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Authors: Kirsi Snellman, Johannes Gartner, , Katja Upadaya

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A transition towards a future where the economy serves society so that it evolves within the safe operating space of the planet calls for fundamental changes in the way managers think, feel and act, and make decisions that relate to social and environmental issues. Sustainable decision-making in organizations are often challenging tasks characterized by trade-offs between environmental, social and financial aspects, thus often bringing forth ethical concerns. Although there have been significant developments in incorporating uncertainty into environmental decision-making and measuring constructs and dimensions in ethical behavior in organizations, the majority of sustainable decision-making models are rationalist-based. Moreover, research in psychology indicates that one’s readiness to make a decision depends on the individual’s state of mind, the feasibility of the implied change, and the compatibility of strategies and tactics of implementation. Although very informative, most of this extant research is limited in the sense that it often directs attention towards the rational instead of the emotional. Hence, little is known about the role of emotions in sustainable decision making, especially in situations where decision-makers evaluate a variety of options and use their feelings as a source of information in tackling the uncertainty. To fill this lacuna, and to embrace the uncertainty and perceived risk involved in decisions that touch upon social and environmental aspects, it is important to add emotion to the evaluation when aiming to reach the one right and good ethical decision outcome. This analysis builds on recent findings in moral psychology that associate feelings and intuitions with ethical decisions and suggests that emotions can sensitize the manager to evaluate the rightness or wrongness of alternatives if ethical concerns are present in sustainable decision making. Capturing such sensitive evaluation as triggered by intuitions, we suggest that rational justification can be complemented by using emotions as a tool to tune in to what feels right in making sustainable decisions. This analysis integrates ethical decision-making theories with recent advancements in emotion theories. It determines the conditions under which emotions play a role in sustainability decisions by contributing to a personal equilibrium in which intuition and rationality are both activated and in accord. It complements the rationalist ethics view according to which nothing fogs the mind in decision making so thoroughly as emotion, and the concept of cheater’s high that links unethical behavior with positive affect. This analysis contributes to theory with a novel theoretical model that specifies when and why managers, who are more emotional, are, in fact, more likely to make ethical decisions than those managers who are more rational. It also proposes practical advice on how emotions can convert the manager’s preferences into choices that benefit both common good and one’s own good throughout the transition towards a more sustainable future.

Keywords: emotion, ethical decision making, intuition, sustainability

Procedia PDF Downloads 115

Authors: Anurag Bhambhani, Jan Peter Van Der Hoek, Zoran Kapelan

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The food system depends on the availability of Phosphorus (P) and Nitrogen (N). Growing population, depleting Phosphorus reserves and energy-intensive industrial nitrogen fixation are threats to their future availability. Recovering P and N from domestic sewage water offers a solution. Recovered P and N can be applied to agricultural land, replacing virgin P and N. Thus, recovery from sewage water offers a solution befitting a circular economy. To ensure minimum waste and maximum resource efficiency a circularity assessment method is crucial to optimize nutrient flows and minimize losses. Material Circularity Indicator (MCI) is a useful method to quantify the circularity of materials. It was developed for materials that remain within the market and recently extended to include biotic materials that may be composted or used for energy recovery after end-of-use. However, MCI has not been used in the context of nutrient recovery. Besides, MCI is time-static, i.e., it cannot account for dynamic systems such as the terrestrial nutrient cycles. Nutrient application to agricultural land is a highly dynamic process wherein flows and stocks change with time. The rate of recycling of nutrients in nature can depend on numerous factors such as prevailing soil conditions, local hydrology, the presence of animals, etc. Therefore, a dynamic model of nutrient flows with indicators is needed for the circularity assessment. A simple substance flow model of P and N will be developed with the help of flow equations and transfer coefficients that incorporate the nutrient recovery step along with the agricultural application, the volatilization and leaching processes, plant uptake and subsequent animal and human uptake. The model is then used for calculating the proportions of linear and restorative flows (coming from reused/recycled sources). The model will simulate the adsorption process based on the quantity of adsorbent and nutrient concentration in the water. Thereafter, the application of the adsorbed nutrients to agricultural land will be simulated based on adsorbate release kinetics, local soil conditions, hydrology, vegetation, etc. Based on the model, the restorative nutrient flow (returning to the sewage plant following human consumption) will be calculated. The developed methodology will be applied to a case study of resource recovery from wastewater. In the aforementioned case study located in Italy, biochar or zeolite is to be used for recovery of P and N from domestic sewage through adsorption and thereafter, used as a slow-release fertilizer in agriculture. Using this model, information regarding the efficiency of nutrient recovery and application can be generated. This can help to optimize the recovery process and application of the nutrients. Consequently, this will help to optimize nutrient recovery and application and reduce the dependence of the food system on the virgin extraction of P and N.

Keywords: circular economy, dynamic substance flow, nutrient cycles, resource recovery from water

Procedia PDF Downloads 186

Authors: Daniel Botero, Oscar Rubiano, Pedro P. Barragan, Jaime Baron, Leonardo Rodriguez Perdomo, Jaime Rodriguez

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In the last decade interval training (IT) has gained importance when is compare with strength training (ST). However, there are few studies analyzing the impact of these training over the autonomic nervous system (ANS). This work has aimed to compare the activity of the autonomic nervous system, when is expose to an IT or ST indoor cycling mode. After approval by the ethics committee, a cross-over clinical trial with 22 healthy participants (age 21 ± 3 years) was implemented. The selection of participants for the groups with sequence force-interval (F-I) and interval-force (I-F) was made randomly with assignation of 11 participants for each group. The temporal series of heart rate was obtained before and after each training using the POLAR TEAM® heart monitor. The evaluation of the ANS was performed with spectral analysis of the heart rate variability (HRV) using the fast Fourier transform (Kubios software). A training of 8 weeks in each sequence (4 weeks with each training) with an intermediate period of two weeks of washout was implemented for each group. The power parameter of the HRV in the low frequency band (LF = 0.04-0.15Hz related to the sympathetic nervous system), high frequency (HF = 0.15-0.4Hz, related to the parasympathetic) and LF/HF (with reference to a modulation of parasympathetic over the sympathetic), were calculated. Afterward, the difference between the parameters before and after was realized. Then, to evaluate statistical differences between each training was implemented the method of Wellek (Wellek and Blettner, 2012, Medicine, 109 (15), 276-81). To determine the difference of effect over parasympathetic when FT and IT are used, the T test is implemented obtaining a T value of 0.73 with p-value ≤ 0.1. For the sympathetic was obtained a T of 0.33 with p ≤ 0.1 and for LF/HF the T was 1.44 with a p ≥ 0.1. Then, the carry over effect was evaluated and was not present. Significant changes over autonomic activity with strength or interval training were not observed. However, a modulation of the parasympathetic over the sympathetic can be observed. Probably, these findings should be explained because the sample is little and/or the time of training was insufficient to generate changes.

Keywords: autonomic nervous, force training, indoor cycling, interval training

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Authors: Syed Kamran Sami, Saqib Siddiqui

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In recent times, flexible supercapacitors retaining high electrochemical performance and steadiness along with mechanical endurance has developed as a spring of attraction due to the exponential progress and innovations in energy storage devices. To meet the rampant increasing demand of energy storage device with the small form factor, a unique, low cost and high-performance supercapacitor with considerably higher capacitance and mechanical robustness is required to recognize their real-life applications. Here in this report, synthesis route of electrode materials with low rigidity and high charge storage performance is reported using 1D-1D hybrid structure of zinc oxide (ZnO) nanorods, and conductive polymer smeared polyvinylidene fluoride–trifluoroethylene (P(VDF–TrFE)) electrospun nanofibers. The ZnO nanorods were uniformly grown on poly (3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT: PSS) coated P(VDF-TrFE) nanofibers using hydrothermal growth to manufacture light weight, permeable electrodes for supercapacitor. The PEDOT: PSS coated P(VDF-TrFE) porous web of nanofibers act as framework with high surface area. The incorporation of ZnO nanorods further boost the specific capacitance by 59%. The symmetric device using the fabricated 1D-1D hybrid electrodes reveals fairly high areal capacitance of 1.22mF/cm² at a current density of 0.1 mA/cm² with a power density of more than 1600 W/Kg. Moreover, the fabricated electrodes show exceptional flexibility and high endurance with 90% and 76% specific capacitance retention after 1000 and 5000 cycles respectively signifying the astonishing mechanical durability and long-term stability. All the properties exhibited by the fabricated electrode make it convenient for making flexible energy storage devices with the low form factor.

Keywords: ZnO nanorods, electrospinning, mechanical endurance, flexible supercapacitor

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Authors: Mahul Bhattacharyya, Niladri Sekhar Dash

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The present research paper is an experimental attempt to investigate the nature of variation in the register in three major text domains, namely, social, cultural, and political texts collected from the corpus of Bangla printed mass media texts. This present study uses a corpus of a moderate amount of Bangla mass media text that contains nearly one million words collected from different media sources like newspapers, magazines, advertisements, periodicals, etc. The analysis of corpus data reveals that each text has certain lexical properties that not only control their identity but also mark their uniqueness across the domains. At first, the subject domains of the texts are classified into two parameters namely, ‘Genre' and 'Text Type'. Next, some empirical investigations are made to understand how the domains vary from each other in terms of lexical properties like both function and content words. Here the method of comparative-cum-contrastive matching of lexical load across domains is invoked through word frequency count to track how domain-specific words and terms may be marked as decisive indicators in the act of specifying the textual contexts and subject domains. The study shows that the common lexical stock that percolates across all text domains are quite dicey in nature as their lexicological identity does not have any bearing in the act of specifying subject domains. Therefore, it becomes necessary for language users to anchor upon certain domain-specific lexical items to recognize a text that belongs to a specific text domain. The eventual findings of this study confirm that texts belonging to different subject domains in Bangla news text corpus clearly differ on the parameters of lexical load, lexical choice, lexical clustering, lexical collocation. In fact, based on these parameters, along with some statistical calculations, it is possible to classify mass media texts into different types to mark their relation with regard to the domains they should actually belong. The advantage of this analysis lies in the proper identification of the linguistic factors which will give language users a better insight into the method they employ in text comprehension, as well as construct a systemic frame for designing text identification strategy for language learners. The availability of huge amount of Bangla media text data is useful for achieving accurate conclusions with a certain amount of reliability and authenticity. This kind of corpus-based analysis is quite relevant for a resource-poor language like Bangla, as no attempt has ever been made to understand how the structure and texture of Bangla mass media texts vary due to certain linguistic and extra-linguistic constraints that are actively operational to specific text domains. Since mass media language is assumed to be the most 'recent representation' of the actual use of the language, this study is expected to show how the Bangla news texts reflect the thoughts of the society and how they leave a strong impact on the thought process of the speech community.

Keywords: Bangla, corpus, discourse, domains, lexical choice, mass media, register, variation

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Authors: Adeiza Matthew, Oluwadamilola Abubakar

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Wood energy, also known as wood fuel, is a renewable energy source that is derived from woody biomass, which is organic matter that is harvested from forests, woodlands, and other lands. Woody biomass includes trees, branches, twigs, and other woody debris that can be used as fuel. Wood energy can be classified based on its sources, such as trees outside forests, residues from wood harvesting and conversion, and energy plantations. There are several policy frameworks that support the use of wood energy, including participatory forest management and agroforestry. These policies aim to promote the sustainable use of woody biomass as a source of energy while also protecting forests and wildlife habitats. There are several options for using wood as a fuel, including central heating systems, pellet-based systems, wood chip-based systems, log boilers, fireplaces, and stoves. Each of these options has its own benefits and drawbacks, and the most appropriate option will depend on factors such as the availability of woody biomass, the heating needs of the household or facility, and the local climate. In order to use wood as a fuel, it must be harvested and stored properly. Hardwood or softwood can be used as fuel, and the heating value of firewood depends on the species of tree and the degree of moisture content. Proper harvesting and storage of wood can help to minimize environmental impacts and improve wildlife habitats. The use of wood energy has several environmental impacts, including the release of greenhouse gases during combustion and the potential for air pollution from combustion by-products. However, wood energy can also have positive environmental impacts, such as the sequestration of carbon in trees and the reduction of reliance on fossil fuels. The regulation and legislation of wood energy vary by country and region, and there is an ongoing debate about the potential use of wood energy in renewable energy technologies. Wood energy is a renewable energy source that can be used to generate electricity, heat, and transportation fuels. Woody biomass is abundant and widely available, making it a potentially significant source of energy for many countries. The use of wood energy can create local economic and employment opportunities, particularly in rural areas. Wood energy can be used to reduce reliance on fossil fuels and reduce greenhouse gas emissions. Properly managed forests can provide a sustained supply of woody biomass for energy, helping to reduce the risk of deforestation and habitat loss. Wood energy can be produced using a variety of technologies, including direct combustion, co-firing with fossil fuels, and the production of biofuels. The environmental impacts of wood energy can be minimized through the use of best practices in harvesting, transportation, and processing. Wood energy is regulated and legislated at the national and international levels, and there are various standards and certification systems in place to promote sustainable practices. Wood energy has the potential to play a significant role in the transition to a low-carbon economy and the achievement of climate change mitigation goals.

Keywords: biomass, timber, charcoal, firewood

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Authors: Tooba N. Shamsi, Romana Perveen, Sadaf Fatima

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Protease Inhibitors (PIs) are widespread in nature, produced by animals, plants and microorganisms. They play vital role in various biological activities by keeping a check on activity of proteases. Present study aims to investigate antioxidant and anti-inflammatory properties of PPI from Cajanus cajan (CCTI) and Phaseolus limensis (LBTI). PPI was purified from C. cajan (PUSA-992) by ammonium sulfate precipitation followed by ion exchange chromatography. The anti-oxidant activity was analyzed by two most common radical scavenging assays of FRAP (ferric reducing antioxidant power) and DPPH (1,1- diphenyl-2-picrylhydrazyl). Also, in-vitro anti-inflammatory activity was evaluated using albumin denaturation assay and membrane stabilization assay at different concentrations. Ascorbic acid and aspirin were used as a standards for antioxidant and anti-inflammatory assays respectively. The PPIs were also checked for antimicrobial activity against a number of bacterial strains. The CCTI and LBTI showed DPPH radical scavenging activity in a concentration–dependent manner with IC50 values 544 µg/ml and 506 µg/ml respectively comparative to ascorbic acid which was 258 µg/ml. Following FRAP assay, it was evaluated that LBTI had 87.5% and CCTI showed 84.4% antioxidant activity, taking value of standard ascorbic acid to be 100%. The PPIs also showed in-vitro anti‐inflammatory activity by inhibiting the heat induced albumin denaturation with IC50 values of 686 µg/ml and 615 µg/ml for CCTI and LBTI respectively compared to the standard (aspirin) which was 70.8 µg/ml. Red blood cells membrane stabilization with IC50 values of 641 µg/ml and 587 µg/ml for CCTI and LBTI respectively against aspirin which showed IC50 value of 70.4 µg/ml. PPIs showed antibacterial activity against 7 known strains while there was apparently no action against fungi.

Keywords: Cajanus cajan, Phaseolus limensis, Lima beans, protein protease inhibitor, antioxidant, anti-inflammatory, antimicrobial activity

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Authors: Rajkumar Ghosh, Shyama Pada Gorai

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Access to safe drinking water is a fundamental human right; however, regions like Purulia, Bankura, Birbhum, Malda, Dinajpur in West Bengal, India, face formidable challenges due to heightened fluoride levels. This paper delves into the hurdles of fresh drinking water production, presenting comprehensive solutions derived from literature reviews, field surveys, and scientific analyses. Encompassing fluoride-affected areas in Purulia, Bankura, Birbhum, Malda, North-South Dinajpur, and South 24 Parganas, the study emphasizes an integrated and sustainable approach. Employing a multidisciplinary methodology, combining scientific analysis and community engagement, the study identifies key factors influencing water quality and proposes sustainable strategies. Elevated fluoride concentrations exceeding international health standards (Purulia: 0.126 – 8.16 mg/L, Bankura: 0.1 – 12.2 mg/L, Malda: 0.1 – 4.54 mg/L, Birbhum: 0.023 – 18 mg/L) necessitate urgent intervention. Infrastructure deficiencies impede water treatment and distribution, while limited awareness obstructs community participation. The proposed solutions embrace advanced water treatment technologies, infrastructure development, community education, and sustainable water management practices. This comprehensive effort aims to provide clean drinking water, safeguarding the health of affected populations. Building on these foundations, the study explores the potential of rooftop rainwater harvesting as an effective and sustainable strategy to mitigate challenges in fresh drinking water production. By addressing fluoride contamination concerns and promoting community involvement, this approach presents a holistic solution to water quality issues in affected regions. The findings underscore the importance of integrating sustainable practices with community engagement to achieve long-term water security in Purulia, Bankura, Birbhum, Malda, North-South Dinajpur, and South 24 Parganas. This study serves as a cornerstone for further research and policy development, addressing fluoride contamination's impact on public health in affected areas. Recommendations include the establishment of long-term monitoring programs to assess the effectiveness of implemented solutions and conducting health impact studies to understand the long-term effects of fluoride contamination on the local population.

Keywords: fluoride mitigation, rainwater harvesting, water quality, sustainable water management, community engagement

Procedia PDF Downloads 45

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

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

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

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Authors: L. Donelle, S. Regan, R. Booth, M. Kerr, J. McMurray, D. Fitzsimmons

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Palliative home health care provision within the Canadian context is challenged by: (i) a shortage of registered nurses (RN) and RNs with palliative care expertise, (ii) an aging population, (iii) reliance on unpaid family caregivers to sustain home care services with limited support to conduct this ‘care work’, (iv) a model of healthcare that assumes client self-care, and (v) competing economic priorities. In response, an interprofessional team of service provider organizations, a software/technology provider, and health care providers developed and implemented a technology-enabled model of home care, the eShift model of palliative home care (eShift). The eShift model combines communication and documentation technology with non-traditional utilization of health human resources to meet patient needs for palliative care in the home. The purpose of this study was to investigate the structure, processes, and outcomes of the eShift model of care. Methodology: Guided by Donebedian’s evaluation framework for health care, this qualitative-descriptive study investigated the structure, processes, and outcomes care of the eShift model of palliative home care. Interviews and focus groups were conducted with health care providers (n= 45), decision-makers (n=13), technology providers (n=3) and family care givers (n=8). Interviews were recorded, transcribed, and a deductive analysis of transcripts was conducted. Study Findings (1) Structure: The eShift model consists of a remotely-situated RN using technology to direct care provision virtually to patients in their home. The remote RN is connected virtually to a health technician (an unregulated care provider) in the patient’s home using real-time communication. The health technician uses a smartphone modified with the eShift application and communicates with the RN who uses a computer with the eShift application/dashboard. Documentation and communication about patient observations and care activities occur in the eShift portal. The RN is typically accountable for four to six health technicians and patients over an 8-hour shift. The technology provider was identified as an important member of the healthcare team. Other members of the team include family members, care coordinators, nurse practitioners, physicians, and allied health. (2) Processes: Conventionally, patient needs are the focus of care; however within eShift, the patient and the family caregiver were the focus of care. Enhanced medication administration was seen as one of the most important processes, and family caregivers reported high satisfaction with the care provided. There was perceived enhanced teamwork among health care providers. (3) Outcomes: Patients were able to die at home. The eShift model enabled consistency and continuity of care, and effective management of patient symptoms and caregiver respite. Conclusion: More than a technology solution, the eShift model of care was viewed as transforming home care practice and an innovative way to resolve the shortage of palliative care nurses within home care.

Keywords: palliative home care, health information technology, patient-centred care, interprofessional health care team

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Authors: Jyoti Singh, Ranju Bansal

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Fighting pain and inflammation is a common problem faced by physicians while dealing with a wide variety of diseases. Since ancient time nonsteroidal anti-inflammatory agents (NSAIDs) and opioids have been the cornerstone of treatment therapy, however, the usefulness of both these classes is limited due to severe side effects. NSAIDs, which are mainly used to treat mild to moderate inflammatory pain, induce gastric irritation and nephrotoxicity whereas opioids show an array of adverse reactions such as respiratory depression, sedation, and constipation. Moreover, repeated administration of these drugs induces tolerance to the analgesic effects and physical dependence. Further discovery of selective COX-2 inhibitors (coxibs) suggested safety without any ulcerogenic side effects; however, long-term use of these drugs resulted in kidney and hepatic toxicity along with an increased risk of secondary cardiovascular effects. The basic approaches towards inflammation and pain treatment are constantly changing, and researchers are continuously trying to develop safer and effective anti-inflammatory drug candidates for the treatment of different inflammatory conditions such as osteoarthritis, rheumatoid arthritis, ankylosing spondylitis, psoriasis and multiple sclerosis. Synthetic 3(2H)-pyridazinones constitute an important scaffold for drug discovery. Structure-activity relationship studies on pyridazinones have shown that attachment of a lactam at N-2 of the pyridazinone ring through a methylene spacer results in significantly increased anti-inflammatory and analgesic properties of the derivatives. Further introduction of the heterocyclic ring at lactam nitrogen results in improvement of biological activities. Keeping in mind these SAR studies, a new series of compounds were synthesized as shown in scheme 1 and investigated for anti-inflammatory, analgesic, anti-platelet activities and docking studies. The structures of newly synthesized compounds have been established by various spectroscopic techniques. All the synthesized pyridazinone derivatives exhibited potent anti-inflammatory and analgesic activity. Homoveratryl substituted derivative was found to possess highest anti-inflammatory and analgesic activity displaying 73.60 % inhibition of edema at 40 mg/kg with no ulcerogenic activity when compared to standard drugs indomethacin. Moreover, 2-substituted-4-benzo[d][1,3]dioxole-6-phenylpyridazin-3(2H)-ones derivatives did not produce significant changes in bleeding time and emerged as safe agents. Molecular docking studies also illustrated good binding interactions at the active site of the cyclooxygenase-2 (hCox-2) enzyme.

Keywords: anti-inflammatory, analgesic, pyridazin-3(2H)-one, selective COX-2 inhibitors

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Authors: S. C. Lin, W. W. Cheng, M. S. Wu

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This study attempted to investigate the connection between teacher professional development program and students’ Learning. This study took Readers’ Theater Teaching Program (RTTP) for professional development as an example to inquiry how participants apply their new knowledge and skills learned from RTTP to their teaching practice and how the impact influence students learning. The goals of the RTTP included: 1) to enhance teachers RT content knowledge; 2) to implement RT instruction in teachers’ classrooms in response to their professional development. 2) to improve students’ ability of reading fluency in professional development teachers’ classrooms. This study was a two-year project. The researchers applied mixed methods to conduct this study including qualitative inquiry and one-group pretest-posttest experimental design. In the first year, this study focused on designing and implementing RTTP and evaluating participants’ satisfaction of RTTP, what they learned and how they applied it to design their English reading curriculum. In the second year, the study adopted quasi-experimental design approach and evaluated how participants RT instruction influenced their students’ learning, including English knowledge, skill, and attitudes. The participants in this study composed two junior high school English teachers and their students. Data were collected from a number of different sources including teaching observation, semi-structured interviews, teaching diary, teachers’ professional development portfolio, Pre/post RT content knowledge tests, teacher survey, and students’ reading fluency tests. To analyze the data, both qualitative and quantitative data analysis were used. Qualitative data analysis included three stages: organizing data, coding data, and analyzing and interpreting data. Quantitative data analysis included descriptive analysis. The results indicated that average percentage of correct on pre-tests in RT content knowledge assessment was 40.75% with two teachers ranging in prior knowledge from 35% to 46% in specific RT content. Post-test RT content scores ranged from 70% to 82% correct with an average score of 76.50%. That gives teachers an average gain of 35.75% in overall content knowledge as measured by these pre/post exams. Teachers’ pre-test scores were lowest in script writing and highest in performing. Script writing was also the content area that showed the highest gains in content knowledge. Moreover, participants hold a positive attitude toward RTTP. They recommended that the approach of professional learning community, which was applied in RTTP was benefit to their professional development. Participants also applied the new skills and knowledge which they learned from RTTP to their practices. The evidences from this study indicated that RT English instruction significantly influenced students’ reading fluency and classroom climate. The result indicated that all of the experimental group students had a big progress in reading fluency after RT instruction. The study also found out several obstacles. Suggestions were also made.

Keywords: teacher’s professional development, program evaluation, readers’ theater, english reading instruction, english reading fluency

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Authors: Ph. Fauquet-Alekhine

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Decision-making occurs several times an hour when working in high risk industry and an erroneous choice might have undesirable outcomes for people and the environment surrounding the industrial plant. Industrial decisions are very often made in a context of acute stress. Time pressure is a crucial stressor leading decision makers sometimes to boost up the decision-making process and if it is not possible then shift to the simplest strategy. We thus found it interesting to update the characterization of the stress factors impairing decision-making at Chinon Nuclear Power Plant (France) in order to optimize decision making contexts and/or associated processes. The investigation was based on the analysis of reports addressing safety events over the last 3 years. Among 93 reports, those explicitly addressing decision-making issues were identified. Characterization of each event was undertaken in terms of three criteria: stressors, biases impairing decision making and weaknesses of the decision-making process. The statistical analysis showed that biases were distributed over 10 possibilities among which the hypothesis confirmation bias was clearly salient. No significant correlation was found between criteria. The analysis indicated that the main stressor was time pressure and highlights an unexpected form of stressor: the trust asymmetry principle of the expert. The analysis led to the conclusion that this stressor impaired decision-making from a psychological angle rather than from a physiological angle: it induces defensive bias of self-esteem, self-protection associated with a bias of confirmation. This leads to the hypothesis that this stressor can intervene in some cases without being detected, and to the hypothesis that other stressors of the same kind might occur without being detected too. Further investigations addressing these hypotheses are considered. The analysis also led to the conclusion that dealing with these issues implied i) decision-making methods being well known to the workers and automated and ii) the decision-making tools being well known and strictly applied. Training was thus adjusted.

Keywords: bias, expert, high risk industry, stress.

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Authors: Farid Khosravikia, Patricia Clayton

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

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

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Authors: Ahmad S. Darwish, Tarek Lemaoui, Hanifa Taher, Inas M. AlNashef, Fawzi Banat

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This research reports a systematic top-down approach for designing neoteric hydrophobic solvents –particularly, deep eutectic solvents (DES) and ionic liquids (IL)– as furfural extractants from aqueous media for the application of sustainable biomass conversion. The first stage of the framework entailed screening 32 neoteric solvents to determine their efficacy against toluene as the application’s conventional benchmark for comparison. The selection criteria for the best solvents encompassed not only their efficiency in extracting furfural but also low viscosity and minimal toxicity levels. Additionally, for the DESs, their natural origins, availability, and biodegradability were also taken into account. From the screening pool, two neoteric solvents were selected: thymol:decanoic acid 1:1 (Thy:DecA) and trihexyltetradecyl phosphonium bis(trifluoromethylsulfonyl) imide [P₁₄,₆,₆,₆][NTf₂]. These solvents outperformed the toluene benchmark, achieving efficiencies of 94.1% and 97.1% respectively, compared to toluene’s 81.2%, while also possessing the desired properties. These solvents were then characterized thoroughly in terms of their physical properties, thermal properties, critical properties, and cross-contamination solubilities. The selected neoteric solvents were then extensively tested under various operating conditions, and an exceptional stable performance was exhibited, maintaining high efficiency across a broad range of temperatures (15–100 °C), pH levels (1–13), and furfural concentrations (0.1–2.0 wt%) with a remarkable equilibrium time of only 2 minutes, and most notably, demonstrated high efficiencies even at low solvent-to-feed ratios. The durability of the neoteric solvents was also validated to be stable over multiple extraction-regeneration cycles, with limited leachability to the aqueous phase (≈0.1%). Moreover, the extraction performance of the solvents was then modeled through machine learning, specifically multiple non-linear regression (MNLR) and artificial neural networks (ANN). The models demonstrated high accuracy, indicated by their low absolute average relative deviations with values of 2.74% and 2.28% for Thy:DecA and [P₁₄,₆,₆,₆][NTf₂], respectively, using MNLR, and 0.10% for Thy:DecA and 0.41% for [P₁₄,₆,₆,₆][NTf₂] using ANN, highlighting the significantly enhanced predictive accuracy of the ANN. The neoteric solvents presented herein offer noteworthy advantages over traditional organic solvents, including their high efficiency in both extraction and regeneration processes, their stability and minimal leachability, making them particularly suitable for applications involving aqueous media. Moreover, these solvents are more environmentally friendly, incorporating renewable and sustainable components like thymol and decanoic acid. This exceptional efficacy of the newly developed neoteric solvents signifies a significant advancement, providing a green and sustainable alternative for furfural production from biowaste.

Keywords: sustainable biomass conversion, furfural extraction, ionic liquids, deep eutectic solvents

Procedia PDF Downloads 51

Authors: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

Procedia PDF Downloads 91

Authors: Chrysoula Mangafa

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Autism is a lifelong condition that affects how individuals interact with others and make sense of the world around them. The two core difficulties associated with autism are difficulties in social communication and interaction, and the manifestation of restricted, repetitive patterns of behaviour. However, children with autism may also have many talents and special interests among which is their affinity with digital technologies. Despite the increasing use of mobile tablets in schools and homes and the children’s motivation in using them, there is limited guidance on how to use the tablets to teach children with autism-specific skills. This study aims to fill this gap in knowledge by providing guidelines about the ways in which iPads and other tablets can be used by parents/carers and their child at home to support the development of social communication skills. Semi-structured interviews with 10 parents of primary school aged children with autism were conducted with the aim to explore their experiences in using mobile devices, such as iPads and Android tablets, and social activities with their children to create opportunities for social communication development. The interview involved questions about the parents’ knowledge and experience in autism, their understanding of social communication skills, the use of technology at home, and their links with the child’s school. Qualitative analysis of the interviews showed that parents used a variety of strategies to boost their child’s social communication skills. Among these strategies were a) the use of communication symbols, b) the use of the child’s special interest as motivator to gain their attention, and c) allowing time to their child to respond. It was also found that parents engaged their child in joint activities such as cooking, role play and creating social stories together on the device. Seven out of ten parents mentioned that the tablet is a motivating tool that can be used to teach social communication skills, nonetheless all parents raised concerns over screen time and their child’s sharing difficulties. The need for training and advice as well as building stronger links with their child’s school was highlighted. In particular, it was mentioned that recommendations would be welcomed about how parents can address their child’s difficulties in initiating or sustaining a conversation, taking turns and sharing, understanding other people’s feelings and facial expressions, and showing interest to other people. The findings of this study resulted in the development of a parents’ guide based on evidence-based practice and the participants’ experiences and concerns. The proposed guidelines aim to urge parents to feel more confident in using the tablet with their child in more collaborative ways. In particular, the guide offers recommendations about how to develop verbal and non-verbal communication, gives examples of tablet-based activities to interact and create things together, as well as it offers suggestions on how to provide a worry-free tablet experience and how to connect with the school.

Keywords: families, perception and cognition in early development, school-age intervention, social development

Procedia PDF Downloads 148

Authors: Y. Jin, N. Zhang, X. Luo, W. Zhang

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China with annual increasing 0.5-0.6 billion squares city residence has brought in enormous energy consumption by HVAC facilities and other appliances. In this regard, governments and researchers are encouraging renewable energy like solar energy, geothermal energy using in houses. However, high cost of equipment and low energy conversion result in a very low acceptable to residents. So what’s the equilibrium point of eco-feedback to reach economic benefit and thermal comfort? That is the main question should be answered. In this paper, the objective is an on-site solar PV and heater house, which has been evaluated as a low energy building. Since HVAC system is considered as main energy consumption equipment, the residence with 24-hour monitoring system set to measure temperature, wind velocity and energy in-out value with no HVAC system for one month of summer and winter. Thermal comfort time period will be analyzed and confirmed; then the air-conditioner will be started within thermal discomfort time for the following one summer and winter month. The same data will be recorded to calculate the average energy consumption monthly for a purpose of whole day thermal comfort. Finally, two analysis work will be done: 1) Original building thermal simulation by computer at design stage with actual measured temperature after construction will be contrastive analyzed; 2) The cost of renewable energy facilities and power consumption converted to cost efficient rate to assess the feasibility of renewable energy input for residence. The results of the experiment showed that a certain deviation exists between actual measured data and simulated one for human thermal comfort, especially in summer period. Moreover, the cost-effectiveness is high for a house in targeting city Guilin now with at least 11 years of cost-covering. The conclusion proves that an eco-feedback of a low energy residence is never only consideration of its energy net value, but also the cost efficiency that is the critical factor to push renewable energy acceptable by the public.

Keywords: cost efficiency, eco-feedback, low energy residence, thermal comfort

Procedia PDF Downloads 242

Authors: Sylwia Krawiec, Joanna Cabaj, Karol Malecha

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Nowadays, progress in the field of the analytical methods is of great interest for reliable biological research and medical diagnostics. Classical techniques of chemical analysis, despite many advantages, do not permit to obtain immediate results or automatization of measurements. Chemical sensors have displaced the conventional analytical methods - sensors combine precision, sensitivity, fast response and the possibility of continuous-monitoring. Biosensor is a chemical sensor, which except of conventer also possess a biologically active material, which is the basis for the detection of specific chemicals in the sample. Each biosensor device mainly consists of two elements: a sensitive element, where is recognition of receptor-analyte, and a transducer element which receives the signal and converts it into a measurable signal. Through these two elements biosensors can be divided in two categories: due to the recognition element (e.g immunosensor) and due to the transducer (e.g optical sensor). Working of optical sensor is based on measurements of quantitative changes of parameters characterizing light radiation. The most often analyzed parameters include: amplitude (intensity), frequency or polarization. Changes in the optical properties one of the compound which reacts with biological material coated on the sensor is analyzed by a direct method, in an indirect method indicators are used, which changes the optical properties due to the transformation of the testing species. The most commonly used dyes in this method are: small molecules with an aromatic ring, like rhodamine, fluorescent proteins, for example green fluorescent protein (GFP), or nanoparticles such as quantum dots (QDs). Quantum dots have, in comparison with organic dyes, much better photoluminescent properties, better bioavailability and chemical inertness. These are semiconductor nanocrystals size of 2-10 nm. This very limited number of atoms and the ‘nano’-size gives QDs these highly fluorescent properties. Rapid and sensitive detection of dopamine is extremely important in modern medicine. Dopamine is very important neurotransmitter, which mainly occurs in the brain and central nervous system of mammals. Dopamine is responsible for the transmission information of moving through the nervous system and plays an important role in processes of learning or memory. Detection of dopamine is significant for diseases associated with the central nervous system such as Parkinson or schizophrenia. In developed optical biosensor for detection of dopamine, are used graphene quantum dots (GQDs). In such sensor dopamine molecules coats the GQD surface - in result occurs quenching of fluorescence due to Resonance Energy Transfer (FRET). Changes in fluorescence correspond to specific concentrations of the neurotransmitter in tested sample, so it is possible to accurately determine the concentration of dopamine in the sample.

Keywords: biosensor, dopamine, fluorescence, quantum dots

Procedia PDF Downloads 354

Authors: Mamoon Mousa Atout

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The industries of construction are in continuous growth not only in Middle East rejoin but almost all over the world. For the last fifteen years, big expansion and increase of different types of projects has been observed. Many infrastructural projects have been developed, high rise buildings, big shopping malls, power sub-stations, roads, bridges, schools, universities and developing many of new cities with full and complete facilities. The growth and enlargement of the mentioned developed projects has been accomplished through many international and local contracting organizations. Senior management of these organizations depend on their qualified and experienced team whom are aware of the implications of project management, construction management, engineering management and resource management during tendering till final completion of the project. This research aims to find out why reasons of principles of construction engineering and management are necessary for contracting firms and their managers. Principles of construction management help contracting organizations to accomplish and deliver projects without delay. This can be maintained by establishing guidelines’ details for updating the adopted system of construction management that they have through qualified and experienced project managers. The research focuses on benefits of other essential skills of projects planning, monitoring and control. Defining roles and responsibilities of contractor project managers during tendering and execution is a part of the investigated factors that will be analyzed. Other skills like optimizing and utilizing the obtainable project resources to deliver the project within time, cost and quality will be also investigated to find out how these factors are affecting the performance of contracting firms, projects managers and projects. The conclusion of the research will help senior management team and the contractors project managers about the benefits of implications and benefits construction management system and its effect upon the performance and knowledge of contract values that they have, and the optimal profit margin of the firm it.

Keywords: construction management, contracting firms, project managers, planning processes, roles and responsibilities

Procedia PDF Downloads 283

Authors: Chung Danbi, Linton Oliver, Whang Yoon-Jae

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Supermodularity, or complementarity, is a popular concept in economics which can characterize many objective functions such as utility, social welfare, and production functions. Further, supermodular dominance captures a preference for greater interdependence among inputs of those functions, and it can be applied to examine which input set would produce higher expected utility, social welfare, or production. Therefore, we propose and justify a consistent testing for a useful implication of supermodular dominance. We also conduct Monte Carlo simulations to explore the finite sample performance of our test, with critical values obtained from the recentered bootstrap method, with and without the selective recentering, and the subsampling method. Under various parameter settings, we confirmed that our test has reasonably good size and power performance. Finally, we apply our test to compare the geographic and distant knowledge spillover in terms of their effects on social welfare using the National Bureau of Economic Research (NBER) patent data. We expect localized citing to supermodularly dominate distant citing if the geographic knowledge spillover engenders greater social welfare than distant knowledge spillover. Taking subgroups based on firm and patent characteristics, we found that there is industry-wise and patent subclass-wise difference in the pattern of supermodular dominance between localized and distant citing. We also compare the results from analyzing different time periods to see if the development of Internet and communication technology has changed the pattern of the dominance. In addition, to appropriately deal with the sparse nature of the data, we apply high-dimensional methods to efficiently select relevant data.

Keywords: supermodularity, supermodular dominance, stochastic dominance, Monte Carlo simulation, bootstrap, subsampling

Procedia PDF Downloads 118

Authors: Sara Dalma Galgoczi, Judith Gabriella Kengyel

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Sex scandals are quite an engaging topic to work with, especially with their judgment in society. Most people are interested in other people's lives, specifically in public figures' such as celebrities or politicians, because ordinary people feel like they have the right to know more things about the famous and notorious ones than they would probably willing to share. Intimacy and sexual acts aren't exceptions; moreover, sexuality is one of the central interests of humans ever since. Besides, knowing and having an opinion about any kind of scandal can change even whole social groups or classes estimation of anyone. This study aims to research the social judgment of some Hungarian politicians' sex scandals and asks important questions like diverse public opinions in the light of gender or delegates’ abuse of power. Considering that this study is about collecting and evaluating opinions from the public, and no one before researched and published this exact topic and cases, an online survey was created. In the survey were different sections. We collected data about party-preference, conservativism-liberalism scale; then we used the following questionnaires: from Zero-sum perspective with regard to gender equality (Ruthig, Kehn, Gamblin, Vanderzanden & Jones, 2017), Ambivalent Sexism Inventory (ASI; Glick & Fiske, 1996), Ambivalence Toward Men Inventory (AMI; Glick & Fiske, 1999). Finally, 5 short summaries were presented about five Hungarian politicians' sex scandal cases (3 males, 2 females) from the recent past. These stories were followed by questions about their opinion of the party and attitudes towards the parties' reactions to the cases. We came to the conclusion that people are more permissive with the scandals of men, and benevolent sexism and ambivalence towards men mediate this relation. Men tend to see these cases as part of politicians' private lives more than women. Party preference had a significant effect - people tend to pass a sentence the delegates of the opposing parties, and they rather release the delegates of their preferred party.

Keywords: sex scandal, sexism, social judgement, politician

Procedia PDF Downloads 104

Authors: Sachin Pawar, Suman Patra, Goutam Mukhopadhyay

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The primary function of a shaft is to transfer power. The shaft can be cast or forged and then machined to the final shape. Manufacturing of ~5 m length and 0.6 m diameter shaft is very critical. More difficult is to maintain its straightness during heat treatment and machining operations, which involve thermal and mechanical loads, respectively. During the machining operation of a such forged mandrel shaft, a deflection of 3-4mm was observed. To remove this deflection shaft was pressed at both ends which led to the development of cracks in it. To investigate the root cause of the deflection and cracking, the sample was cut from the failed shaft. Possible causes were identified with the help of a cause and effect diagram. Chemical composition analysis, microstructural analysis, and hardness measurement were done to confirm whether the shaft meets the required specifications or not. Chemical composition analysis confirmed that the material grade was 42CrMo4. Microstructural analysis revealed the presence of untempered martensite, indicating improper heat treatment. Due to this, ductility and impact toughness values were considerably lower than the specification of the mentioned grade. Residual stress measurement of one more bent shaft manufactured by a similar route was done by portable X-ray diffraction(XRD) technique. For better understanding, measurements were done at twelve different locations along the length of the shaft. The occurrence of a high amount of undesirable tensile residual stresses close to the Ultimate Tensile Strength(UTS) of the material was observed. Untempered martensitic structure, lower ductility, lower impact strength, and presence of a high amount of residual stresses all confirmed the improper tempering heat treatment of the shaft. Tempering relieves the residual stresses. Based on the findings of this study, stress-relieving heat treatment was done to remove the residual stresses and deflection in the shaft successfully.

Keywords: residual stress, mandrel shaft, untempered martensite, portable XRD

Procedia PDF Downloads 100

Authors: Ali Kadivar, Kaveh Niayesh

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The integration of green energy resources is a major focus, and the role of Medium Voltage Direct Current (MVDC) systems is exponentially expanding. However, the protection of MVDC systems against DC faults is a challenge that can have consequences on reliable and safe grid operation. This challenge reveals the need for MVDC circuit breakers (MVDC CB), which are in infancies of their improvement. Therefore will be a lack of MVDC CBs standards, including thresholds for acceptable power losses and operation speed. To establish a baseline for comparison purposes, a benchmark system for testing future MVDC CBs is vital. The literatures just give the timing sequence of each switch and the emphasis is on the topology, without in-depth study on the control algorithm of DCCB, as the circuit breaker control system is not yet systematic. A digital testing benchmark is designed for the Proof-of-concept of simulation studies using software models. It can validate studies based on real-time digital simulators and Transient Network Analyzer (TNA) models. The proposed experimental setup utilizes data accusation from the accurate sensors installed on the tested MVDC CB and through general purpose input/outputs (GPIO) from the microcontroller and PC Prototype studies in the laboratory-based models utilizing Hardware-in-the-Loop (HIL) equipment connected to real-time digital simulators is achieved. The improved control algorithm of the circuit breaker can reduce the peak fault current and avoid arc resignation, helping the coordination of DCCB in relay protection. Moreover, several research gaps are identified regarding case studies and evaluation approaches.

Keywords: DC circuit breaker, hardware-in-the-loop, real time digital simulation, testing benchmark

Procedia PDF Downloads 61

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

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

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

Procedia PDF Downloads 123

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

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

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

Procedia PDF Downloads 95

Authors: Diana Kwok

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Introduction: There is a rising concern on the educational needs of school guidance teachers, counselors, and sex educators to work effectively with students from multicultural groups, such as racial minorities, gender minorities, sexual minorities, and disability groups etc., and to respect cultural diversities. A specialized training model, the multicultural framework based on contact theory is recognized as necessary training model for professional training programs. Methodology: While the major focus of this project is on improving teaching and learning in teacher training courses within the department of Special Education and Counselling, it specifically aims to enhance the cultural competence of 102 participants enrolled in counseling and sexuality education courses by integrating the following teaching and learning strategies: 1) Panel presentation; 2) Case studies; 3) Experiential learning. Data sources from the participants consisted of the following: (a) questionnaires (MCKAS and ATLG) administered in classes; (b) weekly reflective journals, and c) focus group interviews with panel members. The focus group interviews with panel members were documented. Qualitatively, the weekly reflections were content analyzed. The presentation in this specific conference put focus on themes we found from qualitative content analysis of weekly reflective journals from 102 participants. Findings: Content analysis had found the following preliminary emergent themes: Theme I) Cultural knowledge and challenges to personal limitation. Students had gained a new perspective that specific cultural knowledge involved unique values and worldview. Awareness of limitation of counsellors is very important after actively acquiring the cultural knowledge. Theme 2 - Observation, engagement and active learning. Through the sharing and case studies, as well as visits to the communities, students recognized that observation and listening to the needs of cultural group members were the essential steps before taking any intervention steps. Theme 3 - Curiosity and desire for further inter-group dialogue. All students expressed their desire, curiosity, and motivation to have further inter-group dialogue in their future work settings. Theme 4: Experience with teaching and learning strategies. Students shared their perspectives on how teaching and learning strategies had facilitated their acquisition of cultural competence. Results of this analysis suggests that diverse teaching and learning strategies based on contact perspective had stimulated their curiosity to re-examine their values and motivated them to acquire cultural knowledge relevant to the cultural groups. Acknowledgment: The teaching and learning project was funded by the Teaching and Development Grant, Hong Kong Institute of Education (Project Number T0142).

Keywords: cultural competence, Chinese teacher students, teaching and learning, contacts

Procedia PDF Downloads 222

Authors: Zafar Tabrez, Nizamuddin Khan

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Agriculture in India in the pre-green revolution period was mostly controlled by terrain, climate and edaphic factors. But after the introduction of innovative factors and technological inputs, green revolution occurred and agricultural scene witnessed great change. In the development of India’s agriculture, speedy, and extensive introduction of technological change is one of the crucial factors. The technological change consists of adoption of farming techniques such as use of fertilisers, pesticides and fungicides, improved variety of seeds, modern agricultural implements, improved irrigation facilities, contour bunding for the conservation of moisture and soil, which are developed through research and calculated to bring about diversification and increase of production and greater economic return to the farmers. The green revolution in India took place during late 60s, equipped with technological inputs like high yielding varieties seeds, assured irrigation as well as modern machines and implements. Initially the revolution started in Punjab, Haryana and western Uttar Pradesh. With the efforts of government, agricultural planners, as well as policy makers, the modern technocratic agricultural development scheme was also implemented and introduced in backward and marginal regions of the country later on. Agriculture sector occupies the centre stage of India’s social security and overall economic welfare. The country has attained self-sufficiency in food grain production and also has sufficient buffer stock. Our first Prime Minister, Jawaharlal Nehru said ‘everything else can wait but not agriculture’. There is still a continuous change in the technological inputs and cropping patterns. Keeping these points in view, author attempts to investigate extensively the mechanization of agriculture and the change by selecting western Trans-Ghaghara plain as a case study and block a unit of the study. It includes the districts of Gonda, Balrampur, Bahraich and Shravasti which incorporate 44 blocks. It is based on secondary sources of data by blocks for the year 1997 and 2007. It may be observed that there is a wide range of variations and the change in farm mechanization, i.e., agricultural machineries such as ploughs, wooden and iron, advanced harrow and cultivator, advanced thrasher machine, sprayers, advanced sowing instrument, and tractors etc. It may be further noted that due to continuous decline in size of land holdings and outflux of people for the same nature of works or to be employed in non-agricultural sectors, the magnitude and direction of agricultural systems are affected in the study area which is one of the marginalized regions of Uttar Pradesh, India.

Keywords: agriculture, technological inputs, farm mechanization, food production, cropping pattern

Procedia PDF Downloads 293

Authors: Dineshsingh Thakur, S. Nagesh, J. Basha

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A lightweight High Speed Flexible Coupling (HSFC) is used to connect the Engine Gear Box (EGB) with an Accessory Gear Box (AGB) of the combat aircraft. The HSFC transmits the power at high speeds ranging from 10000 to 18000 rpm from the EGB to AGB. The HSFC is also accommodates larger misalignments resulting from thermal expansion of the aircraft engine and mounting arrangement. The HSFC has the series of metallic contoured annular thin cross-sectioned flexible plates to accommodate the misalignments. The flexible plates are accommodating the misalignment by the elastic material flexure. As the HSFC operates at higher speed, the flexural and axial resonance frequencies are to be kept away from the operating speed and proper prediction is required to prevent failure in the transmission line of a single engine fighter aircraft. To study the influence of flexible plate’s contour on the lateral critical speed (LCS) of HSFC, a mathematical model of HSFC as a elven rotor system is developed. The flexible plate being the bending member of the system, its bending stiffness which results from the contoured governs the LCS. Using transfer matrix method, Influence of various flexible plate contours on critical speed is analyzed. In the above analysis, the support bearing flexibility on critical speed prediction is also considered. Based on the study, a model is built with the optimum contour of flexible plate, for validation by experimental modal analysis. A good correlation between the theoretical prediction and model behavior is observed. From the study, it is found that the flexible plate’s contour is playing vital role in modification of system’s dynamic behavior and the present model can be extended for the development of similar type of flexible couplings for its computational simplicity and reliability.

Keywords: flexible rotor, critical speed, experimental modal analysis, high speed flexible coupling (HSFC), misalignment

Procedia PDF Downloads 199

Authors: George Kassar, Phillip A. Cartwright

Abstract:

Based on data collected from The Jones Learning Center (JLC), University of the Ozarks, Arkansas, U.S., this study explores the impact of inclusive classroom practices on neuro-diverse college students’ and their consequent academic performance having participated in integrative therapies designed to support students who are intellectually capable of obtaining a college degree, but who require support for learning challenges owing to disabilities, AD/HD, or ASD. The purpose of this study is two-fold. The first objective is to explore the general process, special techniques, and practices of the (JLC) inclusive program. The second objective is to identify and analyze the effectiveness of the processes, techniques, and practices in supporting the academic performance of enrolled college students with learning disabilities following integration into mainstream university learning. Integrity, transparency, and confidentiality are vital in the research. All questions were shared in advance and confirmed by the concerned management at the JLC. While administering the questionnaire as well as conducted the interviews, the purpose of the study, its scope, aims, and objectives were clearly explained to all participants prior starting the questionnaire / interview. Confidentiality of all participants assured and guaranteed by using encrypted identification of individuals, thus limiting access to data to only the researcher, and storing data in a secure location. Respondents were also informed that their participation in this research is voluntary, and they may withdraw from it at any time prior to submission if they wish. Ethical consent was obtained from the participants before proceeding with videorecording of the interviews. This research uses a mixed methods approach. The research design involves collecting, analyzing, and “mixing” quantitative and qualitative methods and data to enable a research inquiry. The research process is organized based on a five-pillar approach. The first three pillars are focused on testing the first hypothesis (H1) directed toward determining the extent to the academic performance of JLC students did improve after involvement with comprehensive JLC special program. The other two pillars relate to the second hypothesis (H2), which is directed toward determining the extent to which collective and applied knowledge at JLC is distinctive from typical practices in the field. The data collected for research were obtained from three sources: 1) a set of secondary data in the form of Grade Point Average (GPA) received from the registrar, 2) a set of primary data collected throughout structured questionnaire administered to students and alumni at JLC, and 3) another set of primary data collected throughout interviews conducted with staff and educators at JLC. The significance of this study is two folds. First, it validates the effectiveness of the special program at JLC for college-level students who learn differently. Second, it identifies the distinctiveness of the mix of techniques, methods, and practices, including the special individualized and personalized one-on-one approach at JLC.

Keywords: education, neuro-diverse students, program effectiveness, Jones learning center

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