Search results for: diurnal temperature cycle model

Authors: Maxime Alex Junior Kuitche, Ruxandra Mihaela Botez, Jean-Chirstophe Maunand

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The evolution of aircraft is closely linked to the study and improvement of propulsion systems. Determining the propulsion performance is a real challenge in aircraft modeling and design. In addition to theoretical methodologies, experimental procedures are used to obtain a good estimation of the propulsion performances. For piston-propeller propulsion, the propeller needs several experimental tests which could be extremely demanding in terms of time and money. This paper presents a new procedure to estimate the performance of a propeller from a numerical approach using computational fluid dynamic analysis. The propeller was initially scanned, and then, its 3D model was represented using CATIA. A structured meshing and Shear Stress Transition k-ω turbulence model were applied to describe accurately the flow pattern around the propeller. Thus, the Partial Differential Equations were solved using ANSYS FLUENT software. The method was applied on the UAS-S45’s propeller designed and manufactured by Hydra Technologies in Mexico. An extensive investigation was performed for several flight conditions in terms of altitudes and airspeeds with the aim to determine thrust coefficients, power coefficients and efficiency of the propeller. The Computational Fluid Dynamics results were compared with experimental data acquired from wind tunnel tests performed at the LARCASE Price-Paidoussis wind tunnel. The results of this comparison have demonstrated that our approach was highly accurate.

Keywords: CFD analysis, propeller performance, unmanned aerial system propeller, UAS-S45

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Authors: Roslinda Nazar, Ezad Hafidz Hafidzuddin, Norihan M. Arifin, Ioan Pop

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In this paper, the problem of steady laminar boundary layer flow and heat transfer over a permeable exponentially stretching/shrinking sheet with generalized slip velocity is considered. The similarity transformations are used to transform the governing nonlinear partial differential equations to a system of nonlinear ordinary differential equations. The transformed equations are then solved numerically using the bvp4c function in MATLAB. Dual solutions are found for a certain range of the suction and stretching/shrinking parameters. The effects of the suction parameter, stretching/shrinking parameter, velocity slip parameter, critical shear rate, and Prandtl number on the skin friction and heat transfer coefficients as well as the velocity and temperature profiles are presented and discussed.

Keywords: boundary layer, exponentially stretching/shrinking sheet, generalized slip, heat transfer, numerical solutions

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Authors: Alvarez M., Chapela M. J., Balboa E., Rubianes D., Sinde E., Fernandez de Ana C., Rodríguez-Blanco A.

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The gut microbiota plays an important role as gut inflammation could contribute to colorectal cancer development; however, this role is still not fully understood, and tools able to prevent this progression are yet to be developed. The main objective of this study was to monitor the effects of a mushroom extracts formulation in gut microbial community composition of an Azoxymethane (AOM)/Dextran sodium sulfate (DSS) mice model of inflammation-linked carcinogenesis. For the in vivo study, 41 adult male mice of the C57BL / 6 strain were obtained. 36 of them have been induced in a state of colon carcinogenesis by a single intraperitoneal administration of AOM at a dose of 12.5 mg/kg; the control group animals received instead of the same volume of 0.9% saline. DSS is an extremely toxic polysaccharide sulfate that causes chronic inflammation of the colon mucosa, favoring the appearance of severe colitis and the production of tumors induced by AOM. Induction by AOM/DSS is an interesting platform for chemopreventive intervention studies. This time the model was used to monitor gut microbiota changes as a result of supplementation with a specific mushroom extracts formulation previously shown to have prebiotic activity. The animals have been divided into three groups: (i) Cancer + mushroom extracts formulation experimental group: to which the MicoDigest2.0 mushroom extracts formulation developed by Hifas da Terra S.L has been administered dissolved in drinking water at an estimated concentration of 100 mg / ml. (ii) Control group of animals with Cancer: to which normal water has been administered without any type of treatment. (iii) Control group of healthy animals: these are the animals that have not been induced cancer or have not received any treatment in drinking water. This treatment has been maintained for a period of 3 months, after which the animals were sacrificed to obtain tissues that were subsequently analyzed to verify the effects of the mushroom extract formulation. A microbiological analysis has been carried out to compare the microbial communities present in the intestines of the mice belonging to each of the study groups. For this, the methodology of massive sequencing by molecular analysis of the 16S gene has been used (Ion Torrent technology). Initially, DNA extraction and metagenomics libraries were prepared using the 16S Metagenomics kit, always following the manufacturer's instructions. This kit amplifies 7 of the 9 hypervariable regions of the 16S gene that will then be sequenced. Finally, the data obtained will be compared with a database that makes it possible to determine the degree of similarity of the sequences obtained with a wide range of bacterial genomes. Results obtained showed that, similarly to certain natural compounds preventing colorectal tumorigenesis, a mushroom formulation enriched the Firmicutes and Proteobacteria phyla and depleted Bacteroidetes. Therefore, it was demonstrated that the consumption of the mushroom extracts’ formulation developed could promote the recovery of the microbial balance that is disrupted in the mice model of carcinogenesis. More preclinical and clinical studies are needed to validate this promising approach.

Keywords: carcinogenesis, microbiota, mushroom extracts, inflammation

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Authors: Uthumporn Utra, Y. N. Shariffa, M. Maizura, A. S. Ruri

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This research is to study the utilization of pumpkin and winter melon as the main substrate for kefir fermentation in the production of pumpkin and winter melon-based fermented drinks. Optimized temperature and time were chosen for fermentation of pumpkin and winter melon. Physicochemical and microbiological evaluations were conducted to the end products: P (fermented pumpkin juice) and K (fermented winter melon juice). Ethanol content was detected at low concentration of 0.9% (v/wt) in P, and 1.0% (v/wt) in K. Level of glucose and fructose increased significantly (p < 0.05) in both fermented drinks when compared to unfermented pumpkin (CP) and winter melon (CK) juices. Total phenolic content in P & K was higher than CP and CK, while %DPPH inhibition of both decreased significantly. Total Lactobacilli counts in P & K were 8.9 and 7.88 log cfu/ml respectively, while acetic acid bacteria counts were 8.62 and 7.57 log cfu/ml respectively, yeast counts were 4.71 and 5 log cfu/ml, and no E.coli was detected in all samples. Sensory evaluation yield comparable properties in P & K. This concluded that pumpkin and winter melon fermented drinks inoculated by water kefir grains could be promising source of nutrients with probiotic potency.

Keywords: fermented drinks, functional beverage, kefir, pumpkin, winter melon

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Authors: S. F. H. Tasfy, N. A. M. Zabidi, M. S. Shaharun

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Carbon dioxide is highly thermochemical stable molecules where it is very difficult to activate the molecule and achieve higher catalytic conversion into alcohols or other hydrocarbon compounds. In this paper, series of the bimetallic Cu/ZnO-based catalyst supported by SBA-15 were systematically prepared via impregnation technique with different Cu: Zn ratio for hydrogenation of CO₂ to methanol. The synthesized catalysts were characterized by transmission electron microscopy (TEM), temperature programmed desorption, reduction, oxidation and pulse chemisorption (TPDRO), and surface area determination was also performed. All catalysts were tested with respect to the hydrogenation of CO₂ to methanol in microactivity fixed-bed reactor at 250^oC, 2.25 MPa, and H₂/CO₂ ratio of 3. The results demonstrate that the catalytic structure, activity, and methanol selectivity was strongly affected by the ratio between Cu: Zn, Where higher catalytic activity of 14 % and methanol selectivity of 92 % was obtained over Cu/ZnO-SBA-15 catalyst with Cu:Zn ratio of 7:3 wt. %. Comparing with the single catalyst, the synergetic between Cu and Zn provides additional active sites to adsorb more H₂ and CO₂ and accelerate the CO₂ conversion, resulting in higher methanol production under mild reaction conditions.

Keywords: hydrogenation of carbon dioxide, methanol synthesis, Cu/ZnO-based catalyst, mesoporous silica (SBA-15), metal ratio

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Authors: Dejen Alemu, Murray E. Jennex, Temtim Assefa

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This paper is investigated to understand the design, the use, and the consequence of Knowledge Management System (KMS) for knowledge systems sharing and integration. A KMS for knowledge systems sharing and integration is designed to meet the challenges raised by knowledge management researchers and practitioners: the technical, the human, and social factors. Agricultural KMS involves various members coming from different Communities of Practice (CoPs) who possess their own knowledge of multiple practices which need to be combined in the system development. However, the current development of the technology ignored the indigenous knowledge of the local communities, which is the key success factor for agriculture. This research employed the multi-methodological approach to KMS research in action research perspective which consists of four strategies: theory building, experimentation, observation, and system development. Using the KMS development practice of Ethiopian agricultural transformation agency as a case study, this research employed an interpretive analysis using primary qualitative data acquired through in-depth semi-structured interviews and participant observations. The Orlikowski's structuration model of technology has been used to understand the design, the use, and the consequence of the KMS. As a result, the research identified three basic components for the architecture of the shared KMS, namely, the people, the resources, and the implementation subsystems. The KMS were developed using web 2.0 tools to promote knowledge sharing and integration among diverse groups of users in a distributed environment. The use of a shared KMS allows users to access diverse knowledge from a number of users in different groups of participants, enhances the exchange of different forms of knowledge and experience, and creates high interaction and collaboration among participants. The consequences of a shared KMS on the social system includes, the elimination of hierarchical structure, enhance participation, collaboration, and negotiation among users from different CoPs having common interest, knowledge and skill development, integration of diverse knowledge resources, and the requirement of policy and guideline. The research contributes methodologically for the application of system development action research for understanding a conceptual framework for KMS development and use. The research have also theoretical contribution in extending structuration model of technology for the incorporation of variety of knowledge and practical implications to provide management understanding in developing strategies for the potential of web 2.0 tools for sharing and integration of indigenous knowledge.

Keywords: communities of practice, indigenous knowledge, participation, structuration model of technology, Web 2.0 tools

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Authors: Babak Safaei, Ahmad Ghanbari, Arash Rahmani

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In the present study, the free vibration characteristics of double-walled carbon nanotubes (DWCNTs) are investigated. The small-scale effects are taken into account using the Eringen’s nonlocal elasticity theory. The nonlocal elasticity equations are implemented into the different classical beam theories namely as Euler-Bernoulli beam theory (EBT), Timoshenko beam theory (TBT), Reddy beam theory (RBT), and Levinson beam theory (LBT) to analyze the free vibrations of DWCNTs in which each wall of the nanotubes is considered as individual beam with van der Waals interaction forces. Generalized differential quadrature (GDQ) method is utilized to discretize the governing differential equations of each nonlocal beam model along with four commonly used boundary conditions. Then molecular dynamics (MD) simulation is performed for a series of armchair and zigzag DWCNTs with different aspect ratios and boundary conditions, the results of which are matched with those of nonlocal beam models to extract the appropriate values of the nonlocal parameter corresponding to each type of chirality, nonlocal beam model and boundary condition. It is found that the present nonlocal beam models with their proposed correct values of nonlocal parameter have good capability to predict the vibrational behavior of DWCNTs, especially for higher aspect ratios.

Keywords: double-walled carbon nanotubes, nonlocal continuum elasticity, free vibrations, molecular dynamics simulation, generalized differential quadrature method

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Authors: Mohamed A. Moustafa Hassan, Omnia S .S. Hussian, Hany M. Elsaved

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This paper introduces the application of Fuzzy Logic Controller (FLC) to extract the Maximum Power Point Tracking (MPPT) from the PV panel. In addition, the proportional integral (PI) controller is used to be the strategy for battery charge control according to acceptable performance criteria. The parameters of the PI controller have been tuned via Modified Adaptive Accelerated Coefficient Particle Swarm Optimization (MAACPSO) technique. The simulation results, using MATLAB/Simulink tools, show that the FLC technique has advantages for use in the MPPT problem, as it provides a fast response under changes in environmental conditions such as radiation and temperature. In addition, the use of PI controller based on MAACPSO results in a good performance in terms of controlling battery charging with constant voltage and current to execute rapid charging.

Keywords: battery charging, fuzzy logic control, maximum power point tracking, PV system, PI controller, evolutionary technique

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Authors: Henrique Rangel, Alexandre Fadel, Igor De Lazari, Bianca Neri, Carlos Bolonha

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This paper promotes a comparative analysis of American and Brazilian models of federalism assuming their levels of political centralization as main criterion. The central problem faced herein is the Brazilian approach of Unitarian regime. Although the hegemony of federative form after 1989, Brazil had a historical frame of political centralization that remains under the 1988 constitutional regime. Meanwhile, United States framed a federalism in which States absorb significant authorities. The hypothesis holds that the amount of alternative criteria of federalization – which can generate political centralization –, and the way they are upheld on judicial review, are crucial to understand the levels of political centralization achieved in each model. To test this hypothesis, the research is conducted by a methodology temporally delimited to 1994-2014 period. Three paradigmatic precedents of U.S. Supreme Court were selected: United States vs. Morrison (2000), on gender-motivated violence, Gonzales vs. Raich (2005), on medical use of marijuana, and United States vs. Lopez (1995), on firearm possession on scholar zones. These most relevant cases over federalism in the recent activity of Supreme Court indicates a determinant parameter of deliberation: the commerce clause. After observe the criterion used to permit or prohibit the political centralization in America, the Brazilian normative context is presented. In this sense, it is possible to identify the eventual legal treatment these controversies could receive in this Country. The decision-making reveals some deliberative parameters, which characterizes each federative model. At the end of research, the precedents of Rehnquist Court promote a broad revival of federalism debate, establishing the commerce clause as a secure criterion to uphold or not the necessity of centralization – even with decisions considered conservative. Otherwise, the Brazilian federalism solves them controversies upon in a formalist fashion, within numerous and comprehensive – sometimes casuistic too – normative devices, oriented to make an intense centralization. The aim of this work is indicate how jurisdictional federalism found in United States can preserve a consistent model with States robustly autonomous, while Brazil gives preference to normative mechanisms designed to starts from centralization.

Keywords: constitutional design, federalism, U.S. Supreme Court, legislative authority

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Authors: Isomar Lima da Silva, Alcilene Batalha Pontes, Aristeu Jonatas Leite de Oliveira, Roberto Maia Augusto

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Context: Mechanical ventilators are medical devices that help provide oxygen and ventilation to patients with respiratory difficulties. This equipment consists of a manual breathing unit that can be operated by a doctor or nurse and a mechanical ventilator that controls the airflow and pressure in the patient's respiratory system. This type of ventilator is commonly used in emergencies and intensive care units where it is necessary to provide breathing support to critically ill or injured patients. Objective: In this context, this work aims to develop a reliable and low-cost mechanical ventilator to meet the demand of hospitals in treating people affected by Covid-19 and other severe respiratory diseases, offering a chance of treatment as an alternative to mechanical ventilators currently available in the market. Method: The project presents the development of a low-cost auxiliary ventilator with a controlled ventilatory system assisted by integrated hardware and firmware for respiratory cycle control in non-invasive mechanical ventilation treatments using a manual artificial respiration unit. The hardware includes pressure sensors capable of identifying positive expiratory pressure, peak inspiratory flow, and injected air volume. The embedded system controls the data sent by the sensors. It ensures efficient patient breathing through the operation of the sensors, microcontroller, and actuator, providing patient data information to the healthcare professional (system operator) through the graphical interface and enabling clinical parameter adjustments as needed. Results: The test data of the developed mechanical ventilator presented satisfactory results in terms of performance and reliability, showing that the equipment developed can be a viable alternative to commercial mechanical ventilators currently available, offering a low-cost solution to meet the increasing demand for respiratory support equipment.

Keywords: mechanical fans, breathing, medical equipment, COVID-19, intensive care units

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Authors: M. M. Essa, S. Subash, M. Akbar, S. Al-Adawi, A. Al-Asmi, G. J. Guillemein

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Objective: Transgenic (tg) mice which contain an amyloid precursor protein (APP) gene mutation, develop extracellular amyloid beta (Aβ) deposition in the brain, and severe memory and behavioural deficits with age. These mice serve as an important animal model for testing the efficacy of novel drug candidates for the treatment and management of symptoms of Alzheimer's disease (AD). Several reports have suggested that oxidative stress is the underlying cause of Aβ neurotoxicity in AD. Pomegranates contain very high levels of antioxidants and several medicinal properties that may be useful for improving the quality of life in AD patients. In this study, we investigated the effect of dietary supplementation of Omani pomegranate extract on the memory, anxiety and learning skills along with inflammation in an AD mouse model containing the double Swedish APP mutation (APPsw/Tg2576). Methods: The experimental groups of APP-transgenic mice from the age of 4 months were fed custom-mix diets (pellets) containing 4% pomegranate. We assessed spatial memory and learning ability, psychomotor coordination, and anxiety-related behavior in Tg and wild-type mice at the age of 4-5 months and 18-19 months using the Morris water maze test, rota rod test, elevated plus maze test, and open field test. Further, inflammatory parameters also analysed. Results: APPsw/Tg2576 mice that were fed a standard chow diet without pomegranates showed significant memory deficits, increased anxiety-related behavior, and severe impairment in spatial learning ability, position discrimination learning ability and motor coordination along with increased inflammation compared to the wild type mice on the same diet, at the age of 18-19 months In contrast, APPsw/Tg2576 mice that were fed a diet containing 4% pomegranates showed a significant improvements in memory, learning, locomotor function, and anxiety with reduced inflammatory markers compared to APPsw/Tg2576 mice fed the standard chow diet. Conclusion: Our results suggest that dietary supplementation with pomegranates may slow the progression of cognitive and behavioural impairments in AD. The exact mechanism is still unclear and further extensive research needed.

Keywords: Alzheimer's disease, pomegranates, oman, cognitive decline, memory loss, anxiety, inflammation

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Authors: Amir Hossein Ashari, Sedighe Erfan Manesh

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When investigating Iranian traditional and historical urban development, such as that seen in Shiraz, our attention is drawn to mosques as a focal point. Vakil Mosque in Shiraz is completely consistent, coordinated and integrated with the Bazaar, square and school. This is a significant example of traditional urban development. The position of the mosque in the most important urban joint near bazaar in a way that it is considered part of the bazaar structure are factors that have given it social, political, and economic roles in addition to the original religious role. These are among characteristics of sustainable development. The mosque has had an important effect in formation of the city because it is connected to main gates. In terms of access, the mosque has different main and peripheral access paths from different parts of the city. The courtyard of the mosque was located next to the main elements of the city so that it was considered as an urban open space, which made it a more active and more dynamic place. This study is carried out via library and field research with the purpose of finding strategies for taking advantage of useful features of the mosque in traditional urban development. These features include its role as a gathering center for people and city in sustainable urban development. Mosque can be used as a center for enhancing social interactions and creating a sense of association that leads to sustainable social space. These can act as a model which leads us to sustainable cities in terms of social and economic factors.

Keywords: mosque, traditional urban development, sustainable social space, Vakil Mosque, Shiraz

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Authors: S. Ramteke, K. S. Patel

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Aerosols are complex mixture of particulate matters (PM) inclusive of carbons, silica, elements, various salts, etc. Aerosols get deep into the human lungs and cause a broad range of health effects, in particular, respiratory and cardiovascular illnesses. They are one of the major culprits for the climate change. They are emitted by the high thermal processes i.e. vehicles, steel, sponge, cement, thermal power plants, etc. Raipur (22˚33'N to 21˚14'N and 82˚6'E) to 81˚38'E) is a growing industrial city in central India with population of two million. In this work, the distribution of inorganics (i.e. Cl⁻, NO³⁻, SO₄²⁻, NH₄⁺, Na⁺, K⁺, Mg²⁺, Ca²⁺, Al, Cr, Mn, Fe, Ni, Cu, Zn, and Pb) associated to the PM in the ambient air is described. The PM₁₀ in ambient air of Raipur city was collected for duration of one year (December 2014 - December 2015). The PM₁₀ was segregated into nine modes i.e. PM₁₀.₀₋₉.₀, PM₉.₀₋₅.₈, PM₅.₈₋₄.₇, PM₄.₇₋₃.₃, PM₃.₃₋₂.₁, PM₂.₁₋₁.₁, PM₁.₁₋₀.₇, PM₀.₇₋₀.₄ and PM₀.₄ to know their emission sources and health hazards. The analysis of ions and metals was carried out by techniques i.e. ion chromatography and TXRF. The PM₁₀ concentration (n=48) was ranged from 100-450 µg/m³ with mean value of 73.57±20.82 µg/m³. The highest concentration of PM₄.₇₋₃.₃, PM₂.₁₋₁.₁, PM₁.₁₋₀.₇ was observed in the commercial, residential and industrial area, respectively. The effect of meteorology i.e. temperature, humidity, wind speed and wind direction in the PM₁₀ and associated elemental concentration in the air is discussed.

Keywords: ambient aerosol, ions, metals, segregation

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Authors: S. Cencek, A. Markun

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Noise assessment methods are regularly used in scope of Environmental Impact Assessments for planned projects to assess (predict) the expected noise emissions of these projects. Different noise assessment methods could be used. In recent years, we had an opportunity to collaborate in some noise assessment procedures where noise assessments of different laboratories have been performed simultaneously. We identified some significant differences in noise assessment results between laboratories in Slovenia. We estimate that despite good input Georeferenced Data to set up acoustic model exists in Slovenia; there is no clear consensus on methods for predictive noise methods for planned projects. We analyzed input data, methods and results of predictive noise methods for two planned industrial projects, both were done independently by two laboratories. We also analyzed the data, methods and results of two interlaboratory collaborative noise models for two existing noise sources (railway and motorway). In cases of predictive noise modelling, the validations of acoustic models were performed by noise measurements of surrounding existing noise sources, but in varying durations. The acoustic characteristics of existing buildings were also not described identically. The planned noise sources were described and digitized differently. Differences in noise assessment results between different laboratories have ranged up to 10 dBA, which considerably exceeds the acceptable uncertainty ranged between 3 to 6 dBA. Contrary to predictive noise modelling, in cases of collaborative noise modelling for two existing noise sources the possibility to perform the validation noise measurements of existing noise sources greatly increased the comparability of noise modelling results. In both cases of collaborative noise modelling for existing motorway and railway, the modelling results of different laboratories were comparable. Differences in noise modeling results between different laboratories were below 5 dBA, which was acceptable uncertainty set up by interlaboratory noise modelling organizer. The lessons learned from the study were: 1) Predictive noise calculation using formulae from International standard SIST ISO 9613-2: 1997 is not an appropriate method to predict noise emissions of planned projects since due to complexity of procedure they are not used strictly, 2) The noise measurements are important tools to minimize noise assessment errors of planned projects and should be in cases of predictive noise modelling performed at least for validation of acoustic model, 3) National guidelines should be made on the appropriate data, methods, noise source digitalization, validation of acoustic model etc. in order to unify the predictive noise models and their results in scope of Environmental Impact Assessments for planned projects.

Keywords: environmental noise assessment, predictive noise modelling, spatial planning, noise measurements, national guidelines

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Authors: Phanwipa Pangsri, Yawariyah Weahayee

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The lactic acid bacteria (LAB) were isolated from 10 samples of fermented foods (Sa-tor-dong and Bodo) in South locality of Thailand. The 23 isolates of lactic acid bacteria were selected, which were exhibited a clear zone and growth on MRS agar supplemented with CaCO3. All of lactic acid bacteria were tested on morphological and biochemical. The result showed that all isolates were Gram’s positive, non-spore forming but only 10 isolates displayed catalase negative. The 10 isolates including BD 1.1, BD 1.2, BD 2.1, BD2.2, BD 2.3, BD 3.1, BD 4.1, BD 5.2, ST4.1, and ST 5.2 were selected for inhibition activity determination. Only 2 strains (ST 4.1 and BD 2.3) showed inhibition zone on agar, when using Escherichia coli sp. as target strain. The ST 4.1 showed highest inhibition zone on agar, which was selected for probiotic property testing. The ST4.1 isolate could grow in MRS broth containing a high concentration of sodium chloride 6%, bile salts 7%, pH 4-10 and vary temperature at 15-45^oC.

Keywords: lactic acid bacteria, probiotic, antimicrobial, probiotic property testing

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Authors: R. Hellmuth

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The orientation of flexibility and adaptability with regard to factory planning is at machine and process level. Factory buildings are not the focus of current research. Factory planning has the task of designing products, plants, processes, organization, areas and the construction of a factory. The adaptability of a factory can be divided into three types: spatial, organizational and technical adaptability. Spatial adaptability indicates the ability to expand and reduce the size of a factory. Here, the area-related breathing capacity plays the essential role. It mainly concerns the factory site, the plant layout and the production layout. The organizational ability to change enables the change and adaptation of organizational structures and processes. This includes structural and process organization as well as logistical processes and principles. New and reconfigurable operating resources, processes and factory buildings are referred to as technical adaptability. These three types of adaptability can be regarded independently of each other as undirected potentials of different characteristics. If there is a need for change, the types of changeability in the change process are combined to form a directed, complementary variable that makes change possible. When planning adaptability, importance must be attached to a balance between the types of adaptability. The vision of the intelligent factory building and the 'Internet of Things' presupposes the comprehensive digitalization of the spatial and technical environment. Through connectivity, the factory building must be empowered to support a company's value creation process by providing media such as light, electricity, heat, refrigeration, etc. In the future, communication with the surrounding factory building will take place on a digital or automated basis. In the area of industry 4.0, the function of the building envelope belongs to secondary or even tertiary processes, but these processes must also be included in the communication cycle. An integrative view of a continuous communication of primary, secondary and tertiary processes is currently not yet available and is being developed with the aid of methods in this research work. A comparison of the digital twin from the point of view of production and the factory building will be developed. Subsequently, a tool will be elaborated to classify digital twins from the perspective of data, degree of visualization, and the trades. Thus a contribution is made to better integrate the secondary and tertiary processes in a factory into the added value.

Keywords: adaptability, digital factory twin, factory planning, industry 4.0

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Authors: Tomas Vampola, Michael Valášek

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On the basis of simulation-generated failure states of structural elements of a turboprop engine suitable for the busy-jet class of aircraft, an algorithm for early prediction of damage or reduction in functionality of structural elements of the engine is designed and verified with real data obtained at dynamometric testing facilities of aircraft engines. Based on an expanding database of experimentally determined data from temperature and pressure sensors during the operation of turboprop engines, this strategy is constantly modified with the aim of using the minimum number of sensors to detect an inadmissible or deteriorated operating mode of specific structural elements of an aircraft engine. The assembled algorithm for the early prediction of reduced functionality of the aircraft engine significantly contributes to the safety of air traffic and to a large extent, contributes to the economy of operation with positive effects on the reduction of the energy demand of operation and the elimination of adverse effects on the environment.

Keywords: detectability of malfunction, dynamometric testing, prediction of damage, turboprop engine

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Authors: Supriyono, Sumardiyono, Rendy J. Pramono

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Biodiesel is one of the alternative fuels promising for substituting petrodiesel as energy source which has an advantage as it is sustainable and eco-friendly. Due to the raw material that tends to decompose during storage, biodiesel also has the same characteristic that tends to decompose during storage. Biodiesel decomposition will form higher acid value as the result of oxidation to double bond on a fatty acid compound on biodiesel. Thus, free fatty acid value could be used to evaluate degradation of biodiesel due to the oxidation process. High free fatty acid on biodiesel could impact on the engine performance. Decomposition of biodiesel due to oxidation reaction could prevent by introducing a small amount of antioxidant. The origin of raw materials and the process for producing biodiesel will determine the effectiveness of antioxidant. Biodiesel made from high free fatty acid (FFA) crude palm oil (CPO) by using two steps esterification is vulnerable to oxidation process which is resulted in increasing on the FFA value. Tocopherol also known as vitamin E is one of the antioxidant that could improve the stability of biodiesel due to decomposition by the oxidation process. Tocopherol 0.5% concentration on palm oil biodiesel could reduce 13% of increasing FFA under temperature 80 °C and exposing time 180 minute.

Keywords: antioxidant, palm oil biodiesel, decomposition, oxidation, tocopherol

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Authors: Masoomeh Alsadat Mirshafaei

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The present study aims to explore the effect of an 8-week aerobic training regimen combined with cinnamon extract on serum irisin and leptin levels in insulin-resistant rats. Additionally, this research leverages various machine learning (ML) and deep learning (DL) algorithms to model the complex interdependencies between exercise, nutrition, and metabolic markers, offering a groundbreaking approach to obesity and diabetes research. Forty-eight Wistar rats were selected and randomly divided into four groups: control, training, cinnamon, and training cinnamon. The training protocol was conducted over 8 weeks, with sessions 5 days a week at 75-80% VO2 max. The cinnamon and training-cinnamon groups were injected with 200 ml/kg/day of cinnamon extract. Data analysis included serum data, dietary intake, exercise intensity, and metabolic response variables, with blood samples collected 72 hours after the final training session. The dataset was analyzed using one-way ANOVA (P<0.05) and fed into various ML and DL models, including Support Vector Machines (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN). Traditional statistical methods indicated that aerobic training, with and without cinnamon extract, significantly increased serum irisin and decreased leptin levels. Among the algorithms, the CNN model provided superior performance in identifying specific interactions between cinnamon extract concentration and exercise intensity, optimizing the increase in irisin and the decrease in leptin. The CNN model achieved an accuracy of 92%, outperforming the SVM (85%) and RF (88%) models in predicting the optimal conditions for metabolic marker improvements. The study demonstrated that advanced ML and DL techniques could uncover nuanced relationships and potential cellular responses to exercise and dietary supplements, which is not evident through traditional methods. These findings advocate for the integration of advanced analytical techniques in nutritional science and exercise physiology, paving the way for personalized health interventions in managing obesity and diabetes.

Keywords: aerobic training, cinnamon extract, insulin resistance, irisin, leptin, convolutional neural networks, exercise physiology, support vector machines, random forest

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Saad Ahmed, Sanjeev Khannaa

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Glass fiber reinforced polymers are widely used in structural systems as load-bearing elements at both high and low temperatures. This investigation presents the evaluation of glass fiber reinforced unsaturated polyurethane under harsh conditions of changing temperature and moisture content. This study Explores how these parameters affect the optical properties of the polymer matrix and the composite. Using the hand layup method, the polyurethane resin was modified by E-glass fibers (15 vol. %) to manufacture fiber-reinforced composite. This work includes the preparation of glass-like polyurethane resin sheets and estimates all light transmittance properties at high and very low temperatures and wet conditions. All-optical properties were retested to evaluate the level of improvement or failure. The results found that when comprising reinforced composite fiber to the unreinforced specimens, the reinforced composite shows a fair optical property at high temperatures and good performance at low temperatures.

Keywords: unsaturated polyurethane, extreme temperatures, light transmittance, haze number

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Authors: Xiaobo Rui, Zhoumo Zeng, Yibo Li

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A novel tri-cantilever energy harvester with magnetic oscillator was presented, which could convert the ambient vibration into electrical energy to power the low-power devices such as wireless sensor networks. The most common way to harvest vibration energy is based on the use of linear resonant devices such as cantilever beam, since this structure creates the highest strain for a given force. The highest efficiency will be achieved when the resonance frequency of the harvester matches the vibration frequency. The limitation of the structure is the narrow effective bandwidth. To overcome this limitation, this article introduces a broadband tri-cantilever harvester with nonlinear stiffness. This energy harvester typically consists of three thin cantilever beams vertically arranged with Neodymium Magnets ( NdFeB)magnetics at its free end and a fixed base at the other end. The three cantilevers have different resonant frequencies by designed in different thicknesses. It is obviously that a similar advantage of multiple resonant frequencies as piezoelectric cantilevers array structure is built. To achieve broadband energy harvesting, magnetic interaction is used to introduce the nonlinear system stiffness to tune the resonant frequency to match the excitation. Since the three cantilever tips are all free and the magnetic force is distance dependent, the resonant frequencies will be complexly changed with the vertical vibration of the free end. Both model and experiment are built. The electromechanically coupled lumped-parameter model is presented. An electromechanical formulation and analytical expressions for the coupled nonlinear vibration response and voltage response are given. The entire structure is fabricated and mechanically attached to a electromagnetic shaker as a vibrating body via the fixed base, in order to couple the vibrations to the cantilever. The cantilevers are bonded with piezoelectric macro-fiber composite (MFC) materials (Model: M8514P2). The size of the cantilevers is 120*20mm2 and the thicknesses are separately 1mm, 0.8mm, 0.6mm. The prototype generator has a measured performance of 160.98 mW effective electrical power and 7.93 DC output voltage via the excitation level of 10m/s2. The 130% increase in the operating bandwidth is achieved. This device is promising to support low-power devices, peer-to-peer wireless nodes, and small-scale wireless sensor networks in ambient vibration environment.

Keywords: tri-cantilever, ambient vibration, energy harvesting, magnetic oscillator

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Authors: Ramdan B. A. Koad, Ahmed F. Zobaa

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Since the output characteristics of Photovoltaic (PV) system depends on the ambient temperature, solar radiation and load impedance, its maximum Power Point (MPP) is not constant. Under each condition PV module has a point at which it can produce its MPP. Therefore, a Maximum Power Point Tracking (MPPT) method is needed to uphold the PV panel operating at its MPP. This paper presents comparative study between the conventional MPPT methods used in (PV) system: Perturb and Observe (P&O), Incremental Conductance (IncCond), and Particle Swarm Optimization (PSO) algorithm for (MPPT) of (PV) system. To evaluate the study, the proposed PSO MPPT is implemented on a DC-DC converter and has been compared with P&O and INcond methods in terms of their tracking speed, accuracy and performance by using the Matlab tool Simulink. The simulation result shows that the proposed algorithm is simple, and is superior to the P&O and IncCond methods.

Keywords: photovoltaic systems, maximum power point tracking, perturb and observe method, incremental conductance, methods and practical swarm optimization algorithm

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Authors: Imad Khan, Imran Shafi, Sarmad Farooq

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Large diameter pipes, barrels, tubes, and ducts are used in a variety of applications covering civil and defense-related technologies. This may include heating/cooling networks, sign poles, bracing, casing, and artillery and tank gun barrels. These large diameter assemblies require regular inspection and cleaning to increase their life and reduce replacement costs. This paper describes the design, development, and testing results of an efficient yet simplified, low maintenance mechanical design controlled with minimal essential electronics using an electric motor for a non-technical staff. The proposed solution provides a simplified user interface and an automated cleaning mechanism that requires a single user to optimally clean pipes and barrels in the range of 105 mm to 203 mm caliber. The proposed system employs linear motion of specially designed brush along the barrel using a chain of specific strength and a pulley anchor attached to both ends of the barrel. A specially designed and manufactured gearbox is coupled with an AC motor to allow movement of contact brush with high torque to allow efficient cleaning. A suitably powered AC motor is fixed to the front adapter mounted on the muzzle side whereas the rear adapter has a pulley-based anchor mounted towards the breach block in case of a gun barrel. A mix of soft nylon and hard copper bristles-based large surface brush is connected through a strong steel chain to motor and anchor pulley. The system is equipped with limit switches to auto switch the direction when one end is reached on its operation. The testing results based on carefully established performance indicators indicate the superiority of the proposed user-friendly cleaning mechanism vis-à-vis its life cycle cost.

Keywords: pipe cleaning mechanism, limiting switch, pipe cleaning robot, large pipes

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Authors: Raghvendra Singh Yadav, Ivo Kuřitka

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In this report, we studied the impact of Gd3+ substitution on structural, magnetic and electrical properties of CoFe2O4 nanoparticles synthesized by sonochemical method. X-ray diffraction pattern confirmed the formation of cubic spinel structure at low concentration of Gd3+ ions, however, GdFeO3 additional phase was observed at higher concentration of Gd3+ ions. Raman and Fourier Transform Infrared spectroscopy study also confirmed cubic spinel structure of Gd3+ substituted CoFe2O4 nanoparticles. The field emission scanning electron microscopy study revealed that Gd3+ substituted CoFe2O4 nanoparticles were in the range of 5-20 nm. The magnetic properties of Gd3+ substituted CoFe2O4 nanoparticles were investigated by using vibrating sample magnetometer. The variation in saturation magnetization, coercivity and remanent magnetization with Gd3+ concentration in CoFe2O4 nanoparticles was observed. The variation of real and imaginary part of dielectric constant, tan δ, and AC conductivity were studied at room temperature.

Keywords: spinel ferrites, nanoparticles, sonochemical method, magnetic properties

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Authors: Forough Ataollahi, Sumit Pramanik, Belinda Pingguan-Murphy, Wan Abu Bakar Bin Wan Abas, Noor Azuan Bin Abu Osman

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Endothelium proliferation is an important process in cardiovascular homeostasis and can be regulated by extracellular environment, as cells can actively sense mechanical environment. In this study, we evaluated endothelial cell proliferation on PDMS/alumina (Al2O3) composites and pure PDMS. The substrates were prepared from pure PDMS and its composites with 5% and 10% Al2O3 at curing temperature 50˚C for 4 h and then characterized by mechanical, structural and morphological analyses. Higher stiffness was found in the composites compared to the pure PDMS substrate. Cell proliferation of the cultured bovine aortic endothelial cells on substrate materials were evaluated via Resazurin assay and 1, 1’-Dioctadecyl-1, 3, 3, 3’, 3’-Tetramethylindocarbocyanine Perchlorate-Acetylated LDL (Dil-Ac-LDL) cell staining, respectively. The results revealed that stiffer substrates promote more endothelial cells proliferation to the less stiff substrates. Therefore, this study firmly hypothesizes that the stiffness elevates endothelial cells proliferation.

Keywords: stiffness, proliferation, bovine aortic endothelial cells, extra cellular matrix, vascular

Procedia PDF Downloads 332

Authors: Siti Hajar Ya’acob, Nor Sayzwani Sukri, Farah Khaliz Kedri, Rozidaini Mohd Ghazi, Nik Raihan Nik Yusoff, Aweng A/L Eh Rak

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Flood event that occurred in mid-December 2014 in East Coast of Peninsular Malaysia has driven attention from the public nationwide. Apart from loss and damage of properties and belongings, the massive flood event has introduced environmental disturbances on surface water resources in such flood affected area. A study has been conducted to measure the physical and chemical composition of Galas River and Pergau River prior to identification the flood impact towards environmental deterioration in surrounding area. Samples that have been collected were analyzed in-situ using YSI portable instrument and also in the laboratory for acid digestion and heavy metals analysis using Atomic Absorption Spectroscopy (AAS). Results showed that range of temperature (0C), DO (mg/L), Ec (µs/cm), TDS (mg/L), turbidity (NTU), pH, and salinity were 25.05-26.65, 1.51-5.85, 0.032-0.054, 0.022-0.035, 23.2-76.4, 3.46-7.31, and 0.01-0.02 respectively. The results from this study could be used as a primary database to evaluate the status of water quality of the respective river after the massive flood.

Keywords: flood, river, heavy metals, AAS

Procedia PDF Downloads 362

Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP.

Keywords: Chinese restaurant process, Dirichlet prior, infinite mixture model, PCR stutter

Procedia PDF Downloads 315

Authors: M. Alipanah, A. Ranjbar, E. Farnad, F. Alipanah

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Entropy generation of an Al2O3-water nanofluid due to heat transfer and fluid friction irreversibility has been investigated in a square cavity subject to different side wall temperatures using a nanofluid for natural convection flow. This study has been carried out for the pertinent parameters in the following ranges: Rayleigh number between 104 to 107 and volume fraction between 0 to 0.05. Based on the obtained dimensionless velocity and temperature values, the distributions of local entropy generation, average entropy generation and average Bejan number are determined. The results are compared for a pure fluid and a nanofluid. It is totally found that the heat transfer and entropy generation of the nanofluid is more than the pure fluid and minimum entropy generation and Nusselt number occur in the pure fluid at any Rayleigh number. Results depict that the addition of nanoparticles to the pure fluid has more effect on the entropy generation as the Rayleigh number goes up.

Keywords: entropy generation, natural convection, bejan number, nuselt number, nanofluid

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Authors: Silvia Baralla, Raffaella Zucaro, Romina Lorenzetti

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Water management needs to cope with economic, societal, and environmental changes. This could be guaranteed through 'shifting from government to governance'. In the last decades, it was applied in Europe through and within important legislative pillars (Water Framework Directive and Common Agricultural Policy) and their measures focused on resilience and adaptation to climate change, with particular attention to the creation of synergies among policies and all the actors involved at different levels. Within the climate change context, the agricultural sector can play, through sustainable water management, a leading role for climate-resilient growth and environmental integrity. A recent analysis on the water management governance of different countries identified some common gaps dealing with administrative, policy, information, capacity building, funding, objective, and accountability. The ability of a country to fill these gaps is an essential requirement to make some of the changes requested by Europe, in particular the improvement of the agro-ecosystem resilience to the effect of climatic change, supporting green and digital transitions, and sustainable water use. This research aims to contribute in sharing examples of water governances and related advantages useful to fill the highlighted gaps. Italy has developed a strong and exhaustive model of water governance in order to react with strategic and synergic actions since it is one of the European countries most threatened by climate change and its extreme events (drought, floods). In particular, the Italian water governance model was able to overcome several gaps, specifically as concerns the water use in agriculture, adopting strategies as a systemic/integrated approach, the stakeholder engagement, capacity building, the improvement of planning and monitoring ability, and an adaptive/resilient strategy for funding activities. They were carried out, putting in place regulatory, structural, and management actions. Regulatory actions include both the institution of technical committees grouping together water decision-makers and the elaboration of operative manuals and guidelines by means of a participative and cross-cutting approach. Structural actions deal with the funding of interventions within European and national funds according to the principles of coherence and complementarity. Finally, management actions regard the introduction of operational tools to support decision-makers in order to improve planning and monitoring ability. In particular, two cross-functional and interoperable web databases were introduced: SIGRIAN (National Information System for Water Resources Management in Agriculture) and DANIA (National Database of Investments for Irrigation and the Environment). Their interconnection allows to support sustainable investments, taking into account the compliance about irrigation volumes quantified in SIGRIAN, ensuring a high level of attention on water saving, and monitoring the efficiency of funding. Main positive results from the Italian water governance model deal with a synergic and coordinated work at the national, regional, and local level among institutions, the transparency on water use in agriculture, a deeper understanding from the stakeholder side of the importance of their roles and of their own potential benefits and the capacity to guarantee continuity to this model, through a sensitization process and the combined use of management operational tools.

Keywords: agricultural sustainability, governance model, water management, water policies

Procedia PDF Downloads 106