Search results for: energy performance assessment

Authors: Najibullah M, Soumendra Nath Kuiry

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Dams and reservoirs are perceived for their estimable alms to irrigation, water supply, flood control, electricity generation, etc. which civilize the prosperity and wealth of society across the world. Meantime the dam breach could cause devastating flood that can threat to the human lives and properties. Failures of large dams remain fortunately very seldom events. Nevertheless, a number of occurrences have been recorded in the world, corresponding in an average to one to two failures worldwide every year. Some of those accidents have caused catastrophic consequences. So it is decisive to predict the dam break flow for emergency planning and preparedness, as it poses high risk to life and property. To mitigate the adverse impact of dam break, modeling is necessary to gain a good understanding of the temporal and spatial evolution of the dam-break floods. This study will mainly deal with one-dimensional (1D) dam break modeling. Less commonly used in the hydraulic research community, another possible option for modeling the rapidly varied dam-break flows is the extended Boussinesq equations (BEs), which can describe the dynamics of short waves with a reasonable accuracy. Unlike the Shallow Water Equations (SWEs), the BEs taken into account the wave dispersion and non-hydrostatic pressure distribution. To capture the dam-break oscillations accurately it is very much needed of at least fourth-order accurate numerical scheme to discretize the third-order dispersion terms present in the extended BEs. The scope of this work is therefore to develop an 1D fourth-order accurate in both space and time Boussinesq model for dam-break flow analysis by using finite-volume / finite difference scheme. The spatial discretization of the flux and dispersion terms achieved through a combination of finite-volume and finite difference approximations. The flux term, was solved using a finite-volume discretization whereas the bed source and dispersion term, were discretized using centered finite-difference scheme. Time integration achieved in two stages, namely the third-order Adams Basforth predictor stage and the fourth-order Adams Moulton corrector stage. Implementation of the 1D Boussinesq model done using PYTHON 2.7.5. Evaluation of the performance of the developed model predicted as compared with the volume of fluid (VOF) based commercial model ANSYS-CFX. The developed model is used to analyze the risk of cascading dam failures similar to the Panshet dam failure in 1961 that took place in Pune, India. Nevertheless, this model can be used to predict wave overtopping accurately compared to shallow water models for designing coastal protection structures.

Keywords: Boussinesq equation, Coastal protection, Dam-break flow, One-dimensional model

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Authors: Taher Abofol, Yaakov Kareev, Judith Avrahami, Peter M. Todd

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Are children sensitive to their relative strength in competitions against others? Performance on tasks that require cooperation or coordination (e.g. the Ultimatum Game) indicates that early precursors of adult-like notions of fairness and reciprocity, as well as altruistic behavior, are evident at an early age. However, not much is known regarding developmental changes in interactive decision-making, especially in competitive interactions. Thus, it is important to study the developmental aspects of strategic behavior in these situations. The present research focused on cognitive-developmental changes in a competitive interaction. Specifically, it aimed at revealing how children engage in strategic interactions that involve the allocation of limited resources over a number of fields of competition, by manipulating relative strength. Relative strength refers to situations in which player strength changes midway through the game: the stronger player becomes the weaker one, while the weaker player becomes the stronger one. An experiment was conducted to find out if the behavior of children of different age groups differs in the following three aspects: 1. Perception of relative strength. 2. Ability to learn while gaining experience. 3. Ability to adapt to change in relative strength. The task was composed of a resource allocation game. After the players allocated their resources (privately and simultaneously), a competition field was randomly chosen for each player. The player who allocated more resources to the field chosen was declared the winner of that round. The resources available to the two competitors were unequal (or equal, for control). The theoretical solution for this game is that the weaker player should give up on a certain number of fields, depending on the stronger opponent’s relative strength, in order to be able to compete with the opponent on equal footing in the remaining fields. Participants were of three age groups, first-graders (N = 36, mean age = 6), fourth-graders (N = 36, mean age = 10), and eleventh-graders (N = 72, mean age = 16). The games took place between players of the same age and lasted for 16 rounds. There were two experimental conditions – a control condition, in which players were of equal strength, and an experimental condition, in which players differed in strength. In the experimental condition, players' strength was changed midway through the session. Results indicated that players in all age groups were sensitive to their relative strength, and played in line with the theoretical solution: the weaker players gave up on more fields than the stronger ones. This understanding, as well as the consequent difference in allocation between weak and strong players, was more pronounced among older participants. Experience led only to minimal behavioral change. Finally, the children from the two older groups, particularly the eleventh graders adapted quickly to the midway switch in relative strength. In contrast, the first-graders hardly changed their behavior with the change in their relative strength, indicating a limited ability to adapt. These findings highlight young children’s ability to consider their relative strength in strategic interactions and its boundaries.

Keywords: children, competition, decision making, developmental changes, strategic behavior

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Authors: Josie West

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

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

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Authors: E. M. Condori-Peñaloza, S. S. Costa

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Eleusine indica L, known as goose-grass, is considered a troublesome weed that can cause important economic losses in the agriculture worldwide. However, this grass is used as a medicinal plant in some regions of Brazil to treat influenza and pneumonia. In Africa and Asia, it is used to treat malaria and as diuretic, anti-helminthic, among other uses. Despite its therapeutic potential, little is known about the chemical composition and bioactive compounds of E. indica. Hitherto, two major flavonoids, schaftoside and vitexin, were isolated from aerial part of the species and showed inhibitory activity on lung neutrophil influxes in mice, suggesting a beneficial effect on airway inflammation. Therefore, the aim of this study was to analyze the chemical profile of aqueous extracts from aerial parts of Eleusine indica specimens using high performance liquid chromatography (HPLC-DAD) and 1H nuclear magnetic resonance spectroscopy (NMR), with emphasis on phenolic compounds. Specimens of E. indica were collected in Minas Gerais state, Brazil. Aerial parts of fresh plants were extracted by decoction (10% p/v). After spontaneous precipitation of the aqueous extract at 10-12°C for 24 hours, the supernatant obtained was frozen and lyophilized. After that, 1 g of the extract was dissolved into 25 mL of water and fractionated on a reverse phase chromatography column (RP-2), eluted with a gradient of H2O/EtOH. Five fractions were obtained. The extract and fractions had their chemical profile analyzed by using HPLC-DAD (C-18 column: 20 μL, 256 -365 nm; gradient water 0.01% phosphoric acid/ acetonitrile. The extract was also analyzed by NMR (1H, 500 MHz, D2O) in order to access its global chemical composition. HPLC-DAD analyses of crude extract allowed the identification of ten phenolic compounds. Fraction 1, eluted with 100% water, was poor in phenolic compounds and no major peak was detected. In fraction 2, eluted with 100% water, it was possible to observe one major peak at retention time (RT) of 23.75 minutes compatible with flavonoid; fraction 3, also eluted with 100% water, showed four peaks at RT= 21.47, 23.52, 24.33 and 25.84 minutes, all of them compatible with flavonoid. In fraction 4, eluted with 50%/ethanol/50% water, it was possible to observe 3 peaks compatible with flavonoids at RT=24.65, 26.81, 27.49 minutes, and one peak (28.83 min) compatible with a phenolic acid derivative. Finally, in fraction 5, eluted with 100% ethanol, no phenolic substance was detected. The UV spectra of all flavonoids detected were compatible with the flavone subclass (λ= 320-345 nm). The 1H NMR spectra of aerial parts extract showed signals in three regions: δ 0.8-3.0 ppm (aliphatic compounds), δ 3.0-5.5 ppm corresponding to carbohydrates (signals most abundant and overlapped), and δ 6.0-8.5 ppm (aromatic compounds). Signals compatible with flavonoids (rings A and B) could also be detected in the crude extract spectra. These results suggest the presence of several flavonoids in E. indica, which reinforces their therapeutic potential. The pharmacological activities of Eleusine indica extracts and fractions will be further evaluated.

Keywords: flavonoids, HPLC, NMR, phenolic compounds

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Authors: Elkington S. Mnguni

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

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

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Authors: Akinola Helen Olufunke, Soetan Olatunbosun Jonathan, Adeleye Oludamola

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Introduction: Antibiotic resistance has grown significantly, which is a major cause for concern. There have not been many significant developments in antibiotics over the past few decades, and practically all of the ones that are currently in use are losing effectiveness against pathogenic germs. Researchers are starting to focus more on the physiologically active compounds found in plants, particularly phytobiotics in poultry production. Consumption of chicken products is among the greatest in the country, but numerous nations, including Nigeria, use excessive amounts of necessary antibiotics in poultry farming, endangering the safety of such goods (through antimicrobial residues). Drug resistance has become a widespread issue as a result of the risky use of antibiotics in the chicken production industry. In order to replace antibiotics, biotic or natural products like phytobiotics (also known as botanicals or phytogenics) have drawn a lot of interest. Phytobiotics or their components are thought to be a relatively recent category of natural herbs that have acquired acceptance and favor among chicken farmers. The addition of several phytobiotic additions to poultry feed has demonstrated its capacity to improve both the broiler and layer populations' productivity. Design: Experimental research design and cross-sectional study was carried out at every 300 purposively selected farming household in the six-geopolitical zone in Nigeria. Data Analysis: A semi-structured questionnaire was administered to each farmer, and quantitative data were analyzed using Statistical Package for Social Science (SPSS) while the Chi-square test was used to analyze factors mitigating the use of Phytobiotics. Result: The result shows that the benefits associated with the use of phytobiotics are contributed to growth promotion in chickens and enhancement of productive performance of broiler and layer, which could be attributed to their antioxidant activity. The result further revealed that factors mitigating the use of phytobiotics were lack of knowledge in the use of phytobiotics, overdose or underdose usage, and seasonal availability of the phytobiotics. Others are the educational level of the farmers, intrinsic motivation, income poultry farming experience, price of phytobiotics based additives feeds, and intensity of extension agents in visiting them. Conclusion: The difficulties associated with using phytobiotics in chicken farms limit their willingness to boost productivity. The study found that most farmers were ignorant, which prevented them from handling this notion and turning their poultry into a viable enterprise while also allowing them to be creative. They believed that packing phytobiotics-based additive feed was expensive, and lastly, the seasonal availability of some phytobiotics. Recommendation: Further research in phytobiotics use in Nigeria should be carried out in order to establish its efficiency, safety, and awareness.

Keywords: mitigating, antibiotics, phytobiotics, poultry farming

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Authors: Xinyu Wei, Mingming Peng, Kenji Kamiya, Eika Qian

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Iso-stearic acid as a saturated fatty acid with a branched chain shows a low pour point, high oxidative stability and great biodegradability. The industrial production of iso-stearic acid involves first isomerizing unsaturated fatty acids into branched-chain unsaturated fatty acids (BUFAs), followed by hydrogenating the branched-chain unsaturated fatty acids to obtain iso-stearic acid. However, the production yield of iso-stearic acid is reportedly less than 30%. In recent decades, extensive research has been conducted on branched fatty acids. Most research has replaced acidic clays with zeolites due to their high selectivity, good thermal stability, and renewability. It was reported that isomerization of unsaturated fatty acid occurred mainly inside the zeolite channel. In contrast, the production of by-products like dimer acid mainly occurs at acid sites outside the surface of zeolite. Further, the deactivation of catalysts is attributed to the pore blockage of zeolite. In the present study, micro/mesoporous ZSM-22 zeolites were developed. It is clear that the synthesis of a micro/mesoporous ZSM-22 zeolite is regarded as the ideal strategy owing to its ability to minimize coke formation. Different mesoporosities micro/mesoporous H-ZSM-22 zeolites were prepared through recrystallization of ZSM-22 using sodium hydroxide solution (0.2-1M) with cetyltrimethylammonium bromide template (CTAB). The structure, morphology, porosity, acidity, and isomerization performance of the prepared catalysts were characterized and evaluated. The dissolution and recrystallization process of the H-ZSM-22 microporous zeolite led to the formation of approximately 4 nm-sized mesoporous channels on the outer surface of the microporous zeolite, resulting in a micro/mesoporous material. This process increased the weak Brønsted acid sites at the pore mouth while reducing the total number of acid sites in ZSM-22. Finally, an activity test was conducted using oleic acid as a model compound in a fixed-bed reactor. The activity test results revealed that micro/mesoporous H-ZSM-22 zeolites exhibited a high isomerization activity, reaching >70% selectivity and >50% yield of BUFAs. Furthermore, the yield of oligomers was limited to less than 20%. This demonstrates that the presence of mesopores in ZSM-22 enhances contact between the feedstock and the active sites within the catalyst, thereby increasing catalyst activity. Additionally, a portion of the dissolved and recrystallized silica adhered to the catalyst's surface, covering the surface-active sites, which reduced the formation of oligomers. This study offers distinct insights into the production of iso-stearic acid using a fixed-bed reactor, paving the way for future research in this area.

Keywords: Iso-stearic acid, oleic acid, skeletal isomerization, micro/mesoporous, ZSM-22

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Authors: Abid Hussain, Binay Kumar

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Environment-friendly lead-free Na₀.₅₂K₀.₄₄Li₀.₀₄Nb₀.₈₄Ta₀.₁₀Sb₀.₀₆O₃ (NKLNTS) ceramic was synthesized by solid-state reaction method in search of a potential candidate to replace lead-based ceramics such as PbZrO₃-PbTiO₃ (PZT), Pb(Mg₁/₃Nb₂/₃)O₃-PbTiO₃ (PMN-PT) etc., for various applications. The ceramic was calcined at temperature 850 ᵒC and sintered at 1090 ᵒC. The powder X-Ray Diffraction (XRD) pattern revealed the formation of pure perovskite phase having tetragonal symmetry with space group P4mm of the synthesized ceramic. The surface morphology of the ceramic was studied using Field Emission Scanning Electron Microscopy (FESEM) technique. The well-defined grains with homogeneous microstructure were observed. The average grain size was found to be ~ 0.6 µm. A very large value of piezoelectric charge coefficient (d₃₃ ~ 754 pm/V) was obtained for the synthesized ceramic which indicated its potential for use in transducers and actuators. In dielectric measurements, a high value of ferroelectric to paraelectric phase transition temperature (Tm~305 ᵒC), a high value of maximum dielectric permittivity ~ 2110 (at 1 kHz) and a very small value of dielectric loss ( < 0.6) were obtained which suggested the utility of NKLNTS ceramic in high-temperature ferroelectric devices. Also, the degree of diffuseness (γ) was found to be 1.61 which confirmed a relaxor ferroelectric behavior in NKLNTS ceramic. P-E hysteresis loop was traced and the value of spontaneous polarization was found to be ~11μC/cm² at room temperature. The pyroelectric coefficient was obtained to be very high (p ∼ 1870 μCm⁻² ᵒC⁻¹) for the present case indicating its applicability in pyroelectric detector applications including fire and burglar alarms, infrared imaging, etc. NKLNTS ceramic showed fatigue free behavior over 107 switching cycles. Remanent hysteresis task was performed to determine the true-remanent (or intrinsic) polarization of NKLNTS ceramic by eliminating non-switchable components which showed that a major portion (83.10 %) of the remanent polarization (Pr) is switchable in the sample which makes NKLNTS ceramic a suitable material for memory switching devices applications. Time-Dependent Compensated (TDC) hysteresis task was carried out which revealed resistive leakage free nature of the ceramic. The performance of NKLNTS ceramic was found to be superior to many lead based piezoceramics and hence can effectively replace them for use in piezoelectric, pyroelectric and long duration ferroelectric applications.

Keywords: dielectric properties, ferroelectric properties , lead free ceramic, piezoelectric property, solid state reaction, true-remanent polarization

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Soni T. L.

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Sustainable environmental stress is a major concern which needs immediate attention. This paper is an attempt to present participatory action research for sustainable agriculture. Being first and best culture, agriculture protects and improves the natural environment, the social and economic conditions of people, and safeguards the health and welfare of all groups. During course of time agriculture turned to agribusiness, then the values are not safeguarded. Moreover, in today’s busy life many are not taking efforts to take part in agriculture production. Then children are not getting the opportunity to understand agriculture and farming practices. So student initiatives are vital to make them aware. Here the programmes structured by the researcher come under the auspicious of National Service Scheme, a student-centered educational programme, organized by Ministry of Youth Affairs, Government of India. The twin objectives of the study are to examine the role of student initiatives for sustainable agriculture and the role of participatory action research in student initiatives. SWOT analysis is made to study strengths, weaknesses, threats and opportunities. The Methodology adopted is Participatory Action Research. The method is participatory in a sense there is collaboration through participation. The method is action, there is lab land experiences which is real. The method is research that there is documented lessons and creation of new knowledge. Plan of action cover measures adopted and strategies taken i.e., bhavana – kalpana – yojana – sadhana. Through the team effort, the team was successful in converting more than 10 hectares of barren land into cultivable land within and outside the campus. Team efforts of students saved a huge amount of labour cost and produced a huge quantity of organic output and the team was also successful in creating 1000 rain pits in the premises of College for rainwater harvesting. The findings include conveyance of the Message: Food Production is superior to Food donation. Moreover, the study fostered good work ethic and social responsibility among students. Students undertake innovative programmes underlying social and environmental issues and participants got increased opportunities to interact with local and less privileged and acquired increased awareness about real-life experiences which make them confident to interact with people and it resulted in the strengthening of social capital- cooperation, team spirit, social commitment among students. Participants promoted sustainable domestic efforts and ultimately environmental protection is ensured. Finally, there is recognition to the team, institution and the researcher at the university level, state level and at the national level. The learned lessons are, if the approach is good, the response is good and success generates success. Participatory action research is empowering experience for practitioners, focusing the combined time, energy and creativity of a committed group we should lead so many programmes which makes the institution centre of excellence. Authorities should take necessary steps for the Inclusion of community development activities in the curriculum. Action research is problem, client and action centered. So, we must adapt and adopt, coordinates and correlates measures which preserve and conserve the environment.

Keywords: participatory action research, student initiatives, sustainable development, sustainability

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Authors: Doni Dermawan

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Modern sports competition as a consequence of the increase in the value of the business and entertainment in the field of sport has been demanding athletes to always have excellent physical endurance performance. Physical exercise is done in a long time, and intensive may pose a risk of muscle tissue damage caused by the increase of the enzyme creatine kinase. Branched Chain Amino Acids (BCAA) is an essential amino acid that is composed of leucine, isoleucine, and valine which serves to maintain muscle tissue, keeping the immune system, and prevent further loss of coordination and muscle pain. Pea (Pisum sativum L.) is a kind of leguminous plants that are rich in Branched Chain Amino Acids (BCAA) where every one gram of protein pea contains 82.7 mg of leucine; 56.3 mg isoleucine; and 56.0 mg of valine. This research aims to develop Branched Chain Amino Acids (BCAA) from pea extract is applied in dosage forms Gel PVP Kinesio Tape technology using Ultrasound-assisted Extraction. The method used in the writing of this paper is the Cochrane Collaboration Review that includes literature studies, testing the quality of the study, the characteristics of the data collection, analysis, interpretation of results, and clinical trials as well as recommendations for further research. Extraction of BCAA in pea done using ultrasound-assisted extraction technology with optimization variables includes the type of solvent extraction (NaOH 0.1%), temperature (20-250C), time (15-30 minutes) power (80 watt) and ultrasonic frequency (35 KHz). The advantages of this extraction method are the level of penetration of the solvent into the membrane of the cell is high and can increase the transfer period so that the BCAA substance separation process more efficient. BCAA extraction results are then applied to the polymer PVP (Polyvinylpyrrolidone) Gel powder composed of PVP K30 and K100 HPMC dissolved in 10 mL of water-methanol (1: 1) v / v. Preparations Kinesio Tape Gel PVP is the BCAA in the gel are absorbed into the muscle tissue, and joints through tensile force then provides stimulation to the muscle circulation with variable pressure so that the muscle can increase the biomechanical movement and prevent damage to the muscle enzyme creatine kinase. Analysis and evaluation of test preparation include interaction, thickness, weight uniformity, humidity, water vapor permeability, the levels of the active substance, content uniformity, percentage elongation, stability testing, release profile, permeation in vitro and in vivo skin irritation testing.

Keywords: branched chain amino acid, BCAA, Kinesio tape, pea, PVP gel, ultrasound-assisted extraction

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Authors: K. Ghosh, S. N. Tripathi, Manish Joshi, Y. S. Mayya, Arshad Khan, B. K. Sapra

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We have developed a CFD coupled aerosol microphysics model in the context of aerosol generation from a glowing wire. The governing equations can be solved implicitly for mass, momentum, energy transfer along with aerosol dynamics. The computationally efficient framework can simulate temporal behavior of total number concentration and number size distribution. This formulation uniquely couples standard K-Epsilon scheme with boundary layer model with detailed aerosol dynamics through residence time. This model uses measured temperatures (wire surface and axial/radial surroundings) and wire compositional data apart from other usual inputs for simulations. The model predictions show that bulk fluid motion and local heat distribution can significantly affect the aerosol behavior when the buoyancy effect in momentum transfer is considered. Buoyancy generated turbulence was found to be affecting parameters related to aerosol dynamics and transport as well. The model was validated by comparing simulated predictions with results obtained from six controlled experiments performed with a laboratory-made hot wire nanoparticle generator. Condensation particle counter (CPC) and scanning mobility particle sizer (SMPS) were used for measurement of total number concentration and number size distribution at the outlet of reactor cell during these experiments. Our model-predicted results were found to be in reasonable agreement with observed values. The developed model is fast (fully implicit) and numerically stable. It can be used specifically for applications in the context of the behavior of aerosol particles generated from glowing wire technique and in general for other similar large scale domains. Incorporation of CFD in aerosol microphysics framework provides a realistic platform to study natural convection driven systems/ applications. Aerosol dynamics sub-modules (nucleation, coagulation, wall deposition) have been coupled with Navier Stokes equations modified to include buoyancy coupled K-Epsilon turbulence model. Coupled flow-aerosol dynamics equation was solved numerically and in the implicit scheme. Wire composition and temperature (wire surface and cell domain) were obtained/measured, to be used as input for the model simulations. Model simulations showed a significant effect of fluid properties on the dynamics of aerosol particles. The role of buoyancy was highlighted by observation and interpretation of nucleation zones in the planes above the wire axis. The model was validated against measured temporal evolution, total number concentration and size distribution at the outlet of hot wire generator cell. Experimentally averaged and simulated total number concentrations were found to match closely, barring values at initial times. Steady-state number size distribution matched very well for sub 10 nm particle diameters while reasonable differences were noticed for higher size ranges. Although tuned specifically for the present context (i.e., aerosol generation from hotwire generator), the model can also be used for diverse applications, e.g., emission of particles from hot zones (chimneys, exhaust), fires and atmospheric cloud dynamics.

Keywords: nanoparticles, k-epsilon model, buoyancy, CFD, hot wire generator, aerosol dynamics

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Authors: Vinu Viswanath, Lawrence Dsouza, Ugo Ravon

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

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

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Authors: Jianan Sun, Ziwen Ye

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Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

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Authors: Julien Benomar

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The World Bank report published in April 2023 called “Migrants, Refugees and Society” allows us to first distinguish migrants in search of economic opportunities and refugees that flee a situation of danger and choose their destination based on their immediate need for safety. Amongst those two categories, the report distinguished people having professional skills adapted to the labor market of the host country and those who have not. Out of that distinction of four categories, we choose to focus our research on refugees that do not have professional skills adapted to the labor market of the host country. Given that refugees generally have no recourse to public assistance schemes and cannot count on the support of their entourage or support network, we propose to examine the extent to which external assistance, such as international humanitarian action, is likely to accompany refugees' transition to financial empowerment through entrepreneurship. To this end, we propose to carry out a case study structured in three stages: (i) an exchange with a Non-Governmental Organisation (NGO) active in supporting refugee populations from Congo and Burundi to Rwanda, enabling us to (i.i) define together a financial empowerment income, and (i. ii) learn about the content of the support measures taken for the beneficiaries of the humanitarian project; (ii) monitor the population of 118 beneficiaries, including 73 refugees and 45 Rwandans (reference population); (iii) conduct a participatory analysis to identify the level of performance of the project and areas for improvement. The case study thus involved the staff of an international NGO active in helping refugees from Rwanda since 2015 and the staff of a Luxembourg NGO that has been funding this economic aid project through entrepreneurship since 2021. The case study thus involved the staff of an international NGO active in helping refugees from Rwanda since 2015 and the staff of a Luxembourg NGO, which has been funding this economic aid through an entrepreneurship project since 2021, and took place over a 48-day period between April and May 2023. The main results are of two types: (i) the need to associate indicators for monitoring the impact of the project on the indirect beneficiaries of the project (refugee community) and (ii) the identification of success factors making it possible to bring concrete and relevant responses to the constraints encountered. The first result thus made it possible to identify the following indicators: Indicator of community potential ((jobs, training or mentoring) promoted by the activity of the entrepreneur), Indicator of social contribution (tax paid by the entrepreneur), Indicator of resilience (savings and loan capacity generated, and finally impact on social cohesion. The second result made it possible to identify that among the 7 success factors tested, the sector of activity chosen and the level of experience in the sector of the future activity are those that stand out the most clearly.

Keywords: entrepreuneurship, refugees, financial empowerment, international aid

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Authors: Jean Pierre Ribeiro Daquila

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This paper aims to analyze the use of the Theory of Multiple Intelligences as a tool to facilitate students’ learning. This theory, proposed by the American psychologist and educator Howard Gardner, was first established in 1983 and advocates that human beings possess eight intelligence and not only one, as defended by psychologists prior to his theory. These intelligence are bodily-kinesthetic intelligence, musical, linguistic, logical-mathematical, spatial, interpersonal, intrapersonal, and naturalist. This paper will focus on bodily-kinesthetic intelligence. Spatial and bodily-kinesthetic intelligences are sensed by athletes, dancers, and others who use their bodies in ways that exceed normal abilities. These are intelligences that are closely related. A quarterback or a ballet dancer needs to have both an awareness of body motions and abilities as well as a sense of the space involved in the action. Nevertheless, there are many reasons which make classical ballet dance more integrated with other intelligences. Ballet dancers make it look effortless as they move across the stage, from the lifts to the toe points; therefore, there is acting both in the performance of the repertoire and in hiding the pain or physical stress. The ballet dancer has to have great mathematical intelligence to perform a fast allegro; for instance, each movement has to be executed in a specific millisecond. Flamenco dancers need to rely as well on their mathematic abilities, as the footwork requires the ability to make half, two, three, four or even six movements in just one beat. However, the precision of the arm movements is freer than in ballet dance; for this reason, ballet dancers need to be more holistically aware of their movements; therefore, our experiment will test whether this greater attention required by ballet dancers makes them acquire better results in the training sessions when compared to flamenco dancers. An experiment will be carried out in this study by training ballet dancers through dance (four years of experience dancing minimum – experimental group 1); a group of flamenco dancers (four years of experience dancing minimum – experimental group 2). Both experimental groups will be trained in two different domains – phonetics and chemistry – to examine whether there is a significant improvement in these areas compared to the control group (a group of regular students who will receive the same training through a traditional method). However, this paper will focus on phonetic training. Experimental group 1 will be trained with the aid of classical music plus bodily work. Experimental group 2 will be trained with flamenco rhythm and kinesthetic work. We would like to highlight that this study takes dance as an example of a possible area of strength; nonetheless, other types of arts can and should be used to support students, such as drama, creative writing, music and others. The main aim of this work is to suggest that other intelligences, in the case of this study, bodily-kinesthetic, can be used to help improve pronunciation.

Keywords: multiple intelligences, pronunciation, effective pronunciation trainings, short drills, musical intelligence, bodily-kinesthetic intelligence

Procedia PDF Downloads 96

Authors: Ugo Galvanetto, Pirto G. Pavan, Mirco Zaccariotto

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The discipline of Computer-integrated surgery (CIS) will provide equipment able to improve the efficiency of healthcare systems and, which is more important, clinical results. Surgeons and machines will cooperate in new ways that will extend surgeons’ ability to train, plan and carry out surgery. Patient specific CIS of the brain requires several steps: 1 - Fast generation of brain models. Based on image recognition of MR images and equipped with artificial intelligence, image recognition techniques should differentiate among all brain tissues and segment them. After that, automatic mesh generation should create the mathematical model of the brain in which the various tissues (white matter, grey matter, cerebrospinal fluid …) are clearly located in the correct positions. 2 – Reliable and fast simulation of the surgical process. Computational mechanics will be the crucial aspect of the entire procedure. New algorithms will be used to simulate the mechanical behaviour of cutting through cerebral tissues. 3 – Real time provision of visual and haptic feedback A sophisticated human-machine interface based on ergonomics and psychology will provide the feedback to the surgeon. The present work will address in particular point 2. Modelling the cutting of soft tissue in a structure as complex as the human brain is an extremely challenging problem in computational mechanics. The finite element method (FEM), that accurately represents complex geometries and accounts for material and geometrical nonlinearities, is the most used computational tool to simulate the mechanical response of soft tissues. However, the main drawback of FEM lies in the mechanics theory on which it is based, classical continuum Mechanics, which assumes matter is a continuum with no discontinuity. FEM must resort to complex tools such as pre-defined cohesive zones, external phase-field variables, and demanding remeshing techniques to include discontinuities. However, all approaches to equip FEM computational methods with the capability to describe material separation, such as interface elements with cohesive zone models, X-FEM, element erosion, phase-field, have some drawbacks that make them unsuitable for surgery simulation. Interface elements require a-priori knowledge of crack paths. The use of XFEM in 3D is cumbersome. Element erosion does not conserve mass. The Phase Field approach adopts a diffusive crack model instead of describing true tissue separation typical of surgical procedures. Modelling discontinuities, so difficult when using computational approaches based on classical continuum Mechanics, is instead easy for novel computational methods based on Peridynamics (PD). PD is a non-local theory of mechanics formulated with no use of spatial derivatives. Its governing equations are valid at points or surfaces of discontinuity, and it is, therefore especially suited to describe crack propagation and fragmentation problems. Moreover, PD does not require any criterium to decide the direction of crack propagation or the conditions for crack branching or coalescence; in the PD-based computational methods, cracks develop spontaneously in the way which is the most convenient from an energy point of view. Therefore, in PD computational methods, crack propagation in 3D is as easy as it is in 2D, with a remarkable advantage with respect to all other computational techniques.

Keywords: computational mechanics, peridynamics, finite element, biomechanics

Procedia PDF Downloads 80

Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

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Authors: Sina Kazemi, Farshid Torabi, Todd Peterson

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Drilling in shale formations is frequently time-consuming, challenging, and fraught with mechanical failures such as stuck pipes or hole packing off when the cutting removal rate is not sufficient to clean the bottom hole. Crossing the heavy oil shale and sand reservoirs with active shale and microfractures is generally associated with severe fluid losses causing a reduction in the rate of the cuttings removal. These circumstances compromise a well’s integrity and result in a lower rate of penetration (ROP). This study presents collective results of field studies and theoretical analysis conducted on data from South Pars and North Dome in an Iran-Qatar offshore field. Solutions to complications related to drilling in shale formations are proposed through systemically analyzing and applying modeling techniques to select field mud logging data. Field data measurements during actual drilling operations indicate that in a shale formation where the return flow of polymer mud was almost lost in the upper dolomite layer, the performance of hole cleaning and ROP progressively change when higher string rotations are initiated. Likewise, it was observed that this effect minimized the force of rotational torque and improved well integrity in the subsequent casing running. Given similar geologic conditions and drilling operations in reservoirs targeting shale as the producing zone like the Bakken formation within the Williston Basin and Lloydminster, Saskatchewan, a drill bench dynamic modeling simulation was used to simulate borehole cleaning efficiency and mud optimization. The results obtained by altering RPM (string revolution per minute) at the same pump rate and optimized mud properties exhibit a positive correlation with field measurements. The field investigation and developed model in this report show that increasing the speed of string revolution as far as geomechanics and drilling bit conditions permit can minimize the risk of mechanically stuck pipes while reaching a higher than expected ROP in shale formations. Data obtained from modeling and field data analysis, optimized drilling parameters, and hole cleaning procedures are suggested for minimizing the risk of a hole packing off and enhancing well integrity in shale reservoirs. Whereas optimization of ROP at a lower pump rate maintains the wellbore stability, it saves time for the operator while reducing carbon emissions and fatigue of mud motors and power supply engines.

Keywords: ROP, circulating density, drilling parameters, return flow, shale reservoir, well integrity

Procedia PDF Downloads 86

Authors: Claire Tranter, Coral Dando

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Gathering information from others is a fundamental goal for those concerned with investigating crime, and protecting national and international security. Persuading an individual to move from an opposing to converging viewpoint, and an understanding on the cognitive style behind this change can serve to increase understanding of traditional face-to-face interactions, as well as synthetic environments (SEs) often used for communication across varying geographical locations. SEs are growing in usage, and with this increase comes an increase in crime being undertaken online. Communication technologies can allow people to mask their real identities, supporting anonymous communication which can raise significant challenges for investigators when monitoring and managing these conversations inside SEs. To date, the psychological literature concerning how to maximise information-gain in SEs for real-world interviewing purposes is sparse, and as such this aspect of social cognition is not well understood. Here, we introduce an overview of a novel programme of PhD research which seeks to enhance understanding of cross-cultural and cross-gender communication in SEs for maximising information gain. Utilising a dyadic jury paradigm, participants interacted with a confederate who attempted to persuade them to the opposing verdict across three distinct environments: face-to-face, instant messaging, and a novel virtual reality environment utilising avatars. Participants discussed a criminal scenario, acting as a two-person (male; female) jury. Persuasion was manipulated by the confederate claiming an opposing viewpoint (guilty v. not guilty) to the naïve participants from the outset. Pre and post discussion data, and observational digital recordings (voice and video) of participant’ discussion performance was collected. Information regarding cognitive style was also collected to ascertain participants need for cognitive closure and biases towards jumping to conclusions. Findings revealed that individuals communicating via an avatar in a virtual reality environment reacted in a similar way, and thus equally persuasive, when compared to individuals communicating face-to-face. Anonymous instant messaging however created a resistance to persuasion in participants, with males showing a significant decline in persuasive outcomes compared to face to face. The findings reveal new insights particularly regarding the interplay of persuasion on gender and modality, with anonymous instant messaging enhancing resistance to persuasion attempts. This study illuminates how varying SE can support new theoretical and applied understandings of how judgments are formed and modified in response to advocacy.

Keywords: applied cognition, persuasion, social media, virtual reality

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Authors: Sigal Gat-Lazer, Ronny Geva, Dan Ramon, Eitan Gur, Daniel Stein

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Introduction: Eating disorders (ED) are common psychopathologies which involve distorted body image and eating disturbances. Binge-purge eating disorders (B/P ED) are characterized by repetitive events of binge eating followed by purges. Patients with B/P ED behavior may be seen as impulsive especially when relate to food stimulation and affective conditions. The current study included innovative modification of the day-night task targeted to assess inhibitory control among patients with B/P ED. Methods: This prospective study included 50 patients with B/P ED during acute phase of illness (T1) upon their admission to specialized ED department in tertiary center. 34 patients repeated the study towards discharge to ambulatory care (T2). Treatment effect was evaluated by BMI and emotional questionnaires regarding depression and anxiety by the Beck Depression Inventory and State Trait Anxiety Inventory questionnaires. Control group included 36 healthy controls with matched demographic parameters who performed both T1 and T2 assessments. The current modification is based on the emotional day-night task (EDNT) which involves five emotional stimulation added to the sun and moon pictures presented to participants. In the current study, we designed the food-emotional modification day night task (F-EDNT) food stimulations of egg and banana which resemble the sun and moon, respectively, in five emotional states (angry, sad, happy, scrambled and neutral). During this computerized task, participants were instructed to push on “day” bottom in response to moon and banana stimulations and on “night” bottom when sun and egg were presented. Accuracy (A) and reaction time (RT) were evaluated and compared between EDNT and F-EDNT as a reflection of participants’ inhibitory control. Results: Patients with B/P ED had significantly improved BMI, depression and anxiety scores on T2 compared to T1 (all p<0.001). Task performance was similar among patients and controls in the EDNT without significant A or RT differences in both T1 and T2. On F-EDNT during T1, B/P ED patients had significantly reduced accuracy in 4/5 emotional stimulation compared to controls: angry (73±25% vs. 84±15%, respectively), sad (69±25% vs. 80±18%, respectively), happy (73±24% vs. 82±18%, respectively) and scrambled (74±24% vs. 84±13%, respectively, all p<0.05). Additionally, patients’ RT to food stimuli was significantly faster compared to neutral ones, in both cry and neutral emotional stimulations (356±146 vs. 400±141 and 378±124 vs. 412±116 msec, respectively, p<0.05). These significant differences between groups as a function of stimulus type were diminished on T2. Conclusion: Having to process food related content, in particular in emotional context seems to be impaired in patients with B/P ED during the acute phase of their illness and elicits greater impulsivity. Innovative modification using such procedures seem to be sensitive to patients’ illness phase and thus may be implemented during screening and follow up through the clinical management of these patients.

Keywords: binge purge eating disorders, day night task modification, eating disorders, food related stimulations

Procedia PDF Downloads 381

Authors: Chang Liu, Rui Xing, Liyan Tang, Guohong Wang

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Entrepreneurial actions are based on entrepreneurial decisions. The quality of decisions influences entrepreneurial activities and subsequent new venture performance. Uncertainty of surroundings put heightened demands on the team as a whole, and each team member. Diverse team composition provides rich information, which a team can draw when making complex decisions. However, team heterogeneity may cause emotional conflicts, which is adverse to team outcomes. Thus, the effects of team heterogeneity on team outcomes are complex. Although team heterogeneity is an essential factor influencing entrepreneurial decision-making, there is a lack of empirical analysis on under what conditions team heterogeneity plays a positive role in promoting decision-making quality. Entrepreneurial teams always struggle with complex tasks. How a team shapes its teamwork is key in resolving constant issues. As a collective regulatory process, team reflexivity is characterized by continuous joint evaluation and discussion of team goals, strategies, and processes, and adapt them to current or anticipated circumstances. It enables diversified information to be shared and overtly discussed. Instead of hostile interpretation of opposite opinions team members take them as useful insights from different perspectives. Team reflexivity leads to better integration of expertise to avoid the interference of negative emotions and conflict. Therefore, we propose that team reflexivity is a conditional factor that influences the impact of team heterogeneity on high-quality entrepreneurial decisions. In this study, we identify team heterogeneity as a crucial determinant of entrepreneurial decision quality. Integrating the literature on decision-making and team heterogeneity, we investigate the relationship between team heterogeneity and entrepreneurial decision-making quality, treating team reflexivity as a moderator. We tested our hypotheses using the hierarchical regression method and the data gathered from 63 teams and 205 individual members from 45 new firms in China's first-tier cities such as Beijing, Shanghai, and Shenzhen. This research found that both teams' education heterogeneity and teams' functional background heterogeneity were significantly positively related to entrepreneurial decision-making quality, and the positive relation was stronger in teams with a high level of team reflexivity. While teams' specialization of education heterogeneity was negatively related to decision-making quality, and the negative relationship was weaker in teams with a high level of team reflexivity. We offer two contributions to decision-making and entrepreneurial team literatures. Firstly, our study enriches the understanding of the role of entrepreneurial team heterogeneity in entrepreneurial decision-making quality. Different from previous entrepreneurial decision-making literatures, which focus more on decision-making modes of entrepreneurs and the top management team, this study is a significant attempt to highlight that entrepreneurial team heterogeneity makes a unique contribution to generating high-quality entrepreneurial decisions. Secondly, this study introduced team reflexivity as the moderating variable, to explore the boundary conditions under which the entrepreneurial team heterogeneity play their roles.

Keywords: decision-making quality, entrepreneurial teams, education heterogeneity, functional background heterogeneity, specialization of education heterogeneity

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Authors: Nilson Rogério Da Silva, Ingrid Casagrande, Isabela Chicarelli Amaro Santos

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Introduction: People with Autism Spectrum Disorder (ASD) may face difficulties in social inclusion in different segments of society, especially in entering and staying at work. In Brazil, although there is legislation that equates it to the condition of disability, the number of people at work is still low. The United Nations estimates that more than 80 percent of adults with autism are jobless. In Brazil, the scenario is even more nebulous because there is no control and tracking of accurate data on the number of individuals with autism and how many of these are inserted in the labor market. Pereira and Goyos (2019) found that there is practically no scientific production about people with ASD in the labor market. Objective: To describe the experience of people with ASD inserted in the work, facilities and difficulties found in the professional exercise and the strategies used to maintain the job. Methodology: The research was approved by the Research Ethics Committee. As inclusion criteria for participation, the professional should accept to participate voluntarily, be over 18 years of age and have had some experience with the labor market. As exclusion criteria, being under 18 years of age and having never worked in a work activity. Participated in the research of 04 people with a diagnosis of ASD, aged 22 to 32 years. For data collection, an interview script was used that addressed: 1) General characteristics of the participants; 2) Family support; 3) School process; 4) Insertion in the labor market; 5) Exercise of professional activity; (6) Future and Autism; 7) Possible coping strategies. For the analysis of the data obtained, the full transcription of the interviews was performed and the technique of Content Analysis was performed. Results: The participants reported problems in different aspects: In the school environment: difficulty in social relationships, and Bullying. Lack of adaptation to the school curriculum and the structure of the classroom; In the Faculty: difficulty in following the activities, ealizar group work, meeting deadlines and establishing networking; At work: little adaptation in the work environment, difficulty in establishing good professional bonds, difficulty in accepting changes in routine or operational processes, difficulty in understanding veiled social rules. Discussion: The lack of knowledge about what disability is and who the disabled person is leads to misconceptions and negatives regarding their ability to work and in this context, people with disabilities need to constantly prove that they are able to work, study and develop as a human person, which can be classified as ableism. The adaptations and the use of technologies to facilitate the performance of people with ASD, although guaranteed in national legislation, are not always available, highlighting the difficulties and prejudice. Final Considerations: The entry and permanence of people with ASD at work still constitute a challenge to be overcome, involving changes in society in general, in companies, families and government agencies.

Keywords: autism spectrum disorder (ASD), work, disability, autism

Procedia PDF Downloads 79

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

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

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

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Authors: 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 133

Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

Procedia PDF Downloads 138

Authors: Stephanie Gracelyn Rahaman, Chew Yin Teng, Manjit Singh Sandhu

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Corporate scandals have made stakeholders apprehensive of large companies and expect greater transparency in CSR matters. However, companies find it challenging to strategically communicate CSR to intended stakeholders and in the process may fall short on maximizing on CSR efforts. Given that stakeholders have the ability to either reward good companies or take legal action or boycott against corporate brands who do not act socially responsible, companies must create shared understanding of their CSR activities. As a result, communication has become a strategy for many companies to demonstrate CSR engagement and to minimize stakeholder skepticism. The main objective of this research is to examine the types of CSR communication strategies and predictors that guide CSR communication strategies. Employing Morsing & Schultz’s guide on CSR communication strategies, the study integrates stakeholder and institutional theory to develop a conceptual framework. The conceptual framework hypothesized that stakeholder (instrumental and normative) and institutional (regulatory environment, nature of business, mimetic intention, CSR focus and corporate objectives) dimensions would drive CSR communication strategies. Preliminary findings from semi-structured interviews in Malaysia are consistent with the conceptual model in that stakeholder and institutional expectations guide CSR communication strategies. Findings show that most companies use two-way communication strategies. Companies that identified employees, the public or customers as key stakeholders have started to embrace social media to be in-sync with new trends of communication. This is especially with the Gen Y which is their priority. Some companies creatively use multiple communication channels because they recognize different stakeholders favor different communication channels. Therefore, it appears that companies use two-way communication strategies to complement the perceived limitation of one-way communication strategies as some companies prefer a more interactive platform to strategically engage stakeholders in CSR communication. In addition to stakeholders, institutional expectations also play a vital role in influencing CSR communication. Due to industry peer pressures, corporate objectives (attract international investors and customers), companies may be more driven to excel in social performance. For these reasons companies tend to go beyond the basic mandatory requirement, excel in CSR activities and be known as companies that champion CSR. In conclusion, companies use more two-way than one-way communication and companies use a combination of one and two-way communication to target different stakeholders resulting from stakeholder and institutional dimensions. Finally, in order to find out if the conceptual framework actually fits the Malaysian context, companies’ responses for expected organizational outcomes from communicating CSR were gathered from the interview transcripts. Thereafter, findings are presented to show some of the key organizational outcomes (visibility and brand recognition, portray responsible image, attract prospective employees, positive word-of-mouth, etc.) that companies in Malaysia expect from CSR communication. Based on these findings the conceptual framework has been refined to show the new identified organizational outcomes.

Keywords: CSR communication, CSR communication strategies, stakeholder theory, institutional theory, conceptual framework, Malaysia

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Authors: Waleed Omri

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With the growth of the small business sector in emerging markets, developing a better understanding of what drives 'day-to-day' entrepreneurial activities has become an important issue for academicians and practitioners. Innovation, as an entrepreneurial behavior, revolves around individuals who creatively engage in new organizational efforts. In a similar vein, the innovation behaviors and processes at the organizational member level are central to any corporate entrepreneurship strategy. Despite the broadly acknowledged importance of entrepreneurship and innovation at the individual level in the establishment of successful ventures, the literature lacks evidence on how entrepreneurs can effectively harness their skills and knowledge in the workplace. The existing literature illustrates that religion can impact the day-to-day work behavior of entrepreneurs, managers, and employees. Religious beliefs and practices could affect daily entrepreneurial activities by fostering mental abilities and traits such as creativity, intelligence, and self-efficacy. In the present study, we define religious capital as a set of personal and intangible resources, skills, and competencies that emanate from an individual’s religious values, beliefs, practices, and experiences and may be used to increase the quality of economic activities. Religious beliefs and practices give individuals a religious satisfaction, which can lead them to perform better in the workplace. In addition, religious ethics and practices have been linked to various positive employee outcomes in terms of organizational change, job satisfaction, and entrepreneurial intensity. As investigations of their consequences beyond direct task performance are still scarce, we explore if religious capital plays a role in entrepreneurs’ innovative behavior. In sum, this study explores the determinants of individual entrepreneurial behavior by investigating the relationship between religious capital and entrepreneurs’ innovative behavior in the context of small businesses. To further explain and clarify the religious capital-innovative behavior link, the present study proposes a model to examine the mediating role of entrepreneurial creativity. We use both Islamic work ethics (IWE) and Islamic religious practices (IRP) to measure Islamic religious capital. We use structural equation modeling with a robust maximum likelihood estimation to analyze data gathered from 289 Tunisian small businesses and to explore the relationships among the above-described variables. In line with the theory of planned behavior, only religious work ethics are found to increase the innovative behavior of small businesses’ owner-managers. Our findings also clearly demonstrate that the connection between religious capital-related variables and innovative behavior is better understood if the influence of entrepreneurial creativity, as a mediating variable of the aforementioned relationship, is taken into account. By incorporating both religious capital and entrepreneurial creativity into the innovative behavior analysis, this study provides several important practical implications for promoting innovation process in small businesses.

Keywords: entrepreneurial behavior, small business, religion, creativity

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Authors: Astrid Bagireanu, Julio Bros-Williamson, Mila Duncheva, John Currie

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Digital Twins (DTs) have entered the built environment from more established industries like aviation and manufacturing, although there has never been a common goal for utilising DTs at scale. Defined as the cyber-physical integration of data between an asset and its virtual counterpart, DT has been identified in literature from an operational standpoint – in addition to monitoring the performance of a built asset. However, this has never been translated into how DTs should be implemented into a project and what responsibilities each project stakeholder holds in the realisation of a DT. What is needed is an approach to translate these requirements into actionable DT dimensions. This paper presents a foundation for an overarching framework specific to the built environment. For the purposes of this research, the UK widely used the Royal Institute of British Architects (RIBA) Plan of Work from 2020 is used as a basis for itemising project stages. The RIBA Plan of Work consists of eight stages designed to inform on the definition, briefing, design, coordination, construction, handover, and use of a built asset. Similar project stages are utilised in other countries; therefore, the recommendations from the interviews presented in this paper are applicable internationally. Simultaneously, there is not a single mainstream software resource that leverages DT abilities. This ambiguity meets an unparalleled ambition from governments and industries worldwide to achieve a national grid of interconnected DTs. For the construction industry to access these benefits, it necessitates a defined starting point. This research aims to provide a comprehensive understanding of the potential applications and ramifications of DT in the context of the built environment. This paper is an integral part of a larger research aimed at developing a conceptual framework for the Architecture, Engineering, and Construction (AEC) sector following a conventional project timeline. Therefore, this paper plays a pivotal role in providing practical insights and a tangible foundation for developing a stage-by-stage approach to assimilate the potential of DT within the built environment. First, the research focuses on a review of relevant literature, albeit acknowledging the inherent constraint of limited sources available. Secondly, a qualitative study compiling the views of 14 DT experts is presented, concluding with an inductive analysis of the interview findings - ultimately highlighting the barriers and strengths of DT in the context of framework development. As parallel developments aim to progress net-zero-centred design and improve project efficiencies across the built environment, the limited resources available to support DTs should be leveraged to propel the industry to reach its digitalisation era, in which AEC stakeholders have a fundamental role in understanding this, from the earliest stages of a project.

Keywords: digital twins, decision-making, design, net-zero, built environment

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Authors: Zakir Hossain, Md. Saddam Hossain

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A nutritionally balanced diet and selection of appropriate species are important criteria in aquaculture. The present study was conducted to evaluate the effects of polyunsaturated fatty acids (PUFAs) and beta glucan containing diet on growth performance, feed utilization, maturation, immunity, early embryonic and larval development of endangered Pabdah catfish, Ompok pabda. In this study, squid extracted lipids and mushroom powder were used as the source of PUFAs and beta glucan, respectively, and formulated two isonitrogenous diets such as basal or control (CON) diet and treated (PBG) diet with maintaining 30% protein levels. During the study period, similar physicochemical conditions of water such as temperature, pH, and dissolved oxygen (DO) were 26.5±2 °C, 7.4±0.2, and 6.7±0.5 ppm, respectively in each cistern. The results showed that final mean body weight, final mean length gain, food conversion ratio (FCR), specific growth rate (SGR), food conversion efficiency (%), hepatosomatic index (HSI), kidney index (KI), and viscerosomatic index (VSI) were significantly (P<0.01 and P<0.05) higher in fish fed the PBG diet than that of fish fed the CON diet. The length-weight relationship and relative condition factor (K) of O. pabda were significantly (P<0.05) affected by the PBG diet. The gonadosomatic index (GSI), sperm viability, blood serum calcium ion concentrations (Ca²⁺), and vitellogenin level were significantly (P<0.05) higher in fish fed the PBG diet than that of fish fed the CON diet; which was used to the indication of fish maturation. During the spawning season, lipid granules and normal morphological structure were observed in the treated fish liver, whereas fewer lipid granules of liver were observed in the control group. Based on the immunity and stress resistance-related parameters such as hematological indices, antioxidant activity, lysozyme level, respiratory burst activity, blood reactive oxygen species (ROS), complement activity (ACH50 assay), specific IgM, brain AChE, plasma PGOT, and PGPT enzyme activity were significantly (P<0.01 and P<0.05) higher in fish fed the PBG diet than that of fish fed the CON diet. The fecundity, fertilization rate (92.23±2.69%), hatching rate (87.43±2.17 %) and survival (76.62±0.82%) of offspring were significantly higher (P˂0.05) in the PBG diet than in the control. Consequently, early embryonic and larval development was better in PBG treated group than in the control. Therefore, the present study showed that the polyunsaturated fatty acids (PUFAs) and beta glucan enriched experimental diet were more effective and achieved better growth, feed utilization, maturation, immunity, and spawning performances of O. pabda.

Keywords: polyunsaturated fatty acids, beta glucan, maturity, immunity, catfish

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