetables were affected by the selected NSAIDs. Thus, this research contributes to a better understanding of the adverse effects of these drugs on studied plants. Important to mention is that the dietary intake of these drugs contaminated plants, plants with important nutritional value, may also presume a risk to human health, but currently little is known about the fate of the drugs in plants and their effect on or risk to the ecosystem.

Keywords: abiotic stress, green leafy vegetables, pigments content, ultra structure

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Authors: Julien Benomar

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The World Bank report published in April 2023 called “Migrants, Refugees and Society” allows us to first distinguish migrants in search of economic opportunities and refugees that flee a situation of danger and choose their destination based on their immediate need for safety. Amongst those two categories, the report distinguished people having professional skills adapted to the labor market of the host country and those who have not. Out of that distinction of four categories, we choose to focus our research on refugees that do not have professional skills adapted to the labor market of the host country. Given that refugees generally have no recourse to public assistance schemes and cannot count on the support of their entourage or support network, we propose to examine the extent to which external assistance, such as international humanitarian action, is likely to accompany refugees' transition to financial empowerment through entrepreneurship. To this end, we propose to carry out a case study structured in three stages: (i) an exchange with a Non-Governmental Organisation (NGO) active in supporting refugee populations from Congo and Burundi to Rwanda, enabling us to (i.i) define together a financial empowerment income, and (i. ii) learn about the content of the support measures taken for the beneficiaries of the humanitarian project; (ii) monitor the population of 118 beneficiaries, including 73 refugees and 45 Rwandans (reference population); (iii) conduct a participatory analysis to identify the level of performance of the project and areas for improvement. The case study thus involved the staff of an international NGO active in helping refugees from Rwanda since 2015 and the staff of a Luxembourg NGO that has been funding this economic aid project through entrepreneurship since 2021. The case study thus involved the staff of an international NGO active in helping refugees from Rwanda since 2015 and the staff of a Luxembourg NGO, which has been funding this economic aid through an entrepreneurship project since 2021, and took place over a 48-day period between April and May 2023. The main results are of two types: (i) the need to associate indicators for monitoring the impact of the project on the indirect beneficiaries of the project (refugee community) and (ii) the identification of success factors making it possible to bring concrete and relevant responses to the constraints encountered. The first result thus made it possible to identify the following indicators: Indicator of community potential ((jobs, training or mentoring) promoted by the activity of the entrepreneur), Indicator of social contribution (tax paid by the entrepreneur), Indicator of resilience (savings and loan capacity generated, and finally impact on social cohesion. The second result made it possible to identify that among the 7 success factors tested, the sector of activity chosen and the level of experience in the sector of the future activity are those that stand out the most clearly.

Keywords: entrepreuneurship, refugees, financial empowerment, international aid

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Authors: Biao Sun, Tejas Bhatelia, Vishnu Pareek, Ranjeet Utikar, Moses Tadé

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Additive manufacturing (AM), commonly known as 3D printing, with the continuing advances in parallel processing and computational modeling, has created a paradigm shift (with significant radical thinking) in the design and operation of chemical processing plants, especially LNG plants. With the rising energy demands, environmental pressures, and economic challenges, there is a continuing industrial need for disruptive technologies such as AM, which possess capabilities that can drastically reduce the cost of manufacturing and operations of chemical processing plants in the future. However, the continuing challenge for 3D printing is its lack of adaptability in re-designing the process plant equipment coupled with the non-existent theory or models that could assist in selecting the optimal candidates out of the countless potential fabrications that are possible using AM. One of the most common packings used in the LNG process is structured packing in the packed column (which is a unit operation) in the process. In this work, we present an example of an optimum strategy for the application of AM to this important unit operation. Packed columns use a packing material through which the gas phase passes and comes into contact with the liquid phase flowing over the packing, typically performing the necessary mass transfer to enrich the products, etc. Structured packing consists of stacks of corrugated sheets, typically inclined between 40-70° from the plane. Computational Fluid Dynamics (CFD) was used to test and model various geometries to study the governing hydrodynamic characteristics. The results demonstrate that the costly iterative experimental process can be minimized. Furthermore, they also improve the understanding of the fundamental physics of the system at the multiscale level. SpiroPak, patented by Curtin University, represents an innovative structured packing solution currently at a technology readiness level (TRL) of 5~6. This packing exhibits remarkable characteristics, offering a substantial increase in surface area while significantly enhancing hydrodynamic and mass transfer performance. Recent studies have revealed that SpiroPak can reduce pressure drop by 50~70% compared to commonly used commercial packings, and it can achieve 20~50% greater mass transfer efficiency (particularly in CO2 absorption applications). The implementation of SpiroPak has the potential to reduce the overall size of columns and decrease power consumption, resulting in cost savings for both capital expenditure (CAPEX) and operational expenditure (OPEX) when applied to retrofitting existing systems or incorporated into new processes. Furthermore, pilot to large-scale tests is currently underway to further advance and refine this technology.

Keywords: Additive Manufacturing (AM), 3D printing, Computational Fluid Dynamics (CFD, structured packing (SpiroPak)

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Authors: Jean Pierre Ribeiro Daquila

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This paper aims to analyze the use of the Theory of Multiple Intelligences as a tool to facilitate students’ learning. This theory, proposed by the American psychologist and educator Howard Gardner, was first established in 1983 and advocates that human beings possess eight intelligence and not only one, as defended by psychologists prior to his theory. These intelligence are bodily-kinesthetic intelligence, musical, linguistic, logical-mathematical, spatial, interpersonal, intrapersonal, and naturalist. This paper will focus on bodily-kinesthetic intelligence. Spatial and bodily-kinesthetic intelligences are sensed by athletes, dancers, and others who use their bodies in ways that exceed normal abilities. These are intelligences that are closely related. A quarterback or a ballet dancer needs to have both an awareness of body motions and abilities as well as a sense of the space involved in the action. Nevertheless, there are many reasons which make classical ballet dance more integrated with other intelligences. Ballet dancers make it look effortless as they move across the stage, from the lifts to the toe points; therefore, there is acting both in the performance of the repertoire and in hiding the pain or physical stress. The ballet dancer has to have great mathematical intelligence to perform a fast allegro; for instance, each movement has to be executed in a specific millisecond. Flamenco dancers need to rely as well on their mathematic abilities, as the footwork requires the ability to make half, two, three, four or even six movements in just one beat. However, the precision of the arm movements is freer than in ballet dance; for this reason, ballet dancers need to be more holistically aware of their movements; therefore, our experiment will test whether this greater attention required by ballet dancers makes them acquire better results in the training sessions when compared to flamenco dancers. An experiment will be carried out in this study by training ballet dancers through dance (four years of experience dancing minimum – experimental group 1); a group of flamenco dancers (four years of experience dancing minimum – experimental group 2). Both experimental groups will be trained in two different domains – phonetics and chemistry – to examine whether there is a significant improvement in these areas compared to the control group (a group of regular students who will receive the same training through a traditional method). However, this paper will focus on phonetic training. Experimental group 1 will be trained with the aid of classical music plus bodily work. Experimental group 2 will be trained with flamenco rhythm and kinesthetic work. We would like to highlight that this study takes dance as an example of a possible area of strength; nonetheless, other types of arts can and should be used to support students, such as drama, creative writing, music and others. The main aim of this work is to suggest that other intelligences, in the case of this study, bodily-kinesthetic, can be used to help improve pronunciation.

Keywords: multiple intelligences, pronunciation, effective pronunciation trainings, short drills, musical intelligence, bodily-kinesthetic intelligence

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

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Authors: Adam Majczak, Michał Bialy, Zbigniew Czyż, Zdzislaw Kaminski

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Increasingly stringent emission standards for passenger cars require us to find alternative drives. The share of electric vehicles in the sale of new cars increases every year. However, their performance and, above all, range cannot be today successfully compared to those of cars with a traditional internal combustion engine. Battery recharging lasts hours, which can be hardly accepted due to the time needed to refill a fuel tank. Therefore, the ways to reduce the adverse features of cars equipped with electric motors only are searched for. One of the methods is a combination of an electric engine as a main source of power and a small internal combustion engine as an electricity generator. This type of drive enables an electric vehicle to achieve a radically increased range and low emissions of toxic substances. For several years, the leading automotive manufacturers like the Mazda and the Audi together with the best companies in the automotive industry, e.g., AVL have developed some electric drive systems capable of recharging themselves while driving, known as a range extender. An electricity generator is powered by a Wankel engine that has seemed to pass into history. This low weight and small engine with a rotating piston and a very low vibration level turned out to be an excellent source in such applications. Its operation as an energy source for a generator almost entirely eliminates its disadvantages like high fuel consumption, high emission of toxic substances, or short lifetime typical of its traditional application. The operation of the engine at a constant rotational speed enables a significant increase in its lifetime, and its small external dimensions enable us to make compact modules to drive even small urban cars like the Audi A1 or the Mazda 2. The algorithm to maintain a constant speed was investigated on the engine dynamometer with an eddy current brake and the necessary measuring apparatus. The research object was the Aixro XR50 rotary engine with the electronic power supply developed at the Lublin University of Technology. The load torque of the engine was altered during the research by means of the eddy current brake capable of giving any number of load cycles. The parameters recorded included speed and torque as well as a position of a throttle in an inlet system. Increasing and decreasing load did not significantly change engine speed, which means that control algorithm parameters are correctly selected. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: electric vehicle, power generator, range extender, Wankel engine

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Authors: Claire Tranter, Coral Dando

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Gathering information from others is a fundamental goal for those concerned with investigating crime, and protecting national and international security. Persuading an individual to move from an opposing to converging viewpoint, and an understanding on the cognitive style behind this change can serve to increase understanding of traditional face-to-face interactions, as well as synthetic environments (SEs) often used for communication across varying geographical locations. SEs are growing in usage, and with this increase comes an increase in crime being undertaken online. Communication technologies can allow people to mask their real identities, supporting anonymous communication which can raise significant challenges for investigators when monitoring and managing these conversations inside SEs. To date, the psychological literature concerning how to maximise information-gain in SEs for real-world interviewing purposes is sparse, and as such this aspect of social cognition is not well understood. Here, we introduce an overview of a novel programme of PhD research which seeks to enhance understanding of cross-cultural and cross-gender communication in SEs for maximising information gain. Utilising a dyadic jury paradigm, participants interacted with a confederate who attempted to persuade them to the opposing verdict across three distinct environments: face-to-face, instant messaging, and a novel virtual reality environment utilising avatars. Participants discussed a criminal scenario, acting as a two-person (male; female) jury. Persuasion was manipulated by the confederate claiming an opposing viewpoint (guilty v. not guilty) to the naïve participants from the outset. Pre and post discussion data, and observational digital recordings (voice and video) of participant’ discussion performance was collected. Information regarding cognitive style was also collected to ascertain participants need for cognitive closure and biases towards jumping to conclusions. Findings revealed that individuals communicating via an avatar in a virtual reality environment reacted in a similar way, and thus equally persuasive, when compared to individuals communicating face-to-face. Anonymous instant messaging however created a resistance to persuasion in participants, with males showing a significant decline in persuasive outcomes compared to face to face. The findings reveal new insights particularly regarding the interplay of persuasion on gender and modality, with anonymous instant messaging enhancing resistance to persuasion attempts. This study illuminates how varying SE can support new theoretical and applied understandings of how judgments are formed and modified in response to advocacy.

Keywords: applied cognition, persuasion, social media, virtual reality

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Sigal Gat-Lazer, Ronny Geva, Dan Ramon, Eitan Gur, Daniel Stein

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Introduction: Eating disorders (ED) are common psychopathologies which involve distorted body image and eating disturbances. Binge-purge eating disorders (B/P ED) are characterized by repetitive events of binge eating followed by purges. Patients with B/P ED behavior may be seen as impulsive especially when relate to food stimulation and affective conditions. The current study included innovative modification of the day-night task targeted to assess inhibitory control among patients with B/P ED. Methods: This prospective study included 50 patients with B/P ED during acute phase of illness (T1) upon their admission to specialized ED department in tertiary center. 34 patients repeated the study towards discharge to ambulatory care (T2). Treatment effect was evaluated by BMI and emotional questionnaires regarding depression and anxiety by the Beck Depression Inventory and State Trait Anxiety Inventory questionnaires. Control group included 36 healthy controls with matched demographic parameters who performed both T1 and T2 assessments. The current modification is based on the emotional day-night task (EDNT) which involves five emotional stimulation added to the sun and moon pictures presented to participants. In the current study, we designed the food-emotional modification day night task (F-EDNT) food stimulations of egg and banana which resemble the sun and moon, respectively, in five emotional states (angry, sad, happy, scrambled and neutral). During this computerized task, participants were instructed to push on “day” bottom in response to moon and banana stimulations and on “night” bottom when sun and egg were presented. Accuracy (A) and reaction time (RT) were evaluated and compared between EDNT and F-EDNT as a reflection of participants’ inhibitory control. Results: Patients with B/P ED had significantly improved BMI, depression and anxiety scores on T2 compared to T1 (all p<0.001). Task performance was similar among patients and controls in the EDNT without significant A or RT differences in both T1 and T2. On F-EDNT during T1, B/P ED patients had significantly reduced accuracy in 4/5 emotional stimulation compared to controls: angry (73±25% vs. 84±15%, respectively), sad (69±25% vs. 80±18%, respectively), happy (73±24% vs. 82±18%, respectively) and scrambled (74±24% vs. 84±13%, respectively, all p<0.05). Additionally, patients’ RT to food stimuli was significantly faster compared to neutral ones, in both cry and neutral emotional stimulations (356±146 vs. 400±141 and 378±124 vs. 412±116 msec, respectively, p<0.05). These significant differences between groups as a function of stimulus type were diminished on T2. Conclusion: Having to process food related content, in particular in emotional context seems to be impaired in patients with B/P ED during the acute phase of their illness and elicits greater impulsivity. Innovative modification using such procedures seem to be sensitive to patients’ illness phase and thus may be implemented during screening and follow up through the clinical management of these patients.

Keywords: binge purge eating disorders, day night task modification, eating disorders, food related stimulations

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Authors: Chang Liu, Rui Xing, Liyan Tang, Guohong Wang

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Entrepreneurial actions are based on entrepreneurial decisions. The quality of decisions influences entrepreneurial activities and subsequent new venture performance. Uncertainty of surroundings put heightened demands on the team as a whole, and each team member. Diverse team composition provides rich information, which a team can draw when making complex decisions. However, team heterogeneity may cause emotional conflicts, which is adverse to team outcomes. Thus, the effects of team heterogeneity on team outcomes are complex. Although team heterogeneity is an essential factor influencing entrepreneurial decision-making, there is a lack of empirical analysis on under what conditions team heterogeneity plays a positive role in promoting decision-making quality. Entrepreneurial teams always struggle with complex tasks. How a team shapes its teamwork is key in resolving constant issues. As a collective regulatory process, team reflexivity is characterized by continuous joint evaluation and discussion of team goals, strategies, and processes, and adapt them to current or anticipated circumstances. It enables diversified information to be shared and overtly discussed. Instead of hostile interpretation of opposite opinions team members take them as useful insights from different perspectives. Team reflexivity leads to better integration of expertise to avoid the interference of negative emotions and conflict. Therefore, we propose that team reflexivity is a conditional factor that influences the impact of team heterogeneity on high-quality entrepreneurial decisions. In this study, we identify team heterogeneity as a crucial determinant of entrepreneurial decision quality. Integrating the literature on decision-making and team heterogeneity, we investigate the relationship between team heterogeneity and entrepreneurial decision-making quality, treating team reflexivity as a moderator. We tested our hypotheses using the hierarchical regression method and the data gathered from 63 teams and 205 individual members from 45 new firms in China's first-tier cities such as Beijing, Shanghai, and Shenzhen. This research found that both teams' education heterogeneity and teams' functional background heterogeneity were significantly positively related to entrepreneurial decision-making quality, and the positive relation was stronger in teams with a high level of team reflexivity. While teams' specialization of education heterogeneity was negatively related to decision-making quality, and the negative relationship was weaker in teams with a high level of team reflexivity. We offer two contributions to decision-making and entrepreneurial team literatures. Firstly, our study enriches the understanding of the role of entrepreneurial team heterogeneity in entrepreneurial decision-making quality. Different from previous entrepreneurial decision-making literatures, which focus more on decision-making modes of entrepreneurs and the top management team, this study is a significant attempt to highlight that entrepreneurial team heterogeneity makes a unique contribution to generating high-quality entrepreneurial decisions. Secondly, this study introduced team reflexivity as the moderating variable, to explore the boundary conditions under which the entrepreneurial team heterogeneity play their roles.

Keywords: decision-making quality, entrepreneurial teams, education heterogeneity, functional background heterogeneity, specialization of education heterogeneity

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Authors: Nilson Rogério Da Silva, Ingrid Casagrande, Isabela Chicarelli Amaro Santos

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Introduction: People with Autism Spectrum Disorder (ASD) may face difficulties in social inclusion in different segments of society, especially in entering and staying at work. In Brazil, although there is legislation that equates it to the condition of disability, the number of people at work is still low. The United Nations estimates that more than 80 percent of adults with autism are jobless. In Brazil, the scenario is even more nebulous because there is no control and tracking of accurate data on the number of individuals with autism and how many of these are inserted in the labor market. Pereira and Goyos (2019) found that there is practically no scientific production about people with ASD in the labor market. Objective: To describe the experience of people with ASD inserted in the work, facilities and difficulties found in the professional exercise and the strategies used to maintain the job. Methodology: The research was approved by the Research Ethics Committee. As inclusion criteria for participation, the professional should accept to participate voluntarily, be over 18 years of age and have had some experience with the labor market. As exclusion criteria, being under 18 years of age and having never worked in a work activity. Participated in the research of 04 people with a diagnosis of ASD, aged 22 to 32 years. For data collection, an interview script was used that addressed: 1) General characteristics of the participants; 2) Family support; 3) School process; 4) Insertion in the labor market; 5) Exercise of professional activity; (6) Future and Autism; 7) Possible coping strategies. For the analysis of the data obtained, the full transcription of the interviews was performed and the technique of Content Analysis was performed. Results: The participants reported problems in different aspects: In the school environment: difficulty in social relationships, and Bullying. Lack of adaptation to the school curriculum and the structure of the classroom; In the Faculty: difficulty in following the activities, ealizar group work, meeting deadlines and establishing networking; At work: little adaptation in the work environment, difficulty in establishing good professional bonds, difficulty in accepting changes in routine or operational processes, difficulty in understanding veiled social rules. Discussion: The lack of knowledge about what disability is and who the disabled person is leads to misconceptions and negatives regarding their ability to work and in this context, people with disabilities need to constantly prove that they are able to work, study and develop as a human person, which can be classified as ableism. The adaptations and the use of technologies to facilitate the performance of people with ASD, although guaranteed in national legislation, are not always available, highlighting the difficulties and prejudice. Final Considerations: The entry and permanence of people with ASD at work still constitute a challenge to be overcome, involving changes in society in general, in companies, families and government agencies.

Keywords: autism spectrum disorder (ASD), work, disability, autism

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Authors: Huidan Yu, Anurag Deb, Rou Chen, I-Wen Wang

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The use of left ventricle assist devices (LVADs) in patients with heart failure has been a proven and effective therapy for patients with severe end-stage heart failure. Due to the limited availability of suitable donor hearts, LVADs will probably become the alternative solution for patient with heart failure in the near future. While the LVAD is being continuously improved toward enhanced performance, increased device durability, reduced size, a better understanding of implantation management becomes critical in order to achieve better long-term blood supplies and less post-surgical complications such as thrombi generation. Important issues related to the LVAD implantation include the location of outflow grafting (OG), the angle of the OG, the combination between LVAD and native heart pumping, uniform or pulsatile flow at OG, etc. We have hypothesized that an optimal implantation of LVAD is patient specific. To test this hypothesis, we employ a novel in-house computational modeling technique, named InVascular, to conduct a systematic evaluation of cardiac output at aortic arch together with other pertinent hemodynamic quantities for each patient under various implantation scenarios aiming to get an optimal implantation strategy. InVacular is a powerful computational modeling technique that integrates unified mesoscale modeling for both image segmentation and fluid dynamics with the cutting-edge GPU parallel computing. It first segments the aortic artery from patient’s CT image, then seamlessly feeds extracted morphology, together with the velocity wave from Echo Ultrasound image of the same patient, to the computation model to quantify 4-D (time+space) velocity and pressure fields. Using one NVIDIA Tesla K40 GPU card, InVascular completes a computation from CT image to 4-D hemodynamics within 30 minutes. Thus it has the great potential to conduct massive numerical simulation and analysis. The systematic evaluation for one patient includes three OG anastomosis (ascending aorta, descending thoracic aorta, and subclavian artery), three combinations of LVAD and native heart pumping (1:1, 1:2, and 1:3), three angles of OG anastomosis (inclined upward, perpendicular, and inclined downward), and two LVAD inflow conditions (uniform and pulsatile). The optimal LVAD implantation is suggested through a comprehensive analysis of the cardiac output and related hemodynamics from the simulations over the fifty-four scenarios. To confirm the hypothesis, 5 random patient cases will be evaluated.

Keywords: graphic processing unit (GPU) parallel computing, left ventricle assist device (LVAD), lumped-parameter model, patient-specific computational hemodynamics

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Authors: Stephanie Gracelyn Rahaman, Chew Yin Teng, Manjit Singh Sandhu

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Corporate scandals have made stakeholders apprehensive of large companies and expect greater transparency in CSR matters. However, companies find it challenging to strategically communicate CSR to intended stakeholders and in the process may fall short on maximizing on CSR efforts. Given that stakeholders have the ability to either reward good companies or take legal action or boycott against corporate brands who do not act socially responsible, companies must create shared understanding of their CSR activities. As a result, communication has become a strategy for many companies to demonstrate CSR engagement and to minimize stakeholder skepticism. The main objective of this research is to examine the types of CSR communication strategies and predictors that guide CSR communication strategies. Employing Morsing & Schultz’s guide on CSR communication strategies, the study integrates stakeholder and institutional theory to develop a conceptual framework. The conceptual framework hypothesized that stakeholder (instrumental and normative) and institutional (regulatory environment, nature of business, mimetic intention, CSR focus and corporate objectives) dimensions would drive CSR communication strategies. Preliminary findings from semi-structured interviews in Malaysia are consistent with the conceptual model in that stakeholder and institutional expectations guide CSR communication strategies. Findings show that most companies use two-way communication strategies. Companies that identified employees, the public or customers as key stakeholders have started to embrace social media to be in-sync with new trends of communication. This is especially with the Gen Y which is their priority. Some companies creatively use multiple communication channels because they recognize different stakeholders favor different communication channels. Therefore, it appears that companies use two-way communication strategies to complement the perceived limitation of one-way communication strategies as some companies prefer a more interactive platform to strategically engage stakeholders in CSR communication. In addition to stakeholders, institutional expectations also play a vital role in influencing CSR communication. Due to industry peer pressures, corporate objectives (attract international investors and customers), companies may be more driven to excel in social performance. For these reasons companies tend to go beyond the basic mandatory requirement, excel in CSR activities and be known as companies that champion CSR. In conclusion, companies use more two-way than one-way communication and companies use a combination of one and two-way communication to target different stakeholders resulting from stakeholder and institutional dimensions. Finally, in order to find out if the conceptual framework actually fits the Malaysian context, companies’ responses for expected organizational outcomes from communicating CSR were gathered from the interview transcripts. Thereafter, findings are presented to show some of the key organizational outcomes (visibility and brand recognition, portray responsible image, attract prospective employees, positive word-of-mouth, etc.) that companies in Malaysia expect from CSR communication. Based on these findings the conceptual framework has been refined to show the new identified organizational outcomes.

Keywords: CSR communication, CSR communication strategies, stakeholder theory, institutional theory, conceptual framework, Malaysia

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Authors: Waleed Omri

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With the growth of the small business sector in emerging markets, developing a better understanding of what drives 'day-to-day' entrepreneurial activities has become an important issue for academicians and practitioners. Innovation, as an entrepreneurial behavior, revolves around individuals who creatively engage in new organizational efforts. In a similar vein, the innovation behaviors and processes at the organizational member level are central to any corporate entrepreneurship strategy. Despite the broadly acknowledged importance of entrepreneurship and innovation at the individual level in the establishment of successful ventures, the literature lacks evidence on how entrepreneurs can effectively harness their skills and knowledge in the workplace. The existing literature illustrates that religion can impact the day-to-day work behavior of entrepreneurs, managers, and employees. Religious beliefs and practices could affect daily entrepreneurial activities by fostering mental abilities and traits such as creativity, intelligence, and self-efficacy. In the present study, we define religious capital as a set of personal and intangible resources, skills, and competencies that emanate from an individual’s religious values, beliefs, practices, and experiences and may be used to increase the quality of economic activities. Religious beliefs and practices give individuals a religious satisfaction, which can lead them to perform better in the workplace. In addition, religious ethics and practices have been linked to various positive employee outcomes in terms of organizational change, job satisfaction, and entrepreneurial intensity. As investigations of their consequences beyond direct task performance are still scarce, we explore if religious capital plays a role in entrepreneurs’ innovative behavior. In sum, this study explores the determinants of individual entrepreneurial behavior by investigating the relationship between religious capital and entrepreneurs’ innovative behavior in the context of small businesses. To further explain and clarify the religious capital-innovative behavior link, the present study proposes a model to examine the mediating role of entrepreneurial creativity. We use both Islamic work ethics (IWE) and Islamic religious practices (IRP) to measure Islamic religious capital. We use structural equation modeling with a robust maximum likelihood estimation to analyze data gathered from 289 Tunisian small businesses and to explore the relationships among the above-described variables. In line with the theory of planned behavior, only religious work ethics are found to increase the innovative behavior of small businesses’ owner-managers. Our findings also clearly demonstrate that the connection between religious capital-related variables and innovative behavior is better understood if the influence of entrepreneurial creativity, as a mediating variable of the aforementioned relationship, is taken into account. By incorporating both religious capital and entrepreneurial creativity into the innovative behavior analysis, this study provides several important practical implications for promoting innovation process in small businesses.

Keywords: entrepreneurial behavior, small business, religion, creativity

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Authors: Harpreet Singh Kainth

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Rubidium salts have been commonly used as an electrolyte to improve the efficiency cycle of Li-ion batteries. In recent years, it has been implemented into the large scale for further technological advances to improve the performance rate and better cyclability in the batteries. X-ray absorption spectroscopy (XAS) is a powerful tool for obtaining the information in the electronic structure which involves the chemical state analysis in the active materials used in the batteries. However, this technique is not well suited for the industrial applications because it needs a synchrotron X-ray source and special sample file for in-situ measurements. In contrast to this, conventional wavelength dispersive X-ray fluorescence (WDXRF) spectrometer is nondestructive technique used to study the chemical shift in all transitions (K, L, M, …) and does not require any special pre-preparation planning. In the present work, the fluorescent Lα, Lβ₁ , Lβ₃,₄ and Lγ₂,₃ X-ray spectra of rubidium in different chemical forms (Rb₂CO₃ , RbCl, RbBr, and RbI) have been measured first time with high resolution wavelength dispersive X-ray fluorescence (WDXRF) spectrometer (Model: S8 TIGER, Bruker, Germany), equipped with an Rh anode X-ray tube (4-kW, 60 kV and 170 mA). In ₃₇Rb compounds, the measured energy shifts are in the range (-0.45 to - 1.71) eV for Lα X-ray peak, (0.02 to 0.21) eV for Lβ₁ , (0.04 to 0.21) eV for Lβ₃ , (0.15 to 0.43) eV for Lβ₄ and (0.22 to 0.75) eV for Lγ₂,₃ X-ray emission lines. The chemical shifts in rubidium compounds have been measured by considering Rb₂CO₃ compounds taking as a standard reference. A Voigt function is used to determine the central peak position of all compounds. Both positive and negative shifts have been observed in L shell emission lines. In Lα X-ray emission lines, all compounds show negative shift while in Lβ₁, Lβ₃,₄, and Lγ₂,₃ X-ray emission lines, all compounds show a positive shift. These positive and negative shifts result increase or decrease in X-ray energy shifts. It looks like that ligands attached with central metal atom attract or repel the electrons towards or away from the parent nucleus. This pulling and pushing character of rubidium affects the central peak position of the compounds which causes a chemical shift. To understand the chemical effect more briefly, factors like electro-negativity, line intensity ratio, effective charge and bond length are responsible for the chemical state analysis in rubidium compounds. The effective charge has been calculated from Suchet and Pauling method while the line intensity ratio has been calculated by calculating the area under the relevant emission peak. In the present work, it has been observed that electro-negativity, effective charge and intensity ratio (Lβ₁/Lα, Lβ₃,₄/Lα and Lγ₂,₃/Lα) are inversely proportional to the chemical shift (RbCl > RbBr > RbI), while bond length has been found directly proportional to the chemical shift (RbI > RbBr > RbCl).

Keywords: chemical shift in L emission lines, bond length, electro-negativity, effective charge, intensity ratio, Rubidium compounds, WDXRF spectrometer

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Authors: Inna Kornienko, Svetlana Guryeva, Natalia Danilova, Elena Petersen

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Drug toxicity often goes undetected until clinical trials, the most expensive and dangerous phase of drug development. Both human cell culture and animal studies have limitations that cannot be overcome by improvements in drug testing protocols. Tissue engineering is an emerging alternative approach to creating models of human malignant tumors for experimental oncology, personalized medicine, and drug discovery studies. This new generation of bioengineered tumors provides an opportunity to control and explore the role of every component of the model system including cell populations, supportive scaffolds, and signaling molecules. An area that could greatly benefit from these models is cancer research. Recent advances in tissue engineering demonstrated that decellularized tissue is an excellent scaffold for tissue engineering. Decellularization of donor organs such as heart, liver, and lung can provide an acellular, naturally occurring three-dimensional biologic scaffold material that can then be seeded with selected cell populations. Preliminary studies in animal models have provided encouraging results for the proof of concept. Decellularized Organs preserve organ microenvironment, which is critical for cancer metastasis. Utilizing 3D tumor models results greater proximity of cell culture morphological characteristics in a model to its in vivo counterpart, allows more accurate simulation of the processes within a functioning tumor and its pathogenesis. 3D models allow study of migration processes and cell proliferation with higher reliability as well. Moreover, cancer cells in a 3D model bear closer resemblance to living conditions in terms of gene expression, cell surface receptor expression, and signaling. 2D cell monolayers do not provide the geometrical and mechanical cues of tissues in vivo and are, therefore, not suitable to accurately predict the responses of living organisms. 3D models can provide several levels of complexity from simple monocultures of cancer cell lines in liquid environment comprised of oxygen and nutrient gradients and cell-cell interaction to more advanced models, which include co-culturing with other cell types, such as endothelial and immune cells. Following this reasoning, spheroids cultivated from one or multiple patient-derived cell lines can be utilized to seed the matrix rather than monolayer cells. This approach furthers the progress towards personalized medicine. As an initial step to create a new ex vivo tissue engineered model of a cancer tumor, optimized protocols have been designed to obtain organ-specific acellular matrices and evaluate their potential as tissue engineered scaffolds for cultures of normal and tumor cells. Decellularized biomatrix was prepared from animals’ kidneys, urethra, lungs, heart, and liver by two decellularization methods: perfusion in a bioreactor system and immersion-agitation on an orbital shaker with the use of various detergents (SDS, Triton X-100) in different concentrations and freezing. Acellular scaffolds and tissue engineered constructs have been characterized and compared using morphological methods. Models using decellularized matrix have certain advantages, such as maintaining native extracellular matrix properties and biomimetic microenvironment for cancer cells; compatibility with multiple cell types for cell culture and drug screening; utilization to culture patient-derived cells in vitro to evaluate different anticancer therapeutics for developing personalized medicines.

Keywords: 3D models, decellularization, drug discovery, drug toxicity, scaffolds, spheroids, tissue engineering

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Authors: Astrid Bagireanu, Julio Bros-Williamson, Mila Duncheva, John Currie

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Digital Twins (DTs) have entered the built environment from more established industries like aviation and manufacturing, although there has never been a common goal for utilising DTs at scale. Defined as the cyber-physical integration of data between an asset and its virtual counterpart, DT has been identified in literature from an operational standpoint – in addition to monitoring the performance of a built asset. However, this has never been translated into how DTs should be implemented into a project and what responsibilities each project stakeholder holds in the realisation of a DT. What is needed is an approach to translate these requirements into actionable DT dimensions. This paper presents a foundation for an overarching framework specific to the built environment. For the purposes of this research, the UK widely used the Royal Institute of British Architects (RIBA) Plan of Work from 2020 is used as a basis for itemising project stages. The RIBA Plan of Work consists of eight stages designed to inform on the definition, briefing, design, coordination, construction, handover, and use of a built asset. Similar project stages are utilised in other countries; therefore, the recommendations from the interviews presented in this paper are applicable internationally. Simultaneously, there is not a single mainstream software resource that leverages DT abilities. This ambiguity meets an unparalleled ambition from governments and industries worldwide to achieve a national grid of interconnected DTs. For the construction industry to access these benefits, it necessitates a defined starting point. This research aims to provide a comprehensive understanding of the potential applications and ramifications of DT in the context of the built environment. This paper is an integral part of a larger research aimed at developing a conceptual framework for the Architecture, Engineering, and Construction (AEC) sector following a conventional project timeline. Therefore, this paper plays a pivotal role in providing practical insights and a tangible foundation for developing a stage-by-stage approach to assimilate the potential of DT within the built environment. First, the research focuses on a review of relevant literature, albeit acknowledging the inherent constraint of limited sources available. Secondly, a qualitative study compiling the views of 14 DT experts is presented, concluding with an inductive analysis of the interview findings - ultimately highlighting the barriers and strengths of DT in the context of framework development. As parallel developments aim to progress net-zero-centred design and improve project efficiencies across the built environment, the limited resources available to support DTs should be leveraged to propel the industry to reach its digitalisation era, in which AEC stakeholders have a fundamental role in understanding this, from the earliest stages of a project.

Keywords: digital twins, decision-making, design, net-zero, built environment

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Authors: Dominique Parrish

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Globally, higher education institutions are responsible for the quality assurance and accreditation of their educational programmes (Courses). The primary purpose of these activities is to ensure that the educational standards of the governing higher education authority are met and the quality of the education provided to students is assured. Despite policies and frameworks being established in many countries, to improve the veracity and accountability of quality assurance and accreditation processes, there are reportedly still mistakes, gaps and deficiencies in these processes. An analysis of Australian universities’ quality assurance and accreditation processes noted that significant improvements were needed in managing these processes and ensuring that review recommendations were implemented. It has also been suggested that the following principles are critical for higher education quality assurance and accreditation to be effective and sustainable: academic standards and performance outcomes must be defined, attainable and monitored; those involved in providing the higher education must assume responsibility for the associated quality assurance and accreditation; potential academic risks must be identified and management solutions developed; and the expectations of the public, governments and students should be considered and incorporated into Course enhancements. This phenomenological study, which was conducted in a Faculty of Science, Medicine and Health in an Australian university, sought to systematically and iteratively develop an effective quality assurance and accreditation process that integrated the evidence-based principles of success and promoted meaningful and sustainable change. Qualitative evaluative feedback was gathered, over a period of eleven months (January - November 2014), from faculty staff engaged in the quality assurance and accreditation of forty-eight undergraduate and postgraduate Courses. Reflexive analysis was used to analyse the data and inform ongoing modifications and developments to the assurance and accreditation process as well as the associated supporting resources. The study resulted in the development of a formal quality assurance and accreditation process together with a suite of targeted resources that were identified as critical for success. The research findings also provided some insights into the institutional enablers that were antecedents to successful quality assurance and accreditation processes as well as meaningful change in the educational practices of academics. While longitudinal data will be collected to further assess the value of the assurance and accreditation process on educational quality, early indicators are that there has been a change in the pedagogical perspectives and activities of academic staff and growing momentum to explore opportunities to further enhance and develop Courses. This presentation will explain the formal quality assurance and accreditation process as well as the component parts, which resulted from this study. The targeted resources that were developed will be described, the pertinent factors that contributed to the success of the process will be discussed and early indicators of sustainable academic change as well as suggestions for future research will be outlined.

Keywords: academic standards, quality assurance and accreditation, phenomenological study, process, resources

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Authors: C. Hall, J. Ramos, V. Ramasamy

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Hydrocarbon-based fuel vehicles are a major contributor to air pollution due to harmful emissions produced, leading to a demand for cleaner fuel types. A leader in this pursuit is hydrogen, with its application in vehicles producing zero harmful emissions and the only by-product being water. To compete with the performance of conventional vehicles, hydrogen gas must be stored on-board of vehicles in cylinders at high pressures (35–70 MPa) and have a short refueling duration (approximately 3 mins). However, the fast-filling of hydrogen cylinders causes a significant rise in temperature due to the combination of the negative Joule-Thompson effect and the compression of the gas. This can lead to structural failure and therefore, a maximum allowable internal temperature of 85°C has been imposed by the International Standards Organization. The technological solution to tackle the issue of rapid temperature rise during the refueling process is to decrease the temperature of the gas entering the cylinder. Pre-cooling of the gas uses a heat exchanger and requires energy for its operation. Thus, it is imperative to determine the least amount of energy input that is required to lower the gas temperature for cost savings. A validated universal thermodynamic model is used to identify an energy-efficient pre-cooling strategy. The model requires negligible computational time and is applied to previously validated experimental cases to optimize pre-cooling requirements. The pre-cooling characteristics include the location within the refueling timeline and its duration. A constant pressure-ramp rate is imposed to eliminate the effects of rapid changes in mass flow rate. A pre-cooled gas temperature of -40°C is applied, which is the lowest allowable temperature. The heat exchanger is assumed to be ideal with no energy losses. The refueling of the cylinders is modeled with the pre-cooling split in ten percent time intervals. Furthermore, varying burst durations are applied in both the early and late stages of the refueling procedure. The model shows that pre-cooling in the later stages of the refuelling process is more energy-efficient than early pre-cooling. In addition, the efficiency of pre-cooling towards the end of the refueling process is independent of the pressure profile at the inlet. This leads to the hypothesis that pre-cooled gas should be applied as late as possible in the refueling timeline and at very low temperatures. The model had shown a 31% reduction in energy demand whilst achieving the same final gas temperature for a refueling scenario when pre-cooling was applied towards the end of the process. The identification of the most energy-efficient refueling approaches whilst adhering to the safety guidelines is imperative to reducing the operating cost of hydrogen refueling stations. Heat exchangers are energy-intensive and thus, reducing the energy requirement would lead to cost reduction. This investigation shows that pre-cooling should be applied as late as possible and for short durations.

Keywords: cylinder, hydrogen, pre-cooling, refueling, thermodynamic model

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Authors: CA Kishore S. Peshori

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Introduction: India, a country with vast diversity and huge population is going to have largest young population by 2020. Higher education has and will always be the basic requirement for making a developing nation to a developed nation. To improve any system it needs to be bench-marked. There have been various tools for bench-marking the systems. Education is delivered in India by universities which are mainly funded by government. This universities for delivering the education sets up colleges which are again funded mainly by government. Recently however there has also been autonomy given to universities and colleges. Moreover foreign universities are waiting to enter Indian boundaries. With a large number of universities and colleges it has become more and more necessary to measure this institutes for bench-marking. There have been various tools for measuring the institute. In India college assessments have been made compulsory by UGC. Naac has been offically recognised as the accrediation criteria. The Naac criteria has been based on seven criterias namely: 1. Curricular assessments, 2. Teaching learning and evaluation, 3. Research Consultancy and Extension, 4. Infrastructure and learning resources, 5. Student support and progression, 6. Governance leadership and management, 7. Innovation and best practices. The Naac tries to bench mark the institution for identification, sustainability, dissemination and adaption of best practices. It grades the institution according to this seven criteria and the funding of institution is based on these grades. Many of the colleges are struggling to get best of grades but they have not come across a systematic tool to achieve the results. Balanced Scorecard developed by Kaplan has been a successful tool for corporates to develop best of practices so as to increase their financial performance and also retain and increase their customers so as to grow the organization to next level.It is time to test this tool for an educational institute. Methodology: The paper tries to develop a prototype for college based on the secondary data. Once a prototype is developed the researcher based on questionnaire will try to test this tool for successful implementation. The success of this research will depend on its implementation of BSC on an institute and its grading improved due to this successful implementation. Limitation of time is a major constraint in this research as Naac cycle takes minimum 4 years for accreditation and reaccreditation the methodology will limit itself to secondary data and questionnaire to be circulated to colleges along with the prototype model of BSC. Conclusion: BSC is a successful tool for enhancing growth of an organization. Educational institutes are no exception to these. BSC will only have to be realigned to suit the Naac criteria. Once this prototype is developed the success will be tested only on its implementation but this research paper will be the first step towards developing this tool and will also initiate the success by developing a questionnaire and getting and evaluating the responses for moving to the next level of actual implementation

Keywords: balanced scorecard, bench marking, Naac, UGC

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Authors: Xiaoyun Hui, Fiona Gentle, Clemens Engelke, Margaret C. Graham

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Although past work has shown that phosphorus (P), an important nutrient, may form complexes with aqueous humic substances (HS), the principal component of natural organic matter, the nature of such interactions is poorly understood. Humic complexation may not only enhance P concentrations but it may change its bioavailability within such waters and, in addition, influence its transport within catchment settings. This project is examining the relationships and associations of P, HS, and iron (Fe) in Loch Meadie, Sutherland, North Scotland, a mesohumic freshwater loch which has been assessed as reference condition with respect to P. The aim is to identify characteristic spectroscopic parameters which can enhance the performance of the model currently used to predict reference condition TP levels for highly-coloured Scottish lochs under the Water Framework Directive. In addition to Loch Meadie, samples from other reference condition lochs in north Scotland and Shetland were analysed. By including different types of reference condition lochs (clear water, mesohumic and polyhumic water) this allowed the relationship between total phosphorus (TP) and HS to be more fully explored. The pH, [TP], [Fe], UV/Vis absorbance/spectra, [TOC] and [DOC] for loch water samples have been obtained using accredited methods. Loch waters were neutral to slightly acidic/alkaline (pH 6-8). [TP] in loch waters were lower than 50 µg L-1, and in Loch Meadie waters were typically <10 µg L-1. [Fe] in loch waters were mainly <0.6 mg L-1, but for some loch water samples, [Fe] were in the range 1.0-1.8 mg L-1and there was a positive correlation with [TOC] (r2=0.61). Lochs were classified as clear water, mesohumic or polyhumic based on water colour. The range of colour values of sampled lochs in each category were 0.2–0.3, 0.2–0.5 and 0.5–0.8 a.u. (10 mm pathlength), respectively. There was also a strong positive correlation between [DOC] and water colour (R2=0.84). The UV/Vis spectra (200-700 nm) for water samples were featureless with only a slight “shoulder” observed in the 270–290 nm region. Ultrafiltration was then used to separate colloidal and truly dissolved components from the loch waters and, since it contained the majority of aqueous P and Fe, the colloidal component was fractionated by gel filtration chromatography method. Gel filtration chromatographic fractionation of the colloids revealed two brown-coloured bands which had distinctive UV/Vis spectral features. The first eluting band had larger and more aromatic HS molecules than the second band, and in addition both P and Fe were primarily associated with the larger, more aromatic HS. This result demonstrated that P was able to form complexes with Fe-rich components of HS, and thus provided a scientific basis for the significant correlation between [Fe] and [TP] that the previous monitoring data of reference condition lochs from Scottish Environment Protection Agency (SEPA) showed. The distinctive features of the HS will be used as the basis for an improved spectroscopic tool.

Keywords: total phosphorus, humic substances, Scottish loch water, WFD model

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Authors: Michael McCann

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Managerial theories propose that, in joint stock companies, executives may be tempted to waste excess free cash on unprofitable projects to keep control of resources. In order to conceal their projects' poor performance, they may seek to engage in earnings management. On the one hand, managers may manipulate earnings upwards in order to post ‘good’ performances and safeguard their position. On the other, since managers pursuit of unrewarding investments are likely to lead to low long-term profitability, managers will use negative accruals to reduce current year’s earnings, smoothing earnings over time in order to conceal the negative effects. Agency models argue that boards of directors are delegated by shareholders to ensure that companies are governed properly. Part of that responsibility is ensuring the reliability of financial information. Analyses of the impact of board characteristics, particularly board independence on the misuse of free cash flow and earnings management finds conflicting evidence. However, existing characterizations of board independence do not account for such directors gaining firm-specific knowledge over time, influencing their monitoring ability. Further, there is little analysis of the influence of the relative experience of independent directors and executives on decisions surrounding the use of free cash. This paper contributes to this literature regarding the heterogeneous characteristics of boards by investigating the influence of independent director tenure on earnings management and the relative tenures of independent directors and Chief Executives. A balanced panel dataset comprising 51 companies across 11 annual periods from 2005 to 2015 is used for the analysis. In each annual period, firms were classified as conducting earnings management if they had discretionary accruals in the bottom quartile (downwards) and top quartile (upwards) of the distributed values for the sample. Logistical regressions were conducted to determine the marginal impact of independent board tenure and a number of control variables on the probability of conducting earnings management. The findings indicate that both absolute and relative measures of board independence and experience do not have a significant impact on the likelihood of earnings management. It is the level of free cash flow which is the major influence on the probability of earnings management. Higher free cash flow increases the probability of earnings management significantly. The research also investigates whether board monitoring of earnings management is contingent on the level of free cash flow. However, the results suggest that board monitoring is not amplified when free cash flow is higher. This suggests that the extent of earnings management in companies is determined by a range of company, industry and situation-specific factors.

Keywords: corporate governance, boards of directors, agency theory, earnings management

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Authors: A. F. Huseynov, N. T. Mardanov, J. Y. Nakhchivanski

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This practical research is aimed to improve the management quality and efficiency of public administration agencies providing e-services. The monitoring system developed will provide continuous review of the websites compliance with the selected indicators, their evaluation based on the selected indicators and ranking of services according to the quality criteria. The responsible departments in the government agencies were surveyed; the questionnaire includes issues of management and feedback, e-services provided, and the application of information systems. By analyzing the main affecting factors and barriers, the recommendations will be given that lead to the relevant decisions to strengthen the state agencies competencies for the management and the provision of their services. Component 1. E-services monitoring system. Three separate monitoring activities are proposed to be executed in parallel: Continuous tracing of e-government sites using built-in web-monitoring program; this program generates several quantitative values which are basically related to the technical characteristics and the performance of websites. The expert assessment of e-government sites in accordance with the two general criteria. Criterion 1. Technical quality of the site. Criterion 2. Usability/accessibility (load, see, use). Each high-level criterion is in turn subdivided into several sub-criteria, such as: the fonts and the color of the background (Is it readable?), W3C coding standards, availability of the Robots.txt and the site map, the search engine, the feedback/contact and the security mechanisms. The on-line survey of the users/citizens – a small group of questions embedded in the e-service websites. The questionnaires comprise of the information concerning navigation, users’ experience with the website (whether it was positive or negative), etc. Automated monitoring of web-sites by its own could not capture the whole evaluation process, and should therefore be seen as a complement to expert’s manual web evaluations. All of the separate results were integrated to provide the complete evaluation picture. Component 2. Assessment of the agencies/departments efficiency in providing e-government services. - the relevant indicators to evaluate the efficiency and the effectiveness of e-services were identified; - the survey was conducted in all the governmental organizations (ministries, committees and agencies) that provide electronic services for the citizens or the businesses; - the quantitative and qualitative measures are covering the following sections of activities: e-governance, e-services, the feedback from the users, the information systems at the agencies’ disposal. Main results: 1. The software program and the set of indicators for internet sites evaluation has been developed and the results of pilot monitoring have been presented. 2. The evaluation of the (internal) efficiency of the e-government agencies based on the survey results with the practical recommendations related to the human potential, the information systems used and e-services provided.

Keywords: e-government, web-sites monitoring, survey, internal efficiency

Procedia PDF Downloads 277

Authors: Alberto Sanchidrián, José A. Parra, Jesús Alonso, Julián Pecharromán, Antonia Pacios, Consuelo Huerta

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Glass is a commonly used material in building; there is not a unique design solution as plates with a different number of layers and interlayers may be used. In most façades, a security glazing have to be used according to its performance in the impact pendulum. The European Standard EN 12600 establishes an impact test procedure for classification under the point of view of the human security, of flat plates with different thickness, using a pendulum of two tires and 50 kg mass that impacts against the plate from different heights. However, this test does not replicate the actual dimensions and border conditions used in building configurations and so the real stress distribution is not determined with this test. The influence of different boundary conditions, as the ones employed in construction sites, is not well taking into account when testing the behaviour of safety glazing and there is not a detailed procedure and criteria to determinate the glass resistance against human impact. To reproduce the actual boundary conditions on site, when needed, the pendulum test is arranged to be used "in situ", with no account for load control, stiffness, and without a standard procedure. Fracture stress of small and large glass plates fit a Weibull distribution with quite a big dispersion so conservative values are adopted for admissible fracture stress under static loads. In fact, test performed for human impact gives a fracture strength two or three times higher, and many times without a total fracture of the glass plate. Newest standards, as for example DIN 18008-4, states for an admissible fracture stress 2.5 times higher than the ones used for static and wing loads. Now two working areas are open: a) to define a standard for the ‘in situ’ test; b) to prepare a laboratory procedure that allows testing with more real stress distribution. To work on both research lines a laboratory that allows to test medium size specimens with different border conditions, has been developed. A special steel frame allows reproducing the stiffness of the glass support substructure, including a rigid condition used as reference. The dynamic behaviour of the glass plate and its support substructure have been characterized with finite elements models updated with modal tests results. In addition, a new portable impact machine is being used to get enough force and direction control during the impact test. Impact based on 100 J is used. To avoid problems with broken glass plates, the test have been done using an aluminium plate of 1000 mm x 700 mm size and 10 mm thickness supported on four sides; three different substructure stiffness conditions are used. A detailed control of the dynamic stiffness and the behaviour of the plate is done with modal tests. Repeatability of the test and reproducibility of results prove that procedure to control both, stiffness of the plate and the impact level, is necessary.

Keywords: glass plates, human impact test, modal test, plate boundary conditions

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Authors: Felicisimo Azagra Tejuco Jr.

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Mentoring architecture thesis students is a very critical and exhausting task for both the adviser and advisee. It poses the challenges of resource and time management for the candidate while the best professional guidance from the mentor. The University of Santo Tomas (Manila, Philippines) is Asia's oldest university. Among its notable program is its Architecture curriculum. Presently, the five-year Architecture program requires ten semesters of academic coursework. The last three semesters are relevant to each Architecture graduating student's thesis proposal and defense. The thesis proposal is developed and submitted for approval in the subject Research Methods for Architecture (RMA). Data gathering and initial schemes are conducted in Architectural Design (AD), 9, and are finalized and defended in AD 10. In recent years, their graduating students have maintained an average of 300 candidates before the pandemic. They are encouraged to explore any topic of interest or relevance. Since 2019-2020, one thesis class has used a community planning approach in mentoring the class. Compared to other sections, the first meeting of RMA has been allocated for a visioning exercise and assessment of the class's strengths-weaknesses and opportunities-threats (SWOT). Here, the work activities of the group have been finetuned to address some identified concerns while still being aligned with the academic calendar. Occasional peer critics complement class lectures. The course will end with the approval of the student's proposal. The final year or last two semesters of the graduating class will be focused on the approved proposal. Compared to the other class, the 18 weeks of the first semester consist of regular consultations, complemented by lectures from the adviser or guest speakers. Through remote peer consultations, the mentor maximized each meeting in groups of three to five, encouraging constructive criticism among the class. At the end of the first semester, mock presentations to the external jury are conducted to check the design outputs for improvement. The final semester is spent more on the finalization of the plans. Feedback from the previous semester is expected to be integrated into the final outputs. Before the final deliberations, at least two technical rehearsals were conducted per group. Regardless of the outcome, an assessment of each student's performance is held as a class. Personal realizations and observations are encouraged. Through Online surveys, Interviews, and Focused Group Discussions with the former students, the effectiveness of the mentoring strategies was reviewed and evaluated. Initial feedback highlighted the relevance of setting a positive tone for the course, constructive criticisms from peers & experts, and consciousness of deadlines as essential elements for a practical semester.

Keywords: cooperation, competition, student empowerment, class vision

Procedia PDF Downloads 63