Search results for: teacher professional development program

Authors: Hsyi-En Cheng, Ying-Yi Liou

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Metal-oxide semiconductor (MOS) gas sensors are widely used in the gas-detection market due to their high sensitivity, fast response, and simple device structures. However, the high working temperature of MOS gas sensors makes them difficult to integrate with the appliance or consumer goods. One-dimensional (1-D) nanostructures are considered to have the potential to lower their working temperature due to their large surface-to-volume ratio, confined electrical conduction channels, and small feature sizes. Unfortunately, the difficulty of fabricating 1-D nanostructure electrodes has hindered the development of low-temperature MOS gas sensors. In this work, we proposed a method to fabricate nanotube-arrays, and the SnO₂ nanotube-array sensors with different wall thickness were successfully prepared and examined. The fabrication of SnO₂ nanotube arrays incorporates the techniques of barrier-free anodic aluminum oxide (AAO) template and atomic layer deposition (ALD) of SnO₂. First, 1.0 µm Al film was deposited on ITO glass substrate by electron beam evaporation and then anodically oxidized by five wt% phosphoric acid solution at 5°C under a constant voltage of 100 V to form porous aluminum oxide. As the Al film was fully oxidized, a 15 min over anodization and a 30 min post chemical dissolution were used to remove the barrier oxide at the bottom end of pores to generate a barrier-free AAO template. The ALD using reactants of TiCl4 and H₂O was followed to grow a thin layer of SnO₂ on the template to form SnO₂ nanotube arrays. After removing the surface layer of SnO₂ by H₂ plasma and dissolving the template by 5 wt% phosphoric acid solution at 50°C, upright standing SnO₂ nanotube arrays on ITO glass were produced. Finally, Ag top electrode with line width of 5 μm was printed on the nanotube arrays to form SnO₂ nanotube-array sensor. Two SnO₂ nanotube-arrays with wall thickness of 30 and 60 nm were produced in this experiment for the evaluation of gas sensing ability. The flat SnO₂ films with thickness of 30 and 60 nm were also examined for comparison. The results show that the properties of ALD SnO₂ films were related to the deposition temperature. The films grown at 350°C had a low electrical resistivity of 3.6×10-3 Ω-cm and were, therefore, used for the nanotube-array sensors. The carrier concentration and mobility of the SnO₂ films were characterized by Ecopia HMS-3000 Hall-effect measurement system and were 1.1×1020 cm-3 and 16 cm3/V-s, respectively. The electrical resistance of SnO₂ film and nanotube-array sensors in air and in a 5% H₂-95% N₂ mixture gas was monitored by Pico text M3510A 6 1/2 Digits Multimeter. It was found that, at 200 °C, the 30-nm-wall SnO₂ nanotube-array sensor performs the highest responsivity to 5% H₂, followed by the 30-nm SnO₂ film sensor, the 60-nm SnO₂ film sensor, and the 60-nm-wall SnO₂ nanotube-array sensor. However, at temperatures below 100°C, all the samples were insensitive to the 5% H₂ gas. Further investigation on the sensors with thinner SnO₂ is necessary for improving the sensing ability at temperatures below 100 °C.

Keywords: atomic layer deposition, nanotube arrays, gas sensor, tin dioxide

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Authors: Jonathan A. Noble

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‘Origins’ is an exhibition designed and installed by MMA Design Studio, at the 2023 Venice Biennale. The instillation formed part of the ‘Dangerous Liaisons’ group exhibition at the Arsenale building. An immersive experience was created for those who visited, where video projection and the bodies of visitors interacted with the scene. Designed by South African architect, Mphethi Morojele – founder and owner of MMA – the primary inspiration for ‘Origins’ was the recent discovery by Professor Karim Sadr in 2019, of a substantial Tswana settlement. Situated in present day Suikerbosrand Nature Reserve, some 45km south of Johannesburg, this precolonial city named Kweneng, has been dated back to the fifteenth century. This remarkable discovery was achieved thanks to advanced aerial, LiDAR scanning technology, which was used to capture the traces of Kweneng, spanning a terrain of some 10km long and 2km wide. Discovered by light (LiDAR) and exhibited through light, Origins presents a simulated experience of Kweneng. The presentation of Kweneng was achieved primarily though video, with a circular projection onto the floor of an animated LiDAR data sequence, and onto the walls a filmed dance sequence choreographed to embody the architectural, spatial and symbolic significance of Kweneng. This paper documents the design process that was involved in the conceptualization, development and final realization of this noteworthy exhibition, with an elucidation upon key social and cultural questions pertaining to precolonial heritage, reimagined histories and postcolonial identity. Periods of change and of social awakening sometimes spark an interest in questions of origin, of cultural lineage and belonging – and which certainly is the case for contemporary, post-Apartheid South Africa. Researching this paper has required primary study of MMA Design Studio’s project archive, including various proposals and other design related documents, conceptual design sketches, architectural drawings and photographs. This material is supported by the authors first-hand interviews with Morejele and others who were involved, especially with respect to the choreography of the interpretive dance, LiDAR visualization techniques and video production that informed the simulated, immersive experience at the exhibition. Presenting a ‘dangerous liaison’ between architecture and dance, Origins looks into the distant past to frame contemporary questions pertaining to intangible heritage, animism and embodiment through architecture and dance – considerations which are required “to survive the future”, says Morojele.

Keywords: architecture and dance, Kweneng, MMA design studio, origins, Venice Biennale

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Authors: Simona Perga, Chiara Beltramo, Floriana Fruscione, Isabella Martini, Federica Cavallo, Federica Riccardo, Paolo Buracco, Selina Iussich, Elisabetta Razzuoli, Katia Varello, Lorella Maniscalco, Elena Bozzetta, Angelo Ferrari, Paola Modesto

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Introduction: Human and canine melanoma have common clinical, histologic characteristics making dogs a good model for comparative oncology. The identification of specific genes and a better understanding of the genetic landscape, signaling pathways, and tumor–microenvironmental interactions involved in the cancer onset and progression is essential for the development of therapeutic strategies against this tumor in both species. In the present study, the differential expression of genes in spontaneously occurring canine melanoma and in paired normal tissue was investigated by targeted RNAseq. Material and Methods: Total RNA was extracted from 17 canine malignant melanoma (CMM) samples and from five paired normal tissues stored in RNA-later. In order to capture the greater genetic variability, gene expression analysis was carried out using two panels (Qiagen): Human Immuno-Oncology (HIO) and Mouse-Immuno-Oncology (MIO) and the miSeq platform (Illumina). These kits allow the detection of the expression profile of 990 genes involved in the immune response against tumors in humans and mice. The data were analyzed through the CLCbio Genomics Workbench (Qiagen) software using the Canis lupus familiaris genome as a reference. Data analysis were carried out both comparing the biologic group (tumoral vs. healthy tissues) and comparing neoplastic tissue vs. paired healthy tissue; a Fold Change greater than two and a p-value less than 0.05 were set as the threshold to select interesting genes. Results and Discussion: Using HIO 63, down-regulated genes were detected; 13 of those were also down-regulated comparing neoplastic sample vs. paired healthy tissue. Eighteen genes were up-regulated, 14 of those were also down-regulated comparing neoplastic sample vs. paired healthy tissue. Using the MIO, 35 down regulated-genes were detected; only four of these were down-regulated, also comparing neoplastic sample vs. paired healthy tissue. Twelve genes were up-regulated in both types of analysis. Considering the two kits, the greatest variation in Fold Change was in up-regulated genes. Dogs displayed a greater genetic homology with humans than mice; moreover, the results have shown that the two kits are able to detect different genes. Most of these genes have specific cellular functions or belong to some enzymatic categories; some have already been described to be correlated to human melanoma and confirm the validity of the dog as a model for the study of molecular aspects of human melanoma.

Keywords: animal model, canine melanoma, gene expression, spontaneous tumors, targeted RNAseq

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Authors: Oto J. Okwu, Ornan Henry, Victor A. Otene

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The agricultural sector contributes a great deal to the sustenance of Nigeria’s food security and economy, with an attendant impact on rural development. In spite of the relatively high number of farmers in the country, self-sufficiency in food production is still a challenge. Farmers are faced with myriad problems which hinder their production efficiency, one of which is their access to agricultural inputs required for optimum production. To meet the challenges faced by farmers, the government at the federal level has come up with many agricultural policies, one of which is the Agricultural Transformation Agenda (ATA). The Growth Enhancement Support Scheme (GESS) is one of the critical components of ATA, which is aimed at ensuring the effective distribution of agricultural inputs delivered directly to farmers, and at a regulated cost. After about 8 years of launching this policy, it will be necessary to carry out an assessment of GESS and determine the impact it has made on rural farmers with respect to their access to farm inputs. This study was carried out to assess the Growth Enhancement Support Scheme (GESS) in Adamawa State, Nigeria. Crop farmers who registered under the GESS in Adamawa State, Nigeria, formed the population for the study. Primary data for the study were obtained through a survey, and the use of a structured questionnaire. A sample size of 167 respondents was selected using multi-stage, purposive, and random sampling techniques. The validity and reliability of the research instrument (questionnaire) were obtained through pilot testing and test-retest method, respectively. The objectives of the study were to determine the difference in the level of access to agricultural inputs before and after GESS, determine the difference in cost of agricultural inputs before and after GESS, and to determine the challenges faced by rural farmers in accessing agricultural inputs through GESS. Both descriptive and inferential statistics were used in analyzing the collected data. Specifically, Mann-Whitney, student t-test, and factor analysis were used to test the stated hypotheses. Research findings revealed there was a significant difference in the level of access to farm inputs after the introduction of GESS (Z=14.216). Also, there was a significant difference in the cost of agro-inputs after the introduction of GESS (Pr |T| > |t|= 0.0000). The challenges faced by respondents in accessing agro-inputs through GESS were administrative and technical in nature. Based on the findings of the research, it was recommended that efforts be made by the government to sustain the GESS, as it has significantly improved the level of farmers’ access to agricultural inputs and has reduced the cost of agro-inputs, while administrative challenges faced by the respondents in accessing inputs be addressed by the government, and extension agents assist the farmers to overcome the technical challenges they face in accessing inputs.

Keywords: agricultural policy, agro-inputs, assessment, growth enhancement support scheme, rural farmers

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Authors: Ujjwall Sai Sunder Uppuluri

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Group theory is a powerful tool that researchers can use to provide a structural foundation for their Agent Based Models. These Agent Based models are argued by this paper to be the future of the Social Science Disciplines. More specifically, researchers can use them to apply evolutionary theory to the study of complex social systems. This paper illustrates one such example of how theoretically an Agent Based Model can be formulated from the application of Group Theory, Systems Dynamics, and Evolutionary Biology to analyze the strategies pursued by states to mitigate risk and maximize usage of resources to achieve the objective of economic growth. This example can be applied to other social phenomena and this makes group theory so useful to the analysis of complex systems, because the theory provides the mathematical formulaic proof for validating the complex system models that researchers build and this will be discussed by the paper. The aim of this research, is to also provide researchers with a framework that can be used to model political entities such as states on a 3-dimensional plane. The x-axis representing resources (tangible and intangible) available to them, y the risks, and z the objective. There also exist other states with different constraints pursuing different strategies to climb the mountain. This mountain’s environment is made up of risks the state faces and resource endowments. This mountain is also layered in the sense that it has multiple peaks that must be overcome to reach the tallest peak. A state that sticks to a single strategy or pursues a strategy that is not conducive to the climbing of that specific peak it has reached is not able to continue advancement. To overcome the obstacle in the state’s path, it must innovate. Based on the definition of a group, we can categorize each state as being its own group. Each state is a closed system, one which is made up of micro level agents who have their own vectors and pursue strategies (actions) to achieve some sub objectives. The state also has an identity, the inverse being anarchy and/or inaction. Finally, the agents making up a state interact with each other through competition and collaboration to mitigate risks and achieve sub objectives that fall within the primary objective. Thus, researchers can categorize the state as an organism that reflects the sum of the output of the interactions pursued by agents at the micro level. When states compete, they employ a strategy and that state which has the better strategy (reflected by the strategies pursued by her parts) is able to out-compete her counterpart to acquire some resource, mitigate some risk or fulfil some objective. This paper will attempt to illustrate how group theory combined with evolutionary theory and systems dynamics can allow researchers to model the long run development, evolution, and growth of political entities through the use of a bottom up approach.

Keywords: complex systems, evolutionary theory, group theory, international political economy

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Authors: Avijit Dey, Antony Gomes, Subir Chandra Dasgupta

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Tea (Camellia sinensis) is the most popular beverages in the world and is ranked second after the water. Tea has been considered as a health promoting beverage since ancient times due to its health-promoting activity. Recently, immunomodulatory, anti-arthritic, antioxidant, anticancer and cardioprotective activity of tea has been established. Very few studies have demonstrated the effect of high dose of black tea on health. The aim of the present study was to evaluate the role of low & high dose of Black Tea Extract (BTE) on the different physiological parameters of mother and pups during prenatal and postnatal developmental period in the experimental rodent. BTE was orally administered in LD (50mg BTE/kg/day) and HD (100mg BTE/kg/day) except control groups of rats (n=6/group) throughout the prenatal (day 0-21) and postnatal (day 21-42) periods. During prenatal period (0, 7th, 14th, 20th days) body weight, urinary calcium, magnesium, urea and creatinine was measured. In postnatal period physical (0, 10th, 21th days) parameters of pups like body weight, cranial length, cranial diameter, neck width, tail length, craniosacral length of pups were analyzed. Liver and lungs from pups and kidney spleen, etc. from mothers were collected on day 42 for histopathological studies. The comparative urine strip and morphology of RBC was also analyzed by SEM from mothers of different groups on day 42. The level of cytokines like IL-1alpha, IL-1beta, IL-6, IL-10, TNF-alpha were analysed by enzyme-linked immunosorbent assay (ELISA) on day 0, day 20 and day 42. The body weight of LD and HD mothers were also significantly (P<0.05) less than control mothers at 20th day of pregnancy and there was also significant changes in urinary calcium, urea, creatinine. The bio morphometric analysis of pups showed significant alteration (P<0.05) in HD groups relative to control. Some histological alterations were also observed in pups and mothers. Comparative urine strip analysis and morphology of RBC showed significant changes in treated groups. LD and HD treated mothers showed an increase in proinflammatory cytokines like IL-1beta, TNF-alpha and decrease in anti-inflammatory cytokine-like IL-10 on day 20 compared to PC mothers. This study clearly indicated that high dose of BTE possesses detrimental effect on pregnant mother and the pup. Further studies are in progress to elucidate the molecular mechanism of actions. This project work has been sponsored by National Tea Research Foundation vide Project Sanction No.: 17 (305)/2013/4423 dated 11th March, 2014. All experimental protocols described in the study were approved by animal ethics committee.

Keywords: black tea extract, pregnancy, prenatal and postnatal development, inflammation

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Authors: Josie West

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This paper focuses on the conflicts and utility of Marxist Feminist frames for sex work research, drawing on findings uncovered through in-depth interviews with online sex workers, alongside critical discourse analysis of media and political commentary. It brings the critical perspective of women into digital workerism and gig economy dialogue who, despite their significant presence within online work, have been overlooked. The autonomist Marxist concept of class composition is adopted to unpack the social, technical and political composition of this often-invisible segment of the service sector. Autonomism makes visible the perspective of workers engaged in processes of mobilization and demobilizaiton. This allows researchers to find everyday forms of resistance which occur within and outside trade unions. On the other hand, Marxist feminist arguments about invisibility politics can generate unhelpful allegories about sex work as domestic labour within the reproductive sphere. Nick Srnicek’s development of Marx’s notion of infrastructure rents helps theorize experiences of unpaid labour within online sex work. Moreover, debates about anti-work politics can cause conflict among sex workers fighting for the labour movement and those rejecting the capitalist work ethic. This illuminates’ tensions caused by white privilege and differing experiences of sex work. The monopolistic and competitive nature of sex work platforms within platform capitalism, and the vulnerable position of marginalised workers within stigmatized/criminalised markets, complicates anti-work politics further. This paper is situated within the feminist sex wars and the intensely divisive question of whether sex workers are victims of the patriarchy or symbols of feminist resistance. Camgirls are shown to engage in radical tactics of resistance against their technical composition on popular sex work platforms. They also engage in creative acts of resistance through performance art, in an attempt to draw attention to stigma and anti-criminalization politics. This sector offers a fascinating window onto grassroots class-action, alongside education about ‘whorephobia.’ A case study of resistance against Only Fans, and a small workers co-operative which emerged during the pandemic, showcases how workers engage in socialist and political acts without the aid of unions. Workers are victims of neoliberalism and simultaneous adopters of neoliberal strategies of survival. The complex dynamics within unions are explored, including tensions with grass-roots resistance, financial pressures and intersecting complications of class, gender and race.

Keywords: autonomist marxism, digital labor, feminism, neoliberalism, sex work, platform capitalism

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Authors: Moien Mojabi, Aurelien Hospital, Daniel Potts, Chris Young, Albert Leung

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The wave analysis is an integral part of the hydrotechnical assessment carried out during the permitting and design phases for coastal structures, such as marinas. This analysis aims in quantifying: i) the Suitability of the coastal structure design against Small Craft Harbour wave tranquility safety criterion; ii) Potential environmental impacts of the structure (e.g., effect on wave, flow, and sediment transport); iii) Mooring and dock design and iv) Requirements set by regulatory agency’s (e.g., WSA section 11 application). While a complex three-dimensional hydrodynamic modelling approach can be applied on large-scale projects, the need for an efficient and reliable wave analysis method suitable for smaller scale marina projects was identified. As a result, Tetra Tech has developed and applied an integrated analysis framework (hereafter TT approach), which takes the advantage of the state-of-the-art numerical models while preserving the level of simplicity that fits smaller scale projects. The present paper aims to describe the TT approach and highlight the key advantages of using this integrated framework in lake marina projects. The core of this methodology is made by integrating wind, water level, bathymetry, and structure geometry data. To respond to the needs of specific projects, several add-on modules have been added to the core of the TT approach. The main advantages of this method over the simplified analytical approaches are i) Accounting for the proper physics of the lake through the modelling of the entire lake (capturing real lake geometry) instead of a simplified fetch approach; ii) Providing a more realistic representation of the waves by modelling random waves instead of monochromatic waves; iii) Modelling wave-structure interaction (e.g. wave transmission/reflection application for floating structures and piles amongst others); iv) Accounting for wave interaction with the lakebed (e.g. bottom friction, refraction, and breaking); v) Providing the inputs for flow and sediment transport assessment at the project site; vi) Taking in consideration historical and geographical variations of the wind field; and vii) Independence of the scale of the reservoir under study. Overall, in comparison with simplified analytical approaches, this integrated framework provides a more realistic and reliable estimation of wave parameters (and its spatial distribution) in lake marinas, leading to a realistic hydrotechnical assessment accessible to any project size, from the development of a new marina to marina expansion and pile replacement. Tetra Tech has successfully utilized this approach since many years in the Okanagan area.

Keywords: wave modelling, wind-wave, extreme value analysis, marina

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Authors: Elkington S. Mnguni

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Water and sanitation services in South Africa are characterized by both achievements and challenges. After the end of apartheid in 1994 the newly elected government faced the challenge of eradicating backlogs with respect to access to basic services, including water and sanitation. Capital investment made in the development of new water and sanitation infrastructure to provide basic services to previously disadvantaged communities has grown, to a certain extent, at the expense of investment in the operation and maintenance of new and existing infrastructure. Challenges resulting from aging infrastructure and poor plant performance highlight the need for investing in the maintenance, rehabilitation, and replacement of existing infrastructure to optimize the return on investment. Advanced water infrastructure asset management (IAM) is key to achieving adequate levels of service, particularly with regard to reliable and high quality drinking water supply, prevention of urban flooding, efficient use of natural resources and prevention of pollution and associated risks. Against this backdrop, this paper presents an appraisal of water and sanitation IAM systems in South Africa’s three utilities, being metropolitan cities in the Gauteng Province. About a quarter of the national population lives in the three rapidly urbanizing cities of Johannesburg, Ekurhuleni and Tshwane, located in a semi-arid region. A literature review has been done and field visits to some of the utility facilities are being conducted. Semi-structured interviews will be conducted with the three utilities. The following critical factors are being analysed in terms of compliance with the national Water Services IAM Strategy (2011) and other applicable legislation: asset registers; capacity of assets; current and predicted demand; funding availability / budget allocations; plans: operation & maintenance, renewal & replacement, and risk management; no-drop status (non-revenue water levels); blue drop status (water quality); green drop status (effluent quality); and skills availability. Some of the key challenges identified in the literature review include: funding constraints, Skills shortage, and wastewater treatment plants operating beyond their design capacities. These challenges will be verified during field visits and research interviews. Gaps between literature and practice will be identified and relevant recommendations made if necessary. The objective of this study is to contribute to the resolution of the challenges brought about by the backlogs in the operation and maintenance of water and sanitation assets in the country in general, and in the three cities in particular, thus improving the sustainability thereof.

Keywords: asset management, backlogs, levels of service, sustainability, water and sanitation infrastructure

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Authors: S. Hussain, C. Grieco, M. Brosnan

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Background and Aims: Autism is a complex neurobehavioural disorder, characterised by impairments in the development of language and communication skills. The study involved a state-of-art systematic review, in addition to qualitative data analysis, to establish the evidence for social stories as an intervention strategy for autistic children. An up-to-date review of the use of digital technologies in the delivery of interventions to autistic children was also carried out; to propose the efficacy of digital technologies and the use of social stories to improve intervention outcomes for autistic children. Methods: Two student researchers reviewed a range of randomised control trials and observational studies. The aim of the review was to establish if there was adequate evidence to justify recommending social stories to autistic patients. Students devised their own search strategies to be used across a range of search engines, including Ovid-Medline, Google Scholar and PubMed. Students then critically appraised the generated literature. Additionally, qualitative data obtained from a comprehensive online questionnaire on social stories was also thematically analysed. The thematic analysis was carried out independently by each researcher, using a ‘bottom-up’ approach, meaning contributors read and analysed responses to questions and devised semantic themes from reading the responses to a given question. The researchers then placed each response into a semantic theme or sub-theme. The students then joined to discuss the merging of their theme headings. The Inter-rater reliability (IRR) was calculated before and after theme headings were merged, giving IRR for pre- and post-discussion. Lastly, the thematic analysis was assessed by a third researcher, who is a professor of psychology and the director for the ‘Centre for Applied Autism Research’ at the University of Bath. Results: A review of the literature, as well as thematic analysis of qualitative data found supporting evidence for social story use. The thematic analysis uncovered some interesting themes from the questionnaire responses, relating to the reasons why social stories were used and the factors influencing their effectiveness in each case. However, overall, the evidence for digital technologies interventions was limited, and the literature could not prove a causal link between better intervention outcomes for autistic children and the use of technologies. However, they did offer valid proposed theories for the suitability of digital technologies for autistic children. Conclusions: Overall, the review concluded that there was adequate evidence to justify advising the use of social stories with autistic children. The role of digital technologies is clearly a fast-emerging field and appears to be a promising method of intervention for autistic children; however, it should not yet be considered an evidence-based approach. The students, using this research, developed ideas on social story interventions which aim to help autistic children.

Keywords: autistic children, digital technologies, intervention, social stories

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Authors: Padma Chutoo, Elena Kulinskaya, Ilyas Bakbergenuly, Nicholas Steel, Dmitri Pchejetski

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Stroke is associated with a significant risk of morbidity and mortality. There is scarcity of research on the long-term survival after first-ever ischaemic stroke (IS) events in England with regards to effects of different medical therapies and comorbidities. The objective of this study was to model the all-cause mortality after an IS diagnosis in the adult population of England. Using a retrospective case-control design, we extracted the electronic medical records of patients born prior to or in year 1960 in England with a first-ever ischaemic stroke diagnosis from January 1986 to January 2017 within the Health and Improvement Network (THIN) database. Participants with a history of ischaemic stroke were matched to 3 controls by sex and age at diagnosis and general practice. The primary outcome was the all-cause mortality. The hazards of the all-cause mortality were estimated using a Weibull-Cox survival model which included both scale and shape effects and a shared random effect of general practice. The model included sex, birth cohort, socio-economic status, comorbidities and medical therapies. 20,250 patients with a history of IS (cases) and 55,519 controls were followed up to 30 years. From 2008 to 2015, the one-year all-cause mortality for the IS patients declined with an absolute change of -0.5%. Preventive treatments to cases increased considerably over time. These included prescriptions of statins and antihypertensives. However, prescriptions for antiplatelet drugs decreased in the routine general practice since 2010. The survival model revealed a survival benefit of antiplatelet treatment to stroke survivors with hazard ratio (HR) of 0.92 (0.90 – 0.94). IS diagnosis had significant interactions with gender and age at entry and hypertension diagnosis. IS diagnosis was associated with high risk of all-cause mortality with HR= 3.39 (3.05-3.72) for cases compared to controls. Hypertension was associated with poor survival with HR = 4.79 (4.49 - 5.09) for hypertensive cases relative to non-hypertensive controls, though the detrimental effect of hypertension has not reached significance for hypertensive controls, HR = 1.19(0.82-1.56). This study of English primary care data showed that between 2008 and 2015, the rates of prescriptions of stroke preventive treatments increased, and a short-term all-cause mortality after IS stroke declined. However, stroke resulted in poor long-term survival. Hypertension, a modifiable risk factor, was found to be associated with poor survival outcomes in IS patients. Antiplatelet drugs were found to be protective to survival. Better efforts are required to reduce the burden of stroke through health service development and primary prevention.

Keywords: general practice, hazard ratio, health improvement network (THIN), ischaemic stroke, multiple imputation, Weibull-Cox model.

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Authors: Prince S. Campbell, Janine B. Adams, Melusi Thwala, Opeoluwa Oyedele, Paula E. Melariri

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Schistosomiasis, often known as bilharzia, is a parasitic water-borne disease caused by trematode flatworms of the genus Schistosoma. Schistosomiasis infection and prevention have been found to be influenced by a range of socio-cultural risk factors, including human characteristics (e.g., gender, age, education, knowledge, attitude, and practices), as well as environmental and economic elements. Lack of awareness of the disease may also contribute to an individual's tendency to participate in behaviours or activities that heighten their susceptibility to infection. The current study assessed the community knowledge, attitude and practices (KAP) on schistosomiasis and implemented an educational intervention following pre-test interviews. A cross-sectional quasi-experimental research design was used in this quantitative study. Pre- and post-intervention interview format surveys were conducted using a structured questionnaire, targeting individuals aged 18–65 years residing within 5 km of select water bodies. The questionnaire contained 54 close-ended questions about schistosomiasis causes, transmission, and clinical symptoms and the participants were interviewed face-to-face in their homes. Data was captured on Question Pro and analyzed using Microsoft Office Excel 365 (2019) and R (version 4.3.1) software. Overall, 380 individuals completed the pre and post-intervention assessments; 194 and 185 were males (51.1%) and females (48.7%), respectively. A notable 91.3% of participants did not know about schistosomiasis in the pre-intervention phase; however, the mean post-intervention test score (9.4 ± 1.4) for knowledge among participants was higher than the pre-intervention test score (2.2 ± 2.1) indicating a good and improved knowledge of schistosomiasis among the participants. Furthermore, the paired samples t-test results demonstrated that the increase in knowledge levels was statistically significant (p<0.001). Also, the post-intervention improvement of both practice (p<0.001) and attitude (p<0.001) levels was statistically significant. A positive correlation (r=0.23, p<0.001) was found between knowledge and attitude in the pre-intervention stage. Knowledgeable participants had a more positive attitude towards obtaining medical assistance and disease prevention. Moreover, attitudes and practices correlated negatively (r=-0.13, p=0.013) post-intervention; hence, those with positive attitudes did not engage in risky water-related practices, which was the desired outcome. The educational intervention had a favourable impact on the KAP of the study population as the majority were able to recall the disease aetiology, symptoms, transmission pattern, and preventative measures three months post-intervention. Nevertheless, previous research has suggested that participants were unable to recall information about the disease following the intervention. Consequently, research should prioritize behavioural modification strategies that may result in a more persistent outcome in terms of the participants' knowledge, which could ultimately contribute to the development of long-term positive attitudes and practices.

Keywords: educational intervention, knowledge, attitudes and practices, schistosomiasis

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Authors: Anastasios Georgoulas, Manolia Andredaki, Marco Marengo

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The present paper investigates the hydrodynamics and heat transfer characteristics of slug-plug flows under saturated flow boiling conditions within circular micro-channels. Numerical simulations are carried out, using an enhanced version of the open-source CFD-based solver ‘interFoam’ of OpenFOAM CFD Toolbox. The proposed user-defined solver is based in the Volume Of Fluid (VOF) method for interface advection, and the mentioned enhancements include the implementation of a smoothing process for spurious current reduction, the coupling with heat transfer and phase change as well as the incorporation of conjugate heat transfer to account for transient solid conduction. In all of the considered cases in the present paper, a single phase simulation is initially conducted until a quasi-steady state is reached with respect to the hydrodynamic and thermal boundary layer development. Then, a predefined and constant frequency of successive vapour bubbles is patched upstream at a certain distance from the channel inlet. The proposed numerical simulation set-up can capture the main hydrodynamic and heat transfer characteristics of slug-plug flow regimes within circular micro-channels. In more detail, the present investigation is focused on exploring the interaction between subsequent vapour slugs with respect to their generation frequency, the hydrodynamic characteristics of the liquid film between the generated vapour slugs and the channel wall as well as of the liquid plug between two subsequent vapour slugs. The proposed investigation is carried out for the 3 different working fluids and three different values of applied heat flux in the heated part of the considered microchannel. The post-processing and analysis of the results indicate that the dynamics of the evolving bubbles in each case are influenced by both the upstream and downstream bubbles in the generated sequence. In each case a slip velocity between the vapour bubbles and the liquid slugs is evident. In most cases interfacial waves appear close to the bubble tail that significantly reduce the liquid film thickness. Finally, in accordance with previous investigations vortices that are identified in the liquid slugs between two subsequent vapour bubbles can significantly enhance the convection heat transfer between the liquid regions and the heated channel walls. The overall results of the present investigation can be used to enhance the present understanding by providing better insight of the complex, underpinned heat transfer mechanisms in saturated boiling within micro-channels in the slug-plug flow regime.

Keywords: slug-plug flow regime, micro-channels, VOF method, OpenFOAM

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Authors: Anirudh Lahiri

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

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

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Authors: Vinu Viswanath, Lawrence Dsouza, Ugo Ravon

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Syngas typically and intermediary gas product has a wide range of application of producing various chemical products, such as mixed alcohols, hydrogen, ammonia, Fischer-Tropsch products methanol, ethanol, aldehydes, alcohols, etc. There are several technologies available for the syngas production. An alternative to the conventional processes an attractive route of utilizing carbon dioxide and methane in equimolar ratio to generate syngas of ratio close to one has been developed which is also termed as Dry Reforming of Methane technology. It also gives the privilege to utilize the greenhouse gases like CO2 and CH4. The dry reforming process is highly endothermic, and indeed, ΔG becomes negative if the temperature is higher than 900K and practically, the reaction occurs at 1000-1100K. At this temperature, the sintering of the metal particle is happening that deactivate the catalyst. However, by using this strategy, the methane is just partially oxidized, and some cokes deposition occurs that causing the catalyst deactivation. The current research work was focused to mitigate the main challenges of dry reforming process such coke deposition, and metal sintering at high temperature.To achieve these objectives, we employed three different strategies of catalyst development. 1) Use of bulk catalysts such as olivine and pyrochlore type materials. 2) Use of metal doped support materials, like spinel and clay type material. 3) Use of core-shell model catalyst. In this approach, a thin layer (shell) of redox metal oxide is deposited over the MgAl2O4 /Al2O3 based support material (core). For the core-shell approach, an active metal is been deposited on the surface of the shell. The shell structure formed is a doped metal oxide that can undergo reduction and oxidation reactions (redox), and the core is an alkaline earth aluminate having a high affinity towards carbon dioxide. In the case of metal-doped support catalyst, the enhanced redox properties of doped CeO2 oxide and CO2 affinity property of alkaline earth aluminates collectively helps to overcome coke formation. For all of the mentioned three strategies, a systematic screening of the metals is carried out to optimize the efficiency of the catalyst. To evaluate the performance of them, the activity and stability test were carried out under reaction conditions of temperature ranging from 650 to 850 ̊C and an operating pressure ranging from 1 to 20 bar. The result generated infers that the core-shell model catalyst showed high activity and better stable DR catalysts under atmospheric as well as high-pressure conditions. In this presentation, we will show the results related to the strategy.

Keywords: carbon dioxide, dry reforming, supports, core shell catalyst

Procedia PDF Downloads 179

Authors: Osman Turkoglu, Alvin Estilo, Ritu Gupta, Liliam Pineda-Salgado, Rajesh Pandey

Abstract:

Background: Hepatotoxicity can be linked to a variety of clinical symptoms and histopathological signs, posing a great challenge in the surveillance of suspected drug-induced liver injury (DILI) cases in the safety database. Additionally, the majority of such cases are rare, idiosyncratic, highly unpredictable, and tend to demonstrate unique individual susceptibility; these qualities, in turn, lend to a pharmacovigilance monitoring process that is often tedious and time-consuming. Objective: Develop a multifactorial algorithm to assist pharmacovigilance physicians in identifying high-risk hepatotoxicity cases associated with DILI from the sponsor’s safety database (Argus). Methods: Multifactorial selection criteria were established using Structured Query Language (SQL) and the TIBCO Spotfire® visualization tool, via a combination of word fragments, wildcard strings, and mathematical constructs, based on Hy’s law criteria and pattern of injury (R-value). These criteria excluded non-eligible cases from monthly line listings mined from the Argus safety database. The capabilities and limitations of these criteria were verified by comparing a manual review of all monthly cases with system-generated monthly listings over six months. Results: On an average, over a period of six months, the algorithm accurately identified 92% of DILI cases meeting established criteria. The automated process easily compared liver enzyme elevations with baseline values, reducing the screening time to under 15 minutes as opposed to multiple hours exhausted using a cognitively laborious, manual process. Limitations of the algorithm include its inability to identify cases associated with non-standard laboratory tests, naming conventions, and/or incomplete/incorrectly entered laboratory values. Conclusions: The newly developed multifactorial algorithm proved to be extremely useful in detecting potential DILI cases, while heightening the vigilance of the drug safety department. Additionally, the application of this algorithm may be useful in identifying a potential signal for DILI in drugs not yet known to cause liver injury (e.g., drugs in the initial phases of development). This algorithm also carries the potential for universal application, due to its product-agnostic data and keyword mining features. Plans for the tool include improving it into a fully automated application, thereby completely eliminating a manual screening process.

Keywords: automation, drug-induced liver injury, pharmacovigilance, post-marketing

Procedia PDF Downloads 152

Authors: Marcela De Oliveira, Marina P. Da Silva, Fernando C. G. Da Rocha, Jorge M. Santos, Jaime S. Cardoso, Paulo N. Lisboa-Filho

Abstract:

Multiple Sclerosis (MS) is an immune-mediated disease of the central nervous system characterized by neurodegeneration, inflammation, demyelination, and axonal loss. Magnetic resonance imaging (MRI), due to the richness in the information details provided, is the gold standard exam for diagnosis and follow-up of neurodegenerative diseases, such as MS. Brain atrophy, the gradual loss of brain volume, is quite extensive in multiple sclerosis, nearly 0.5-1.35% per year, far off the limits of normal aging. Thus, the brain volume quantification becomes an essential task for future analysis of the occurrence atrophy. The analysis of MRI has become a tedious and complex task for clinicians, who have to manually extract important information. This manual analysis is prone to errors and is time consuming due to various intra- and inter-operator variability. Nowadays, computerized methods for MRI segmentation have been extensively used to assist doctors in quantitative analyzes for disease diagnosis and monitoring. Thus, the purpose of this work was to evaluate the brain volume in MRI of MS patients. We used MRI scans with 30 slices of the five patients diagnosed with multiple sclerosis according to the McDonald criteria. The computational methods for the analysis of images were carried out in two steps: segmentation of the brain and brain volume quantification. The first image processing step was to perform brain extraction by skull stripping from the original image. In the skull stripper for MRI images of the brain, the algorithm registers a grayscale atlas image to the grayscale patient image. The associated brain mask is propagated using the registration transformation. Then this mask is eroded and used for a refined brain extraction based on level-sets (edge of the brain-skull border with dedicated expansion, curvature, and advection terms). In the second step, the brain volume quantification was performed by counting the voxels belonging to the segmentation mask and converted in cc. We observed an average brain volume of 1469.5 cc. We concluded that the automatic method applied in this work can be used for the brain extraction process and brain volume quantification in MRI. The development and use of computer programs can contribute to assist health professionals in the diagnosis and monitoring of patients with neurodegenerative diseases. In future works, we expect to implement more automated methods for the assessment of cerebral atrophy and brain lesions quantification, including machine-learning approaches. Acknowledgements: This work was supported by a grant from Brazilian agency Fundação de Amparo à Pesquisa do Estado de São Paulo (number 2019/16362-5).

Keywords: brain volume, magnetic resonance imaging, multiple sclerosis, skull stripper

Procedia PDF Downloads 146

Authors: Marine Regnier, Pascal Bost, Matthieu Horgnies

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Some of the problems to be solved for the concrete industry are linked to the use of low-reactivity cement, the hardening of concrete under cold-weather and the manufacture of pre-casted concrete without costly heating step. The development of these applications needs to accelerate the hydration kinetics, in order to decrease the setting time and to obtain significant compressive strengths as soon as possible. The mechanisms enhancing the hydration kinetics of alite or Portland cement (e.g. the creation of nucleation sites) were already studied in literature (e.g. by using distinct additions such as titanium dioxide nanoparticles, calcium carbonate fillers, water-soluble polymers, C-S-H, etc.). However, the goal of this study was to establish a clear ranking of the efficiency of several types of additions by using a robust and reproducible methodology based on isothermal calorimetry (performed at 20°C). The cement was a CEM I 52.5N PM-ES (Blaine fineness of 455 m²/kg). To ensure the reproducibility of the experiments and avoid any decrease of the reactivity before use, the cement was stored in waterproof and sealed bags to avoid any contact with moisture and carbon dioxide. The experiments were performed on Portland cement pastes by using a water-to-cement ratio of 0.45, and incorporating different compounds (industrially available or laboratory-synthesized) that were selected according to their main composition and their specific surface area (SSA, calculated using the Brunauer-Emmett-Teller (BET) model and nitrogen adsorption isotherms performed at 77K). The intrinsic effects of (i) dry powders (e.g. fumed silica, activated charcoal, nano-precipitates of calcium carbonate, afwillite germs, nanoparticles of iron and iron oxides , etc.), and (ii) aqueous solutions (e.g. containing calcium chloride, hydrated Portland cement or Master X-SEED 100, etc.) were investigated. The influence of the amount of addition, calculated relatively to the dry extract of each addition compared to cement (and by conserving the same water-to-cement ratio) was also studied. The results demonstrated that the X-SEED®, the hydrated calcium nitrate, the calcium chloride (and, at a minor level, a solution of hydrated Portland cement) were able to accelerate the hydration kinetics of Portland cement, even at low concentration (e.g. 1%wt. of dry extract compared to cement). By using higher rates of additions, the fumed silica, the precipitated calcium carbonate and the titanium dioxide can also accelerate the hydration. In the case of the nano-precipitates of calcium carbonate, a correlation was established between the SSA and the accelerating effect. On the contrary, the nanoparticles of iron or iron oxides, the activated charcoal and the dried crystallised hydrates did not show any accelerating effect. Future experiments will be scheduled to establish the ranking of these additions, in terms of accelerating effect, by using low-reactivity cements and other water to cement ratios.

Keywords: acceleration, hydration kinetics, isothermal calorimetry, Portland cement

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Authors: Melese Wondatir

Abstract:

Flooding ranks among the most destructive natural disasters, impacting millions of individuals globally and resulting in substantial economic, social, and environmental repercussions. This study's objective was to create a comprehensive model that assesses the Nile River basin's susceptibility to flood damage and improves existing flood risk management strategies. Authorities responsible for enacting policies and implementing measures may benefit from this research to acquire essential information about the flood, including its scope and susceptible areas. The identification of severe flood damage locations and efficient mitigation techniques were made possible by the use of geospatial data. Slope, elevation, distance from the river, drainage density, topographic witness index, rainfall intensity, distance from road, NDVI, soil type, and land use type were all used throughout the study to determine the vulnerability of flood damage. Ranking elements according to their significance in predicting flood damage risk was done using the Analytic Hierarchy Process (AHP) and geospatial approaches. The analysis finds that the most important parameters determining the region's vulnerability are distance from the river, topographic witness index, rainfall, and elevation, respectively. The consistency ratio (CR) value obtained in this case is 0.000866 (<0.1), which signifies the acceptance of the derived weights. Furthermore, 10.84m2, 83331.14m2, 476987.15m2, 24247.29m2, and 15.83m2 of the region show varying degrees of vulnerability to flooding—very low, low, medium, high, and very high, respectively. Due to their close proximity to the river, the northern-western regions of the Nile River basin—especially those that are close to Sudanese cities like Khartoum—are more vulnerable to flood damage, according to the research findings. Furthermore, the AUC ROC curve demonstrates that the categorized vulnerability map achieves an accuracy rate of 91.0% based on 117 sample points. By putting into practice strategies to address the topographic witness index, rainfall patterns, elevation fluctuations, and distance from the river, vulnerable settlements in the area can be protected, and the impact of future flood occurrences can be greatly reduced. Furthermore, the research findings highlight the urgent requirement for infrastructure development and effective flood management strategies in the northern and western regions of the Nile River basin, particularly in proximity to major towns such as Khartoum. Overall, the study recommends prioritizing high-risk locations and developing a complete flood risk management plan based on the vulnerability map.

Keywords: analytic hierarchy process, Blue Nile Basin, geospatial techniques, flood vulnerability, multi-criteria decision making

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Authors: Aziz Ikhlef

Abstract:

Most of multi-slices CT scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80kVp and 140kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

Procedia PDF Downloads 271

Authors: Farid Khosravikia, Patricia Clayton

Abstract:

The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

Procedia PDF Downloads 106

Authors: Skyler Kim

Abstract:

An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

Procedia PDF Downloads 187

Authors: Marita Pigłowska, Beata Kurc, Paweł Daszkiewicz

Abstract:

Railway vehicles are divided into two groups: traction (powered) vehicles and wagons. The traction vehicles include locomotives (line and shunting), railcars (sometimes referred to as railbuses), and multiple units (electric and diesel), consisting of several or a dozen carriages. In vehicles with diesel traction, fuel energy (petrol, diesel, or compressed gas) is converted into mechanical energy directly in the internal combustion engine or via electricity. In the latter case, the combustion engine generator produces electricity that is then used to drive the vehicle (diesel-electric drive or electric transmission). In Poland, such a solution dominates both in heavy linear and shunting locomotives. The classic diesel drive is available for the lightest shunting locomotives, railcars, and passenger diesel multiple units. Vehicles with electric traction do not have their own source of energy -they use pantographs to obtain electricity from the traction network. To determine the competitiveness of the hydrogen propulsion system, it is essential to understand how it works. The basic elements of the construction of a railway vehicle drive system that uses hydrogen as a source of traction force are fuel cells, batteries, fuel tanks, traction motors as well as main and auxiliary converters. The compressed hydrogen is stored in tanks usually located on the roof of the vehicle. This resource is supplemented with the use of specialized infrastructure while the vehicle is stationary. Hydrogen is supplied to the fuel cell, where it oxidizes. The effect of this chemical reaction is electricity and water (in two forms -liquid and water vapor). Electricity is stored in batteries (so far, lithium-ion batteries are used). Electricity stored in this way is used to drive traction motors and supply onboard equipment. The current generated by the fuel cell passes through the main converter, whose task is to adjust it to the values required by the consumers, i.e., batteries and the traction motor. The work will attempt to construct a fuel cell with unique electrodes. This research is a trend that connects industry with science. The first goal will be to obtain hydrogen on a large scale in tube furnaces, to thoroughly analyze the obtained structures (IR), and to apply the method in fuel cells. The second goal is to create low-energy energy storage and distribution station for hydrogen and electric vehicles. The scope of the research includes obtaining a carbon variety and obtaining oxide systems on a large scale using a tubular furnace and then supplying vehicles. Acknowledgments: This work is supported by the Polish Ministry of Science and Education, project "The best of the best! 4.0", number 0911/MNSW/4968 – M.P. and grant 0911/SBAD/2102—B.K.

Keywords: railway, hydrogen, fuel cells, hybrid vehicles

Procedia PDF Downloads 189

Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

Abstract:

Large eddy simulation (LES) has been extensively used in the investigation of turbulence. LES calculates the grid-resolved large-scale motions and leaves small scales modeled by sublfilterscale (SFS) models. Among the existing SFS models, the deconvolution model has been used successfully in the LES of the engineering flows and geophysical flows. Despite the wide application of deconvolution models, the effects of subfilter scale dynamics and filter anisotropy on the accuracy of SFS modeling have not been investigated in depth. The results of LES are highly sensitive to the selection of filters and the anisotropy of the grid, which has been overlooked in previous research. In the current study, two critical aspects of LES are investigated. Firstly, we analyze the influence of sub-filter scale (SFS) dynamics on the accuracy of direct deconvolution models (DDM) at varying filter-to-grid ratios (FGR) in isotropic turbulence. An array of invertible filters are employed, encompassing Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The significance of FGR becomes evident, as it acts as a pivotal factor in error control for precise SFS stress prediction. When FGR is set to 1, the DDM models cannot accurately reconstruct the SFS stress due to the insufficient resolution of SFS dynamics. Notably, prediction capabilities are enhanced at an FGR of 2, resulting in accurate SFS stress reconstruction, except for cases involving Helmholtz I and II filters. A remarkable precision close to 100% is achieved at an FGR of 4 for all DDM models. Additionally, the further exploration extends to the filter anisotropy to address its impact on the SFS dynamics and LES accuracy. By employing dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with the anisotropic filter, aspect ratios (AR) ranging from 1 to 16 in LES filters are evaluated. The findings highlight the DDM's proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. High correlation coefficients exceeding 90% are observed in the a priori study for the DDM's reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as lter anisotropy increases. In the a posteriori studies, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, encompassing velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strain-rate tensors, and SFS stress. It is observed that as filter anisotropy intensify, the results of DSM and DMM become worse, while the DDM continues to deliver satisfactory results across all filter-anisotropy scenarios. The findings emphasize the DDM framework's potential as a valuable tool for advancing the development of sophisticated SFS models for LES of turbulence.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

Procedia PDF Downloads 75

Authors: Ritika Chaturvedi

Abstract:

Introduction: Sexual objectification, characterized by the reduction of an individual to a mere object of sexual desire, remains a pervasive societal issue with profound repercussions on individual well-being. Such experiences, often rooted in systemic and cultural norms, have long-lasting implications for mental and emotional health. This study aims to explore the intricate relationship between experiences of sexual objectification and insidious trauma, further investigating the potential moderating effects of overexcitability as proposed by Dabrowski's theory of positive disintegration. Methodology: The research involved a comprehensive cohort of 204 women, spanning ages from 18 to 65 years. Participants were tasked with completing self-administered questionnaires designed to capture their experiences with sexual objectification. Additionally, the questionnaire assessed symptoms indicative of insidious trauma and explored overexcitability across five distinct domains: emotional, intellectual, psychomotor, sensory, and imaginational. Employing advanced statistical techniques, including multiple regression and moderation analysis, the study sought to decipher the intricate interplay among these variables. Findings: The study's results revealed a compelling positive correlation between experiences of sexual objectification and the onset of symptoms indicative of insidious trauma. This correlation underscores the profound and detrimental effects of sexual objectification on an individual's psychological well-being. Interestingly, the moderation analyses introduced a nuanced understanding, highlighting the differential roles of various overexcitability. Specifically, emotional, intellectual, and sensual overexcitability were found to exacerbate trauma symptomatology. In contrast, psychomotor overexcitability emerged as a protective factor, demonstrating a mitigating influence on the relationship between sexual objectification and trauma. Implications: The study's findings hold significant implications for a diverse array of stakeholders, encompassing mental health practitioners, educators, policymakers, and advocacy groups. The identified moderating effects of overexcitability emphasize the need for tailored interventions that consider individual differences in coping and resilience mechanisms. By recognizing the pivotal role of overexcitability in modulating the traumatic consequences of sexual objectification, this research advocates for the development of more nuanced and targeted support frameworks. Moreover, the study underscores the importance of continued research endeavors to unravel the intricate mechanisms and dynamics underpinning these relationships. Such endeavors are crucial for fostering the evolution of informed, evidence-based interventions and strategies aimed at mitigating the adverse effects of sexual objectification and promoting holistic well-being.

Keywords: sexual objectification, insidious trauma, emotional overexcitability, intellectual overexcitability, sensual overexcitability, psychomotor overexcitability, imaginational overexcitability

Procedia PDF Downloads 53

Authors: Charly Julien Nyobe, Eric Jacquelin, Denis Brizard, Alexy Mercier

Abstract:

The performance of road side safety barriers depends largely on the dynamic interactions between post and soil. These interactions play a key role in the response of barriers to crash testing. In the literature, soil-post interaction is modeled in crash test simulations using three approaches. Many researchers have initially used the finite element approach, in which the post is embedded in a continuum soil modelled by solid finite elements. This method represents a more comprehensive and detailed approach, employing a mesh-based continuum to model the soil’s behavior and its interaction with the post. Although this method takes all soil properties into account, it is nevertheless very costly in terms of simulation time. In the second approach, all the points of the post located at a predefined depth are fixed. Although this approach reduces CPU computing time, it overestimates soil-post stiffness. The third approach involves modeling the post as a beam supported by a set of nonlinear springs in the horizontal directions. For support in the vertical direction, the posts were constrained at a node at ground level. This approach is less costly, but the literature does not provide a simple procedure to determine the constitutive law of the springs The aim of this study is to propose a simple and low-cost procedure to obtain the constitutive law of nonlinear springs that model the soil-post interaction. To achieve this objective, we will first present a procedure to obtain the constitutive law of nonlinear springs thanks to the simulation of a soil compression test. The test consists in compressing the soil contained in the tank by a rigid solid, up to a vertical displacement of 200 mm. The resultant force exerted by the ground on the rigid solid and its vertical displacement are extracted and, a force-displacement curve was determined. The proposed procedure for replacing the soil with springs must be tested against a reference model. The reference model consists of a wooden post embedded into the ground and impacted with an impactor. Two simplified models with springs are studied. In the first model, called Kh-Kv model, the springs are attached to the post in the horizontal and vertical directions. The second Kh model is the one described in the literature. The two simplified models are compared with the reference model according to several criteria: the displacement of a node located at the top of the post in vertical and horizontal directions; displacement of the post's center of rotation and impactor velocity. The results given by both simplified models are very close to the reference model results. It is noticeable that the Kh-Kv model is slightly better than the Kh model. Further, the former model is more interesting than the latter as it involves less arbitrary conditions. The simplified models also reduce the simulation time by a factor 4. The Kh-Kv model can therefore be used as a reliable tool to represent the soil-post interaction in a future research and development of road safety barriers.

Keywords: crash tests, nonlinear springs, soil-post interaction modeling, constitutive law

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Authors: Shi-Bo Feng, Sheng-Jie Zhang, Jin Zhou

Abstract:

The relationship between microbial diversity and algal bloom has received considerable attention for decades. Microbes undoubtedly affect annual bloom events and impact the physiology of both partners, as well as shape ecosystem diversity. However, knowledge about interactions and network correlations among broader-spectrum microbes that lead to the dynamics in a complete bloom cycle are limited. In this study, pyrosequencing and network approaches simultaneously assessed the associate patterns among bacteria, archaea, and microeukaryotes in surface water and sediments in response to a natural dinoflagellate (Alexandrium sp.) bloom. In surface water, among the bacterial community, Gamma-Proteobacteria and Bacteroidetes dominated in the initial bloom stage, while Alpha-Proteobacteria, Cyanobacteria, and Actinobacteria become the most abundant taxa during the post-stage. In the archaea biosphere, it clustered predominantly with Methanogenic members in the early pre-bloom period while the majority of species identified in the later-bloom stage were ammonia-oxidizing archaea and Halobacteriales. In eukaryotes, dinoflagellate (Alexandrium sp.) was dominated in the onset stage, whereas multiply species (such as microzooplankton, diatom, green algae, and rotifera) coexistence in bloom collapse stag. In sediments, the microbial species biomass and richness are much higher than the water body. Only Flavobacteriales and Rhodobacterales showed a slight response to bloom stages. Unlike the bacteria, there are small fluctuations of archaeal and eukaryotic structure in the sediment. The network analyses among the inter-specific associations show that bacteria (Alteromonadaceae, Oceanospirillaceae, Cryomorphaceae, and Piscirickettsiaceae) and some zooplankton (Mediophyceae, Mamiellophyceae, Dictyochophyceae and Trebouxiophyceae) have a stronger impact on the structuring of phytoplankton communities than archaeal effects. The changes in population were also significantly shaped by water temperature and substrate availability (N & P resources). The results suggest that clades are specialized at different time-periods and that the pre-bloom succession was mainly a bottom-up controlled, and late-bloom period was controlled by top-down patterns. Additionally, phytoplankton and prokaryotic communities correlated better with each other, which indicate interactions among microorganisms are critical in controlling plankton dynamics and fates. Our results supplied a wider view (temporal and spatial scales) to understand the microbial ecological responses and their network association during algal blooming. It gives us a potential multidisciplinary explanation for algal-microbe interaction and helps us beyond the traditional view linked to patterns of algal bloom initiation, development, decline, and biogeochemistry.

Keywords: microbial community, harmful algal bloom, ecological process, network

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Authors: Natalia Buderatskaya, Igor Ilyin, Julia Gontar, Sergey Lavrynenko, Olga Parnitskaya, Ekaterina Ilyina, Eduard Kapustin, Yana Lakhno

Abstract:

Introduction: It is known that cryopreservation of oocytes has peculiar features due to the complex structure of the oocyte. One of the most important features is that mature oocytes contain meiotic division spindle which is very sensitive even to the slightest variation in temperature. Thus, the main objective of this study is to analyse the resulting euploid embryos obtained from thawed oocytes in comparison with the data of preimplantation genetic screening (PGS) in fresh embryo cycles. Material and Methods: The study was conducted at 'Medical Centre IGR' from January to July 2016. Data were analysed for 908 donor oocytes obtained in 67 cycles of assisted reproductive technologies (ART), of which 693 oocytes were used in the 51 'fresh' cycles (group A), and 215 oocytes - 16 ART programs with vitrification female gametes (group B). The average age of donors in the groups match 27.3±2.9 and 27.8±6.6 years. Stimulation of superovulation was conducted the standard way. Vitrification was performed in 1-2 hours after transvaginal puncture and thawing of oocytes were carried out in accordance with the standard protocol of Cryotech (Japan). Manipulation ICSI was performed 4-5 hours after transvaginal follicle puncture for fresh oocytes, or after defrosting - for vitrified female gametes. For the PGS, an embryonic biopsy was done on the third or on the fifth day after fertilization. Diagnostic procedures were performed using fluorescence in situ hybridization with the study of such chromosomes as 13, 16, 18, 21, 22, X, Y. Only morphologically quality blastocysts were used for the transfer, the estimation of which corresponded to the Gardner criteria. The statistical hypotheses were done using the criteria t, x^2 at a significance levels p<0.05, p<0.01, p<0.001. Results: The mean number of mature oocytes per cycle in group A was 13.58±6.65 and in group B - 13.44±6.68 oocytes for patient. The survival of oocytes after thawing totaled 95.3% (n=205), which indicates a highly effective quality of performed vitrification. The proportion of zygotes in the group A corresponded to 91.1%(n=631), in the group B – 80.5%(n=165), which shows statistically significant difference between the groups (p<0.001) and explained by non-viable oocytes elimination after vitrification. This is confirmed by the fact that on the fifth day of embryos development a statistically significant difference in the number of blastocysts was absent (p>0.05), and constituted respectively 61.6%(n=389) and 63.0%(n=104) in the groups. For the PGS performing 250 embryos analyzed in the group A and 72 embryos - in the group B. The results showed that euploidy in the studied chromosomes were 40.0%(n=100) embryos in the group A and 41.7% (n=30) - in the group B, which shows no statistical significant difference (p>0.05). The indicators of clinical pregnancies in the groups amounted to 64.7% (22 pregnancies per 34 embryo transfers) and 61.5% (8 pregnancies per 13 embryo transfers) respectively, and also had no significant difference between the groups (p>0.05). Conclusions: The results showed that the vitrification does not affect the resulting euploid embryos in assisted reproductive technologies and are not reflected in their morphological characteristics in ART programs.

Keywords: euploid embryos, preimplantation genetic screening, thawing oocytes, vitrification

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Authors: S. Wesebaum, S. Willeke

Abstract:

Production companies are faced with an increasingly turbulent business environment, which demands very high production volumes- and delivery date flexibility. If a decoupling by storage stages is not possible (e.g. at a contract manufacturing company) or undesirable from a logistical point of view, load scattering effects the production processes. ‘Load’ characterizes timing and quantity incidence of production orders (e.g. in work content hours) to workstations in the production, which results in specific capacity requirements. Insufficient coordination between load (demand capacity) and capacity supply results in heavy load scattering, which can be described by deviations and uncertainties in the input behavior of a capacity unit. In order to respond to fluctuating loads, companies try to implement consistent and realizable input behavior using the capacity supply available. For example, a uniform and high level of equipment capacity utilization keeps production costs down. In contrast, strong load scattering at workstations leads to performance loss or disproportionately fluctuating WIP, whereby the logistics objectives are affected negatively. Options for reducing load scattering are e.g. shifting the start and end dates of orders, batch splitting and outsourcing of operations or shifting to other workstations. This leads to an adjustment of load to capacity supply, and thus to a reduction of load scattering. If the adaptation of load to capacity cannot be satisfied completely, possibly flexible capacity must be used to ensure that the performance of a workstation does not decrease for a given load. Where the use of flexible capacities normally raises costs, an adjustment of load to capacity supply reduces load scattering and, in consequence, costs. In the literature you mostly find qualitative statements for describing load scattering. Quantitative evaluation methods that describe load mathematically are rare. In this article the authors discuss existing approaches for calculating load scattering and their various disadvantages such as lack of opportunity for normalization. These approaches are the basis for the development of our mathematical quantification approach for describing load scattering that compensates the disadvantages of the current quantification approaches. After presenting our mathematical quantification approach, the method of batch splitting will be described. Batch splitting allows the adaptation of load to capacity to reduce load scattering. After describing the method, it will be explicitly analyzed in the context of the logistic curve theory by Nyhuis using the stretch factor α1 in order to evaluate the impact of the method of batch splitting on load scattering and on logistic curves. The conclusion of this article will be to show how the methods and approaches presented can help companies in a turbulent environment to quantify the occurring work load scattering accurately and apply an efficient method for adjusting work load to capacity supply. In this way, the achievements of the logistical objectives are increased without causing additional costs.

Keywords: batch splitting, production logistics, production planning and control, quantification, load scattering

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Authors: Aaron Akinloye

Abstract:

this research focuses on the impact of jungle justice on the emotional health challenges experienced by residents in the Lagos metropolitan city in Nigeria. Jungle justice refers to the practice of individuals taking the law into their own hands and administering punishment without proper legal procedures. The aim of this study is to investigate the influence of jungle justice on the emotional challenges faced by residents in Lagos. The specific objectives of the study are to examine the effects of jungle justice on trauma, pressure, fear, and depression among residents. The study adopts a descriptive survey research design and uses a questionnaire as the research instrument. The population of the study consisted of residents in the three senatorial districts that make up Lagos State. A simple random sampling technique was used to select two Local Government Areas (Yaba and Shomolu) from each of the three senatorial districts of Lagos State. Also, a simple random sampling technique was used to select fifty (50) residents from each of the chosen Local Government Areas to make three hundred (300) residents that formed the sample of the study. Accidental sampling technique is employed to select a sample of 300 residents. Data on the variables of interest is collected using a self-developed questionnaire. The research instrument undergoes validation through face, content, and construct validation processes. The reliability coefficient of the instrument is found to be 0.84. The study reveals that jungle justice significantly influences trauma, pressure, fear, and depression among residents in Lagos metropolitan city. The statistical analysis shows significant relationships between jungle justice and these emotional health challenges (df (298) t= 2.33, p< 0.05; df (298) t= 2.16, p< 0.05; df (298) t= 2.20, p< 0.05; df (298) t= 2.14, p< 0.05). This study contributes to the literature by highlighting the negative effects of jungle justice on the emotional well-being of residents. It emphasizes the importance of addressing this issue and implementing measures to prevent such vigilante actions. Data is collected through the administration of the self-developed questionnaire to the selected residents. The collected data is then analyzed using inferential statistics, specifically mean analysis, to examine the relationships between jungle justice and the emotional health challenges experienced by the residents. The main question addressed in this study is how jungle justice affects the emotional health challenges faced by residents in Lagos metropolitan city. Conclusion: The study concludes that jungle justice has a significant influence on trauma, pressure, fear, and depression among residents. To address this issue, recommendations are made, including the implementation of comprehensive awareness campaigns, improvement of law enforcement agencies, development of support systems for victims, and revision of the legal framework to effectively address jungle justice. Overall, this research contributes to the understanding of the consequences of jungle justice and provides recommendations for intervention to protect the emotional well-being of residents in Lagos metropolitan city.

Keywords: jungle justice, emotional health, depression, anger

Procedia PDF Downloads 78