Search results for: methanol concentration and support structure

Authors: Edwin Foo, Woei Wen, Lui, Meijun Zhao, Shigeru Kuchii, Chin Sai Wong, Chung Sern Goh, Yi Hao He

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This presentation presents an elderly care and assistive social robot development work. We named this robot JOS and he is restricted to table top operation. JOS is designed to have a maximum volume of 3600 cm3 with its base restricted to 250 mm and his mission is to provide companion, assist and help the elderly. In order for JOS to accomplish his mission, he will be equipped with perception, reaction and cognition capability. His appearance will be not human like but more towards cute and approachable type. JOS will also be designed to be neutral gender. However, the robot will still have eyes, eyelid and a mouth. For his eyes and eyelids, they will be built entirely with Robotis Dynamixel AX18 motor. To realize this complex task, JOS will be also be equipped with micro-phone array, vision camera and Intel i5 NUC computer and a powered by a 12 V lithium battery that will be self-charging. His face is constructed using 1 motor each for the eyelid, 2 motors for the eyeballs, 3 motors for the neck mechanism and 1 motor for the lips movement. The vision senor will be house on JOS forehead and the microphone array will be somewhere below the mouth. For the vision system, Omron latest OKAO vision sensor is used. It is a compact and versatile sensor that is only 60mm by 40mm in size and operates with only 5V supply. In addition, OKAO vision sensor is capable of identifying the user and recognizing the expression of the user. With these functions, JOS is able to track and identify the user. If he cannot recognize the user, JOS will ask the user if he would want him to remember the user. If yes, JOS will store the user information together with the capture face image into a database. This will allow JOS to recognize the user the next time the user is with JOS. In addition, JOS is also able to interpret the mood of the user through the facial expression of the user. This will allow the robot to understand the user mood and behavior and react according. Machine learning will be later incorporated to learn the behavior of the user so as to understand the mood of the user and requirement better. For the speech system, Microsoft speech and grammar engine is used for the speech recognition. In order to use the speech engine, we need to build up a speech grammar database that captures the commonly used words by the elderly. This database is built from research journals and literature on elderly speech and also interviewing elderly what do they want to robot to assist them with. Using the result from the interview and research from journal, we are able to derive a set of common words the elderly frequently used to request for the help. It is from this set that we build up our grammar database. In situation where there is more than one person near JOS, he is able to identify the person who is talking to him through an in-house developed microphone array structure. In order to make the robot more interacting, we have also included the capability for the robot to express his emotion to the user through the facial expressions by changing the position and movement of the eyelids and mouth. All robot emotions will be in response to the user mood and request. Lastly, we are expecting to complete this phase of project and test it with elderly and also delirium patient by Feb 2015.

Keywords: social robot, vision, elderly care, machine learning

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Authors: Mauro Cristeche

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This paper approaches the intervention of the American State in the social arena and the modeling of the rights system from the Argentinian experience, by observing the characteristics of its federal budgetary system, the evolution of social public spending and welfare programs in recent years, labor and poverty statistics, and the changes on the labor market structure. The analysis seeks to combine different methodologies and sources: in-depth interviews with specialists, analysis of theoretical and mass-media material, and statistical sources. Among the results, it could be mentioned that the tendency to state interventionism (what has been called ‘nationalization of social life’) is quite evident in the United States, and manifests itself in multiple forms. The bibliography consulted, and the experts interviewed pointed out this increase of the state presence in historical terms (beyond short-term setbacks) in terms of increase of public spending, fiscal pressure, public employment, protective and control mechanisms, the extension of welfare policies to the poor sectors, etc. In fact, despite the significant differences between both countries, the United States and Argentina have common patterns of behavior in terms of the aforementioned phenomena. On the other hand, dissimilarities are also important. Some of them are determined by each country's own political history. The influence of political parties on the economic model seems more decisive in the United States than in Argentina, where the tendency to state interventionism is more stable. The centrality of health spending is evident in America, while in Argentina that discussion is more concentrated in the social security system and public education. The biggest problem of the labor market in the United States is the disqualification as a consequence of the technological development while in Argentina it is a result of its weakness. Another big difference is the huge American public spending on Defense. Then, the more federal character of the American State is also a factor of differential analysis against a centralized Argentine state. American public employment (around 10%) is comparatively quite lower than the Argentinian (around 18%). The social statistics show differences, but inequality and poverty have been growing as a trend in the last decades in both countries. According to public rates, poverty represents 14% in The United States and 33% in Argentina. American public spending is important (welfare spending and total public spending represent around 12% and 34% of GDP, respectively), but a bit lower than Latin-American or European average). In both cases, the tendency to underemployment and disqualification unemployment does not assume a serious gravity. Probably one of the most important aspects of the analysis is that private initiative and public intervention are much more intertwined in the United States, which makes state intervention more ‘fuzzy’, while in Argentina the difference is clearer. Finally, the power of its accumulation of capital and, more specifically, of the industrial and services sectors in the United States, which continues to be the engine of the economy, express great differences with Argentina, supported by its agro-industrial power and its public sector.

Keywords: state intervention, welfare policies, labor market, system of rights, United States of America

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Authors: Serdar Yaman, Hanzade Haykiri-Acma

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Biomass is a CO₂-neutral fuel that is renewable and sustainable along with having very huge global potential. Efficient use of biomass in power generation and production of biomass-based biofuels can mitigate the greenhouse gasses (GHG) and reduce dependency on fossil fuels. There are also other beneficial effects of biomass energy use such as employment creation and pollutant reduction. However, most of the biomass materials are not capable of competing with fossil fuels in terms of energy content. High moisture content and high volatile matter yields of biomass make it low calorific fuel, and it is very significant concern over fossil fuels. Besides, the density of biomass is generally low, and it brings difficulty in transportation and storage. These negative aspects of biomass can be overcome by thermal pretreatments that upgrade the fuel property of biomass. That is, torrefaction is such a thermal process in which biomass is heated up to 300ºC under non-oxidizing conditions to avoid burning of the material. The treated biomass is called as biochar that has considerably lower contents of moisture, volatile matter, and oxygen compared to the parent biomass. Accordingly, carbon content and the calorific value of biochar increase to the level which is comparable with that of coal. Moreover, hydrophilic nature of untreated biomass that leads decay in the structure is mostly eliminated, and the surface properties of biochar turn into hydrophobic character upon torrefaction. In order to investigate the effectiveness of torrefaction process on biomass properties, several biomass species such as olive milling residue (OMR), Rhododendron (small shrubby tree with bell-shaped flowers), and ash tree (timber tree) were chosen. The fuel properties of these biomasses were analyzed through proximate and ultimate analyses as well as higher heating value (HHV) determination. For this, samples were first chopped and ground to a particle size lower than 250 µm. Then, samples were subjected to torrefaction in a horizontal tube furnace by heating from ambient up to temperatures of 200, 250, and 300ºC at a heating rate of 10ºC/min. The biochars obtained from this process were also tested by the methods applied to the parent biomass species. Improvement in the fuel properties was interpreted. That is, increasing torrefaction temperature led to regular increases in the HHV in OMR, and the highest HHV (6065 kcal/kg) was gained at 300ºC. Whereas, torrefaction at 250ºC was seen optimum for Rhododendron and ash tree since torrefaction at 300ºC had a detrimental effect on HHV. On the other hand, the increase in carbon contents and reduction in oxygen contents were determined. Burning characteristics of the biochars were also studied using thermal analysis technique. For this purpose, TA Instruments SDT Q600 model thermal analyzer was used and the thermogravimetric analysis (TGA), derivative thermogravimetry (DTG), differential scanning calorimetry (DSC), and differential thermal analysis (DTA) curves were compared and interpreted. It was concluded that torrefaction is an efficient method to upgrade the fuel properties of biomass and the biochars from which have superior characteristics compared to the parent biomasses.

Keywords: biochar, biomass, fuel upgrade, torrefaction

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Authors: Laila A. H. F. Dashti, Tom Jackson, Andrew West, Lisa Jackson

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Traceability systems are important in the agri-food and halal food sectors for monitoring ingredient movements, tracking sources, and ensuring food integrity. However, designing a traceability system for the halal food supply chain is challenging due to diverse stakeholder requirements and complex needs. Existing literature on stakeholder mapping and identifying requirements for halal food supply chains is limited. To address this gap, a pilot study was conducted to identify the objectives, requirements, and recommendations of stakeholders in the Kuwaiti halal food industry. The study collected data through semi-structured interviews with an international halal food manufacturer based in Kuwait. The aim was to gain a deep understanding of stakeholders' objectives, requirements, processes, and concerns related to the design of a traceability system in the country's halal food sector. Traceability systems are being developed and tested in the agri-food and halal food sectors due to their ability to monitor ingredient movements, track sources, and detect potential issues related to food integrity. Designing a traceability system for the halal food supply chain poses significant challenges due to diverse stakeholder requirements and the complexity of their needs (including varying food ingredients, different sources, destinations, supplier processes, certifications, etc.). Achieving a halal food traceability solution tailored to stakeholders' requirements within the supply chain necessitates prior knowledge of these needs. Although attempts have been made to address design-related issues in traceability systems, literature on stakeholder mapping and identification of requirements specific to halal food supply chains is scarce. Thus, this pilot study aims to identify the objectives, requirements, and recommendations of stakeholders in the halal food industry. The paper presents insights gained from the pilot study, which utilized semi-structured interviews to collect data from a Kuwait-based international halal food manufacturer. The objective was to gain an in-depth understanding of stakeholders' objectives, requirements, processes, and concerns pertaining to the design of a traceability system in Kuwait's halal food sector. The stakeholder mapping results revealed that government entities, food manufacturers, retailers, and suppliers are key stakeholders in Kuwait's halal food supply chain. Lessons learned from this pilot study regarding requirement capture for traceability systems include the need to streamline communication, focus on communication at each level of the supply chain, leverage innovative technologies to enhance process structuring and operations and reduce halal certification costs. The findings also emphasized the limitations of existing traceability solutions, such as limited cooperation and collaboration among stakeholders, high costs of implementing traceability systems without government support, lack of clarity regarding product routes, and disrupted communication channels between stakeholders. These findings contribute to a broader research program aimed at developing a stakeholder requirements framework that utilizes "business process modelling" to establish a unified model for traceable stakeholder requirements.

Keywords: supply chain, traceability system, halal food, stakeholders’ requirements

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Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

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Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

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Authors: Elina Vroblevska, Toms Ratfelders

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This paper examines the impact of international status-seeking aspirations on great power behavior within the international system. In particular, we seek to test the assumption advanced by the proponents of the Social Identity Theory (SIT) that the inability to achieve social mobilization through joining perceived higher-status social groups (of states) leads great powers to adopt the approach of social competition in which they aim to equal or outdo the dominant group in the area on which its claim to superior status rests. Since the dissolution of the Soviet Union, Russia has struggled to be accepted as a great power by the group of Western states that had created the dominant international system order, while the Soviet states were isolated. While the 1990s and the beginning of the 21st century can be characterized by striving to integrate into the existing order, the second decade has seen a rather sharp turn towards creating a new power center for Russia through the realization of ideas of multipolarity rivalry and uniqueness of the state itself. Increasingly, we have seen the Kremlin striving to collaborate and mobilize groups of states that fall outside of the categories of democracy, multiculturalism, and international order, the way that is perceived by the dominant group, which can be described as the West. Instead, Russia builds its own narrative where it creates an alternative understanding of these values, differentiating from the higher-status social group. The Global South, from a Russian perspective, is the group of states that can still be swayed to create an alternative power center in the international system - one where Russia can assert its status as a great power. This is based on a number of reasons, the most important being that the global north is already highly institutionalized in terms of economy (the EU) and defense (NATO), leaving no room for Russia but to integrate within the existing framework. Second, the difference in values and their interpretation - Russia has been adamant, for the last twenty years, on basing its moral code on traditional values like religion, the heterosexual family model, and moral superiority, which contradict the overall secularism of the Global North. And last, the striking difference in understanding of state governance models - with Russia becoming more autocratic over the course of the last 20 years, it has deliberately created distance between itself and democratic states, entering a “gray area” of alternative understanding of democracy which is more relatable to the global South countries. Using computational text analysis of the excerpts of Vladimir Putin’s speeches delivered from 2000-2022 regarding the areas that fall outside the immediate area of interest of Russia (the Global South), we identify 80 topics that relate to the particular component of the great power status - interest to use force globally. These topics are compared across four temporal frames that capture the periods of more and less permissible Western social boundaries. We find that there exists a negative association between such permissiveness and Putin’s emphasis on the “use of force” topics. This lends further support to the Social Identity Theory and contributes to broadening its applicability to explaining the questions related to great power assertiveness in areas outside of their primary focus regions.

Keywords: Russia, Global South, great power, identity

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Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway network systems play a vital role in disaster response for disaster-damaged areas. Damaged bridges in such network systems can impede disaster response by disrupting transportation of rescue teams or humanitarian supplies. Therefore, emergency inspection and repair of bridges to quickly collect damage information of bridges and recover the functionality of highway networks is of paramount importance to disaster response. A widely used measure of a network’s capability to recover from disasters is resilience. To enhance highway network resilience, plenty of studies have developed various repair scheduling methods for the prioritization of bridge-repair tasks. These methods assume that repair activities are performed after the damage to a highway network is fully understood via inspection, although inspecting all bridges in a regional highway network may take days, leading to the significant delay in repairing bridges. In reality, emergency repair activities can be commenced as soon as the damage data of some bridges that are crucial to emergency response are obtained. Given that emergency bridge inspection and repair (EBIR) activities are executed simultaneously in the response phase, the real-time interactions between these activities can occur – the blockage of highways due to repair activities can affect inspection routes which in turn have an impact on emergency repair scheduling by providing real-time information on bridge damages. However, the impact of such interactions on the optimal emergency inspection routes (EIR) and emergency repair schedules (ERS) has not been discussed in prior studies. To overcome the aforementioned deficiencies, this study develops a routing and scheduling model for EBIR while accounting for real-time inspection-repair interactions to maximize highway network resilience. A stochastic, time-dependent integer program is proposed for the complex and real-time interacting EBIR problem given multiple inspection and repair teams at locations as set post-disaster. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. Computational tests are performed using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that the simultaneous implementation of bridge inspection and repair activities can significantly improve the highway network resilience. Moreover, the deployment of inspection and repair teams should match each other, and the network resilience will not be improved once the unilateral increase in inspection teams or repair teams exceeds a certain level. This study contributes to both knowledge and practice. First, the developed mathematical model makes it possible for capturing the impact of real-time inspection-repair interactions on inspection routing and repair scheduling and efficiently deriving optimal EIR and ERS on a large and complex highway network. Moreover, this study contributes to the organizational dimension of highway network resilience by providing optimal strategies for highway bridge management. With the decision support tool, disaster managers are able to identify the most critical bridges for disaster management and make decisions on proper inspection and repair strategies to improve highway network resilience.

Keywords: disaster management, emergency bridge inspection and repair, highway network, resilience, uncertainty

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Authors: Cristina Maria Mendoza Sanchez, Maria Angeles Navarro Perán

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Introduction: Nursing as a profession, from its initial formation and after its development in practice, has been built and identified mainly from its technical competence and professionalization within the positivist approach of the XIX century that provides a conception of the disease built on the basis of to the biomedical paradigm, where the care provided is more focused on the physiological processes and the disease than on the suffering person understood as a whole. The main issue that is in need of study here is a review of the nursing profession's history to get to know how the nursing profession was before the XIX century. It is unclear if there were organizations or people with knowledge about looking after others or if many people survived by chance. The holistic care, in which the appearance of the disease directly affects all its dimensions: physical, emotional, cognitive, social and spiritual. It is not a concept from the 21st century. It is common practice, most probably since established life in this world, with the final purpose of covering all these perspectives through quality care. Objective: In this paper, we describe and analyze the history of education in nursing learning in terms of reviewing and analysing theoretical foundations of clinical teaching and learning in nursing, with the final purpose of determining and describing the development of the nursing profession along the history. Method: We have done a descriptive systematic review study, doing a systematically searched of manuscripts and articles in the following health science databases: Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL. The selection of articles has been made according to PRISMA criteria, doing a critical reading of the full text using the CASPe method. A compliment to this, we have read a range of historical and contemporary sources to support the review, such as manuals of Florence Nightingale and John of God as primary manuscripts to establish the origin of modern nursing and her professionalization. We have considered and applied ethical considerations of data processing. Results: After applying inclusion and exclusion criteria in our search, in Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL, we have obtained 51 research articles. We have analyzed them in such a way that we have distinguished them by year of publication and the type of study. With the articles obtained, we can see the importance of our background as a profession before modern times in public health and as a review of our past to face challenges in the near future. Discussion: The important influence of key figures other than Nightingale has been overlooked and it emerges that nursing management and development of the professional body has a longer and more complex history than is generally accepted. Conclusions: There is a paucity of studies on the subject of the review to be able to extract very precise evidence and recommendations about nursing before modern times. But even so, as more representative data, an increase in research about nursing history has been observed. In light of the aspects analyzed, the need for new research in the history of nursing emerges from this perspective; in order to germinate studies of the historical construction of care before the XIX century and theories created then. We can assure that pieces of knowledge and ways of care were taught before the XIX century, but they were not called theories, as these concepts were created in modern times.

Keywords: nursing history, nursing theory, Saint John of God, Florence Nightingale, learning, nursing education

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Authors: Andrea Bikfalvi, Josep Llach, Ferran Lazaro, Bojan Jovanovski

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Due to the continuous need to foster university-business cooperation in both developed and developing countries, some higher education institutions face the challenge of designing, piloting, operating, and consolidating knowledge and technology transfer units. University-business cooperation has different maturity stages worldwide, with some higher education institutions excelling in these practices, but with lots of others that could be qualified as intermediate, or even some situated at the very beginning of their knowledge transfer adventure. These latter face the imminent necessity to formally create the technology transfer unit and to draw its roadmap. The complexity of this operation is due to various aspects that need to align and coordinate, including a major change in mission, vision, structure, priorities, and operations. Qualitative in approach, this study presents 5 case studies, consisting of higher education institutions located in the Western Balkans – 2 in Albania, 2 in Bosnia and Herzegovina, 1 in Montenegro- fully immersed in the entrepreneurial journey of creating their knowledge and technology transfer unit. The empirical evidence is developed in a pan-European project, illustratively called KnowHub (reconnecting universities and enterprises to unleash regional innovation and entrepreneurial activity), which is being implemented in three countries and has resulted in at least 15 pilot cooperation agreements between academia and business. Based on a peer-mentoring approach including more experimented and more mature technology transfer models of European partners located in Spain, Finland, and Austria, a series of initial lessons learned are already available. The findings show that each unit developed its tailor-made approach to engage with internal and external stakeholders, offer value to the academic staff, students, as well as business partners. The latest technology underpinning KnowHub services and institutional commitment are found to be key success factors. Although specific strategies and plans differ, they are based on a general strategy jointly developed and based on common tools and methods of strategic planning and business modelling. The main output consists of providing good practice for designing, piloting, and initial operations of units aiming to fully valorise knowledge and expertise available in academia. Policymakers can also find valuable hints on key aspects considered vital for initial operations. The value of this contribution is its focus on the intersection of three perspectives (service orientation, organisational innovation, business model) since previous research has only relied on a single topic or dual approaches, most frequently in the business context and less frequently in higher education.

Keywords: business model, capacity building, entrepreneurial education, knowledge transfer

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Authors: Heba Kamal Mohamed

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Introduction: Tramadol is a weak -opioid receptor agonist with an analgesic effect because of the inhibition of uptake of norepinephrine and serotonin. Nowadays, tramadol hydrochloride is frequently used as a pain reliever. Tramadol is recommended for the management of acute and chronic pain of moderate to severe intensity associated with a variety of diseases or problems, including osteoarthritis, diabetic neuropathy, neuropathic pain, and even perioperative pain in human patients. In obstetrics and gynecology, tramadol is used extensively to treat postoperative pain. Aim of the study: This study was undertaken to investigate the histological (light and electron microscopic) and immunohistochemical effects of long term tramadol treatment on the ovary of adult rats and the possible recovery after tramadol withdrawal. Design: Experimental study. Materials and methods: Thirty adult female albino rats were used in this study. They were classified into three main groups (10 rats each). Group I served as the control group. Group II, rats were subcutaneously injected with tramadol 40 mg/kg three times per week for 8 weeks. Group III, rats were subcutaneously injected with tramadol 40 mg/kg three times per week for 8 weeks then were kept for another 8 weeks without treatment for recovery. At the end of the experiment rats were sacrificed and bilateral oophorectomy was carried out; the ovaries were processed for histological study (light and electron microscopic) and immunohistochemical reaction for caspase-3 (apoptotic protein). Results: Examination of the ovary of tramadol-treated rats (group II) revealed many atretic ovarian follicles, some follicles showed detachment of the oocyte from surrounding granulosa cells and others showed loss of the oocyte. Many follicles revealed degenerated vacuolated oocytes and vacuolated theca folliculi cells. Granulosa cells appeared shrunken, disrupted and loosely attached with vacuolated cytoplasm and pyknotic nuclei. Some follicles showed separation of granulosa cells from the theca folliculi layer. The ultrastructural study revealed the presence of granulosa cells with electron dense indented nuclei, damaged mitochondria and granular vacuolated cytoplasm. Other cells showed accumulation of large amount of lipid droplets in their cytoplasm. Some follicles revealed rarifaction of the cytoplasm of oocytes and absent zona pellucida. Moreover, apoptotic changes were detected by immunohistochemical staining in the form of increased staining intensity to caspase-3 (apoptotic protein). With Masson's Trichrome stain, there was an increased collagen fibre deposition in the ovarian cortical stroma. The wall of blood vessels appeared thickened. In the withdrawal group (group III), there was a little improvement in the histological and immunohistochemical changes. Conclusion: Tramadol had serious deleterious effects on ovarian structure. Thus, it should be used with caution, especially when a long term treatment is indicated. Withdrawal of tramadol led to a little improvement in the structural impairment of the ovary.

Keywords: tramadol, ovary, withdrawal, rats

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Authors: Amanda Kavner, Richard Lamb

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Faster growth in science and technology of other nations may make staying globally competitive more difficult without shifting focus on how science is taught in US classes. An integral part of learning science involves visual and spatial thinking since complex, and real-world phenomena are often expressed in visual, symbolic, and concrete modes. The primary barrier to spatial thinking and visual literacy in Science, Technology, Engineering, and Math (STEM) fields is representational competence, which includes the ability to generate, transform, analyze and explain representations, as opposed to generic spatial ability. Although the relationship is known between the foundational visual literacy and the domain-specific science literacy, science literacy as a function of science learning is still not well understood. Moreover, the need for a more reliable measure is necessary to design resources which enhance the fundamental visuospatial cognitive processes behind scientific literacy. To support the improvement of students’ representational competence, first visualization skills necessary to process these science representations needed to be identified, which necessitates the development of an instrument to quantitatively measure visual literacy. With such a measure, schools, teachers, and curriculum designers can target the individual skills necessary to improve students’ visual literacy, thereby increasing science achievement. This project details the development of an artificial neural network capable of measuring science literacy using functional Near-Infrared Spectroscopy (fNIR) data. This data was previously collected by Project LENS standing for Leveraging Expertise in Neurotechnologies, a Science of Learning Collaborative Network (SL-CN) of scholars of STEM Education from three US universities (NSF award 1540888), utilizing mental rotation tasks, to assess student visual literacy. Hemodynamic response data from fNIRsoft was exported as an Excel file, with 80 of both 2D Wedge and Dash models (dash) and 3D Stick and Ball models (BL). Complexity data were in an Excel workbook separated by the participant (ID), containing information for both types of tasks. After changing strings to numbers for analysis, spreadsheets with measurement data and complexity data were uploaded to RapidMiner’s TurboPrep and merged. Using RapidMiner Studio, a Gradient Boosted Trees artificial neural network (ANN) consisting of 140 trees with a maximum depth of 7 branches was developed, and 99.7% of the ANN predictions are accurate. The ANN determined the biggest predictors to a successful mental rotation are the individual problem number, the response time and fNIR optode #16, located along the right prefrontal cortex important in processing visuospatial working memory and episodic memory retrieval; both vital for science literacy. With an unbiased measurement of science literacy provided by psychophysiological measurements with an ANN for analysis, educators and curriculum designers will be able to create targeted classroom resources to help improve student visuospatial literacy, therefore improving science literacy.

Keywords: artificial intelligence, artificial neural network, machine learning, science literacy, neuroscience

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Authors: Iris Alkaher, Nurit Carmi

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It is widely agreed among scientists that population growth (PG) is a major factor that drives the global environmental crisis. Many researchers recognize that explicitly addressing the impact of PG on the environment and human quality of life through education systems worldwide could play a significant role in improving understanding regarding the links between rapid PG and environmental degradation and changing perceptions, attitudes, and behaviors concerning the necessity to reduce the fertility rate. However, the issue of PG is still rarely included in schools' curricula, mainly because of its complexity and controversiality. This study aims to explore the perspectives of teachers with an academic background in environmental and sustainability education (ESEteachers) and teachers with no such background (non-ESE teachers) regarding PG as an environmental risk. The study also explores the teachers’ willingness to include PG in their teaching and identifies what predicts their inclusion of it. In this mixed-methods research study, data were collected using questionnaires and interviews. The findings portray a complex picture concerning the debate aboutPG as a major factor that drives the global environmental crisis in the Israeli context. Consistent with other countries, we found that the deep-rooted pronatalist culture in the Israeli society, as well as a robust national pronatalist agenda and policies, have a tremendous impact on the education system. Therefore, we found that an academic background in ESE had a limited impact on teachers' perceptions concerning PG as a problem and on their willingness to include it in their teaching and discuss its controversiality. Teachers' attitudes related to PG demonstrated social, cultural, and politically oriented disavowal justification regarding the negative impacts of rapid PG, identified in the literature as population-skepticism and population-fatalism. Specifically, factors such as the ongoing Israeli-Palestinian conflict, the Jewish anxiety of destruction, and the religious command to“be fruitful and multiply”influenced the perceptions of both ESE and non-ESE teachers. While these arguments are unique to the Israeli context, pronatalist policies are international. In accordance with the pronatalist policy, we also found that the absence of PG from both school curricula and the Israeli public discourse was reported by ESE and non-ESE teachers as major reasons for their disregarding PG in their teaching. Under these circumstances, the role of the education system to bring the population question to the front stage in Israel and elsewhere is more challenging. To encourage science and social studies teachers to incorporate the controversial issue of PG in their teaching and successfully confront dominant pronatalist cultures, they need strong and ongoing scaffolding and support. In accordance with scientists' agreement regarding the role of PG as a major factor that drives the global environmental crisis, we call on stakeholders and policymakers in the education system to bring the population debate into schools' curricula, the sooner, the better. And not only as part of human efforts to mitigate environmental degradation but also to use this controversial topic as a platform for shaping critical learners and responsible and active citizens who are tolerant of different people’s opinions.

Keywords: population growth, environmental and sustainability education, controversial environmental sustainability issues, pronatalism

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Authors: O. Gsib, U. Peirera, C. Egles, S. A. Bencherif

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In skin regenerative medicine, one of the critical issues is to produce a three-dimensional scaffold with optimized porosity for dermal fibroblast infiltration and neovascularization, which exhibits high mechanical properties and displays sufficient wound healing characteristics. In this study, we report on the synthesis and characterization of macroporous sequential interpenetrating polymer networks (IPNs) combining skin wound healing properties of fibrin with the excellent physical properties of polyethylene glycol (PEG). Fibrin fibers serve as a provisional biologically active network to promote cell adhesion and proliferation while PEG provides the mechanical stability to maintain the entire 3D construct. After having modified both PEG and Serum Albumin (used for promoting enzymatic degradability) by adding methacrylate residues (PEGDM and SAM, respectively), Fibrin/PEGDM-SAM sequential IPNs were synthesized as follows: Macroporous sponges were first produced from PEGDM-SAM hydrogels by a freeze-drying technique and then rehydrated by adding the fibrin precursors. Environmental Scanning Electron Microscopy (ESEM) and Confocal Laser Scanning Microscopy (CLSM) were used to characterize their microstructure. Human dermal fibroblasts were cultivated during one week in the constructs and different cell culture parameters (viability, morphology, proliferation) were evaluated. Subcutaneous implantations of the scaffolds were conducted on five-week old male nude mice to investigate their biocompatibility in vivo. We successfully synthesized interconnected and macroporous Fibrin/PEGDM-SAM sequential IPNs. The viability of primary dermal fibroblasts was well maintained (above 90%) after 2 days of culture. Cells were able to adhere, spread and proliferate in the scaffolds suggesting the suitable porosity and intrinsic biologic properties of the constructs. The fibrin network adopted a spider web shape that covered partially the pores allowing easier cell infiltration into the macroporous structure. To further characterize the in vitro cell behavior, cell proliferation (EdU incorporation, MTS assay) is being studied. Preliminary histological analysis of animal studies indicated the persistence of hydrogels even after one-month post implantation and confirmed the absence of inflammation response, good biocompatibility and biointegration of our scaffolds within the surrounding tissues. These results suggest that our Fibrin/PEGDM-SAM IPNs could be considered as potential candidates for dermis regenerative medicine. Histological analysis will be completed to further assess scaffold remodeling including de novo extracellular matrix protein synthesis and early stage angiogenesis analysis. Compression measurements will be conducted to investigate the mechanical properties.

Keywords: fibrin, hydrogels for dermal reconstruction, polyethylene glycol, semi-interpenetrating polymer network

Procedia PDF Downloads 215

Authors: Reham Khalaf-Nazzal, Imad Dweikat, Paula Gimenez, Iker Oyenarte, Alfonso Martinez-Cruz, Domonik Muller

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Metal cation transport mediator (CNNM) gene family comprises 4 isoforms that are expressed in various human tissues. Structurally, CNNMs are complex proteins that contain an extracellular N-terminal domain preceding a DUF21 transmembrane domain, a ‘Bateman module’ and a C-terminal cNMP-binding domain. Mutations in CNNM2 cause familial dominant hypomagnesaemia. Growing evidence highlights the role of CNNM2 in neurodevelopment. Mutations in CNNM2 have been implicated in epilepsy, intellectual disability, schizophrenia, and others. In the present study, we aim to elucidate the function of CNNM2 in the developing brain. Thus, we present the genetic origin of symptoms in two family cohorts. In the first family, three siblings of a consanguineous Palestinian family in which parents are first cousins, and consanguinity ran over several generations, presented a varying degree of intellectual disability, cone-rod dystrophy, and autism spectrum disorder. Exome sequencing and segregation analysis revealed the presence of homozygous pathogenic mutation in the CNNM2 gene, the parents were heterozygous for that gene mutation. Magnesium blood levels were normal in the three children and their parents in several measurements. They had no symptoms of hypomagnesemia. The CNNM2 mutation in this family was found to locate in the CBS1 domain of the CNNM2 protein. The crystal structure of the mutated CNNM2 protein was not significantly different from the wild-type protein, and the binding of AMP or MgATP was not dramatically affected. This suggests that the CBS1 domain could be involved in pure neurodevelopmental functions independent of its magnesium-handling role, and this mutation could have affected a protein partner binding or other functions in this protein. In the second family, another autosomal dominant CNNM2 mutation was found to run in a large family with multiple individuals over three generations. All affected family members had hypomagnesemia and hypermagnesuria. Oral supplementation of magnesium did not increase the levels of magnesium in serum significantly. Some affected members of this family have defects in fine motor skills such as dyslexia and dyslalia. The detected mutation is located in the N-terminal part, which contains a signal peptide thought to be involved in the sorting and routing of the protein. In this project, we describe heterogenous clinical phenotypes related to CNNM2 mutations and protein functions. In the first family, and up to the authors’ knowledge, we report for the first time the involvement of CNNM2 in retinal photoreceptor development and function. In addition, we report the presence of a neurophenotype independent of magnesium status related to the CNNM2 protein mutation. Taking into account the different modes of inheritance and the different positions of the mutations within CNNM2 and its different structural and functional domains, it is likely that CNNM2 might be involved in a wide spectrum of neuropsychiatric comorbidities with considerable varying phenotypes.

Keywords: magnesium transport, autosomal recessive, autism, neurodevelopment, CBS domain

Procedia PDF Downloads 129

Authors: Makhan Maharjan, Mani Ulaganathan, Vanchiappan Aravindan, Srinivasan Madhavi, Jing-Yuan Wang, Tuti Mariana Lim

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There is great interest to exploit sustainable, low-cost, renewable resources as carbon precursors for energy storage applications. Research on development of energy storage devices has been growing rapidly due to mismatch in power supply and demand from renewable energy sources This paper reported the synthesis of porous activated carbon from biomass waste and evaluated its performance in supercapicators. In this work, we employed orange peel (waste material) as the starting material and synthesized activated carbon by pyrolysis of KOH impregnated orange peel char at 800 °C in argon atmosphere. The resultant orange peel-derived activated carbon (OP-AC) exhibited a high BET surface area of 1,901 m2 g-1, which is the highest surface area so far reported for the orange peel. The pore size distribution (PSD) curve exhibits the pores centered at 11.26 Å pore width, suggesting dominant microporosity. The OP-AC was studied as positive electrode in combination with different negative electrode materials, such as pre-lithiated graphite (LiC6) and Li4Ti5O12 for making different hybrid capacitors. The lithium ion capacitor (LIC) fabricated using OP-AC with pre-lithiated graphite delivered a high energy density of ~106 Wh kg–1. The energy density for OP-AC||Li4Ti5O12 capacitor was ~35 Wh kg–1. For comparison purpose, configuration of OP-AC||OP-AC capacitors were studied in both aqueous (1M H2SO4) and organic (1M LiPF6 in EC-DMC) electrolytes, which delivered the energy density of 6.6 Wh kg-1 and 16.3 Wh kg-1, respectively. The cycling retentions obtained at current density of 1 A g–1 were ~85.8, ~87.0 ~82.2 and ~58.8% after 2500 cycles for OP-AC||OP-AC (aqueous), OP-AC||OP-AC (organic), OP-AC||Li4Ti5O12 and OP-AC||LiC6 configurations, respectively. In addition, characterization studies were performed by elemental and proximate composition, thermogravimetry, field emission-scanning electron microscopy, Raman spectra, X-ray diffraction (XRD) pattern, Fourier transform-infrared, X-ray photoelectron spectroscopy (XPS) and N2 sorption isotherms. The morphological features from FE-SEM exhibited well-developed porous structures. Two typical broad peaks observed in the XRD framework of the synthesized carbon implies amorphous graphitic structure. The ratio of 0.86 for ID/IG in Raman spectra infers high degree of graphitization in the sample. The band spectra of C 1s in XPS display the well resolved peaks related to carbon atoms in various chemical environments; for instances, the characteristics binding energies appeared at ~283.83, ~284.83, ~286.13, ~288.56, and ~290.70 eV which correspond to sp2 -graphitic C, sp3 -graphitic C, C-O, C=O and π-π*, respectively. Characterization studies revealed the synthesized carbon to be promising electrode material towards the application for energy storage devices. The findings opened up the possibility of developing high energy LICs from abundant, low-cost, renewable biomass waste.

Keywords: lithium-ion capacitors, orange peel, pre-lithiated graphite, supercapacitors

Procedia PDF Downloads 213

Authors: Ana Nemsadze

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Contemporary era and society are called postindustrial era and postindustrial society and/or informational era and informational society. Today science intends to define concept of information and comprehend informations role and function in contemporary society. Organization of social environment and governance of public processes on the base of information and tools of communication are main characteristics of informational era. This was defined by technological changes which were accomplished in culture in the second half of twentieth century. Today Georgia as an independent state needs to create an informational discourse of the country and therefore it is very important to study political and social cases which accomplished in the country after collapse of the Soviet Union because they start to define the present and the future of the country. The purpose of this study is to analyze political cases of the latest history of Georgia in terms of culture and information, concretely to elucidate which political cases transformed social life of post Soviet Georgia most of all who accomplished these political cases which visual and verbal messages was each political case spread with. The research is conducted on the base of interview. Participants of the interview are people of various specializations. Their professional activity is related to reflections on culture and theme of visual communication. They are philosophers sociologists a journalist media researcher a politologist a painter. The participants of the interview enumerated political cases and characterized them separately. Every expert thinks that declaration of independence of Georgia is the most important fact among all facts which were implemented in Georgia after collapse of the Soviet Union. The research revealed important social and political cases. Most of the cases are related to independence and territorial integrity of the state. Presidents of Georgia Zviad Gamsakhurdia Eduard Shevardnadze Mikheil Saakashvili Catholocos-Patriarch of All Georgia, the Archbishop of Mtskheta Tbilisi and Metropolitan bishop of Bichvinta and Tskhum Abkhazia Ilia II, businessman Bidzina Ivanishvili assumed dominating roles in cases. Verbal narrative of the cases accomplished during Zviad Gamsakhurdia presidential term expresses national freedom and visual part of cases of the same period expresses ruin of social-political structure. Verbal narrative of the cases accomplished during Eduard Sevardnadze presidential term expresses Free State and stability and reestablishment of Georgias political function in international relations and visual part of cases of the same period describes the most important moment of his presidential term and Eduard Shevardnadzes face appears too. Verbal narrative of the cases accomplished during Mikheil Saakashvilis presidential term expresses social renewal and visual part of cases of the same period describes August war and Mikheil Saakashvilis face appears too. The results of the study also reveal other details of visual verbal narrative of political and social cases of post Soviet Georgia. This gives a chance to start further reflection.

Keywords: culture, narrative, post soviet, visual communication

Procedia PDF Downloads 285

Authors: Maxwell Henderson, Tristan Cook, Justin Chan Jin Le, Mark Hodson, YoungJung Chang, John Novak, Daniel Padilha, Nishan Kulatilaka, Ansu Bagchi, Sanjoy Ray, John Kelly

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We present a method of using adiabatic quantum optimization (AQO) to solve a mixed integer nonlinear programming (MINLP) problem instance. The MINLP problem is a general form of a set of NP-hard optimization problems that are critical to many business applications. It requires optimizing a set of discrete and continuous variables with nonlinear and potentially nonconvex constraints. Obtaining an exact, optimal solution for MINLP problem instances of non-trivial size using classical computation methods is currently intractable. Current leading algorithms leverage heuristic and divide-and-conquer methods to determine approximate solutions. Creating more accurate and efficient algorithms is an active area of research. Quantum computing (QC) has several theoretical benefits compared to classical computing, through which QC algorithms could obtain MINLP solutions that are superior to current algorithms. AQO is a particular form of QC that could offer more near-term benefits compared to other forms of QC, as hardware development is in a more mature state and devices are currently commercially available from D-Wave Systems Inc. It is also designed for optimization problems: it uses an effect called quantum tunneling to explore all lowest points of an energy landscape where classical approaches could become stuck in local minima. Our work used a novel algorithm formulated for AQO to solve a special type of MINLP problem. The research focused on determining: 1) if the problem is possible to solve using AQO, 2) if it can be solved by current hardware, 3) what the currently achievable performance is, 4) what the performance will be on projected future hardware, and 5) when AQO is likely to provide a benefit over classical computing methods. Two different methods, integer range and 1-hot encoding, were investigated for transforming the MINLP problem instance constraints into a mathematical structure that can be embedded directly onto the current D-Wave architecture. For testing and validation a D-Wave 2X device was used, as well as QxBranch’s QxLib software library, which includes a QC simulator based on simulated annealing. Our results indicate that it is mathematically possible to formulate the MINLP problem for AQO, but that currently available hardware is unable to solve problems of useful size. Classical general-purpose simulated annealing is currently able to solve larger problem sizes, but does not scale well and such methods would likely be outperformed in the future by improved AQO hardware with higher qubit connectivity and lower temperatures. If larger AQO devices are able to show improvements that trend in this direction, commercially viable solutions to the MINLP for particular applications could be implemented on hardware projected to be available in 5-10 years. Continued investigation into optimal AQO hardware architectures and novel methods for embedding MINLP problem constraints on to those architectures is needed to realize those commercial benefits.

Keywords: adiabatic quantum optimization, mixed integer nonlinear programming, quantum computing, NP-hard

Procedia PDF Downloads 500

Authors: Anupalli Roja Rani, Pavithra Dasari

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Background: Among several, breast cancer has emerged as the most common female cancer in developing countries. It is the most common cause of cancer-related deaths worldwide among women. It is a molecularly and clinically heterogeneous disease. Moreover, it is a hormone–dependent tumor in which estrogens can regulate the growth of breast cells by binding with estrogen receptors (ERs). Moreover, the use of natural products in cancer therapeutics is due to their properties of biocompatibility and less toxicity. Plants are the vast reservoirs for various bioactive compounds. Coleus barbatus (Lamiaceae) contains anticancer properties against several cancer cell lines. Method: In the present study, an attempt is being made to enrich the knowledge of the anticancer activity of pure compounds extracted from Coleus barbatus (Andrew). On human breast cancer cell lines MCF-7. Here in, we are assessing the antiproliferative activity of Coleus barbatus (Andrew) plant extracts against MCF 7 and also evaluating their toxicity in normal human mammary cell lines such as Human Mammary Epithelial Cells (HMEC). The active fraction of plant extract was further purified with the help of Flash chromatography, Medium Pressure Liquid Chromatography (MPLC) and preparative High-Performance Liquid Chromatography (HPLC). The structure of pure compounds will be elucidated by using modern spectroscopic methods like Nuclear magnetic resonance (NMR), Electrospray Ionisation Mass Spectrometry (ESI-MS) methods. Later, the growth inhibition morphological assessment of cancer cells and cell cycle analysis of purified compounds were assessed using FACS. The growth and progression of signaling molecules HER2, GRP78 was studied by secretion assay using ELISA and expression analysis by flow cytometry. Result: Cytotoxic effect against MCF-7 with IC50 values were derived from dose response curves, using six concentrations of twofold serially diluted samples, by SOFTMax Pro software (Molecular device) and respectively Ellipticine and 0.5% DMSO were used as a positive and negative control. Conclusion: The present study shows the significance of various bioactive compounds extracted from Coleus barbatus (Andrew) root material. It acts as an anti-proliferative and shows cytotoxic effects on human breast cancer cell lines MCF7. The plant extracts play an important role pharmacologically. The whole plant has been used in traditional medicine for decades and the studies done have authenticated the practice. Earlier, as described, the plant has been used in the ayurveda and homeopathy medicine. However, more clinical and pathological studies must be conducted to investigate the unexploited potential of the plant. These studies will be very useful for drug designing in the future.

Keywords: coleus barbatus, HPLC, MPLC, NMR, MCF7, flash chromatograph, ESI-MS, FACS, ELISA.

Procedia PDF Downloads 89

Authors: Magdalena Idzikowska, Katarzyna Pająk, Kamil Kowalczyk

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Seafloor topography is a fundamental issue in geological, geophysical, and oceanographic studies. Single-beam or multibeam sonars attached to the hulls of ships are used to emit a hydroacoustic signal from transducers and reproduce the topography of the seabed. This solution provides relevant accuracy and spatial resolution. Bathymetric data from ships surveys provides National Centers for Environmental Information – National Oceanic and Atmospheric Administration. Unfortunately, most of the seabed is still unidentified, as there are still many gaps to be explored between ship survey tracks. Moreover, such measurements are very expensive and time-consuming. The solution is raster bathymetric models shared by The General Bathymetric Chart of the Oceans. The offered products are a compilation of different sets of data - raw or processed. Indirect data for the development of bathymetric models are also measurements of gravity anomalies. Some forms of seafloor relief (e.g. seamounts) increase the force of the Earth's pull, leading to changes in the sea surface. Based on satellite altimetry data, Sea Surface Height and marine gravity anomalies can be estimated, and based on the anomalies, it’s possible to infer the structure of the seabed. The main goal of the work is to create regional bathymetric models and models of the sea surface in the area of the east coast of North America – a region of seamounts and undulating seafloor. The research includes an analysis of the methods and techniques used, an evaluation of the interpolation algorithms used, model thickening, and the creation of grid models. Obtained data are raster bathymetric models in NetCDF format, survey data from multibeam soundings in MB-System format, and satellite altimetry data from Copernicus Marine Environment Monitoring Service. The methodology includes data extraction, processing, mapping, and spatial analysis. Visualization of the obtained results was carried out with Geographic Information System tools. The result is an extension of the state of the knowledge of the quality and usefulness of the data used for seabed and sea surface modeling and knowledge of the accuracy of the generated models. Sea level is averaged over time and space (excluding waves, tides, etc.). Its changes, along with knowledge of the topography of the ocean floor - inform us indirectly about the volume of the entire water ocean. The true shape of the ocean surface is further varied by such phenomena as tides, differences in atmospheric pressure, wind systems, thermal expansion of water, or phases of ocean circulation. Depending on the location of the point, the higher the depth, the lower the trend of sea level change. Studies show that combining data sets, from different sources, with different accuracies can affect the quality of sea surface and seafloor topography models.

Keywords: seafloor, sea surface height, bathymetry, satellite altimetry

Procedia PDF Downloads 59

Authors: Kraiem Khadija, Hamadi Kallali, Naceur Jedidi

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Constructed wetland systems are eco-technology recognized as environmentally friendly and emerging innovative solutions remediation as these systems are cost-effective and sustainable wastewater treatment systems. The performance of these biological system is affected by various factors such as plant, substrate, wastewater type, hydraulic loading rate, hydraulic retention time, water depth, and operation mood. The objective of this study was to to assess the alters of plant species on pollutants reduction and enrichment of anammox and nitrifing denitrifing bacteria in a modified vertical flow (VFCW) constructed wetland. This tests were carried out using three modified vertical constructed wetlands with a surface of 0.23 m² and depth 80 cm. It was a saturated vertical constructed wetland at the bottom. The saturation zone is maintained by the siphon structure at the outlet. The VFCW (₁) system was unplanted, VFCW (₂) planted with Typha angustofolia, and VFCW(₃) planted with Phragmites australis. The experimental units were fed with domestic wastewater and were operated by batch mode during 8 months at an average hydraulic loading rate around 20 cm day− 1. The operation cycle was two days feeding and five days rest. Results indicated that plants presence improved the removal efficiency; the removal rates of organic matter (85.1–90.9%; COD and 81.8–88.9%; BOD5), nitrogen (54.2–73%; NTK and 66–77%; NH4 -N) were higher by 10.7–30.1% compared to the unplanted vertical constructed wetland. On the other hand, the plant species had no significant effect on removal efficiency of COD, The removal of COD was similar in VFCW (₂) and VFCW (₃) (p > 0.05), attaining average removal efficiencies of 88.7% and 85.2%, respectively. Whereas it had a significant effect on NTK removal (p > 0.05), with an average removal rate of 72% versus 51% for VFCW (₂) and VFCW (₃), respectively. Among the three sets of vertical flow constructed wetlands, the VFCW(₂) removed the highest percent of total streptococcus, fecal streptococcus total coliforms, fecal coliforms, E. coli as 59, 62, 52, 63, and 58%, respectively. The presence and the plant species alters the community composition and abundance of the bacteria. The abundance of bacteria in the planted wetland was much higher than that in the unplanted one. VFCW(₃) had the highest relative abundance of nitrifying bacteria such as Nitrosospira (18%), Nitrosospira (12%), and Nitrobacter (8%). Whereas the vertical constructed wetland planted with typha had larger number of denitrifying species, with relative abundances of Aeromonas (13%), Paracoccus (11%), Thauera (7%), and Thiobacillus (6%). However, the abundance of nitrifying bacteria was very lower in this system than VFCW(₂). Interestingly, the presence of Thypha angustofolia species favored the enrichment of anammox bacteria compared to unplanted system and system planted with phragmites australis. The results showed that the middle layer had the most accumulation of anammox bacteria, which the anaerobic condition is better and the root system is moderate. Vegetation has several characteristics that make it an essential component of wetlands, but its exact effects are complex and debated.

Keywords: wastawater, constructed wetland, anammox, removal

Procedia PDF Downloads 80

Authors: Motaz Alsolaim

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Nowadays, the challenges of running a start-up can be very complex and are perhaps more difficult than at any other time in the past. Changes in technology, manufacturing innovation, and product development, combined with intense competition and market regulations are factors that have put pressure on classic ways of managing firms, thereby forcing change. As a result, the rate of closure, exit or discontinuation of start-ups and young businesses is very high. Despite the essential role of small firms in an economy, they still tend to face obstacles that exert a negative influence on their performance and rate of survival. In fact, it is not easy to determine with any certainty the reasons why small firms fail. For this reason, failure itself is not clearly defined, and its exact causes are hard to diagnose. In this current study, therefore, the barriers to survival will be covered more broadly, especially personal/entrepreneurial, enterprise and environmental factors with regard to various possible reasons for this failure, in order to determine the best solutions and make appropriate recommendations. Methodology: It could be argued that mixed methods might help to improve entrepreneurship research addressing challenges emphasis in previous studies and to achieve the triangulation. Calls for the combined use of quantitative and qualitative research were also made in the entrepreneurship field since entrepreneurship is a multi-faceted area of research. Therefore, explanatory sequential mixed method was used, using questionnaire online survey for entrepreneurs, followed by semi-structure interview. Collecting over 750 surveys and accepting 296 valid surveys, after that 13 interviews from government official seniors, businessmen successful entrepreneurs, and non-successful entrepreneurs. Findings: The first phase findings ( quantitative) shows the obstacles to survive; starting from the personal/ entrepreneurial factors such as; past work experience, lack of skills and interest, are positive factors, while; gender, age and education level of the owner are negative factors. Internal factors such as lack of marketing research and weak business planning are positive. The environmental factors; in economic perspectives; difficulty to find labors, in socio-cultural perspectives; Social restriction and traditions found to be a negative factors. In other hand, from the political perspective; cost of compliance and insufficient government plans found to be a positive factors for small business failure. From infrastructure perspective; lack of skills labor, high level of bureaucracy and lack of information are positive factors. Conclusion: This paper serves to enrich the understanding of failure factors in MENA region more precisely in SA, by minimizing the probability of failure in small-micro entrepreneurial start-up in SA, in the light of the Saudi government’s Vision 2030 plan.

Keywords: small business barriers, start-up business, entrepreneurship, Saudi Arabia

Procedia PDF Downloads 166

Authors: Reggie Chandra

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Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.

Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal

Procedia PDF Downloads 140

Authors: Mayank Gupta, Siba Prasad Samal, Vasu Kakkirala

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The internet world and its priorities have changed considerably in the last decade. Browsing on smart phones has increased manifold and is set to explode much more. Users spent considerable time browsing different websites, that gives a great deal of insight into user’s preferences. Instead of plain information classifying different aspects of browsing like Bookmarks, History, and Download Manager into useful categories would improve and enhance the user’s experience. Most of the classification solutions are server side that involves maintaining server and other heavy resources. It has security constraints and maybe misses on contextual data during classification. On device, classification solves many such problems, but the challenge is to achieve accuracy on classification with resource constraints. This on device classification can be much more useful in personalization, reducing dependency on cloud connectivity and better privacy/security. This approach provides more relevant results as compared to current standalone solutions because it uses content rendered by browser which is customized by the content provider based on user’s profile. This paper proposes a Naive Bayes based lightweight classification engine targeted for a resource constraint devices. Our solution integrates with Web Browser that in turn triggers classification algorithm. Whenever a user browses a webpage, this solution extracts DOM Tree data from the browser’s rendering engine. This DOM data is a dynamic, contextual and secure data that can’t be replicated. This proposal extracts different features of the webpage that runs on an algorithm to classify into multiple categories. Naive Bayes based engine is chosen in this solution for its inherent advantages in using limited resources compared to other classification algorithms like Support Vector Machine, Neural Networks, etc. Naive Bayes classification requires small memory footprint and less computation suitable for smartphone environment. This solution has a feature to partition the model into multiple chunks that in turn will facilitate less usage of memory instead of loading a complete model. Classification of the webpages done through integrated engine is faster, more relevant and energy efficient than other standalone on device solution. This classification engine has been tested on Samsung Z3 Tizen hardware. The Engine is integrated into Tizen Browser that uses Chromium Rendering Engine. For this solution, extensive dataset is sourced from dmoztools.net and cleaned. This cleaned dataset has 227.5K webpages which are divided into 8 generic categories ('education', 'games', 'health', 'entertainment', 'news', 'shopping', 'sports', 'travel'). Our browser integrated solution has resulted in 15% less memory usage (due to partition method) and 24% less power consumption in comparison with standalone solution. This solution considered 70% of the dataset for training the data model and the rest 30% dataset for testing. An average accuracy of ~96.3% is achieved across the above mentioned 8 categories. This engine can be further extended for suggesting Dynamic tags and using the classification for differential uses cases to enhance browsing experience.

Keywords: chromium, lightweight engine, mobile computing, Naive Bayes, Tizen, web browser, webpage classification

Procedia PDF Downloads 139

Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

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Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

Procedia PDF Downloads 22

Authors: Monika Jurkeviciute, Amia Enam, Johanna Torres Bonilla, Henrik Eriksson

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Introduction: Many evaluations of eHealth interventions conclude that the evidence for improved clinical outcomes is limited, especially when the intervention is short, such as one year. Often, evaluation design does not address the feasibility of achieving clinical outcomes. Evaluations are designed to reflect upon clinical goals of intervention without utilizing the opportunity to illuminate effects on organizations and cost. A comprehensive design of evaluation can better support decision-making regarding the effectiveness and potential transferability of eHealth. Hence, the purpose of this paper is to present a feasible and comprehensive design of evaluation for eHealth intervention, including the design process in different contexts. Methodology: The situation of limited feasibility of clinical outcomes was foreseen in the European Union funded project called “DECI” (“Digital Environment for Cognitive Inclusion”) that is run under the “Horizon 2020” program with an aim to define and test a digital environment platform within corresponding care models that help elderly people live independently. A complex intervention of eHealth implementation into elaborate care models in four different countries was planned for one year. To design the evaluation, a participative approach was undertaken using Pettigrew’s lens of change and transformations, including context, process, and content. Through a series of workshops, observations, interviews, and document analysis, as well as a review of scientific literature, a comprehensive design of evaluation was created. Findings: The findings indicate that in order to get evidence on clinical outcomes, eHealth interventions should last longer than one year. The content of the comprehensive evaluation design includes a collection of qualitative and quantitative methods for data gathering which illuminates non-medical aspects. Furthermore, it contains communication arrangements to discuss the results and continuously improve the evaluation design, as well as procedures for monitoring and improving the data collection during the intervention. The process of the comprehensive evaluation design consists of four stages: (1) analysis of a current state in different contexts, including measurement systems, expectations and profiles of stakeholders, organizational ambitions to change due to eHealth integration, and the organizational capacity to collect data for evaluation; (2) workshop with project partners to discuss the as-is situation in relation to the project goals; (3) development of general and customized sets of relevant performance measures, questionnaires and interview questions; (4) setting up procedures and monitoring systems for the interventions. Lastly, strategies are presented on how challenges can be handled during the design process of evaluation in four different countries. The evaluation design needs to consider contextual factors such as project limitations, and differences between pilot sites in terms of eHealth solutions, patient groups, care models, national and organizational cultures and settings. This implies a need for the flexible approach to evaluation design to enable judgment over the effectiveness and potential for adoption and transferability of eHealth. In summary, this paper provides learning opportunities for future evaluation designs of eHealth interventions in different national and organizational settings.

Keywords: ehealth, elderly, evaluation, intervention, multi-cultural

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Authors: Chandan Kundu, Sankar Bhattacharya

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A significant disadvantage of fossil fuel energy production is the considerable amount of carbon dioxide (CO₂) released, which is one of the contributors to climate change. Apart from environmental concerns, changing fossil fuel prices have pushed society gradually towards renewable energy sources in recent years. Biomass is a plentiful and renewable resource and a source of carbon. Recent years have seen increased research interest in generating fuels and chemicals from biomass. Unlike fossil-based resources, biomass is composed of lignocellulosic material, which does not contribute to the increase in atmospheric CO₂ over a longer term. These considerations contribute to the current move of the chemical industry from non-renewable feedstock to renewable biomass. This presentation focuses on generating bio-oil and two major platform chemicals that can potentially improve the environment. Thermochemical processes such as pyrolysis are considered viable methods for producing bio-oil and biomass-based platform chemicals. Fluidized bed reactors, on the other hand, are known to boost bio-oil yields during pyrolysis due to their superior mixing and heat transfer features, as well as their scalability. This review and the associated experimental work are focused on the thermochemical conversion of biomass to bio-oil and two high-value platform chemicals, Levoglucosenone (LGO) and 5-Chloromethyl furfural (5-CMF), in a fluidized bed reactor. These two active molecules with distinct features can potentially be useful monomers in the chemical and pharmaceutical industries since they are well adapted to the manufacture of biologically active products. This process took several meticulous steps. To begin, the biomass was delignified using a peracetic acid pretreatment to remove lignin. Because of its complicated structure, biomass must be pretreated to remove the lignin, increasing access to the carbohydrate components and converting them to platform chemicals. The biomass was then characterized by Thermogravimetric analysis, Synchrotron-based THz spectroscopy, and in-situ DRIFTS in the laboratory. Based on the results, a continuous-feeding fluidized bed reactor system was constructed to generate platform chemicals from pretreated biomass using hydrogen chloride acid-gas as a catalyst. The procedure also yields biochar, which has a number of potential applications, including soil remediation, wastewater treatment, electrode production, and energy resource utilization. Consequently, this research also includes a preliminary experimental evaluation of the biochar's prospective applications. The biochar obtained was evaluated for its CO₂ and steam reactivity. The outline of the presentation will comprise the following: Biomass pretreatment for effective delignification Mechanistic study of the thermal and thermochemical conversion of biomass Thermochemical conversion of untreated and pretreated biomass in the presence of an acid catalyst to produce LGO and CMF A thermo-catalytic process for the production of LGO and 5-CMF in a continuously-fed fluidized bed reactor and efficient separation of chemicals Use of biochar generated from the platform chemicals production through gasification

Keywords: biomass, pretreatment, pyrolysis, levoglucosenone

Procedia PDF Downloads 109

Authors: Tiptunya Duangsri, Panwilai Chomchid, Natchanok Jansawang

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This research study was to investigate of education decisions must be made which a part of it should be passed on to future generations as obligatory for all members of a chemistry class for students who will prepare themselves for a special position. The descriptions of instructional design were provided and the recent criticisms are discussed. This research study to an outline of an integrative framework for the description of information and the instructional design model give structure to negotiate a semblance of conscious understanding. The aims of this study are to describe the instructional design model for comparisons between students’ genders of their effects on STEM educational learning achievement motives to their science attitudes and logical thinking abilities with a sample size of 18 students at the 11th grade level with the cluster random sampling technique in Mahawichanukul School were designed. The chemistry learning environment was administered with the STEM education method. To build up the 5-instrument lesson instructional plan issues were instructed innovations, the 30-item Logical Thinking Test (LTT) on 5 scales, namely; Inference, Recognition of Assumptions, Deduction, Interpretation and Evaluation scales was used. Students’ responses of their perceptions with the Test Of Chemistry-Related Attitude (TOCRA) were assessed of their attitude in science toward chemistry. The validity from Index Objective Congruence value (IOC) checked by five expert specialist educator in two chemistry classroom targets in STEM education, the E1/E2 process were equaled evidence of 84.05/81.42 which results based on criteria are higher than of 80/80 standard level with the IOC from the expert educators. Comparisons between students’ learning achievement motives with STEM educational model on stoichiometry issue in chemistry classes with different genders were differentiated at evidence level of .05, significantly. Associations between students’ learning achievement motives on their posttest outcomes and logical thinking abilities, the predictive efficiency (R2) values indicate that 69% and 70% of the variances in different male and female student groups of their logical thinking abilities. The predictive efficiency (R2) values indicate that 73%; and 74% of the variances in different male and female student groups of their science attitudes toward chemistry were associated. Statistically significant on students’ perceptions of their chemistry learning classroom environment and their science attitude toward chemistry when using the MCI and TOCRA, the predictive efficiency (R2) values indicated that 72% and 74% of the variances in different male and female student groups of their chemistry classroom climate, consequently. Suggestions that supporting chemistry or science teachers from science, technology, engineering and mathematics (STEM) in addressing complex teaching and learning issues related instructional design to develop, teach, and assess traditional are important strategies with a focus on STEM education instructional method.

Keywords: development, the instructional design model, students learning achievement motives, science attitudes with STEM educational model, stoichiometry issue, chemistry classes, genders

Procedia PDF Downloads 257

Authors: Oluwaseun Adeleke, Grace Amarachi Omenife, Jennifer Adebambo, Mopelola Raji, Anthony Nwala, Mogbonjubade Adesulure

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Introduction: The incorporation of digital technology in healthcare systems is instrumental in transforming the delivery, management, and overall experience of healthcare and holds the potential to scale up access through over 200 million active mobile phones used in Nigeria. Digital tools enable increased access to care, stronger client engagement, progress in research and data-driven insights, and more effective promotion of self-care and do-it-yourself practices. The Delivering Innovation in Self-Care (DISC) project 2021 has played a pivotal role in granting women greater autonomy over their sexual and reproductive health (SRH) through a variety of approaches, including information and training to self-inject contraception (DMPA-SC). To optimize its outcomes, the project also leverages digital technology platforms like social media: Facebook, Instagram, and Meet Tina (Chatbot) via WhatsApp, Customer Relationship Management (CRM) applications Freshworks, and Viamo. Methodology: The project has been successful at optimizing in-person digital cyberspace interaction to sensitize individuals effectively about self-injection and provide linkages to SI services. This platform employs the Freshworks CRM software application, along with specially trained personnel known as Cyber IPC Agents and DHIS calling centers. Integration of Freshworks CRM software with social media allows a direct connection with clients to address emerging issues, schedule follow-ups, send reminders to improve compliance with self-injection schedules, enhance the overall user experience for self-injection (SI) clients, and generate comprehensive reports and analytics on client interactions. Interaction covers a range of topics, including – How to use SI, learning more about SI, side-effects and its management, accessing services, fertility, ovulation, other family planning methods, inquiries related to Sexual Reproductive Health as well as uses an address log to connect them with nearby facilities or online pharmaceuticals. Results: Between the months of March to September, a total of 5,403 engagements were recorded. Among these, 4,685 were satisfactorily resolved. Since the program's inception, digital advertising has created 233,633,075 impressions, reached 12,715,582 persons, and resulted in 3,394,048 clicks. Conclusion: Leveraging digital technology has proven to be an invaluable tool in client management and improving client experience. The use of Cyber technology has enabled the successful development and maintenance of client relationships, which have been effective at providing support, facilitating delivery and compliance with DMPA-SC self-injection services, and ensuring overall client satisfaction. Concurrently, providing qualitative data, including user experience feedback, has enabled the derivation of crucial insights that inform the decision-making process and guide in normalizing self-care behavior.

Keywords: selfcare, DMPA-SC self-injection, digital technology, cyber technology, freshworks CRM software

Procedia PDF Downloads 51

Authors: Bai-Chen Xie, Xian-Peng Chen

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China has become the world's largest energy producer and consumer, and its development of renewable energy is of great significance to global energy governance and the fight against climate change. The rapid growth of solar power in China could help achieve its ambitious carbon peak and carbon neutrality targets early. However, the non-technical costs of solar power in China are much higher than at international levels, meaning that inefficiencies are rooted in poor management and improper policy design and that efficiency distortions have become a serious challenge to the sustainable development of the renewable energy industry. Unlike fossil energy generation technologies, the output of solar power is closely related to the volatile solar resource, and the spatial unevenness of solar resource distribution leads to potential efficiency spatial distribution differences. It is necessary to develop an efficiency evaluation method that considers the volatility of solar resources and explores the mechanism of the influence of natural geography and social environment on the spatially varying characteristics of efficiency distribution to uncover the root causes of managing inefficiencies. The study sets solar resources as stochastic inputs, introduces a chance-constrained data envelopment analysis model combined with the directional distance function, and measures the solar resource utilization efficiency of 222 solar power plants in representative photovoltaic bases in northwestern China. By the meta-frontier analysis, we measured the characteristics of different power plant clusters and compared the differences among groups, discussed the mechanism of environmental factors influencing inefficiencies, and performed statistical tests through the system generalized method of moments. Rational localization of power plants is a systematic project that requires careful consideration of the full utilization of solar resources, low transmission costs, and power consumption guarantee. Suitable temperature, precipitation, and wind speed can improve the working performance of photovoltaic modules, reasonable terrain inclination can reduce land cost, and the proximity to cities strongly guarantees the consumption of electricity. The density of electricity demand and high-tech industries is more important than resource abundance because they trigger the clustering of power plants to result in a good demonstration and competitive effect. To ensure renewable energy consumption, increased support for rural grids and encouraging direct trading between generators and neighboring users will provide solutions. The study will provide proposals for improving the full life-cycle operational activities of solar power plants in China to reduce high non-technical costs and improve competitiveness against fossil energy sources.

Keywords: solar power plants, environmental factors, data envelopment analysis, efficiency evaluation

Procedia PDF Downloads 72

Authors: Wang Shuai, Su Rong, K. J.Tseng, V. Viswanathan, S. Ramakrishna

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The More-Electric-Aircraft concept in aircraft industry levies an increasing demand on the embedded starter/generators (ESG). The high-speed and high-temperature environment within an engine poses great challenges to the operation of such machines. In view of such challenges, squirrel cage induction machines (SCIM) have shown advantages due to its simple rotor structure, absence of temperature-sensitive components as well as low torque ripples etc. The tight operation constraints arising from typical ESG applications together with the detailed operation principles of SCIMs have been exploited to derive the mathematical interpretation of the ESG-SCIM design process. The resultant non-linear mathematical treatment yielded unique solution to the SCIM design problem for each configuration of pole pair number p, slots/pole/phase q and conductors/slot zq, easily implemented via loop patterns. It was also found that not all configurations led to feasible solutions and corresponding observations have been elaborated. The developed mathematical procedures also proved an effective framework for optimization among electromagnetic, thermal and mechanical aspects by allocating corresponding degree-of-freedom variables. Detailed 3D FEM analysis has been conducted to validate the resultant machine performance against design specifications. To obtain higher power ratings, electrical machines often have to increase the slot areas for accommodating more windings. Since the available space for embedding such machines inside an engine is usually short in length, axial air gap arrangement appears more appealing compared to its radial gap counterpart. The aforementioned approach has been adopted in case studies of designing series of AFIMs and RFIMs respectively with increasing power ratings. Following observations have been obtained. Under the strict rotor diameter limitation AFIM extended axially for the increased slot areas while RFIM expanded radially with the same axial length. Beyond certain power ratings AFIM led to long cylinder geometry while RFIM topology resulted in the desired short disk shape. Besides the different dimension growth patterns, AFIMs and RFIMs also exhibited dissimilar performance degradations regarding power factor, torque ripples as well as rated slip along with increased power ratings. Parametric response curves were plotted to better illustrate the above influences from increased power ratings. The case studies may provide a basic guideline that could assist potential users in making decisions between AFIM and RFIM for relevant applications.

Keywords: axial flux induction machine, electrical starter/generator, finite element analysis, squirrel cage induction machine

Procedia PDF Downloads 438