Search results for: object based

Authors: Nicolaas Unland, John Webb

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The acidification and mobilisation of metals during the oxidation of acid sulfate soils exposed during lake bed drying is an increasingly common phenomenon under climate scenarios with reduced rainfall. In order to assess the risk of generating high concentrations of acidity and dissolved metals, chromium suite analysis are fundamental, but sometimes limited in characterising the potential risks they pose. This study combines such fundamental test work, along with incubation tests and 1D modelling to investigate the risks associated with the drying of Third Reedy Lake in South East Australia. Core samples were collected from a variable depth of 0.5 m below the lake bed, at 19 locations across the lake’s footprint, using a boat platform. Samples were subjected to a chromium suite of analysis, including titratable actual acidity, chromium reducible sulfur and acid neutralising capacity. Concentrations of reduced sulfur up to 0.08 %S and net acidities up to 0.15 %S indicate that acid sulfate soils have formed on the lake bed during permanent inundation over the last century. A further sub-set of samples were prepared in 7 columns and subject to accelerated heating, drying and wetting over a period of 64 days in laboratory. Results from the incubation trial indicate that while pyrite oxidation proceeded, minimal change to soil pH or the acidity of leachate occurred, suggesting that the internal buffering capacity of lake bed sediments was sufficient to neutralise a large proportion of the acidity produced. A 1D mass balance model was developed to assess potential changes in lake water quality during drying based on the results of chromium suite and incubation tests. Results from the above test work and modelling suggest that acid sulfate soils pose a moderate to low risk to the Third Reedy Lake system. Further, the risks can be effectively managed during the initial stages of lake drying via flushing with available mildly alkaline water. The study finds that while test work such as chromium suite analysis are fundamental in characterizing acid sulfate soil environments, they can the overestimate risks associated with the soils. Subsequent incubation test work may more accurately characterise such soils and lead to better-informed management strategies.

Keywords: acid sulfate soil, incubation, management, model, risk

Procedia PDF Downloads 359

Authors: Wissal Ben Arfi, Jean-Michel Sahut

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The purpose of this paper is to provide a deeper understanding of the succession process from a knowledge management perspective. By doing that, succession process in family businesses, as an environment for creating and sharing knowledge, was explored. Design/Methodology/Approach: To support our reasoning, we collected qualitative data through 16 in-depth interviews conducted with all decision makers involved in the family businesses succession process in France. These open-ended responses were subsequently exposed to thematic discourse analysis. Findings: Central to this exhibit is the nature and magnitude of knowledge creation and sharing among the actors within the family succession context and how can tacit knowledge sharing facilitate the succession process. We also identified factors that inhibit down the knowledge creation and sharing processes. The sharing and creation of knowledge among members of a family business appear to be a complex process that must be part of a strategy for change. This implies that it requests trust and takes a certain amount of time because it requires organizational change and a clear and coherent strategic vision that is accepted and assimilated by all the members. Professional and leadership skills are of particular importance in knowledge sharing and creation processes. In most cases, tacit knowledge is crucial when it is shared and accumulated collectively. Our findings reveal that managers should find ways of implementing knowledge sharing and creation processes while acknowledging the succession process within family firms. This study highlights the importance of generating knowledge strategies in order to enhance the performance and the success of intergenerational succession. The empirical outcomes contribute to enrich the field of succession management process and enhance the role of knowledge in shaping family performance and longevity. To a large extent, the lessons learned from the study of succession processes in family-owned businesses are that when there is a deliberate effort to introduce a knowledge-based approach, this action becomes a seminal event in the life of the organization. Originality/Value: The paper contributes to the deep understanding of interactions among actors by examining the knowledge creation and sharing processes since current researches in family succession focused on aspects such as personal development of potential, intra-family succession intention, decision-making processes in family businesses. Besides, as succession is one of the key factors that determine the longevity and the performance of family businesses, it also contributes to literature by examining how tacit knowledge is transferred, shared and created in family businesses and how this can facilitate the intergenerational succession process.

Keywords: family-owned businesses, succession process, knowledge, performance

Procedia PDF Downloads 210

Authors: Ayat-Allah Bouramdane

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Power generation from offshore wind energy does not emit carbon dioxide or other air pollutants and therefore play a role in reducing greenhouse gas emissions from the energy sector. In addition, these systems are considered more efficient than onshore wind farms, as they generate electricity from the wind blowing across the sea, thanks to the higher wind speed and greater consistency in direction due to the lack of physical interference that the land or human-made objects can present. This means offshore installations require fewer turbines to produce the same amount of energy as onshore wind farms. However, offshore wind farms require more complex infrastructure to support them and, as a result, are more expensive to construct. In addition, higher wind speeds, strong seas, and accessibility issues makes offshore wind farms more challenging to maintain. This study uses a combination of Geographic Referenced Information (GRI) and Analytic Hierarchy Process (AHP) to identify the most suitable sites for offshore wind farm development in Morocco, with a particular focus on the Dakhla city. A range of environmental, socio-economic, and technical criteria are taken into account to solve this complex Multi-Criteria Decision-Making (MCDM) problem. Based on experts' knowledge, a pairwise comparison matrix at each level of the hierarchy is performed, and fourteen sub-criteria belong to the main criteria have been weighted to generate the site suitability of offshore wind plants and obtain an in-depth knowledge on unsuitable areas, and areas with low-, moderate-, high- and very high suitability. We find that wind speed is the most decisive criteria in offshore wind farm development, followed by bathymetry, while proximity to facilities, the sediment thickness, and the remaining parameters show much lower weightings rendering technical parameters most decisive in offshore wind farm development projects. We also discuss the potential of other marine renewable energy potential, in Morocco, such as wave and tidal energy. The proposed approach and analysis can help decision-makers and can be applied to other countries in order to support the site selection process of offshore wind farms.

Keywords: analytic hierarchy process, dakhla, geographic referenced information, morocco, multi-criteria decision-making, offshore wind, site suitability

Procedia PDF Downloads 162

Authors: Orkide Donma, Mustafa M. Donma

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Basal metabolic rate (BMR) is widely used and an accepted measure of energy expenditure. Its principal determinant is body mass. However, this parameter is also correlated with a variety of other factors. The objective of this study is to measure BMR and compare it with the values obtained from predictive equations in adults classified according to their body mass index (BMI) values. 276 adults were included into the scope of this study. Their age, height and weight values were recorded. Five groups were designed based on their BMI values. First group (n = 85) was composed of individuals with BMI values varying between 18.5 and 24.9 kg/m². Those with BMI values varying from 25.0 to 29.9 kg/m² constituted Group 2 (n = 90). Individuals with 30.0-34.9 kg/m², 35.0-39.9 kg/m², > 40.0 kg/m² were included in Group 3 (n = 53), 4 (n = 28) and 5 (n = 20), respectively. The most commonly used equations to be compared with the measured BMR values were selected. For this purpose, the values were calculated by the use of four equations to predict BMR values, by name, introduced by Food and Agriculture Organization (FAO)/World Health Organization (WHO)/United Nations University (UNU), Harris and Benedict, Owen and Mifflin. Descriptive statistics, ANOVA, post-Hoc Tukey and Pearson’s correlation tests were performed by a statistical program designed for Windows (SPSS, version 16.0). p values smaller than 0.05 were accepted as statistically significant. Mean ± SD of groups 1, 2, 3, 4 and 5 for measured BMR in kcal were 1440.3 ± 210.0, 1618.8 ± 268.6, 1741.1 ± 345.2, 1853.1 ± 351.2 and 2028.0 ± 412.1, respectively. Upon evaluation of the comparison of means among groups, differences were highly significant between Group 1 and each of the remaining four groups. The values were increasing from Group 2 to Group 5. However, differences between Group 2 and Group 3, Group 3 and Group 4, Group 4 and Group 5 were not statistically significant. These insignificances were lost in predictive equations proposed by Harris and Benedict, FAO/WHO/UNU and Owen. For Mifflin, the insignificance was limited only to Group 4 and Group 5. Upon evaluation of the correlations of measured BMR and the estimated values computed from prediction equations, the lowest correlations between measured BMR and estimated BMR values were observed among the individuals within normal BMI range. The highest correlations were detected in individuals with BMI values varying between 30.0 and 34.9 kg/m². Correlations between measured BMR values and BMR values calculated by FAO/WHO/UNU as well as Owen were the same and the highest. In all groups, the highest correlations were observed between BMR values calculated from Mifflin and Harris and Benedict equations using age as an additional parameter. In conclusion, the unique resemblance of the FAO/WHO/UNU and Owen equations were pointed out. However, mean values obtained from FAO/WHO/UNU were much closer to the measured BMR values. Besides, the highest correlations were found between BMR calculated from FAO/WHO/UNU and measured BMR. These findings suggested that FAO/WHO/UNU was the most reliable equation, which may be used in conditions when the measured BMR values are not available.

Keywords: adult, basal metabolic rate, fao/who/unu, obesity, prediction equations

Procedia PDF Downloads 135

Authors: Tatjana Kochetkova

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This paper explores the pivotal role of environmental education, specifically outdoor education, in facilitating a psychological connection to nature among young adults. This research aims to contribute to building an empirical and conceptual basis of ecopsychology by providing a picture of psyche-nature interaction. It presents the results of the four-day connection-to-nature workshop. It intends to find out the effects of the awareness of nature on subjective well-being and perception of the meaning of life. This led to finding a battery-recharging effect of nature and the influence of nature at four levels of awareness: external physical perception, internal (bodily) sensation, emotions, and existential meaning. The research on the psychological bond of humans with the natural environment, the subject of ecopsychology, is still in its infancy. However, despite several courageous and fruitful attempts, there are still no direct answers to the fundamental questions about the way in which the natural environment influences humans and the specific role of nature in the human psyche. The urge to address this question was the primary reason for the current experiment. The methodology of this study was taken from the study of Patterson, and from White and Hendee. The methodology included a series of assignments on the perception of nature (the exercises are described in the attachment). Experiences were noted in a personal diary, which we used later for analysis. There are many trustworthy claims that contact with nature has positive effects on human subjective well-being and that it is of essential psychological and spiritual value. But, there is a need for more support and theoretical explanation for this phenomenon. As a contribution to filling these gaps, this qualitative study was conducted. The aim of this study is to explore the psychological effects of short-term awareness of wilderness on one’s subjective well-being and on one’s sense of the meaning of life. This specific study is based on the more general hypothesis that there are positive relationships between the experience of wilderness and the development of the self, feelings of community, and spiritual development. It restricted the study of the psychological effects of short term stay in nature to two variables (subjective well-being and the sense of meaning of life). The study aimed at (i) testing the hypothesis that there are positive effects of the awareness of wilderness on the subjective sense of well-being and meaning in life, (ii) understanding the nature of the psychological need for wilderness. Although there is a substantial amount of data on the psychological benefits of nature, we still lack a theory that explains the findings. The present research aims to contribute to such a theory. This is an experiment aimed specifically at the effects of nature on the sense of well-being and meaning in life.

Keywords: environmental education, psychological connection to nature, subjective well-being, symbolic meaning of nature, emotional reaction to nature, meaning of life

Procedia PDF Downloads 74

Authors: Hamed Ahari, Behrouz Akbari Adreghani, Vadood Razavilar, Amirali Anvar, Sima Moradi, Hourieh Shalchi

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Considering the ever increasing population and industrialization of the developmental trend of humankind's life, we are no longer able to detect the toxins produced in food products using the traditional techniques. This is due to the fact that the isolation time for food products is not cost-effective and even in most of the cases, the precision in the practical techniques like the bacterial cultivation and other techniques suffer from operator errors or the errors of the mixtures used. Hence with the advent of nanotechnology, the design of selective and smart sensors is one of the greatest industrial revelations of the quality control of food products that in few minutes time, and with a very high precision can identify the volume and toxicity of the bacteria. Methods and Materials: In this technique, based on the bacterial antibody connection to nanoparticle, a sensor was used. In this part of the research, as the basis for absorption for the recognition of bacterial toxin, medium sized silica nanoparticles of 10 nanometer in form of solid powder were utilized with Notrino brand. Then the suspension produced from agent-linked nanosilica which was connected to bacterial antibody was positioned near the samples of distilled water, which were contaminated with Staphylococcus aureus bacterial toxin with the density of 10-3, so that in case any toxin exists in the sample, a connection between toxin antigen and antibody would be formed. Finally, the light absorption related to the connection of antigen to the particle attached antibody was measured using spectrophotometry. The gene of 23S rRNA that is conserved in all Staphylococcus spp., also used as control. The accuracy of the test was monitored by using serial dilution (l0-6) of overnight cell culture of Staphylococcus spp., bacteria (OD600: 0.02 = 107 cell). It showed that the sensitivity of PCR is 10 bacteria per ml of cells within few hours. Result: The results indicate that the sensor detects up to 10-4 density. Additionally, the sensitivity of the sensors was examined after 60 days, the sensor by the 56 days had confirmatory results and started to decrease after those time periods. Conclusions: Comparing practical nano biosensory to conventional methods like that culture and biotechnology methods(such as polymerase chain reaction) is accuracy, sensitiveness and being unique. In the other way, they reduce the time from the hours to the 30 minutes.

Keywords: exotoxin, nanobiosensor, recognition, Staphylococcus aureus

Procedia PDF Downloads 388

Authors: Gabrielle Brand, Christopher Etherton-Beer

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The learning landscape of higher education environment is changing, with an increased focus over the past decade on how educators might begin to cultivate reflective skills in health professions students. In addition, changing professional requirements demand that health professionals are adequately prepared to practice in today’s complex Australian health care systems, including responding to changing demographics of population ageing. To counteract a widespread perception of health professions students’ disinterest in caring for older persons, the authors will report on an exploratory, mixed method research study that used photographs, narrative and small group work to enhance medical and nursing students’ reflective learning experience. An innovative photo-elicitation technique and reflective questioning prompts were used to increase engagement, and challenge students to consider new perspectives (around ageing) by constructing shared storylines in small groups. The qualitative themes revealed how photographs, narratives and small group work created learning spaces for reflection whereby students could safely explore their own personal and professional values, beliefs and perspectives around ageing. By providing the space for reflection, the students reported how they found connection and meaning in their own learning through a process of self-exploration that often challenged their assumptions of both older people and themselves as future health professionals. By integrating cognitive and affective elements into the learning process, this research demonstrates the importance of embedding visual methodologies that enhance reflection and transformative learning. The findings highlight the importance of integrating the arts into predominantly empirically driven health professional curricula and can be used as a catalyst for individual and/or collective reflection which can potentially enhance empathy, insight and understanding of the lived experiences of older patients. Based on these findings, the authors have developed ‘Depth of Field: Exploring Ageing’ an innovative, interprofessional, digital reflective learning resource that uses Prezi Inc. software (storytelling tool that presents ideas on a virtual canvas) to enhance students’ reflective capacity in the higher education environment.

Keywords: narrative, photo-elicitation, reflective learning, qualitative research

Procedia PDF Downloads 288

Authors: Mei Lin, Chang Liu

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Argumentative writing is the most prevalent genre in diverse writing tests. How to construct academic arguments is often regarded as a difficult task by most English as a foreign language (EFL) learners. A failure to generate enough ideas and organise them coherently and logically as well as a lack of competence in supporting their arguments with relevant evidence are frequent problems faced by EFL learners when approaching an English argumentative writing task. Overall, these problems are closely related to planning, and planning an argumentative writing at pre-writing stage plays a vital role in a good academic essay. However, how teachers can effectively guide students to generate ideas is rarely discussed in planning English argumentative writing, apart from brainstorming. Brainstorming has been a common practice used by teachers to help students generate ideas. However, some limitations of brainstorming suggest that it can help students generate many ideas, but ideas might not necessarily be coherent and logic, and could sometimes impede production. It calls for a need to explore effective instructional strategies at pre-writing stage of English argumentative writing. This paper will first examine how a Six Thinking Hats approach can be used to provide a dialogic space for EFL learners to experience and collaboratively generate ideas from multiple perspectives at pre-writing stage. Part of the findings of the impact of a twelve-week intervention (from March to July 2021) on students learning to generate ideas through engaging in group discussions of using Six Thinking Hats will then be reported. The research design is based on the sociocultural theory. The findings present evidence from a mixed-methods approach and fifty-nine participants from two first-year undergraduate natural classes in a Chinese university. Analysis of pre- and post- questionnaires suggests that participants had a positive attitude toward the Six Thinking Hats approach. It fosters their understanding of prewriting and argumentative writing, helps them to generate more ideas not only from multiple perspectives but also in a systematic way. A comparison of participants writing plans confirms an improvement in generating counterarguments and rebuttals to support their arguments. Above all, visual and transcripts data of group discussion collected from different weeks throughout the intervention enable teachers and researchers to ‘see’ the hidden process of learning to generate ideas in action.

Keywords: argumentative writing, innovative pedagogy, six thinking hats, dialogic space, prewriting, higher education

Procedia PDF Downloads 89

Authors: R. Clancy, M. Ahern, D. O’Sullivan, K. Bruton

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The manufacturing industry is currently undergoing a digital transformation as part of the mega-trend Industry 4.0. As part of this phase of the industrial revolution, traditional manufacturing processes are being combined with digital technologies to achieve smarter and more efficient production. To successfully digitally transform a manufacturing facility, the processes must first be digitized. This is the conversion of information from an analogue format to a digital format. The objective of this study was to explore the research area of digitizing manufacturing data as part of the worldwide paradigm, Industry 4.0. The formal methodology of a systematic mapping study was utilized to capture a representative sample of the research area and assess its current state. Specific research questions were defined to assess the key benefits and limitations associated with the digitization of manufacturing data. Research papers were classified according to the type of research and type of contribution to the research area. Upon analyzing 54 papers identified in this area, it was noted that 23 of the papers originated in Germany. This is an unsurprising finding as Industry 4.0 is originally a German strategy with supporting strong policy instruments being utilized in Germany to support its implementation. It was also found that the Fraunhofer Institute for Mechatronic Systems Design, in collaboration with the University of Paderborn in Germany, was the most frequent contributing Institution of the research papers with three papers published. The literature suggested future research directions and highlighted one specific gap in the area. There exists an unresolved gap between the data science experts and the manufacturing process experts in the industry. The data analytics expertise is not useful unless the manufacturing process information is utilized. A legitimate understanding of the data is crucial to perform accurate analytics and gain true, valuable insights into the manufacturing process. There lies a gap between the manufacturing operations and the information technology/data analytics departments within enterprises, which was borne out by the results of many of the case studies reviewed as part of this work. To test the concept of this gap existing, the researcher initiated an industrial case study in which they embedded themselves between the subject matter expert of the manufacturing process and the data scientist. Of the papers resulting from the systematic mapping study, 12 of the papers contributed a framework, another 12 of the papers were based on a case study, and 11 of the papers focused on theory. However, there were only three papers that contributed a methodology. This provides further evidence for the need for an industry-focused methodology for digitizing and analyzing manufacturing data, which will be developed in future research.

Keywords: analytics, digitization, industry 4.0, manufacturing

Procedia PDF Downloads 114

Authors: Flavien Marteau, Pedro Affonso Nóbrega, Pascal Biwole, Nicolas Autrusson, Iona De Bievre, Christian Beauger

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Effective water management is essential for the optimal performance of fuel cells. For this reason, many vehicle systems use a membrane humidifier, a passive device that humidifies the air before the cathode inlet. Although they offer good performance, humidifiers are voluminous, costly, and fragile, hence the desire to find an alternative. Direct water injection could be an option, although this method lacks maturity. It consists of injecting liquid water as a spray in the dry heated air coming out from the compressor. This work focuses on the evaluation of direct water injection and its performance compared to the membrane humidifier selected as a reference. Two architectures were experimentally tested to humidify an industrial 2 kW short stack made up of 20 cells of 150 cm² each. For the reference architecture, the inlet air is humidified with a commercial membrane humidifier. For the direct water injection architecture, a pneumatic nozzle was selected to generate a fine spray in the air flow with a Sauter mean diameter of about 20 μm. Initial performance was compared over the entire range of current based on polarisation curves. Then, the influence of various parameters impacting water management was studied, such as the temperature, the gas stoichiometry, and the water injection flow rate. The experimental results obtained confirm the possibility of humidifying the fuel cell using direct water injection. This study, however shows the limits of this humidification method, the mean cell voltage being significantly lower in some operating conditions with direct water injection than with the membrane humidifier. The voltage drop reaches 30 mV per cell (4 %) at 1 A/cm² (1,8 bara, 80 °C) and increases in more demanding humidification conditions. It is noteworthy that the heat of compression available is not enough to evaporate all the injected liquid water in the case of DWI, resulting in a mix of liquid and vapour water entering the fuel cell, whereas only vapour is present with the humidifier. Variation of the injection flow rate shows that part of the injected water is useless for humidification and seems to cross channels without reaching the membrane. The stack was successfully humidified thanks to direct water injection. Nevertheless, our work shows that its implementation requires substantial adaptations and may reduce the fuel cell stack performance when compared to conventional membrane humidifiers, but opportunities for optimisation have been identified.

Keywords: cathode humidification, direct water injection, membrane humidifier, proton exchange membrane fuel cell

Procedia PDF Downloads 47

Authors: Diana Islam, Juan Fang, Vito Fanelli, Bing Han, Julie Khang, Jianfeng Wu, Arthur S. Slutsky, Haibo Zhang

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Introduction: MSC delivery in preclinical models of ARDS has demonstrated significant improvements in lung function and recovery from acute injury. However, the role of MSC delivery in ARDS associated pulmonary fibrosis is not well understood. Some animal studies using bleomycin, asbestos, and silica-induced pulmonary fibrosis show that MSC delivery can suppress fibrosis. While other animal studies using radiation induced pulmonary fibrosis, liver, and kidney fibrosis models show that MSC delivery can contribute to fibrosis. Hypothesis: The beneficial and deleterious effects of MSC in ARDS are modulated by the lung microenvironment at the time of MSC delivery. Methods: To induce ARDS a two-hit mouse model of Hydrochloric acid (HCl) aspiration (day 0) and mechanical ventilation (MV) (day 2) was used. HCl and injurious MV generated fibrosis within 14-28 days. 0.5x106 mouse MSCs were delivered (via both intratracheal and intravenous routes) either in the active inflammatory phase (day 2) or during the remodeling phase (day 14) of ARDS (mouse fibroblasts or PBS used as a control). Lung injury accessed using inflammation score and elastance measurement. Pulmonary fibrosis was accessed using histological score, tissue collagen level, and collagen expression. In addition alveolar epithelial (E) and mesenchymal (M) marker expression profile was also measured. All measurements were taken at day 2, 14, and 28. Results: MSC delivery 2 days after HCl exacerbated lung injury and fibrosis compared to HCl alone, while the day 14 delivery showed protective effects. However in the absence of HCl, MSC significantly reduced the injurious MV-induced fibrosis. HCl injury suppressed E markers and up-regulated M markers. MSC delivery 2 days after HCl further amplified M marker expression, indicating their role in myofibroblast proliferation/activation. While with 14-day delivery E marker up-regulation was observed indicating their role in epithelial restoration. Conclusions: Early MSC delivery can be protective of injurious MV. Late MSC delivery during repair phase may also aid in recovery. However, early MSC delivery during the exudative inflammatory phase of HCl-induced ARDS can result in pro-fibrotic profiles. It is critical to understand the interaction between MSC and the lung microenvironment before MSC-based therapies are utilized for ARDS.

Keywords: acute respiratory distress syndrome (ARDS), mesenchymal stem cells (MSC), hydrochloric acid (HCl), mechanical ventilation (MV)

Procedia PDF Downloads 672

Authors: V. I. Kozyavkin, L. F. Shestopalova, T. B. Voloshyn

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Introduction: Rehabilitation of children with Autism is the issue of the day in psychiatry and neurology. It is attributed to constantly increasing quantity of autistic children - Autistic Spectrum Disorders (ASD) Existing rehabilitation approaches in treatment of children with Autism improve their medico- social and social- psychological adjustment. Experience of treatment for different kinds of Autistic disorders in International Clinic of Rehabilitation (ICR) reveals the necessity of complex intensive approach for healing this malady and wider implementation of a Kozyavkin method for treatment of children with ASD. Methods: 19 children aged from 3 to 14 years were examined. They were diagnosed ‘Autism’ (F84.0) with comorbid neurological pathology (from pyramidal insufficiency to para- and tetraplegia). All patients underwent rehabilitation in ICR during two weeks, where INRS approach was used. INRS included methods like biomechanical correction of the spine, massage, physical therapy, joint mobilization, wax-paraffin applications. They were supplemented by art- therapy, ergotherapy, rhythmical group exercises, computer game therapy, team Olympic games and other methods for improvement of motivation and social integration of the child. Estimation of efficacy was conducted using parent’s questioning and done twice- on the onset of INRS rehabilitation course and two weeks afterward. For efficacy assessment of rehabilitation of autistic children in ICR standardized tool was used, namely Autism Treatment Evaluation Checklist (ATEC). This scale was selected because any rehabilitation approaches for the child with Autism can be assessed using it. Results: Before the onset of INRS treatment mean score according to ATEC scale was 64,75±9,23, it reveals occurrence in examined children severe communication, speech, socialization and behavioral impairments. After the end of the rehabilitation course, the mean score was 56,5±6,7, what indicates positive dynamics in comparison to the onset of rehabilitation. Generally, improvement of psychoemotional state occurred in 90% of cases. Most significant changes occurred in the scope of speech (16,5 before and 14,5 after the treatment), socialization (15.1 before and 12,5 after) and behavior (20,1 before and 17.4 after). Conclusion: As a result of INRS rehabilitation course reduction of autistic symptoms was noted. Particularly improvements in speech were observed (children began to spell out new syllables, words), there was some decrease in signs of destructiveness, quality of contact with the surrounding people improved, new skills of self-service appeared. The prospect of the study is further, according to evidence- based medicine standards, deeper examination of INRS and assessment of its usefulness in treatment for Autism and ASD.

Keywords: intensive neurophysiological rehabilitation system (INRS), international clinic od rehabilitation, ASD, rehabilitation

Procedia PDF Downloads 172

Authors: Fernando Nobre Cavalcante

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In Brazil, and more recently in the city of Fortaleza, there is a new form of entrepreneurship that is focused on the information and communication technology service sector and that draws the attention of young people, investors, governments, authors and media companies: it is known as the start-up movement. Today, it is considered to be a driving force behind the creative economy. Rooted on progressive discourse, the words enterprise and innovation seduce new economic agents motivated by success stories from Silicon Valley in America along with increasing commercial activity for digital goods and services. This article assesses, from a sociological point of view, the new productive wave problematized by the light of Manuel Castells’ informational capitalism. Considering the skeptical as well as the optimistic opinions about the impact of this new entrepreneurial rearrangement, the following question is asked: How Brazilian entrepreneurs evaluate public policy incentives for startups Brazilian Federal Government? The raised hypotheses are based on employability factors as well as cultural, economical, and political matters related to innovation and technology. This study has produced a nationwide quantitative assessment with a special focus on the reality of these Ceará firms; as well as comparative qualitative interviews on Brazilian experiences lived by identified agents. This article outlines the public incentive policy of the federal government, the Start-up Brasil Program, from the perspective of these companies and provides details as to the discipline methods of the new enterprising way born in the United States. The startups are very young companies that are headed towards the economic sustainment of the productive sector services. These companies are dropping the seeds that will produce the re-enchantment of young people and bring them back to participation in political debate; they provide relief and reheats the job market; and they produce a democratization of the entrepreneurial ‘Do-It-Yourself’ culture. They capitalize the pivot of the wall street wolves and of agents being charged for new masks. There are developmental logic’s prophylaxis in the face of dreadful innovation stagnation. The lack of continuity in Brazilian governmental politics and cultural nuances related to entrepreneurship are barring the desired regional success of this ecosystem.

Keywords: creative economy, entrepreneurship, informationalism, innovation, startups, start-up brasil program

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Authors: Kamran Jawed, Anu Jose Mattam, Zia Fatma, Saima Wajid, Malik Z. Abdin, Syed Shams Yazdani

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Worldwide demand of natural and sustainable fuels and chemicals have encouraged researchers to develop microbial platform for synthesis of short chain fatty acids as they are useful precursors to replace petroleum-based fuels and chemicals. In this study, we evaluated the role of fatty acid synthesis and β-oxidation cycle of Escherichia coli to produce butyric acid, a 4-carbon short chain fatty acid, with the help of three thioesterases, i.e., TesAT from Anaerococcus tetradius, TesBF from Bryantella formatexigens and TesBT from Bacteroides thetaiotaomicron. We found that E. coli strain transformed with gene for TesBT and grown in presence of 8 g/L glucose produced maximum butyric acid titer at 1.46 g/L, followed by that of TesBF at 0.85 g/L and TesAT at 0.12 g/L, indicating that these thioesterases were efficiently converting short chain fatty acyl-ACP intermediate of fatty acid synthesis pathway into the corresponding acid. The titer of butyric acid varied significantly depending upon the plasmid copy number and strain genotype. Deletion of genes for fatty acyl-CoA synthetase and acyl-CoA dehydrogenase, which are involved in initiating the fatty acid degradation cycle, and overexpression of FadR, which is a dual transcriptional regulator and exerts negative control over fatty acid degradation pathway, reduced up to 30% of butyric acid titer. This observation suggested that β-oxidation pathway is working synergistically with fatty acid synthesis pathway in production of butyric acid. Moreover, accelerating the fatty acid elongation cycle by overexpressing acetyl-CoA carboxyltransferase (Acc) and 3-hydroxy-acyl-ACP dehydratase (FabZ) or by deleting FabR, the transcription suppressor of elongation, did not improve the butyric acid titer, rather favored the long chain fatty acid production. Finally, a balance between cell growth and butyric acid production was achieved with the use of phosphorous limited growth medium and 14.3 g/L butyric acid, and 17.5 g/L total free fatty acids (FFAs) titer was achieved during fed-batch cultivation. We have engineered an E. coli strain which utilizes the intermediate of both fatty acid synthesis and degradation pathway, i.e. butyryl-ACP and -CoA, to produce butyric acid from glucose. The strategy used in this study resulted in highest reported titers of butyric acid and FFAs in engineered E. coli.

Keywords: butenoic acid, butyric acid, Escherichia coli, fed-batch fermentation, short chain fatty acids, thioesterase

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Authors: Fikret Yalcinkaya, Hamza Unsal

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To understand how neurons work, it is required to combine experimental studies on neural science with numerical simulations of neuron models in a computer environment. In this regard, the simplicity and applicability of spiking neuron modeling functions have been of great interest in computational neuron science and numerical neuroscience in recent years. Spiking neuron models can be classified by exhibiting various neuronal behaviors, such as spiking and bursting. These classifications are important for researchers working on theoretical neuroscience. In this paper, three different spiking neuron models; Izhikevich, Adaptive Exponential Integrate Fire (AEIF) and Hindmarsh Rose (HR), which are based on first order differential equations, are discussed and compared. First, the physical meanings, derivatives, and differential equations of each model are provided and simulated in the Matlab environment. Then, by selecting appropriate parameters, the models were visually examined in the Matlab environment and it was aimed to demonstrate which model can simulate well-known biological neuron behaviours such as Tonic Spiking, Tonic Bursting, Mixed Mode Firing, Spike Frequency Adaptation, Resonator and Integrator. As a result, the Izhikevich model has been shown to perform Regular Spiking, Continuous Explosion, Intrinsically Bursting, Thalmo Cortical, Low-Threshold Spiking and Resonator. The Adaptive Exponential Integrate Fire model has been able to produce firing patterns such as Regular Ignition, Adaptive Ignition, Initially Explosive Ignition, Regular Explosive Ignition, Delayed Ignition, Delayed Regular Explosive Ignition, Temporary Ignition and Irregular Ignition. The Hindmarsh Rose model showed three different dynamic neuron behaviours; Spike, Burst and Chaotic. From these results, the Izhikevich cell model may be preferred due to its ability to reflect the true behavior of the nerve cell, the ability to produce different types of spikes, and the suitability for use in larger scale brain models. The most important reason for choosing the Adaptive Exponential Integrate Fire model is that it can create rich ignition patterns with fewer parameters. The chaotic behaviours of the Hindmarsh Rose neuron model, like some chaotic systems, is thought to be used in many scientific and engineering applications such as physics, secure communication and signal processing.

Keywords: Izhikevich, adaptive exponential integrate fire, Hindmarsh Rose, biological neuron behaviours, spiking neuron models

Procedia PDF Downloads 184

Authors: Xiaohong Li, Wenfan Yan

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Background: While it is widely considered that the university library plays a critical role in fulfilling the institution's mission and providing students’ learning experience beyond the classrooms, how the technology-enhanced library reform changed college students’ learning experience hasn’t been thoroughly investigated. The purpose of this study is to explore how technology-enhanced library reform affects students’ learning experience and career readiness and further identify the factors and effective conditions that enable the quality learning outcome of Chinese college students. Methodologies: This study selected the qualitative comparative analysis (QCA) method to explore the effects of technology-enhanced university library reform on college students’ learning experience and career readiness. QCA is unique in explaining the complex relationship between multiple factors from a holistic perspective. Compared with the traditional quantitative and qualitative analysis, QCA not only adds some quantitative logic but also inherits the characteristics of qualitative research focusing on the heterogeneity and complexity of samples. Shenyang Normal University (SNU) selected a sample of the typical comprehensive university in China that focuses on students’ learning and application of professional knowledge and trains professionals to different levels of expertise. A total of 22 current university students and 30 graduates who joined the Library Readers Association of SNU from 2011 to 2019 were selected for semi-structured interviews. Based on the data collected from these participating students, qualitative comparative analysis (QCA), including univariate necessity analysis and the multi-configuration analysis, was conducted. Findings and Discussion: QCA analysis results indicated that the influence of technology-enhanced university library restructures and reorganization on student learning experience and career readiness is the result of multiple factors. Technology-enhanced library equipment and other hardware restructured to meet the college students learning needs and have played an important role in improving the student learning experience and learning persistence. More importantly, the soft characteristics of technology-enhanced library reform, such as library service innovation space and culture space, have a positive impact on student’s career readiness and development. Technology-enhanced university library reform is not only the change in the building's appearance and facilities but also in library service quality and capability. The study also provides suggestions for policy, practice, and future research.

Keywords: career readiness, college student learning experience, qualitative comparative analysis (QCA), technology-enhanced library reform

Procedia PDF Downloads 83

Authors: Saifalarab A. Mohmmed, Morgana E. Vianna, Jonathan C. Knowles

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The issue of apical periodontitis has received considerable critical attention. Bacteria is integrated into communities, attached to surfaces and consequently form biofilm. The biofilm structure provides bacteria with a series protection skills against, antimicrobial agents and enhances pathogenicity (e.g. apical periodontitis). Sodium hypochlorite (NaOCl) has become the irrigant of choice for elimination of bacteria from the root canal system based on its antimicrobial findings. The aim of the study was to investigate the effect of different agitation techniques on the efficacy of 2.5% NaOCl to eliminate the biofilm from the surface of the lateral canal using the residual biofilm, and removal rate of biofilm as outcome measures. The effect of canal complexity (lateral canal) on the efficacy of the irrigation procedure was also assessed. Forty root canal models (n = 10 per group) were manufactured using 3D printing and resin materials. Each model consisted of two halves of an 18 mm length root canal with apical size 30 and taper 0.06, and a lateral canal of 3 mm length, 0.3 mm diameter located at 3 mm from the apical terminus. E. faecalis biofilms were grown on the apical 3 mm and lateral canal of the models for 10 days in Brain Heart Infusion broth. Biofilms were stained using crystal violet for visualisation. The model halves were reassembled, attached to an apparatus and tested under a fluorescence microscope. Syringe and needle irrigation protocol was performed using 9 mL of 2.5% NaOCl irrigant for 60 seconds. The irrigant was either left stagnant in the canal or activated for 30 seconds using manual (gutta-percha), sonic and ultrasonic methods. Images were then captured every second using an external camera. The percentages of residual biofilm were measured using image analysis software. The data were analysed using generalised linear mixed models. The greatest removal was associated with the ultrasonic group (66.76%) followed by sonic (45.49%), manual (43.97%), and passive irrigation group (control) (38.67%) respectively. No marked reduction in the efficiency of NaOCl to remove biofilm was found between the simple and complex anatomy models (p = 0.098). The removal efficacy of NaOCl on the biofilm was limited to the 1 mm level of the lateral canal. The agitation of NaOCl results in better penetration of the irrigant into the lateral canals. Ultrasonic agitation of NaOCl improved the removal of bacterial biofilm.

Keywords: 3D printing, biofilm, root canal irrigation, sodium hypochlorite

Procedia PDF Downloads 233

Authors: Atefe Malekkhani, Lee Beattie, Mohsen Mohammadzadeh

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Unprecedented growth of megacities and urban areas all around the world have resulted in numerous risks, concerns, and problems across various aspects of urban life, including environmental, social, and economic domains like climate change, spatial and social inequalities. In this situation, ever-increasing progress of technology has created a hope for urban authorities that the negative effects of various socio-economic and environmental crises can potentially be mitigated with the use of information and communication technologies. The concept of 'smart city' represents an emerging solution to urban challenges arising from increased urbanization using ICTs. However, smart cities are often perceived primarily as technological initiatives and are implemented without considering the social and cultural contexts of cities and the needs of their residents. The implementation of smart city projects and initiatives has the potential to (un)intentionally exacerbate pre-existing social, spatial, and cultural segregation. Investigating the impact of smart city on social capital of people who are users of smart city systems and with governance as policymakers is worth exploring. The importance of inhabitants to the existence and development of smart cities cannot be overlooked. This concept has gained different perspectives in the smart city studies. Reviewing the literature about social capital and smart city show that social capital play three different roles in smart city development. Some research indicates that social capital is a component of a smart city and has embedded in its dimensions, definitions, or strategies, while other ones see it as a social outcome of smart city development and point out that the move to smart cities improves social capital; however, in most cases, it remains an unproven hypothesis. Other studies show that social capital can enhance the functions of smart cities, and the consideration of social capital in planning smart cities should be promoted. Despite the existing theoretical and practical knowledge, there is a significant research gap reviewing the knowledge domain of smart city studies through the lens of social capital. To shed light on this issue, this study aims to explore the domain of existing research in the field of smart city through the lens of social capital. This research will use the 'Preferred Reporting Items for Systematic Reviews and Meta-Analyses' (PRISMA) method to review relevant literature, focusing on the key concepts of 'Smart City' and 'Social Capital'. The studies will be selected Web of Science Core Collection, using a selection process that involves identifying literature sources, screening and filtering studies based on titles, abstracts, and full-text reading.

Keywords: smart city, urban digitalisation, ICT, social capital

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Authors: Jung-En Kuan, Whei-Fen Wu

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In this study, a symbiotic bacteria from yellow mealworm's (Tenebrio molitor) mid-gut was isolated with characteristics of growth on minimal-tributyrin medium. After a PCR-amplification of its 16s rDNA, the resultant nucleotide sequences were then analyzed by schemes of the phylogeny trees. Accordingly, it was designated as Pseudomonas nitroreducens D-01. Next, by searching the lipolytic enzymes in its protein data bank, one of those potential lipolytic α/β hydrolases was identified, again using PCR-amplification and nucleotide-sequencing methods. To construct an expression of this lipolytic gene in plasmids, the target-gene primers were then designed, carrying the C-terminal his-tag sequences. Using the vector pET21a, a recombinant lipolytic hydrolase D gene with his-tag nucleotides was successfully cloned into it, of which the lipolytic D gene is under a control of the T7 promoter. After transformation of the resultant plasmids into Eescherichia coli BL21 (DE3), an IPTG inducer was used for the induction of the recombinant proteins. The protein products were then purified by metal-ion affinity column, and the purified proteins were found capable of forming a clear zone on tributyrin agar plate. Shortly, its enzyme activities were determined by degradation of p-nitrophenyl ester(s), and the substantial yellow end-product, p-nitrophenol, was measured at O.D.405 nm. Specifically, this lipolytic enzyme efficiently targets p-nitrophenyl butyrate. As well, it shows the most reactive activities at 40°C, pH 8 in potassium phosphate buffer. In thermal stability assays, the activities of this enzyme dramatically drop when the temperature is above 50°C. In metal ion assays, MgCl₂ and NH₄Cl induce the enzyme activities while MnSO₄, NiSO₄, CaCl₂, ZnSO₄, CoCl₂, CuSO₄, FeSO₄, and FeCl₃ reduce its activities. Besides, NaCl has no effects on its enzyme activities. Most organic solvents decrease the activities of this enzyme, such as hexane, methanol, ethanol, acetone, isopropanol, chloroform, and ethyl acetate. However, its enzyme activities increase when DMSO exists. All the surfactants like Triton X-100, Tween 80, Tween 20, and Brij35 decrease its lipolytic activities. Using Lineweaver-Burk double reciprocal methods, the function of the enzyme kinetics were determined such as Km = 0.488 (mM), Vmax = 0.0644 (mM/min), and kcat = 3.01x10³ (s⁻¹), as well the total efficiency of kcat/Km is 6.17 x10³ (mM⁻¹/s⁻¹). Afterwards, based on the phylogenetic analyses, this lipolytic protein is classified to type IV lipase by its homologous conserved region in this lipase family.

Keywords: enzyme, esterase, lipotic hydrolase, type IV

Procedia PDF Downloads 134

Authors: Riddhiman Sherlekar, Umang Paladia, Rachit Desai, Yash Patel

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A number of surfactants which exhibit ultra-low interfacial tension and an excellent microemulsion phase behavior with crude oils of low to medium gravity are not sufficiently soluble at optimum salinity to produce stable aqueous solutions. Such solutions often show phase separation after a few days at reservoir temperature, which does not suffice the purpose and the time is short when compared to the residence time in a reservoir for a surfactant flood. The addition of polymer often exacerbates the problem although the poor stability of the surfactant at high salinity remains a pivotal issue. Surfactants such as SDS, Ctab with large hydrophobes produce lowest IFT, but are often not sufficiently water soluble at desired salinity. Hydrophilic co-solvents and/or co-surfactants are needed to make the surfactant-polymer solution stable at the desired salinity. This study focuses on contrasting the effect of addition of a co-solvent in stability of a surfactant –oil emulsion. The idea is to use a co-surfactant to increase stability of an emulsion. Stability of the emulsion is enhanced because of creation of micro-emulsion which is verified both visually and with the help of particle size analyzer at varying concentration of salinity, surfactant and co-surfactant. A lab-experimental method description is provided and the method is described in detail to permit readers to emulate all results. The stability of the oil-water emulsion is visualized with respect to time, temperature, salinity of the brine and concentration of the surfactant. Nonionic surfactant TX-100 when used as a co-surfactant increases the stability of the oil-water emulsion. The stability of the prepared emulsion is checked by observing the particle size distribution. For stable emulsion in volume% vs particle size curve, the peak should be obtained for particle size of 5-50 nm while for the unstable emulsion a bigger sized particles are observed. The UV-Visible spectroscopy is also used to visualize the fraction of oil that plays important role in the formation of micelles in stable emulsion. This is important as the study will help us to decide applicability of the surfactant based EOR method for a reservoir that contains a specific type of crude. The use of nonionic surfactant as a co-surfactant would also increase the efficiency of surfactant EOR. With the decline in oil discoveries during the last decades it is believed that EOR technologies will play a key role to meet the energy demand in years to come. Taking this into consideration, the work focuses on the optimization of the secondary recovery(Water flooding) with the help of surfactant and/or co-surfactants by creating desired conditions in the reservoir.

Keywords: co-surfactant, enhanced oil recovery, micro-emulsion, surfactant flooding

Procedia PDF Downloads 256

Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

Procedia PDF Downloads 127

Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

Procedia PDF Downloads 82

Authors: N. Balaban, A. Buernstein, F. Gelman, Z. Ronen

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Brominated flame retardants are widespread pollutants, and are known to be toxic, carcinogenic, endocrinic disrupting as well as recalcitrant. The industrial complex Neot Hovav, in the Northern Negev, Israel, is situated above a fractured chalk aquitard, which is polluted by a wide variety of halogenated organic compounds. Two of the abundant pollutants found in the site are Dibromoneopentyl-glycol (DBNPG) and tribromoneopentyl-alcohol (TBNPA). Due to the elusive nature of the groundwater flow, it is difficult to connect between the spatial changes in contaminant concentrations to degradation. In this study, we attempt to determine whether these compounds are biodegraded in the groundwater, and to gain a better understanding concerning the bacterial community in the groundwater. This was achieved through the application of compound-specific isotope analysis (CSIA) of carbon (13^C/12^C) and bromine (81^Br/79^Br), and new-generation MiSeq pyrosequencing. The sampled boreholes were distributed among three main areas of the industrial complex: around the production plant of TBNPA and DBNPG; along the Hovav Wadi (small ephemeral stream) which crosses and drains the industrial complex; and downstream to the industrial area. TBNPA and DBNPG are found in all three areas, with no clear connection to the proximity of the borehole to the production plant. Initial isotopic data of TBNPA from boreholes in the area surrounding the production plant, reveal no changes in the carbon and bromine isotopic values. When observing the microbial groundwater community, the dominant phylum is Proteobacteria. Known anaerobic dehalogenating bacteria such as Dehalococcoides from the Chloroflexi phylum have also been detected. A statistical comparison of the groundwater microbial diversity using a multi-variant ordination of non-metric multidimensional scaling (NMDS) reveals three main clusters in accordance to spatial location in the industrial complex: all the boreholes sampled adjacent to the production plant cluster together and separately from the Wadi Hovav boreholes cluster and the downstream to the industrial area borehole cluster. This work provides the basis for the development and implication of an isotopic fractionation based tool for assessing the biodegradation of brominated organic compounds in contaminated environments, and a novel attempt to characterize the spatial microbial diversity in the contaminated site.

Keywords: biodegradation, brominated flame retardants, groundwater, isotopic fractionation, microbial diversity

Procedia PDF Downloads 237

Authors: Adem Peker, Yüksel Eroğlu, İsmail Ay

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As the information and communication technologies have become embedded in everyday life of adolescents, both their possible benefits and risks to adolescents are being identified. The information and communication technologies provide opportunities for adolescents to connect with peers and to access to information. However, as with other social connections, users of information and communication devices have the potential to meet and interact with in harmful ways. One emerging example of such interaction is cyber bullying. Cyber bullying occurs when someone uses the information and communication technologies to harass or embarrass another person. Cyber bullying can take the form of malicious text messages and e-mails, spreading rumours, and excluding people from online groups. Cyber bullying has been linked to psychological problems for cyber bullies and victims. Therefore, it is important to determine how internet addiction contributes to cyber bullying. Building on this question, this study takes a closer look at the relationship between internet addiction and cyber bullying. For this purpose, in this study, based on descriptive relational model, it was hypothesized that loss of control, excessive desire to stay online, and negativity in social relationships, which are dimensions of internet addiction, would be associated positively with cyber bullying and victimization. Participants were 383 high school students (176 girls and 207 boys; mean age, 15.7 years). Internet addiction was measured by using Internet Addiction Scale. The Cyber Victim and Bullying Scale was utilized to measure cyber bullying and victimization. The scales were administered to the students in groups in the classrooms. In this study, stepwise regression analyses were utilized to examine the relationships between dimensions of internet addiction and cyber bullying and victimization. Before applying stepwise regression analysis, assumptions of regression were verified. According to stepwise regression analysis, cyber bullying was predicted by loss of control (β=.26, p<.001) and negativity in social relationships (β=.13, p<.001). These variables accounted for 9 % of the total variance, with the loss of control explaining the higher percentage (8 %). On the other hand, cyber victimization was predicted by loss of control (β=.19, p<.001) and negativity in social relationships (β=.12, p<.001). These variables altogether accounted for 8 % of the variance in cyber victimization, with the best predictor loss of control (7 % of the total variance). The results of this study demonstrated that, as expected, loss of control and negativity in social relationships predicted cyber bullying and victimization positively. However, excessive desire to stay online did not emerge a significant predictor of both cyberbullying and victimization. Consequently, this study would enhance our understanding of the predictors of cyber bullying and victimization since the results proposed that internet addiction is related with cyber bullying and victimization.

Keywords: cyber bullying, internet addiction, adolescents, regression

Procedia PDF Downloads 314

Authors: Fatemeh Elmi, Zahra Etemadifar

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Improvement of soil mechanical properties is crucial before its use in construction, as the low mechanical strength and unstable structure of soil in many parts of the world can lead to the destruction of engineering infrastructure, resulting in financial and human losses. Although, conventional methods, such as chemical injection, are often utilized to enhance soil strength and stiffness, they are generally expensive, require heavy machinery, and cause significant environmental effects due to chemical usage, and also disrupt urban infrastructure. Moreover, they are not suitable for treating large volume of soil. Recently, an alternative method to improve various soil properties, including strength, hardness, and permeability, has received much attention: the application of biological methods. One of the most widely used is biocementation, which is based on the microbial precipitation of calcium carbonte crystalls using ureolytic bacteria However, there are still limitations to its large-scale use that need to be resolved before it can be commercialized. These issues have not received enough attention in prior research. One limitation of MICP (microbially induced calcium carbonate precipitation) is that microorganisms cannot operate effectively in harsh and variable environments, unlike the controlled conditions of a laboratory. Another limitation of applying this technique on a large scale is the high cost of producing a substantial amount of bacterial culture and reagents required for soil treatment. Therefore, the purpose of the present study was to investigate soil improvement using the biocementation activity of poly-extremophile, calcium carbonate crystal- producing bacterial strain, Bhargavaea cecembensis N1, in whey as an inexpensive medium. This strain was isolated and molecularly identified from sandy soils in our previous research, and its 16S rRNA gene sequences was deposited in the NCBI Gene Bank with an accession number MK420385. This strain exhibited a high level of urease activity (8.16 U/ml) and produced a large amount of calcium carbonate (4.1 mg/ ml). It was able to improve the soil by increasing the compressive strength up to 205 kPa and reducing permeability by 36%, with 20% of the improvement attributable of calcium carbonate production. This was achieved using this strain in a whey culture medium. This strain can be an eco-friendly and economical alternative to conventional methods in soil stabilization, and other MICP related applications.

Keywords: biocementation, Bhargavaea cecembensis, soil improvement, whey culture medium

Procedia PDF Downloads 58

Authors: Yagya Murti Aryal, Bipin Adhikari, Pradeep Gyawali

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The Lesser Himalaya zone of Nepal consists of thrusting and folding belts, which play an important role in the sustainable management of groundwater in the Himalayan regions. The study area is located in the Dolakha and Ramechhap Districts of Bagmati Province, Nepal. Geologically, these districts are situated in the Lesser Himalayas and partly encompass the Higher Himalayan rock sequence, which includes low-grade to high-grade metamorphic rocks. Following the Gorkha Earthquake in 2015, numerous springs dried up, and many others are currently experiencing depletion due to the distortion of the natural groundwater flow. The primary objective of this study is to identify potential groundwater areas and determine suitable sites for artificial groundwater recharge. Two distinct statistical approaches were used to develop models: The Frequency Ratio (FR) and Shannon Entropy (SE) methods. The study utilized both primary and secondary datasets and incorporated significant role and controlling factors derived from field works and literature reviews. Field data collection involved spring inventory, soil analysis, lithology assessment, and hydro-geomorphology study. Additionally, slope, aspect, drainage density, and lineament density were extracted from a Digital Elevation Model (DEM) using GIS and transformed into thematic layers. For training and validation, 114 springs were divided into a 70/30 ratio, with an equal number of non-spring pixels. After assigning weights to each class based on the two proposed models, a groundwater potential map was generated using GIS, classifying the area into five levels: very low, low, moderate, high, and very high. The model's outcome reveals that over 41% of the area falls into the low and very low potential categories, while only 30% of the area demonstrates a high probability of groundwater potential. To evaluate model performance, accuracy was assessed using the Area under the Curve (AUC). The success rate AUC values for the FR and SE methods were determined to be 78.73% and 77.09%, respectively. Additionally, the prediction rate AUC values for the FR and SE methods were calculated as 76.31% and 74.08%. The results indicate that the FR model exhibits greater prediction capability compared to the SE model in this case study.

Keywords: groundwater potential mapping, frequency ratio, Shannon’s Entropy, Lesser Himalaya Zone, sustainable groundwater management

Procedia PDF Downloads 83

Authors: Hala M. Abdel Mageed, Ahmed I. Omar, Shady H. E. Abdel Aleem

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This paper describes in details a commercial green building that has been designed and constructed in Marsa Matrouh, Egypt. The balance between homebuilding and the sustainable environment has been taken into consideration in the design and construction of this building. The building consists of one floor with 3 m height and 2810 m² area while the envelope area is 1400 m². The building construction fulfills the natural ventilation requirements. The glass curtain walls are about 50% of the building and the windows area is 300 m². 6 mm greenish gray tinted temper glass as outer board lite, 6 mm safety glass as inner board lite and 16 mm thick dehydrated air spaces are used in the building. Visible light with 50% transmission, 0.26 solar factor, 0.67 shading coefficient and 1.3 W/m².K thermal insulation U-value are implemented to realize the performance requirements. Optimum electrical distribution for lighting system, air conditions and other electrical loads has been carried out. Power and quantity of each type of the lighting system lamps and the energy consumption of the lighting system are investigated. The design of the air conditions system is based on summer and winter outdoor conditions. Ventilated, air conditioned spaces and fresh air rates are determined. Variable Refrigerant Flow (VRF) is the air conditioning system used in this building. The VRF outdoor units are located on the roof of the building and connected to indoor units through refrigerant piping. Indoor units are distributed in all building zones through ducts and air outlets to ensure efficient air distribution. The green building energy consumption is evaluated monthly all over one year and compared with the consumed energy in the non-green conditions using the Hourly Analysis Program (HAP) model. The comparison results show that the total energy consumed per year in the green building is about 1,103,221 kWh while the non-green energy consumption is about 1,692,057 kWh. In other words, the green building total annual energy cost is reduced from 136,581 $ to 89,051 $. This means that, the energy saving and consequently the money-saving of this green construction is about 35%. In addition, 13 points are awarded by applying one of the most popular worldwide green energy certification programs (Leadership in Energy and Environmental Design “LEED”) as a rating system for the green construction. It is concluded that this green building ensures sustainability, saves energy and offers an optimum energy performance with minimum cost.

Keywords: energy consumption, energy saving, green building, leadership in energy and environmental design, sustainability

Procedia PDF Downloads 304

Authors: S. Rodosik, J. P. Poirot-Crouvezier, Y. Bultel

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With the expansion of the hydrogen economy, Proton Exchange Membrane Fuel Cell (PEMFC) systems are often presented as promising energy converters suitable for transport applications. However, reaching a durability of 5000 h recommended by the U.S. Department of Energy and decreasing system cost are still major hurdles to their development. In order to increase the system efficiency and simplify the system without affecting the fuel cell lifetime, an architecture called alternative fuel feeding has been developed. It consists in a fuel cell stack divided into two parts, alternatively fed, implemented on a 5-kW system for real scale testing. The operation strategy can be considered close to Dead End Anode (DEA) with specific modifications to avoid water and nitrogen accumulation in the cells. The two half-stacks are connected in series to enable each stack to be alternatively fed. Water and nitrogen accumulated can be shifted from one half-stack to the other one according to the alternative feeding frequency. Thanks to the homogenization of water vapor along the stack, water management was improved. The operating conditions obtained at system scale are close to recirculation without the need of a pump or an ejector. In a first part, a performance comparison with the DEA strategy has been performed. At high temperature and low pressure (80°C, 1.2 bar), performance of alternative fuel feeding was higher, and the system efficiency increased. In a second part, in order to highlight the benefits of the architecture on the fuel cell lifetime, two durability tests, lasting up to 1000h, have been conducted. A test on the 5-kW system has been compared to a reference test performed on a test bench with a shorter stack, conducted with well-controlled operating parameters and flow-through hydrogen strategy. The durability test is based upon the Fuel Cell Dynamic Load Cycle (FC-DLC) protocol but adapted to the system limitations: without OCV steps and a maximum current density of 0.4 A/cm². In situ local measurements with a segmented S++® plate performed all along the tests, showed a more homogeneous distribution of the current density with alternative fuel feeding than in flow-through strategy. Tests performed in this work enabled the understanding of this architecture advantages and drawbacks. Alternative fuel feeding architecture appeared to be a promising solution to ensure the humidification function at the anode side with a simplified fuel cell system.

Keywords: automotive conditions, durability, fuel cell system, proton exchange membrane fuel cell, stack architecture

Procedia PDF Downloads 143

Authors: Haris Setiawan, Phongsakorn Chuammitri, Korawan Sringarm, Montira Intanon, Anucha Sathanawongs

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Capacitation is a prerequisite to achieving sperm competency to penetrate the oocyte naturally occurring in vivo throughout the female reproductive tract and entangling secretory fluid and epithelial cells. One of the crucial compounds in the oviductal fluid which promotes capacitation is albumin, secreted in major concentrations. However, the difficulties in the collection and the inconsistency of the oviductal fluid composition throughout the estrous cycle have replaced its function with serum-based albumins such as bovine serum albumin (BSA). BSA has been primarily involved and evidenced for their stabilizing effect to maintain the acrosome intact during the capacitation process, modulate hyperactivation, and elevate the number of sperm bound to zona pellucida. Contrary to its benefits, the use of blood-derived products in the culture system is not sustainable and increases the risk of disease transmissions, such as Creutzfeldt-Jakob disease (CJD) and bovine spongiform encephalopathy (BSE). Moreover, it has been asserted that this substance is an aeroallergen that produces allergies and respiratory problems. In an effort to identify an alternative sustainable and non-toxic albumin source, the present work evaluated sperm reactions to a capacitation medium containing albumin derived from the flesh of the snakehead fish (Channa striata). Before examining the ability of this non-serum albumin to promote capacitation in bovine sperm, the presence of albumin was detected using bromocresol purple (BCP) at the level of 25% from snakehead fish extract. Following the SDS-PAGE and densitometric analysis, two major bands at 40 kDa and 47 kDa consisting of 57% and 16% of total protein loaded were detected as the potential albumin-related bands. Significant differences were observed in all kinematic parameters upon incubation in the capacitation medium. Moreover, consistently higher values were shown for the kinematic parameters related to hyperactivation, such as amplitude lateral head (ALH), velocity curve linear (VCL), and linearity (LIN) when sperm were treated with 3 mg/mL of snakehead fish albumin among other treatments. Likewise, substantial differences of higher acrosome intact presented in sperm upon incubation with various concentrations of snakehead fish albumin for 90 minutes, indicating that this level of snakehead fish albumin can be used to replace the bovine serum albumin. However, further study is highly required to purify the albumin from snakehead fish extract for more reliable findings.

Keywords: capacitation promoter, snakehead fish, non-serum albumin, bovine sperm

Procedia PDF Downloads 116

Authors: Zunaira Zaman, David Bohannon

Abstract:

This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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