Search results for: traditional physical therapy program

Authors: Wei Ji

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This study was conducted in the Kansas City metropolitan area of the United States, which has experienced significant urban sprawling in recent decades. The remote sensing of land cover changes in this area spanned over four decades from 1972 through 2010. The project was implemented in two stages: the first stage focused on detection of long-term trends of urban land cover change, while the second one examined how to detect the coupled effects of human impact and climate change on urban landscapes. For the first-stage study, six Landsat images were used with a time interval of about five years for the period from 1972 through 2001. Four major land cover types, built-up land, forestland, non-forest vegetation land, and surface water, were mapped using supervised image classification techniques. The study found that over the three decades the built-up lands in the study area were more than doubled, which was mainly at the expense of non-forest vegetation lands. Surprisingly and interestingly, the area also saw a significant gain in surface water coverage. This observation raised questions: How have human activities and precipitation variation jointly impacted surface water cover during recent decades? How can we detect such coupled impacts through remote sensing analysis? These questions led to the second stage of the study, in which we designed and developed approaches to detecting fine-scale surface waters and analyzing coupled effects of human impact and precipitation variation on the waters. To effectively detect urban landscape changes that might be jointly shaped by precipitation variation, our study proposed “urban wetscapes” (loosely-defined urban wetlands) as a new indicator for remote sensing detection. The study examined whether urban wetscape dynamics was a sensitive indicator of the coupled effects of the two driving forces. To better detect this indicator, a rule-based classification algorithm was developed to identify fine-scale, hidden wetlands that could not be appropriately detected based on their spectral differentiability by a traditional image classification. Three SPOT images for years 1992, 2008, and 2010, respectively were classified with this technique to generate the four types of land cover as described above. The spatial analyses of remotely-sensed wetscape changes were implemented at the scales of metropolitan, watershed, and sub-watershed, as well as based on the size of surface water bodies in order to accurately reveal urban wetscape change trends in relation to the driving forces. The study identified that urban wetscape dynamics varied in trend and magnitude from the metropolitan, watersheds, to sub-watersheds in response to human impacts at different scales. The study also found that increased precipitation in the region in the past decades swelled larger wetlands in particular while generally smaller wetlands decreased mainly due to human development activities. These results confirm that wetscape dynamics can effectively reveal the coupled effects of human impact and climate change on urban landscapes. As such, remote sensing of this indicator provides new insights into the relationships between urban land cover changes and driving forces.

Keywords: urban land cover, human impact, climate change, rule-based classification, across-scale analysis

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Authors: Nada Poropat Jeletic, Gordana Hrzica

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Bilingual conversational corpora represent a meaningful and the most comprehensive data source for investigating the genuine contact phenomena in non-monitored bi-lingual speech productions. They can be particularly useful for bilingual research since some features of bilingual interaction can hardly be accessed with more traditional methodologies (e.g., elicitation tasks). The method of language sampling provides the resources for describing language interaction in a bilingual community and/or in bilingual situations (e.g. code-switching, amount of languages used, number of languages used, etc.). To capture these phenomena in genuine communication situations, such sampling should be as close as possible to spontaneous communication. Bilingual spoken corpus design is methodologically demanding. Therefore this paper aims at describing the methodological challenges that apply to the corpus design of the conversational corpus design of the Istrian Istrovenetian-Croatian Bilingual Corpus. Croatian is the first official language of the Croatian-Italian officially bilingual Istria County, while Istrovenetian is a diatopic subvariety of Venetian, a longlasting lingua franca in the Istrian peninsula, the mother tongue of the members of the Italian National Community in Istria and the primary code of informal everyday communication among the Istrian Italophone population. Within the CLARIN infrastructure, TalkBank is being used, as it provides relevant procedures for designing and analyzing bilingual corpora. Furthermore, it allows public availability allows for easy replication of studies and cumulative progress as a research community builds up around the corpus, while the tools developed within the field of corpus linguistics enable easy retrieval and analysis of information. The method of language sampling employed is kept at the level of spontaneous communication, in order to maximise the naturalness of the collected conversational data. All speakers have provided written informed consent in which they agree to be recorded at a random point within the period of one month after signing the consent. Participants are administered a background questionnaire providing information about the socioeconomic status and the exposure and language usage in the participants social networks. Recording data are being transcribed, phonologically adapted within a standard-sized orthographic form, coded and segmented (speech streams are being segmented into communication units based on syntactic criteria) and are being marked following the CHAT transcription system and its associated CLAN suite of programmes within the TalkBank toolkit. The corpus consists of transcribed sound recordings of 36 bilingual speakers, while the target is to publish the whole corpus by the end of 2020, by sampling spontaneous conversations among approximately 100 speakers from all the bilingual areas of Istria for ensuring representativeness (the participants are being recruited across three generations of native bilingual speakers in all the bilingual areas of the peninsula). Conversational corpora are still rare in TalkBank, so the Corpus will contribute to BilingBank as a highly relevant and scientifically reliable resource for an internationally established and active research community. The impact of the research of communities with societal bilingualism will contribute to the growing body of research on bilingualism and multilingualism, especially regarding topics of language dominance, language attrition and loss, interference and code-switching etc.

Keywords: conversational corpora, bilingual corpora, code-switching, language sampling, corpus design methodology

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Authors: Sum Lau, Wing Chung Cleo Lau, Wing Yan Chu, Long Ching Ip, Wan Yin Lo, Jo Long Sam Yau, Ka Ho Hui, Sze Yi Mak

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Biomedical engineering (BME) is an interdisciplinary subject where knowledge about biology and medicine is applied to novel applications, solving clinical problems. This subject is crucial for cities such as Hong Kong, where the burden on the medical system is rising due to reasons like the ageing population. Hong Kong, who is actively boosting technological advancements in recent years, sets BME, or biotechnology, as a major category, as reflected in the 2018-19 Budget, where biotechnology was one of the four pillars for development. Over the years, while resources in terms of money and space have been provided, there has been a lack of talents expressed by both the academia and industry. While exogenous factors, such as COVID, may have hindered talents from outside Hong Kong to come, endogenous factors should also be considered. In particular, since there are already a few local universities offering BME programmes, their curriculum or style of education requires to be reviewed to intensify the network of the BME community and support post-academic career development. It was observed that while undergraduate (UG) studies focus on knowledge teaching with some technical training and postgraduate (PG) programmes concentrate on upstream research, the programmes are generally confined to the academic sector and lack connections to the industry. In light of that, a “Biomedical Innovation and Outreach Programme 2022” (“B.I.O.2022”) was held to connect students and professors from academia with clinicians and engineers from the industry, serving as a comparative approach to conventional education methods (UG and PG programmes from tertiary institutions). Over 100 participants, including undergraduates, postgraduates, secondary school students, researchers, engineers, and clinicians, took part in various outreach events such as conference and site visits, all held from June to July 2022. As a case study, this programme aimed to tackle the aforementioned problems with the theme of “4Cs” (connection, communication, collaboration, and commercialisation). The effectiveness of the programme is investigated by its ability to serve as an adult and continuing education and the effectiveness of causing social change to tackle current societal challenges, with the focus on tackling the lack of talents engaging in biomedical engineering. In this study, B.I.O.2022 is found to be able to complement the traditional educational methods, particularly in terms of knowledge exchange between the academia and the industry. With enhanced communications between participants from different career stages, there were students who followed up to visit or even work with the professionals after the programme. Furthermore, connections between the academia and industry could foster the generation of new knowledge, which ultimately pointed to commercialisation, adding value to the BME industry while filling the gap in terms of human resources. With the continuation of events like B.I.O.2022, it provides a promising starting point for the development and relationship strengthening of a BME community in Hong Kong, and shows potential as an alternative way of adult education or learning with societal benefits.

Keywords: biomedical engineering, adult education for social change, comparative methods and principles, lifelong learning, faced problems, promises, challenges and pitfalls

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Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

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Authors: Alejandra Torres-Landa López

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Introduction: Can architecture students be creative in spaces conformed by an educational infrastructure build with paradigms of the past?, this question and others related are answered in this paper as it presents the PhD research: An anthropic conflict in Mexican Higher Education Institutes, problems and challenges of the educational infrastructure in teaching and learning History of Architecture. This research was finished in 2013 and is one of the first studies conducted nationwide in Mexico that analysis the educational infrastructure impact in learning architecture; its objective was to identify which elements of the educational infrastructure of Mexican Higher Education Institutes where architects are formed, hinder or contribute to the teaching and learning of History of Architecture; how and why it happens. The methodology: A mixed methodology was used combining quantitative and qualitative analysis. Different resources and strategies for data collection were used, such as questionnaires for students and teachers, interviews to architecture research experts, direct observations in Architecture classes, among others; the data collected was analyses using SPSS and MAXQDA. The veracity of the quantitative data was supported by the Cronbach’s Alpha Coefficient, obtaining a 0.86, figure that gives the data enough support. All the above enabled to certify the anthropic conflict in which Mexican Universities are. Major findings of the study: Although some of findings were probably not unknown, they haven’t been systematized and analyzed with the depth to which it’s done in this research. So, it can be said, that the educational infrastructure of most of the Higher Education Institutes studied, is a barrier to the educational process, some of the reasons are: the little morphological variation of space, the inadequate control of lighting, noise, temperature, equipment and furniture, the poor or none accessibility for disable people; as well as the absence, obsolescence and / or insufficiency of information technologies are some of the issues that generate an anthropic conflict understanding it as the trouble that teachers and students have to relate between them, in order to achieve significant learning). It is clear that most of the educational infrastructure of Mexican Higher Education Institutes is anchored to paradigms of the past; it seems that they respond to the previous era of industrialization. The results confirm that the educational infrastructure of Mexican Higher Education Institutes where architects are formed, is perceived as a "closed container" of people and data; infrastructure that becomes a barrier to teaching and learning process. Conclusion: The research results show it's time to change the paradigm in which we conceive the educational infrastructure, it’s time to stop seen it just only as classrooms, workshops, laboratories and libraries, as it must be seen from a constructive, urban, architectural and human point of view, taking into account their different dimensions: physical, technological, documental, social, among others; so the educational infrastructure can become a set of elements that organize and create spaces where ideas and thoughts can be shared; to be a social catalyst where people can interact between each other and with the space itself.

Keywords: educational infrastructure, impact of space in learning architecture outcomes, learning environments, teaching architecture, learning architecture

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Authors: Nurul Huda Baharuddin, Nik Meriam Nik Sulaiman, Mohammed Kheireddine Aroua

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The effects of pH, polymer concentration, and metal ions feed concentration for four selected heavy metals Zn (II), Pb (II), Cr (III) and Cr (VI) were tested by using Polymer Enhanced Ultrafiltration (PEUF). An alternative biopolymer namely unmodified starch is proposed as a binding reagent in consequences, as compared to commonly used water-soluble polymers namely polyethylene glycol (PEG) and polyethyleneimine (PEI) in the removal of selected four heavy metal ions. The speciation species profiles of four selected complexes ions namely Zn (II), Pb (II), Cr (III) and Cr (VI) and the present of hydroxides ions (OH-) in variously charged ions were investigated by available software at certain pH range. In corresponds to identify the potential of complexation behavior between metal ion-polymers, potentiometric titration studies were obtained at first before carried out experimental works. Experimental works were done using ultrafiltration systems obtained by laboratory ultrafiltration bench scale equipped with 10 kDa polysulfone hollow fiber membrane. Throughout the laboratory works, the rejection coefficient and permeate flux were found to be significantly affected by the main operating parameter, namely the effects of pH, polymer composition and metal ions concentrations. The interaction of complexation between two binding polymers namely unmodified starch and PEG were occurred due to physical attraction of metal ions to the polymer on the molecular surface with high possibility of chemical occurrence. However, these selected metal ions are mainly complexes by polymer functional groups whenever there is interaction with PEI polymer. For study of single metal ions solutions, Zn (II) ions' rejections approaching over 90% were obtained at pH 7 for each tested polymer. This behavior was similar to Pb (II), Cr (III) and Cr (VI); where the rejections were obtained at lower acidic pH and increased at neutral pH of 7. Different behavior was found by Cr (VI) ions where a high rejection was only achieved at acidic pH region with PEI. Polymer concentration and metal ions concentration are found to have a significant effect on rejections. For mixed metal ion solutions, the behavior of metal ion rejections was similar to single metal ion solutions for investigation on the effects of pH. Rejection values were high at pH 7 for Zn (II) pH 7 for Zn (II) and Cr (III) ions, corresponding to higher rejections with unmodified starch. Pb (II) ions obtained high rejections when tested with PEG whenever carried out in mixed metal ion solutions. High Cr (VI) ions' rejection was found with PEI in single and mixed metal ions solutions at neutral pH range. The influence of starch’s granule structure towards the rejections of these four selected metal ions is found to be attracted in a non-ionic manner. No significant effects on permeate flux were obtained when tested at different pH ranges, polymer concentrations and metal ions feed either by single or mixtures metal ions solutions. Canizares Model was employed as the theoretical model to predict permeate flux and metal ions retention on the study of heavy metal ions removal.

Keywords: polyethyleneimine, polyethylene glycol, polymer-enhanced ultrafiltration, unmodified starch

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Authors: Yana Snegireva

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Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.

Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model

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Authors: Mustafa M. Donma, Orkide Donma

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Obesity is associated with cardiovascular disease risk factors and metabolic syndrome (MetS). In this study, associations between adipokines and adipokine as well as obesity indices were evaluated. Plasma adipokine levels may exhibit variations according to body adipose tissue mass. Besides, upon consideration of obesity as an inflammatory disease, adipokines may play some roles in this process. The ratios of proinflammatory adipokines to adiponectin may act as highly sensitive indicators of body adipokine status. The aim of the study is to present some adipokine indices, which are thought to be helpful for the evaluation of childhood obesity and also to determine the best discriminators in the diagnosis of MetS. 80 prepubertal children (aged between 6-9.5 years) included in the study were divided into three groups; 30 children with normal weight (NW), 25 morbid obese (MO) children and 25 MO children with MetS. Physical examinations were performed. Written informed consent forms were obtained from the parents. The study protocol was approved by Ethics Committee of Namik Kemal University Medical Faculty. Anthropometric measurements, such as weight, height, waist circumference (C), hip C, head C, neck C were recorded. Values for body mass index (BMI), diagnostic obesity notation model assessment Index-II (D2 index) as well as waist-to-hip, head-to-neck ratios were calculated. Adiponectin, resistin, leptin, chemerin, vaspin, progranulin assays were performed by ELISA. Adipokine-to-adiponectin ratios were obtained. SPSS Version 20 was used for the evaluation of data. p values ≤ 0.05 were accepted as statistically significant. Values of BMI and D2 index, waist-to-hip, head-to-neck ratios did not differ between MO and MetS groups (p ≥ 0.05). Except progranulin (p ≤ 0.01), similar patterns were observed for plasma levels of each adipokine. There was not any difference in vaspin as well as resistin levels between NW and MO groups. Significantly increased leptin-to-adiponectin, chemerin-to-adiponectin and vaspin-to-adiponectin values were noted in MO in comparison with those of NW. The most valuable adipokine index was progranulin-to-adiponectin (p ≤ 0.01). This index was strongly correlated with vaspin-to-adiponectin ratio in all groups (p ≤ 0.05). There was no correlation between vaspin-to-adiponectin and chemerin-to--adiponectin in NW group. However, a correlation existed in MO group (r = 0.486; p ≤ 0.05). Much stronger correlation (r = 0.609; p ≤ 0.01) was observed in MetS group between these two adipokine indices. No correlations were detected between vaspin and progranulin as well as vaspin and chemerin levels. Correlation analyses showed a unique profile confined to MetS children. Adiponectin was found to be correlated with waist-to-hip (r = -0.435; p ≤ 0.05) as well as head-to-neck (r = 0.541; p ≤ 0.05) ratios only in MetS children. In this study, it has been investigated if adipokine indices have priority over adipokine levels. In conclusion, vaspin-to-adiponectin, progranulin-to-adiponectin, chemerin-to-adiponectin along with waist-to-hip and head-to-neck ratios were the optimal combinations. Adiponectin, waist-to-hip, head-to-neck, vaspin-to-adiponectin, chemerin-to-adiponectin ratios had appropriate discriminatory capability for MetS children.

Keywords: adipokine indices, metabolic syndrome, obesity indices, pediatric obesity

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Authors: Hawraa Zbeeb, Hala Khalifeh, Mohamad Khalil, Francesca Storace, Francesca Baldini, Giulio Lupidi, Laura Vergani

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Sarcopoterium spinosum, a widely distributed spiny shrub belonging to the Rosaceae family, is rich in essential and beneficial constituents. In fact, S. spinosum fruits and roots are traditionally used as herbal medicine in the eastern Mediterranean landscape, and this shrub is mentioned as a medicinal plant in a large number of ethnobotanical surveys. Aqueous root extracts from S. spinosum are used by traditional medicinal practitioners for weight loss treatment of diabetes and pain. Moreover, the anti-diabetic activity of S. spinosum root extract has been reported in different studies, but the beneficial effects of aerial parts, especially fruits, have not been elucidated yet. The aim of the present study was to investigate the in vitro antioxidant and lipid-lowering properties of an ethanolic extract from S. spinosum fruits using both hepatic (FaO) and endothelial (HECV) cells in an attempt to evaluate its possible employment as a nutraceutical supplement. First of all, in vitro spectrophotometric assays were employed to characterize the extract. The total phenol content (TPC) was evaluated by Folin–Ciocalteu spectrophotometric method and the radical scavenging activity was tested by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2, 2'-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) assays. After that, the beneficial effects of the extract were tested on cells. FaO cells treated for 3 hours with 0.75 mM oleate/palmitate mix (1:2 molar ratio) mimic in vitro a moderate hepato-steatosis. HECV cells exposed for 1 hour to 100 µM H₂O₂ mimic an oxidative insult leading to oxidative stress conditions. After the metabolic and oxidative insult, both cell lines were treated with increasing concentrations of the S. spinosum extract (1, 10, 25 µg/mL) for 24 hours. The results showed the S. spinosum ethanolic extract is rather rich in phenols (TPC of 18.6 mgGAE/g dry extracts). Moreover, the extract showed a good scavenging ability in vitro (IC₅₀ 15.9 µg/ml and 10.9 µg/ml measured by DPPH and ABTS assays, respectively). When the extract was tested on cells, the results showed that it could ameliorate some markers of cell dysfunction. The three concentrations of the extract led to a significant decrease in the intracellular triglyceride (TG) content in steatotic FaO cells measured by spectrophotometric assay. On the other hand, HECV cells treated with increasing concentrations of the extract did not result in a significant decrease in both lipid peroxidation measured by the Thiobarbituric Acid Reactive Substances (TBARS) assay, and in reactive oxygen species (ROS) production measured by fluorometric analysis after DCF staining. Interestingly, the ethanolic extract was able to accelerate the wound repair of confluent HECV cells with respect to H₂O₂-insulted cells as measured by T-scratch assay. Taken together, these results seem to indicate that the ethanol extract from S. spinosum fruits is rich in phenol compounds and plays considerable lipid-lowering activity in vitro on steatotic hepatocytes and accelerates wound healing repair on endothelial cells. In light of that, the ethanolic extract from S. spinosum fruits could be a potential candidate for nutraceutical applications.

Keywords: antioxidant activity, ethanolic extract, lipid-lowering activity, phenolic compounds, Sarcopoterium spinosum fruits

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Authors: D. Scarpanti, M. Brondino, M. Pasini

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Background: the present study explores the role of light and restorativeness on work. According with the Attention Restoration Theory (ART) and a Model of Work Environment, the main idea is that some features of environment, i.e., lighting, influences the direct attention, and so, the performance. Restorativeness refers to the presence/absence level of all the characteristics of physical environment that help to regenerate direct attention. Specifically, lighting can affect level of fascination and attention in one hand; and in other hand promotes several biological functions via pineal gland. Different reviews on this topic show controversial results. In order to bring light on this topic, the hypotheses of this study are that lighting can affect the construct of restorativeness and, in the second time, the restorativeness can affect the performance. Method: the participants are 30 workers of a mechatronic company in the North Italy. Every subject answered to a questionnaire valuing their subjective perceptions of environment in a different way: some objective features of environment, like lighting, temperature and air quality; some subjective perceptions of this environment; finally, the participants answered about their perceived performance. The main attention is on the features of light and his components: visual comfort, general preferences and pleasantness; and the dimensions of the construct of restorativeness; fascination, coherence and being away. The construct of performance per se is conceptualized in three level: individual, team membership and organizational membership; and in three different components: proficiency, adaptability, and proactivity, for a total of 9 subcomponents. Findings: path analysis showed that some characteristics of lighting respectively affected the dimension of fascination; and, as expected, the dimension of fascination affected work performance. Conclusions: The present study is a first pilot step of a wide research. These first results can be summarized with the statement that lighting and restorativeness contribute to explain work performance variability: in details perceptions of visual comfort, satisfaction and pleasantness, and fascination respectively. Results related to fascination are particularly interesting because fascination is conceptualized as the opposite of the construct of direct attention. The main idea is, in order to regenerate attentional capacity, it’s necessary to provide a lacking of attention (fascination). The sample size did not permit to test simultaneously the role of the perceived characteristics of light to see how they differently contribute to predict fascination of the work environment. However, the results highlighted the important role that light could have in predicting restorativeness dimensions and probably with a larger sample we could find larger effects also on work performance. Furthermore, longitudinal data will contribute to better analyze the causal model along time. Applicative implications: the present pilot study highlights the relevant role of lighting and perceived restorativeness in the work environment and the importance to focus attention on light features and the restorative characteristics in the design of work environments.

Keywords: lighting, performance, restorativeness, workplace

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Authors: Jennifer Buz, Alvin Spivey

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The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

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Authors: Maria Fontenele, Claude-Gilles Dussap, Vincent Dumouilla, Baptiste Boit

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Roquette Frères is a producer of plant-based ingredients that employs many processes to extract relevant molecules and often transforms them through chemical and physical processes to create desired ingredients with specific functionalities. In this context, Roquette encounters numerous multi-component complex systems in their processes, including fibers, proteins, and carbohydrates, in an aqueous environment. To develop, control, and optimize both new and old processes, Roquette aims to develop new in silico tools. Currently, Roquette uses process modelling tools which include specific thermodynamic models and is willing to develop computational methodologies such as molecular dynamics simulations to gain insights into the complex interactions in such complex media, and especially hydrogen bonding interactions. The issue at hand concerns aqueous mixtures of polyols with high dry matter content. The polyols mannitol and sorbitol molecules are diastereoisomers that have nearly identical chemical structures but very different physicochemical properties: for example, the solubility of sorbitol in water is 2.5 kg/kg of water, while mannitol has a solubility of 0.25 kg/kg of water at 25°C. Therefore, predicting liquid-solid equilibrium properties in this case requires sophisticated solution models that cannot be based solely on chemical group contributions, knowing that for mannitol and sorbitol, the chemical constitutive groups are the same. Recognizing the significance of solvation phenomena in polyols, the GePEB (Chemical Engineering, Applied Thermodynamics, and Biosystems) team at Institut Pascal has developed the COSMO-UCA model, which has the structural advantage of using quantum mechanics tools to predict formation and phase equilibrium properties. In this work, we use molecular dynamics simulations to elucidate the behavior of polyols in aqueous solution. Specifically, we employ simulations to compute essential metrics such as radial distribution functions and hydrogen bond autocorrelation functions. Our findings illuminate a fundamental contrast: sorbitol and mannitol exhibit disparate hydrogen bond lifetimes within aqueous environments. This observation serves as a cornerstone in elucidating the divergent physicochemical properties inherent to each compound, shedding light on the nuanced interplay between their molecular structures and water interactions. We also present a methodology to predict the physicochemical properties of complex solutions, taking as sole input the three-dimensional structure of the molecules in the medium. Finally, by developing knowledge models, we represent some physicochemical properties of aqueous solutions of sorbitol and mannitol.

Keywords: COSMO models, hydrogen bond, molecular dynamics, thermodynamics

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Authors: Awatef Ahmed Ben Ramadan, Aqsa Arshad

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Background: There is a huge Muslim migration movement to North America and Europe for several reasons, primarily refuge from war areas and partly to search for better work and educational chances. There are always concerns regarding first-Generation Immigrant women's health and computer literacy, an adequate understanding of the health systems, and the use of the existing healthcare technology and services effectively and efficiently. Language proficiency level, preference for cultural and traditional remedies, socioeconomic factors, fear of stereotyping, limited accessibility to health services, and general unfamiliarity with the existing health services and resources are familiar variables among these women. Aims: The current study aims to assess the health and digital literacy of first-generation Muslim women in Atlanta city. Also, the study aims to examine how the COVID-19 pandemic has encouraged the use of health information technology and increased technology awareness among the targeted women. Methods: The study design is cross-sectional correlational research. The study will be conducted to produce preliminary results that the investigators want to have to supplement an NIH grant application about leveraging information technology to reduce the health inequalities amongst the first-generation immigrant Muslim women in Atlanta City. The investigators will collect the study data in two phases using different tools. Phase one was conducted in June 2022; the investigators used tools to measure health and digital literacy amongst 42 first-generation immigrant Muslim women. Phase two was conducted in November 2022; the investigators measured the Knowledge, Attitude, and Practice (KAP) of using health information technology such as telehealth from a sample of 45 first-generation Muslim immigrant women in Atlanta; in addition, the investigators measured how the current pandemic has affected their KAP to use telemedicine and telehealth services. Both phases' study participants were recruited using convenience sampling methodology. The investigators collected around 40 of 18 years old or older first-generation Muslim immigrant women for both study phases. The study excluded Immigrants who hold work visas and second-generation immigrants. Results: At the point of submitting this abstract, the investigators are still analyzing the study data to produce preliminary results to apply for an NIH grant entitled "Leveraging Health Information Technology (Health IT) to Address and Reduce Health Care Disparities (R01 Clinical Trial Optional)". This research will be the first step of a comprehensive research project to assess and measure health and digital literacy amongst a vulnerable community group. The targeted group might have different points of view from the U.S.-born inhabitants on how to: promote their health, gain healthy lifestyles and habits, screen for diseases, adhere to health treatment and follow-up plans, perceive the importance of using available and affordable technology to communicate with their providers and improve their health, and help in making serious decisions for their health. The investigators aim to develop an educational and instructional health mobile application considering the language and cultural factors that affect immigrants' ability to access different health and social support sources, know their health rights and obligations in their communities, and improve their health behavior and behavior lifestyles.

Keywords: first-generation immigrant Muslim women, telehealth, COVID-19 pandemic, health information technology, health and digital literacy

Procedia PDF Downloads 86

Authors: Farah Islam, Md. Monirul Islam, Mosammat Salma Akter, Goutam Kumar Kundu

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The continuous variability of climate and the risk associated with it have a significant impact on the fisheries leading to a global concern for about half a billion fishery-based livelihoods. Though in the context of Bangladesh mounting evidence on the impacts of climate change on fishery-based livelihoods or their socioeconomic conditions are present, the country’s inland fisheries sector remains in a negligible corner as compared to the coastal areas which are spotted on the highlight due to its higher vulnerability to climatic hazards. The available research on inland fisheries, particularly river fisheries, has focussed mainly on fish production, pollution, fishing gear, fish biodiversity and livelihoods of the fishers. This study assesses the impacts of climate variability and changes on the Jamuna (a transboundary river called Brahmaputra in India) River fishing communities and their coping and adaptation strategies. This study has used primary data collected from Kalitola Ghat and Debdanga fishing communities of the Jamuna River during May, August and December 2015 using semi-structured interviews, oral history interviews, key informant interviews, focus group discussions and impact matrix as well as secondary data. This study has found that both communities are exposed to storms, floods and land erosions which impact on fishery-based livelihood assets, strategies, and outcomes. The impact matrix shows that human and physical capitals are more affected by climate hazards which in turn affect financial capital. Both communities have been responding to these exposures through multiple coping and adaptation strategies. The coping strategies include making dam with soil, putting jute sac on the yard, taking shelter on boat or embankment, making raised platform or ‘Kheua’ and involving with temporary jobs. While, adaptation strategies include permanent migration, change of livelihood activities and strategies, changing fishing practices and making robust houses. The study shows that migration is the most common adaptation strategy for the fishers which resulted in mostly positive outcomes for the migrants. However, this migration has impacted negatively on the livelihoods of existing fishers in the communities. In sum, the Jamuna river fishing communities have been impacted by several climatic hazards and they have traditionally coped with or adapted to the impacts which are not sufficient to maintain sustainable livelihoods and fisheries. In coming decades, this situation may become worse as predicted by latest scientific research and an enhanced level of response would be needed.

Keywords: climatic hazards, impacts and adaptation, fisherfolk, the Jamuna River

Procedia PDF Downloads 319

Authors: Sagar Saroha, Sawan S. Sinha, Sunil Lakshmipathy

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Reynolds averaged Navier-Stokes (RANS) model is the popular computational tool for prediction of turbulent flows. Being computationally less expensive as compared to direct numerical simulation (DNS), RANS has received wide acceptance in industry and research community as well. However, for high Reynolds number flows, the traditional RANS approach based on the Boussinesq hypothesis is incapacitated to capture all the essential flow characteristics, and thus, its performance is restricted in high Reynolds number flows of practical interest. RANS performance turns out to be inadequate in regimes like flow over curved surfaces, flows with rapid changes in the mean strain rate, duct flows involving secondary streamlines and three-dimensional separated flows. In the recent decade, partially averaged Navier-Stokes (PANS) methodology has gained acceptability among seamless bridging methods of turbulence- placed between DNS and RANS. PANS methodology, being a scale resolving bridging method, is inherently more suitable than RANS for simulating turbulent flows. The superior ability of PANS method has been demonstrated for some cases like swirling flows, high-speed mixing environment, and high Reynolds number turbulent flows. In our work, we intend to evaluate PANS in case of separated turbulent flows past bluff bodies -which is of broad aerodynamic research and industrial application. PANS equations, being derived from base RANS, continue to inherit the inadequacies from the parent RANS model based on linear eddy-viscosity model (LEVM) closure. To enhance PANS’ capabilities for simulating separated flows, the shortcomings of the LEVM closure need to be addressed. Inabilities of the LEVMs have inspired the development of non-linear eddy viscosity models (NLEVM). To explore the potential improvement in PANS performance, in our study we evaluate the PANS behavior in conjugation with NLEVM. Our work can be categorized into three significant steps: (i) Extraction of PANS version of NLEVM from RANS model, (ii) testing the model in the homogeneous turbulence environment and (iii) application and evaluation of the model in the canonical case of separated non-homogeneous flow field (flow past prismatic bodies and bodies of revolution at high Reynolds number). PANS version of NLEVM shall be derived and implemented in OpenFOAM -an open source solver. Homogeneous flows evaluation will comprise the study of the influence of the PANS’ filter-width control parameter on the turbulent stresses; the homogeneous analysis performed over typical velocity fields and asymptotic analysis of Reynolds stress tensor. Non-homogeneous flow case will include the study of mean integrated quantities and various instantaneous flow field features including wake structures. Performance of PANS + NLEVM shall be compared against the LEVM based PANS and LEVM based RANS. This assessment will contribute to significant improvement of the predictive ability of the computational fluid dynamics (CFD) tools in massively separated turbulent flows past bluff bodies.

Keywords: bridging methods of turbulence, high Re-CFD, non-linear PANS, separated turbulent flows

Procedia PDF Downloads 145

Authors: Arjun Kumar Rath, Titus Dhanasingh

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Embedded product development requires software to test hardware functionality during development and finding issues during manufacturing in larger quantities. As the components are getting integrated, the devices are tested for their full functionality using advanced software tools. Benchmarking tools are used to measure and compare the performance of product features. At present, these tests are based on a variety of methods involving varying hardware and software platforms. Typically, these tests are custom built for every product and remain unusable for other variants. A majority of the tests goes undocumented, not updated, unusable when the product is released. To bridge this gap, a solution accelerator in the form of a framework can address these issues for running all these tests from one place, using an off-the-shelf tests library in a continuous integration environment. There are many open-source test frameworks or tools (fuego. LAVA, AutoTest, KernelCI, etc.) designed for testing embedded system devices, with each one having several unique good features, but one single tool and framework may not satisfy all of the testing needs for embedded systems, thus an extensible framework with the multitude of tools. Embedded product testing includes board bring-up testing, test during manufacturing, firmware testing, application testing, and assembly testing. Traditional test methods include developing test libraries and support components for every new hardware platform that belongs to the same domain with identical hardware architecture. This approach will have drawbacks like non-reusability where platform-specific libraries cannot be reused, need to maintain source infrastructure for individual hardware platforms, and most importantly, time is taken to re-develop test cases for new hardware platforms. These limitations create challenges like environment set up for testing, scalability, and maintenance. A desirable strategy is certainly one that is focused on maximizing reusability, continuous integration, and leveraging artifacts across the complete development cycle during phases of testing and across family of products. To get over the stated challenges with the conventional method and offers benefits of embedded testing, an embedded test framework (ETF), a solution accelerator, is designed, which can be deployed in embedded system-related products with minimal customizations and maintenance to accelerate the hardware testing. Embedded test framework supports testing different hardwares including microprocessor and microcontroller. It offers benefits such as (1) Time-to-Market: Accelerates board brings up time with prepacked test suites supporting all necessary peripherals which can speed up the design and development stage(board bring up, manufacturing and device driver) (2) Reusability-framework components isolated from the platform-specific HW initialization and configuration makes the adaptability of test cases across various platform quick and simple (3) Effective build and test infrastructure with multiple test interface options and preintegrated with FUEGO framework (4) Continuos integration - pre-integrated with Jenkins which enabled continuous testing and automated software update feature. Applying the embedded test framework accelerator throughout the design and development phase enables to development of the well-tested systems before functional verification and improves time to market to a large extent.

Keywords: board diagnostics software, embedded system, hardware testing, test frameworks

Procedia PDF Downloads 145

Authors: Emma S. Bowers

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Perturbations in global environments and temperatures have heightened the urgency of creating cost-efficient, energy-neutral building techniques. Structural responses to this thermal crisis have included designs (including those of the building standard PassivHaus) with airtightness, window placement, insulation, solar orientation, shading, and heat-exchange ventilators as potential solutions or interventions. Limitations in the predictability of the circulation of cooled air through the ambient temperature gradients throughout a structure are one of the major obstacles facing these enhanced building methods. A diverse range of air-cooling devices utilizing varying technologies is implemented around the world. Many of them worsen the problem of climate change by consuming energy. Using natural ventilation principles of air buoyancy and density to circulate fresh air throughout a building with no energy input can combat these obstacles. A unique prototype of an energy-neutral air-circulation system was constructed in order to investigate potential temperature and pressure gradients related to the stack effect (updraft of air through a building due to changes in air pressure). The stack effect principle maintains that since warmer air rises, it will leave an area of low pressure that cooler air will rush in to fill. The result is that warmer air will be expelled from the top of the building as cooler air is directed through the bottom, creating an updraft. Stack effect can be amplified by cooling the air near the bottom of a building and heating the air near the top. Using readily available, mostly recyclable or biodegradable materials, an insulated building module was constructed. A tri-part construction model was utilized: a subterranean earth-tube heat exchanger constructed of PVC pipe and placed in a horizontally oriented trench, an insulated, airtight cube aboveground to represent a building, and a solar chimney (painted black to increase heat in the out-going air). Pressure and temperature sensors were placed at four different heights within the module as well as outside, and data was collected for a period of 21 days. The air pressures and temperatures over the course of the experiment were compared and averaged. The promise of this design is that it represents a novel approach which directly addresses the obstacles of air flow and expense, using the physical principle of stack effect to draw a continuous supply of fresh air through the structure, using low-cost and readily available materials (and zero manufactured energy). This design serves as a model for novel approaches to creating temperature controlled buildings using zero energy and opens the door for future research into the effects of increasing module scale, increasing length and depth of the earth tube, and shading the building. (Model can be provided).

Keywords: air circulation, PassivHaus, stack effect, thermal gradient

Procedia PDF Downloads 154

Authors: Loyd R. Hook, Maryam Moharek

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With the envisioned future growth of low altitude urban aircraft operations for airborne delivery service and advanced air mobility, strategies to coordinate and deconflict aircraft flight paths must be prioritized. Autonomous coordination and planning of flight trajectories is the preferred approach to the future vision in order to increase safety, density, and efficiency over manual methods employed today. Difficulties arise because any conflict resolution must be constrained by all other aircraft, all airspace restrictions, and all ground-based obstacles in the vicinity. These considerations make pair-wise tactical deconfliction difficult at best and unlikely to find a suitable solution for the entire system of vehicles. In addition, more traditional methods which rely on long time scales and large protected zones will artificially limit vehicle density and drastically decrease efficiency. Instead, strategic planning, which is able to respond to highly dynamic conditions and still account for high density operations, will be required to coordinate multiple vehicles in the highly constrained low altitude urban environment. This paper develops and evaluates such a planning algorithm which can be implemented autonomously across multiple aircraft and situations. Data from this evaluation provide promising results with simulations showing up to 10 aircraft deconflicted through a relatively narrow low-altitude urban canyon without any vehicle to vehicle or obstacle conflict. The algorithm achieves this level of coordination beginning with the assumption that each vehicle is controlled to follow an independently constructed flight path, which is itself free of obstacle conflict and restricted airspace. Then, by preferencing speed change deconfliction maneuvers constrained by the vehicles flight envelope, vehicles can remain as close to the original planned path and prevent cascading vehicle to vehicle conflicts. Performing the search for a set of commands which can simultaneously ensure separation for each pair-wise aircraft interaction and optimize the total velocities of all the aircraft is further complicated by the fact that each aircraft's flight plan could contain multiple segments. This means that relative velocities will change when any aircraft achieves a waypoint and changes course. Additionally, the timing of when that aircraft will achieve a waypoint (or, more directly, the order upon which all of the aircraft will achieve their respective waypoints) will change with the commanded speed. Put all together, the continuous relative velocity of each vehicle pair and the discretized change in relative velocity at waypoints resembles a hybrid reachability problem - a form of control reachability. This paper proposes two methods for finding solutions to these multi-body problems. First, an analytical formulation of the continuous problem is developed with an exhaustive search of the combined state space. However, because of computational complexity, this technique is only computable for pairwise interactions. For more complicated scenarios, including the proposed 10 vehicle example, a discretized search space is used, and a depth-first search with early stopping is employed to find the first solution that solves the constraints.

Keywords: strategic planning, autonomous, aircraft, deconfliction

Procedia PDF Downloads 95

Authors: Valerii Levshakov, Olga Fedorova

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Specific features of ship structures, made from composites, i.e. simultaneous shaping of material and structure, large sizes, complicated outlines and tapered thickness have defined leading role of technology, integrating test results from material science, designing and structural analysis. Main procedures of composite shipbuilding are contact molding, vacuum molding and winding. Now, the most demanded composite shipbuilding technology is the manufacture of structures from fiberglass and multilayer hybrid composites by means of vacuum molding. This technology enables the manufacture of products with improved strength properties (in comparison with contact molding), reduction of production duration, weight and secures better environmental conditions in production area. Mechanized winding is applied for the manufacture of parts, shaped as rotary bodies – i.e. parts of ship, oil and other pipelines, deep-submergence vehicles hulls, bottles, reservoirs and other structures. This procedure involves processing of reinforcing fiberglass, carbon and polyaramide fibers. Polyaramide fibers have tensile strength of 5000 MPa, elastic modulus value of 130 MPa and rigidity of the same can be compared with rigidity of fiberglass, however, the weight of polyaramide fiber is 30% less than weight of fiberglass. The same enables to the manufacture different structures, including that, using both – fiberglass and organic composites. Organic composites are widely used for the manufacture of parts with size and weight limitations. High price of polyaramide fiber restricts the use of organic composites. Perspective area of winding technology development is the manufacture of carbon fiber shafts and couplings for ships. JSC ‘Shipbuilding & Shiprepair Technology Center’ (JSC SSTC) developed technology of dielectric uncouplers for cryogenic lines, cooled by gaseous or liquid cryogenic agents (helium, nitrogen, etc.) for temperature range 4.2-300 K and pressure up to 30 MPa – the same is used for separating components of electro physical equipment with different electrical potentials. Dielectric uncouplers were developed, the manufactured and tested in accordance with International Thermonuclear Experimental Reactor (ITER) Technical specification. Spiral uncouplers withstand operating voltage of 30 kV, direct-flow uncoupler – 4 kV. Application of spiral channel instead of rectilinear enables increasing of breakdown potential and reduction of uncouplers sizes. 95 uncouplers were successfully the manufactured and tested. At the present time, Russian the manufacturers of ship composite structures have started absorption of technology of manufacturing the same using automated prepreg laminating; this technology enables the manufacture of structures with improved operational specifications.

Keywords: fiberglass, infusion, polymeric composites, winding

Procedia PDF Downloads 238

Authors: Mei Xuan Tan, Gim-Yang Maggie Pee, Mei Chee Tan

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Academic performance, in the form of scoring high grades in enrolled subjects, is not the only significant trait in achieving success. Engineering graduates with experience in working on hands-on projects in a team setting are highly sought after in industry upon graduation. Such projects are typically real world problems that require the integration and application of knowledge and skills from several disciplines. In a traditional university setting, subjects are taught in a silo manner with no cross participation from other departments or disciplines. This may lead to knowledge compartmentalization and students are unable to understand and connect the relevance and applicability of the subject. University instructors thus see this integration across disciplines as a challenging task as they aim to better prepare students in understanding and solving problems for work or future studies. To improve students’ academic performance and to cultivate various skills such as critical thinking, there has been a gradual uptake in the use of an active learning approach in introductory science and engineering courses, where lecturing is traditionally the main mode of instruction. This study aims to discuss the implementation and experience of a hands-on, interdisciplinary project that involves all the four core subjects taught during the term at the Singapore University of Technology Design (SUTD). At SUTD, an interdisciplinary design activity, named 2D, is integrated into the curriculum to help students reinforce the concepts learnt. A student enrolled in SUTD experiences his or her first 2D in Term 1. This activity. which spans over one week in Week 10 of Term 1, highlights the application of chemistry, physics, mathematics, humanities, arts and social sciences (HASS) in designing an engineering product solution. The activity theme for Term 1 2D revolved around “work and play”. Students, in teams of 4 or 5, used a scaled-down model of a chemical launcher to launch a projectile across the room. It involved the use of a small chemical combustion reaction between ethanol (a highly volatile fuel) and oxygen. This reaction generated a sudden and large increase in gas pressure built up in a closed chamber, resulting in rapid gas expansion and ejection of the projectile out of the launcher. Students discussed and explored the meaning of play in their lives in HASS class while the engineering aspects of a combustion system to launch an object using underlying principles of energy conversion and projectile motion were revisited during the chemistry and physics classes, respectively. Numerical solutions on the distance travelled by the projectile launched by the chemical launcher, taking into account drag forces, was developed during the mathematics classes. At the end of the activity, students developed skills in report writing, data collection and analysis. Specific to this 2D activity, students gained an understanding and appreciation on the application and interdisciplinary nature of science, engineering and HASS. More importantly, students were exposed to design and problem solving, where human interaction and discussion are important yet challenging in a team setting.

Keywords: active learning, collaborative learning, first year undergraduate, interdisciplinary, STEAM

Procedia PDF Downloads 122

Authors: Zakia Fatima, Liu Lu, Donghao Li

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The analysis of biological fluid metabolites holds significant importance in various areas, such as medical research, food science, and public health. Investigating the levels and distribution of nutrients and their metabolites in biological samples allows researchers and healthcare professionals to determine nutritional status, find hypovitaminosis or hypervitaminosis, and monitor the effectiveness of interventions such as dietary supplementation. Moreover, analysis of nutrient metabolites provides insight into their metabolism, bioavailability, and physiological processes, aiding in the clarification of their health roles. Hence, the exploration of a distinct, efficient, eco-friendly, and simpler methodology is of great importance to evaluate the metabolic content of complex biological samples. In this work, a green and rapid analytical method based on an automated online two-dimensional microscale carbon fiber/activated carbon fiber fractionation system and time-of-flight mass spectrometry (2DμCFs-TOF-MS) was used to evaluate metabolites of urine samples after oral administration of food supplements. The automated 2DμCFs instrument consisted of a microcolumn system with bare carbon fibers and modified carbon fiber coatings. Carbon fibers and modified carbon fibers exhibit different surface characteristics and retain different compounds accordingly. Three kinds of mobile-phase solvents were used to elute the compounds of varied chemical heterogeneities. The 2DμCFs separation system has the ability to effectively separate different compounds based on their polarity and solubility characteristics. No complicated sample preparation method was used prior to analysis, which makes the strategy more eco-friendly, practical, and faster than traditional analysis methods. For optimum analysis results, mobile phase composition, flow rate, and sample diluent were optimized. Water-soluble vitamins, fat-soluble vitamins, and amino acids, as well as 22 vitamin metabolites and 11 vitamin metabolic pathway-related metabolites, were found in urine samples. All water-soluble vitamins except vitamin B12 and vitamin B9 were detected in urine samples. However, no fat-soluble vitamin was detected, and only one metabolite of Vitamin A was found. The comparison with a blank urine sample showed a considerable difference in metabolite content. For example, vitamin metabolites and three related metabolites were not detected in blank urine. The complete single-run screening was carried out in 5.5 minutes with the minimum consumption of toxic organic solvent (0.5 ml). The analytical method was evaluated in terms of greenness, with an analytical greenness (AGREE) score of 0.72. The method’s practicality has been investigated using the Blue Applicability Grade Index (BAGI) tool, obtaining a score of 77. The findings in this work illustrated that the 2DµCFs-TOF-MS approach could emerge as a fast, sustainable, practical, high-throughput, and promising analytical tool for screening and accurate detection of various metabolites, pharmaceuticals, and ingredients in dietary supplements as well as biological fluids.

Keywords: metabolite analysis, sustainability, carbon fibers, urine.

Procedia PDF Downloads 28

Authors: Hao Huang

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INTRODUCTION: The Association of American Colleges and Universities (AACU) recommends the development of ‘high-impact practices,’ in an effort to increase rates of student retention and student engagement at undergraduate institutions. To achieve these goals, the Scripps College Humanities Institute and HI Fellows Seminar not only featured distinguished academics presenting their scholarship about current immigration policy and its consequences in the USA and around the world but integrated socially significant community leaders and creative activists/artivists in public talks, student workshops and collaborative art events. Students participated in experiential learning that involved guest personal presentations and discussions, oral history interviews that applied standard oral history methodologies, detailed cultural documentation, collaborative artistic interventions, and weekly posts in Internet Digital Learning Environment Sakai collaborative course forums and regular responses to other students’ comments. Our teaching pedagogies addressed the four learning styles outlined in Kolb’s Learning Style Inventory. PROJECT DESCRIPTION: Over the academic year 2017-18, the Scripps College Humanities Institute and HI Fellows Seminar presented a Fall 2017 topic, ‘The World at Our Doorsteps: Immigration and Deportation in Los Angeles’. Our purpose was to address how current federal government anti-immigration measures have affected many students of color, some of whom are immigrants, many of whom are related to and are friends with people who are impacted by the attitudes as well as the practices of the U.S. Citizenship and Immigration Services. In Spring 2018, we followed with the topic, ‘Exclusive Nationalisms: Global Migration and Immigration’. This addresses the rise of white supremacists who have ascended to position of power worldwide, in America, Europe, Russia, and xenophobic nationalisms in China, Myanmar and the Philippines. Recent scholarship has suggested the existence of categories of refugees beyond the political or social, who fit into the more inclusive category of migrants. ASSESSMENT METHODOLOGIES: Assessment methodologies not only included qualitative student interviews and quantitative student evaluations in standard rubric format, but also Outcome Assessments, Formative Evaluations, and Outside Guest Teacher feedback. These indicated that the most effective educational practices involved collaborative inquiry in undergraduate research, community-based learning, and capstone projects. Assessments of E-portfolios, written and oral coursework, and final creative projects with associated 10-12 page analytic paper revealed that students developed their understanding of how government and social organizations work; they developed communication skills that enhanced working with others from different backgrounds; they developed their ability to thoughtfully evaluate their course performance by adopting reflective practices; they gained analytic and interpretive skills that encouraged self-confidence and self- initiative not only academically, but also with regards to independent projects. CONCLUSION: Most importantly, the Scripps Humanities Institute experiential learning project spurred on real-world actions by our students, such as a public symposium on how to cope with bigots, a student tutoring program for immigrant staff children, student negotiations with the administration to establish meaningful, sustainable diversity and inclusion programs on-campus. Activism is not only to be taught to and for our students– it has to be enacted by our students.

Keywords: immigration, migration, human rights, learning assessment

Procedia PDF Downloads 131

Authors: Eli Avraham

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The Arab Spring was widely covered in the global media and the number of Western tourists traveling to the area began to fall. The goal of this study was to analyze which media strategies marketers in Middle Eastern countries chose to employ in their attempts to repair the negative image of the area in the wake of the Arab Spring. Several studies were published concerning image-restoration strategies of destinations during crises around the globe; however, these strategies were not part of an overarching theory, conceptual framework or model from the fields of crisis communication and image repair. The conceptual framework used in the current study was the ‘multi-step model for altering place image’, which offers three types of strategies: source, message and audience. Three research questions were used: 1.What public relations crisis techniques and advertising campaign components were used? 2. What media policies and relationships with the international media were adopted by Arab officials? 3. Which marketing initiatives (such as cultural and sports events) were promoted? This study is based on qualitative content analysis of four types of data: 1) advertising components (slogans, visuals and text); (2) press interviews with Middle Eastern officials and marketers; (3) official media policy adopted by government decision-maker (e.g. boycotting or arresting newspeople); and (4) marketing initiatives (e.g. organizing heritage festivals and cultural events). The data was located in three channels from December 2010, when the events started, to September 31, 2013: (1) Internet and video-sharing websites: YouTube and Middle Eastern countries' national tourism board websites; (2) News reports from two international media outlets, The New York Times and Ha’aretz; these are considered quality newspapers that focus on foreign news and tend to criticize institutions; (3) Global tourism news websites: eTurbo news and ‘Cities and countries branding’. Using the ‘multi-step model for altering place image,’ the analysis reveals that Middle Eastern marketers and officials used three kinds of strategies to repair their countries' negative image: 1. Source (cooperation and media relations; complying, threatening and blocking the media; and finding alternatives to the traditional media) 2. Message (ignoring, limiting, narrowing or reducing the scale of the crisis; acknowledging the negative effect of an event’s coverage and assuring a better future; promotion of multiple facets, exhibitions and softening the ‘hard’ image; hosting spotlight sporting and cultural events; spinning liabilities into assets; geographic dissociation from the Middle East region; ridicule the existing stereotype) and 3. Audience (changing the target audience by addressing others; emphasizing similarities and relevance to specific target audience). It appears that dealing with their image problems will continue to be a challenge for officials and marketers of Middle Eastern countries until the region stabilizes and its regional conflicts are resolved.

Keywords: Arab spring, cultural events, image repair, Middle East, tourism marketing

Procedia PDF Downloads 285

Authors: Dieudonne Uwizeye, Reuben Muhayiteto

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Teenage pregnancy is a challenging problem for sustainable development due to restrictions it poses to socioeconomic opportunities for young mothers, their children and families. Being unable to take appropriate economic and social responsibilities, teen mothers get trapped into poverty and become economic burden to their family and country. Besides, teenage pregnancy is also a health problem because children born to very young mothers are vulnerable with greater risk of illnesses and deaths, and teenage mothers are more likely to be exposed to greater risk of maternal mortality and to other health and psychological problems. In Kigali city, in Rwanda, teenage pregnancy rate is currently high and its increase in recent years is worrisome. However, only individual factors influencing the teenage pregnancy tend to be the basis of interventions. It is important to understand the important socioeconomic factors at the household level that are associated with teenage pregnancy to help government, parents, and other stakeholders to appropriately address the problem with sustainable measures. This study analyzed secondary data from the Fifth Rwanda Demographic and Health Survey (RDHS-V 2014-2015) conducted by the National Institute of Statistics of Rwanda (NISR). The aim was to examine household socio-economic factors that are associated with incidence of teenage pregnancies in Kigali city. In addition to descriptive analysis, Pearson’s Chi Square and Binary Logistic Regression were used in the analysis. Findings indicate that marital status and age of household head, number of members in a household, number of rooms used for sleeping, educational level of the household head and household's wealth are significantly associated with teenage pregnancy in Rwanda ( p< 0.05). It was found that teenagers living with parents, those having parents with higher education and those from richer families are less likely to become pregnant. Age of household head was pinpointed as factor to teenage pregnancy, with teenage-headed households being more vulnerable. The findings also revealed that household composition correlates with the probability of teenage pregnancy (p < 0.05) with teenagers from households with less number of members being more vulnerable. Regarding the size of the house, the study suggested that the more rooms available in households, the less incidences of teenage pregnancy are likely to be observed (p < 0.05). However, teenage pregnancy was not significantly associated with physical violence among parents (p = 0.65) and sex of household heads (p = 0.52), except in teen-headed households of which female are predominantly heads. The study concludes that teenage pregnancy remains a serious social, economic and health problem in Rwanda. The study informs government officials, parents and other stakeholders to take interventions and preventive measures through community sex education, policies and strategies to foster effective parental guidance, care and control of young girls through meeting their necessary social and financial needs within households.

Keywords: household socio-economic factors, Rwanda, Rwanda demographic and health survey, teenage pregnancy

Procedia PDF Downloads 179

Authors: Ponchang Apollos Wuyep, Alice Njolke Mafe, Longchi Satkat Zacheaus, Dogun Ojochogu, Dabot Ayuba Yakubu

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Fungi causes huge losses when infections occur both in plants and animals. Synthetic Antifungal drugs are mostly very expensive and highly cytotoxic when taken. This study was aimed at determining the in vitro and in vivo antifungal activities of the leaves and stem extracts of Terminalia mantaly (Umbrella tree)H. Perrier on Aspergillus species in a bid to identify potential sources of cheap starting materials for the synthesis of new drugs to address the growing antimicrobial resistance. T. mantaly leave and stem powdered plant was extracted by fractionation using the method of solvent partition co-efficient in their graded form in the order n-hexane, Ethyl acetate, methanol and distilled water and phytochemical screening of each fraction revealed the presence of alkaloids, saponins, Tannins, flavonoids, carbohydrates, steroids, anthraquinones, cardiac glycosides and terpenoids in varying degrees. The Agar well diffusion technique was used to screen for antifungal activity of the fractions on clinical isolates of Aspergillus species (Aspergillus flavus and Aspergillus fumigatus). Minimum inhibitory concentration (MIC50) of the most active extracts was determined by the broth dilution method. The fractions test indicated a high antifungal activity with zones of inhibition ranging from 6 to 26 mm and 8 to 30mm (leave fractions) and 10mm to 34mm and 14mm to36mm (stem fractions) on A. flavus and A. fumigatus respectively. All the fractions indicated antifungal activity in a dose response relationship at concentrations of 62.5mg/ml, 125mg/ml, 250mg/ml and 500mg/ml. Better antifungal efficacy was shown by the Ethyl acetate, Hexane and Methanol fractions in the in vitro as the most potent fraction with MIC ranging from 62.5 to 125mg/ml. There was no statistically significant difference (P>0.05) in the potency of the Eight fractions from leave and stem (Hexane, Ethyl acetate, methanol and distilled water, antifungal (fluconazole), which served as positive control and 10% DMSO(Dimethyl Sulfoxide)which served as negative control. In the in vivo investigations, the ingestion technique was used for the infectious studies Female Drosophilla melanogaster(UAS-Diptericin)normal flies(positive control),infected and not treated flies (negative control) and infected flies with A. fumigatus and placed on normal diet, diet containing fractions(MSM and HSM each at concentrations of 10mg/ml 20mg/ml, 30mg/ml, 40mg/ml, 50mg/ml, 60mg/ml, 70mg/ml, 80mg/ml, 90mg/ml and 100mg/ml), diet containing control drugs(fluconazole as positive control)and infected flies on normal diet(negative control), the flies were observed for fifteen(15) days. Then the total mortality of flies was recorded each day. The results of the study reveals that the flies were susceptible to infection with A. fumigatus and responded to treatment with more effectiveness at 50mg/ml, 60mg/ml and 70mg/ml for both the Methanol and Hexane stem fractions. Therefore, the Methanol and Hexane stem fractions of T. mantaly contain therapeutically useful compounds, justifying the traditional use of this plant for the treatment of fungal infections.

Keywords: Terminalia mantaly, Aspergillus fumigatus, cytotoxic, Drosophila melanogaster, antifungal

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Authors: Cristina Diaz, Lucia Perez-Gandarillas, Gonzalo Garcia-Fuentes, Simone Visigalli, Roberto Canziani, Giuseppe Di Florio, Paolo Gronchi

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During their lifetime, industrial machines are often subjected to chemical, mechanical and thermal extreme conditions. In some cases, the loss of efficiency comes from the degradation of the surface as a result of its exposition to abrasive environments that can cause wear. This is a common problem to be solved in industries of diverse nature such as food, paper or concrete industries, among others. For this reason, a good selection of the material is of high importance. In the machine design context, stainless steels such as AISI 304 and 316 are widely used. However, the severity of the external conditions can require additional protection for the steel and sometimes coating solutions are demanded in order to extend the lifespan of these materials. Therefore, the development of effective coatings with high wear resistance is of utmost technological relevance. In this research, bilayer coatings made of Titanium-Tantalum, Titanium-Niobium, Titanium-Hafnium, and Titanium-Zirconium have been developed using magnetron sputtering configuration by PVD (Physical Vapor Deposition) technology. Their tribological behavior has been measured and evaluated under different environmental conditions. Two kinds of steels were used as substrates: AISI 304, AISI 316. For the comparison with these materials, titanium alloy substrate was also employed. Regarding the characterization, wear rate and friction coefficient were evaluated by a tribo-tester, using a pin-on-ball configuration with different lubricants such as tomato sauce, wine, olive oil, wet compost, a mix of sand and concrete with water and NaCl to approximate the results to real extreme conditions. In addition, topographical images of the wear tracks were obtained in order to get more insight of the wear behavior and scanning electron microscope (SEM) images were taken to evaluate the adhesion and quality of the coating. The characterization was completed with the measurement of nanoindentation hardness and elastic modulus. Concerning the results, thicknesses of the samples varied from 100 nm (Ti-Zr layer) to 1.4 µm (Ti-Hf layer) and SEM images confirmed that the addition of the Ti layer improved the adhesion of the coatings. Moreover, results have pointed out that these coatings have increased the wear resistance in comparison with the original substrates under environments of different severity. Furthermore, nanoindentation hardness results showed an improvement of the elastic strain to failure and a high modulus of elasticity (approximately 200 GPa). As a conclusion, Ti-Ta, Ti-Zr, Ti-Nb, and Ti-Hf are very promising and effective coatings in terms of tribological behavior, improving considerably the wear resistance and friction coefficient of typically used machine materials.

Keywords: coating, stainless steel, tribology, wear

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Authors: Camilo Cerda Sarabia, Fernanda Bravo Cornejo, Diego Santibanez Oyarce, Hugo Osses Prado, Esteban Gómez Terán, Belén Diaz Diaz, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Antimicrobial resistance (AMR) represents a significant and rapidly escalating global health threat. Projections estimate that by 2050, AMR infections could claim up to 10 million lives annually. Respiratory infections, in particular, pose a severe risk not only to individual patients but also to the broader public health system. Despite the alarming rise in resistant respiratory infections, AMR within the lung microbiome (microbial community) remains underexplored and poorly characterized. The lungs, as a complex and dynamic microbial environment, host diverse communities of microorganisms whose interactions and resistance mechanisms are not fully understood. Unlike studies that focus on individual genomes, analyzing the entire microbiome provides a comprehensive perspective on microbial interactions, resistance gene transfer, and community dynamics, which are crucial for understanding AMR. However, this holistic approach introduces significant computational challenges and exposes the limitations of traditional analytical methods such as the difficulty of identifying the AMR. Machine learning has emerged as a powerful tool to overcome these challenges, offering the ability to analyze complex genomic data and uncover novel insights into AMR that might be overlooked by conventional approaches. This study investigates microbial resistance within the lung microbiome using unsupervised machine learning approaches to uncover resistance patterns and potential clinical associations. it downloaded and selected lung microbiome data from HumanMetagenomeDB based on metadata characteristics such as relevant clinical information, patient demographics, environmental factors, and sample collection methods. The metadata was further complemented by details on antibiotic usage, disease status, and other relevant descriptions. The sequencing data underwent stringent quality control, followed by a functional profiling focus on identifying resistance genes through specialized databases like Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. Subsequent analyses employed unsupervised machine learning techniques to unravel the structure and diversity of resistomes in the microbial community. Some of the methods employed were clustering methods such as K-Means and Hierarchical Clustering enabled the identification of sample groups based on their resistance gene profiles. The work was implemented in python, leveraging a range of libraries such as biopython for biological sequence manipulation, NumPy for numerical operations, Scikit-learn for machine learning, Matplotlib for data visualization and Pandas for data manipulation. The findings from this study provide insights into the distribution and dynamics of antimicrobial resistance within the lung microbiome. By leveraging unsupervised machine learning, we identified novel resistance patterns and potential drivers within the microbial community.

Keywords: antibiotic resistance, microbial community, unsupervised machine learning., sequences of AMR gene

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Authors: Mohammed El Raey, Moustafa Osman Mohammed

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The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s System. Naturally exchange patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. The probabilistic risk assessment (PRA) technique is utilized to assess the safety of industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The plant safety parameters are identified for engineering topology as employed in assessment safety of industrial ecology. In particular, the most severe accidental release of hazardous gaseous is postulated, analyzed and assessment in industrial region. The IAEA- safety assessment procedure is used to account the duration and rate of discharge of liquid chlorine. The ecological model of plume dispersion width and concentration of chlorine gas in the downwind direction is determined using Gaussian Plume Model in urban and ruler areas and presented with SURFER®. The prediction of accident consequences is traced in risk contour concentration lines. The local greenhouse effect is predicted with relevant conclusions. The spatial-ecological model is also predicted the distribution schemes from the perspective of pollutants that considered multiple factors of multi-criteria analysis. The data extends input–output analysis to evaluate the spillover effect, and conducted Monte Carlo simulations and sensitivity analysis. Their unique structure is balanced within “equilibrium patterns”, such as the biosphere and collective a composite index of many distributed feedback flows. These dynamic structures are related to have their physical and chemical properties and enable a gradual and prolonged incremental pattern. While this spatial model structure argues from ecology, resource savings, static load design, financial and other pragmatic reasons, the outcomes are not decisive in artistic/ architectural perspective. The hypothesis is an attempt to unify analytic and analogical spatial structure for development urban environments using optimization software and applied as an example of integrated industrial structure where the process is based on engineering topology as optimization approach of systems ecology.

Keywords: spatial-ecological modeling, spatial structure orientation impact, composite structure, industrial ecology

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Authors: R. Simide, T. Miard

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Integrated multi-trophic aquaculture (IMTA) is used to reduce waste from aquaculture and increase productivity by co-cultured species. In this study, we designed a recirculating multi-trophic aquaculture system which requires low energy consumption, low water renewal and easy-care. European seabass (Dicentrarchus labrax) were raised with co-cultured sea urchin (Paracentrotus lividus), deteritivorous polychaete fed on settled particulate matter, mussels (Mytilus galloprovincialis) used to extract suspended matters, macroalgae (Ulva sp.) used to uptake dissolved nutrients and gastropod (Phorcus turbinatus) used to clean the series of 4 tanks from fouling. Experiment was performed in triplicate during one month in autumn under an experimental greenhouse at the Institute Océanographique Paul Ricard (IOPR). Thanks to the absence of a physical filter, any pomp was needed to pressure water and the water flow was carried out by a single air-lift followed by gravity flow.Total suspended solids (TSS), biochemical oxygen demand (BOD5), turbidity, phytoplankton estimation and dissolved nutrients (ammonium NH₄, nitrite NO₂⁻, nitrate NO₃⁻ and phosphorus PO₄³⁻) were measured weekly while dissolved oxygen and pH were continuously recorded. Dissolved nutrients stay under the detectable threshold during the experiment. BOD5 decreased between fish and macroalgae tanks. TSS highly increased after 2 weeks and then decreased at the end of the experiment. Those results show that bioremediation can be well used for aquaculture system to keep optimum growing conditions. Fish were the only feeding species by an external product (commercial fish pellet) in the system. The others species (extractive species) were fed from waste streams from the tank above or from Ulva produced by the system for the sea urchin. In this way, between the fish aquaculture only and the addition of the extractive species, the biomass productivity increase by 5.7. In other words, the food conversion ratio dropped from 1.08 with fish only to 0.189 including all species. This experimental recirculating multi-trophic aquaculture system was efficient enough to reduce waste and increase productivity. In a second time, this technology has been reproduced at a commercial scale. The IOPR in collaboration with Les 4 Marais company run for 6 month a recirculating IMTA in 8000 m² of water allocate between 4 marsh ponds. A similar air-lift and gravity recirculating system was design and only one feeding species of shrimp (Palaemon sp.) was growth for 3 extractive species. Thanks to this joint work at the laboratory and commercial scales we will be able to challenge IMTA system and discuss about this sustainable aquaculture technology.

Keywords: bioremediation, integrated multi-trophic aquaculture (IMTA), laboratory and commercial scales, recirculating aquaculture, sustainable

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

Procedia PDF Downloads 61