Search results for: diurnal temperature cycle model

Authors: Vichai Tienthavorn

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Background: Recently, the patients of non-communicable diseases (NCDs) are increasing in Thailand; especially hypertension and diabetes. Hypertension and Diabetes patients were found to be of 3.7 million in 2008. The varieties of human behaviors have been extensively changed in health. Hence, Thai Government has a policy to reduce NCDs. Generally, primary care plays an important role in treatment using medical process. However, NCDs patients have not been decreased. Objectives: This study not only reduce the patient and mortality rate but also increase the quality of life, could apply in different areas and propose to be the national policy, effectively for a long term operation. Methods: Here we report that primary health care (PHC), which is a primary process to screening, rapidly seek the person's risk. The screening tool of the study was Vichai's 7 color balls model, the medical education tool to transfer knowledge from student health team to community through health volunteers, creating community engagement in terms of social participation. It was found that people in community were realized in their health and they can evaluate the level of risk using this model. Results: Projects implementation (2015) in Nong Lom Health Center in Phayao (target group 15-65 years, 2529); screening hypertension coveraged 99.01%, risk group (light green) was decreased to normal group (white) from 1806 to 1893, significant severe patient (red) was decreased to moderate (orange) from 10 to 5. Health Program in behaving change with best practice of 3Es (Eating, Exercise, Emotion) and 3Rs (Reducing tobacco, alcohol, obesity) were applied in risk group; and encourage strictly medication, investigation in severe patient (red). Conclusion: This is the first demonstration of knowledge transfer to community engagement by student, which is the sustainable education in PHC.

Keywords: non-communicable disease, surveillance control and prevention systems, community engagement, primary health care

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Authors: Ieva Gaide, Violeta Makareviciene

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Increasing environmental pollution is caused by various factors, including the usage of vehicles. Legislation is focused on the increased usage of renewable energy sources for fuel production. Electric car usage is also important; however, it is relatively new and expensive transport. It is necessary to increase the amount of renewable energy in the production of diesel fuel, whereas many agricultural machineries are powered by diesel, as are water vehicles. For this reason, research on biodiesel production is relevant. The majority of studies globally are related to the improvement of conventional biofuel production technologies by applying the transesterification process of oil using alcohol and catalyst. Some of the more recent methods to produce biodiesel are based on heterogeneous catalysis, which has the advantage of easy separation of catalyst from the final product. It is known that a large amount of eggshells is treated as waste; therefore, it is eliminated in landfills without any or with minimal pre-treatment. CaO, which is known as a good catalyst for biodiesel synthesis, is a key component of eggshells. In the present work, we evaluated the catalytic efficiency of eggshells and determined the optimal transesterification conditions to obtain biodiesel that meets the standards. Content CaO in eggshells was investigated. Response surface methodology was used to determine the optimal reaction conditions. Three independent variables were investigated: the molar ratio of alcohol to oil, the amount of the catalyst, and the duration of the reaction. It was obtained that the optimum transesterification conditions when the methanol and eggshells as a heterogeneous catalyst are used and the process temperature is 64°C are the following: the alcohol-to-oil molar ratio 10.93:1, the reaction duration 9.48 h, and the catalyst amount 6.80 wt%. Under these conditions, 97.79 wt% of the ester yield was obtained.

Keywords: heterogeneous catalysis, eggshells, biodiesel, oil

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Authors: Chin-Tsu Ma, Yi-Jhen Wu, Hsia Ying Cheng, Han Hsiang Huang, Shyh Ming Kuo

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The use of specific molecules including nutrients and pharmacological agents has been tried in modulation of stem cells differentiation (MSCs) to insulin producing cells. The aim of this study is to investigate the ability of nano collagen molecules (nutrient or scaffold) to enhance the MSCs differentiation into insulin-producing cells in combination with nicotinamide and exendin-4 (pharmacological agents) in vitro and in vivo. The results demonstrated that the cells exhibit morphologically islet-like clusters after treatment with nano collagen molecules, nicotinamide and exendin-4. MSCs extra treated with nano collagen molecules showed significant increases in Nkx6.1 and insulin mRNA expression at 14-d and 21-d culture compared with those merely treated with nicotinamide and exendin-4. Early 7-day elevation in PDX-1 mRNA expression was observed. Furthermore, the MSCs exposed to nano collagen molecules produced the highest secretion of insulin (p ＜ 0.05). Type-2 diabetes induced by high-fat diet and low dose of streptozotocin in rat model was built in this study. This rat exhibited higher food intake, water intake, lower glucose tolerance, lower-insulin tolerance, and higher HbA1C (significant increases, p ＜ 0.01) as compared with the normal rat that demonstrated the model of type-2 diabetes was successfully built. Biopsy examinations also showed that obvious destruction of islet. After injection of differentiated MSCs into the destructed pancreas of diabetes rat, more regenerated islet were observed at the rats that treated with nano collagen molecules and exhibited much lower HbA1C as compared with the normal rat and diabetes rat after 4 weeks (significant deceases, p ＜ 0.001). These results indicate that the culturing MSCs with nano collagen molecules, nicotinamide, and exendin-4 are beneficial for MSCs differentiation into islet-like cells. These nano collagen molecules may lead to alternations or up-regulation of gene expression and influence the differentiated outcomes induced by nicotinamide and exendin-4.

Keywords: nano collagen molecules, nicotinamide, MSCs, diabetes

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Authors: Wen Liu, Errol Haarhoff, Lee Beattie

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In 2010, New Zealand’s central government re-organise the local governments arrangements in Auckland, New Zealand by amalgamating its previous regional council and seven supporting local government units into a single unitary council, the Auckland Council. The Auckland Council is charged with providing local government services to approximately 1.5 million people (a third of New Zealand’s total population). This includes addressing Auckland’s strategic urban growth management and setting its urban planning policy directions for the next 40 years. This is expressed in the first ever spatial plan in the region – the Auckland Plan (2012). The Auckland plan supports implementing a compact city model by concentrating the larger part of future urban growth and development in, and around, existing and proposed transit centres, with the intention of Auckland to become globally competitive city and achieving ‘the most liveable city in the world’. Turning that vision into reality is operatized through the statutory land use plan, the Auckland Unitary Plan. The Unitary plan replaced the previous regional and local statutory plans when it became operative in 2016, becoming the ‘rule book’ on how to manage and develop the natural and built environment, using land use zones and zone standards. Common to the broad range of literature on urban growth management, one significant issue stands out about intensification. The ‘gap’ between strategic planning and what has been achieved is evident in the argument for the ‘compact’ urban form. Although the compact city model may have a wide range of merits, the extent to which these are actualized largely rely on how intensification actually is delivered. The transformation of the rhetoric of the residential intensification model into reality is of profound influence, yet has enjoyed limited empirical analysis. In Auckland, the establishment of the Auckland Plan set up the strategies to deliver intensification into diversified arenas. Nonetheless, planning policy itself does not necessarily achieve the envisaged objectives, delivering the planning system and high capacity to enhance and sustain plan implementation is another demanding agenda. Though the Auckland Plan provides a wide ranging strategic context, its actual delivery is beholden on the Unitary Plan. However, questions have been asked if the Unitary Plan has the necessary statutory tools to deliver the Auckland Plan’s policy outcomes. In Auckland, there is likely to be continuing tension between the strategies for intensification and their envisaged objectives, and made it doubtful whether the main principles of the intensification strategies could be realized. This raises questions over whether the Auckland Plan’s policy goals can be achieved in practice, including delivering ‘quality compact city’ and residential intensification. Taking Auckland as an example of traditionally sprawl cities, this article intends to investigate the efficacy plan making and implementation directed towards higher density development. This article explores the process of plan development, plan making and implementation frameworks of the first ever spatial plan in Auckland, so as to explicate the objectives and processes involved, and consider whether this will facilitate decision making processes to realize the anticipated intensive urban development.

Keywords: urban intensification, sustainable development, plan making, governance and implementation

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Authors: Padmalochan Panda, R. Ramaseshan

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Aluminum nitride (AlN) is a potential candidate for semiconductor industry due to its wide band gap (6.2 eV), high thermal conductivity and low thermal coefficient of expansion. A-plane oriented AlN film finds an important role in deep UV-LED with higher isotropic light extraction efficiency. Also, Cr-doped AlN films exhibit dilute magnetic semiconductor property with high Curie temperature (300 K), and thus compatible with modern day microelectronics. In this work, highly a-axis oriented wurtzite AlN and Al1-xMxN (M = Cr, Ti) films have synthesized by reactive co-sputtering technique at different concentration. Crystal structure of these films is studied by Grazing incidence X-ray diffraction (GIXRD) and Transmission electron microscopy (TEM). Identification of binding energy and concentration (x) in these films is carried out by X-ray photoelectron spectroscopy (XPS). Local crystal structure around the Cr and Ti atom of these films are investigated by X-ray absorption spectroscopy (XAS). It is found that Cr and Ti replace the Al atom in AlN lattice and the bond lengths in first and second coordination sphere with N and Al, respectively, decrease concerning doping concentration due to strong p-d hybridization. The nano-indentation hardness of Cr and Ti-doped AlN films seems to increase from 17.5 GPa (AlN) to around 23 and 27.5 GPa, respectively. An-isotropic optical properties of these films are studied by the Spectroscopic Ellipsometry technique. Refractive index and extinction coefficient of these films are enhanced in normal dispersion region as compared to the parent AlN film. The optical band gap energies also seem to vary between deep UV to UV regions with the addition of Cr, thus by bringing out the usefulness of these films in the area of optoelectronic device applications.

Keywords: ellipsometry, GIXRD, hardness, XAS

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Authors: Stephen O. Amiandamhen, Martina Meinken, Luvuyo Tyhoda

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The properties of Hemp (Cannabis sativa) in phosphate bonded composites were investigated in this research. Hemp hurds were collected from the Hemporium institute for research, South Africa. The hurds were air-dried and shredded using a hammer mill. The shives were screened into different particle sizes and were treated separately with 5% solution of acetic anhydride and sodium hydroxide. The binding matrix was prepared using a reactive magnesia, phosphoric acid, class S fly ash and unslaked lime. The treated and untreated hemp fibers were mixed thoroughly in different ratios with the inorganic matrix. Boric acid and excess water were used to retard and control the rate of the reaction and the setting of the binder. The Hemp composite was formed in a rectangular mold and compressed at room temperature at a pressure of 100KPa. After de-molding the composites, they were cured in a conditioning room for 96 h. Physical and mechanical tests were conducted to evaluate the properties of the composites. A central composite design (CCD) was used to determine the best conditions to optimize the performance of the composites. Thereafter, these combinations were applied in the production of the composites, and the properties were evaluated. Scanning electron microscopy (SEM) was used to carry out the advance examination of the behavior of the composites while X-ray diffractometry (XRD) was used to analyze the reaction pathway in the composites. The results revealed that all properties of phosphate bonded Hemp composites exceeded the LD-1 grade classification of particle boards. The proposed product can be used for ceiling, partitioning, wall claddings and underlayment.

Keywords: CCD, fly ash, magnesia, phosphate bonded hemp composites, phosphoric acid, unslaked lime

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Authors: S. V. Patil, P. S. Dounde, S. S. Patil

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Emulgels have emerged as one of the most interesting topical delivery system as it has dual release control system that is gel and emulsion. The major objective behind this formulation is delivery of hydrophobic drugs to systemic circulation via skin. In fact presence of a gelling agent in water phase converts a classical emulsion in to emulgel. The emulgel for dermatological use has several favorable properties such as being thixotropic, greaseless, easily spreadable, easily removable, emollient, non-staining, water-soluble, longer shelf life, bio-friendly, transparent and pleasing appearance. Various penetration enhancers can potentiate the effect. So this can be used as better topical drug delivery systems over present conventional systems available in market. Piroxicam is a non-steroidal anti-inflammatory drug that has major problems when administered orally; it is an insoluble drug and has irritant effect on gastro intestinal tract lead to ulceration and bleeding. The aim of this study was to overcoming these problems through preparation of topical emulgel of this drug. Emulgel of Piroxicam was prepared using Carbopol 940 along with mentha oil and clove oil as permeation enhancer. The prepared emulgel were evaluated for their physical appearance, pH determination, viscosity, spreadability, in vitro drug release, ex vivo permeation studies. All the prepared formulations showed acceptable physical properties, homogeneity, consistency, spreadability, viscosity and pH value. The emulgel was found to be stable with respect to physical appearance, pH, rheological properties and drug content at all temperature and conditions for three month.

Keywords: emulgel, piroxicam, menthe oil, clove oil

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Authors: Breanna Macumber, Victor A. Huayamave, Emir A. Vela, Wangdo Kim, Tamara T. Chamber, Esteban Centeno

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Spina bifida is a type of neural tube defect that affects the nervous system and can lead to problems such as total leg paralysis. Treatment requires physical therapy and rehabilitation. Robotic exoskeletons have been used for rehabilitation to train muscle movement and assist in injury recovery; however, current models focus on the adult populations and not on the infant population. The proposed framework aims to couple a musculoskeletal infant model with a robotic exoskeleton using vacuum-powered artificial muscles to provide rehabilitation to infants affected by spina bifida. The study that drove the input values for the robotic exoskeleton used motion capture technology to collect data from the spontaneous kicking movement of a 2.4-month-old infant lying supine. OpenSim was used to develop the musculoskeletal model, and Inverse kinematics was used to estimate hip joint angles. A total of 4 kicks (A, B, C, D) were selected, and the selection was based on range, transient response, and stable response. Kicks had at least 5° of range of motion with a smooth transient response and a stable period. The robotic exoskeleton used a Vacuum-Powered Artificial Muscle (VPAM) the structure comprised of cells that were clipped in a collapsed state and unclipped when desired to simulate infant’s age. The artificial muscle works with vacuum pressure. When air is removed, the muscle contracts and when air is added, the muscle relaxes. Bench testing was performed using a 6-month-old infant mannequin. The previously developed exoskeleton worked really well with controlled ranges of motion and frequencies, which are typical of rehabilitation protocols for infants suffering with spina bifida. However, the random kicking motion in this study contained high frequency kicks and was not able to accurately replicate all the investigated kicks. Kick 'A' had a greater error when compared to the other kicks. This study has the potential to advance the infant rehabilitation field.

Keywords: musculoskeletal modeling, soft robotics, rehabilitation, pediatrics

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Authors: Seulki Lee, Seoung Bum Kim

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Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.

Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process

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Authors: Louk Aourelien Andrianos, Edward Dommen, Athena Peralta

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Greed, as epitomized by overconsumption of natural resources, is at the root of ecological destruction and unsustainability of modern societies. Presently economies rely on unrestricted structural greed which fuels unlimited economic growth, overconsumption, and individualistic competitive behavior. Structural greed undermines the life support system on earth and threatens ecological integrity, social justice and peace. The World Council of Churches (WCC) has developed a program on ecological and economic justice (EEJ) with the aim to promote an economy of life where the economy is embedded in society and society in ecology. This paper aims at analyzing and assessing the economy of life (EcoLife) by offering an empirical tool to measure and monitor the root causes and effects of unsustainability resulting from human greed on global, national, institutional and individual levels. This holistic approach is based on the integrity of ecology and economy in a society founded on justice. The paper will discuss critical questions such as ‘what is an economy of life’ and ‘how to measure and control it from the effect of greed’. A model called GLIMS, which stands for Greed Lines and Indices Measurement System is used to clarify the concept of greed and help measuring the economy of life index by fuzzy logic reasoning. The inputs of the model are from statistical indicators of natural resources consumption, financial realities, economic performance, social welfare and ethical and political facts. The outputs are concrete measures of three primary indices of ecological, economic and socio-political greed (ECOL-GI, ECON-GI, SOCI-GI) and one overall multidimensional economy of life index (EcoLife-I). EcoLife measurement aims to build awareness of an economy life and to address the effects of greed in systemic and structural aspects. It is a tool for ethical diagnosis and policy making.

Keywords: greed line, sustainability indicators, fuzzy logic, eco-justice, World Council of Churches (WCC)

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Authors: Behzad Ahdiharab, Senol Baskaya, Tamer Calisir

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Heat exchangers are one of the most widely used systems in factories, refineries etc. In this study, natural convection heat transfer using nano-fluids in between two cylinders is numerically investigated. The inner and outer cylinders are kept at constant temperatures. One of the most important assumptions in the project is that the working fluid is non-Newtonian. In recent years, the use of nano-fluids in industrial applications has increased profoundly. In this study, nano-Newtonian fluids containing metal particles with high heat transfer coefficients have been used. All fluid properties such as homogeneity has been calculated. In the present study, solutions have been obtained under unsteady conditions, base fluid was water, and effects of various parameters on heat transfer have been investigated. These parameters are Rayleigh number (103 < Ra < 106), power-law index (0.6 < n < 1.4), aspect ratio (0 < AR < 0.8), nano-particle composition, horizontal and vertical displacement of the inner cylinder, rotation of the inner cylinder, and volume fraction of nanoparticles. Results such as the internal cylinder average and local Nusselt number variations, contours of temperature, flow lines are presented. The results are also discussed in detail. From the validation study performed it was found that a very good agreement exists between the present results and those from the open literature. It was found out that the heat transfer is always affected by the investigated parameters. However, the degree to which the heat transfer is affected does change in a wide range.

Keywords: heat transfer, circular space, non-Newtonian, nano fluid, computational fluid dynamics.

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Authors: Ankit Kumar Yadav, Nagendra R. Velaga

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Driving under the influence of alcohol impairs the driving performance and increases the crash risks worldwide. The present study investigated the effect of different Blood Alcohol Concentrations (BAC) on the accelerating and braking behaviour of drivers with the help of driving simulator experiments. Eighty-two licensed Indian drivers drove on the rural road environment designed in the driving simulator at BAC levels of 0.00%, 0.03%, 0.05%, and 0.08% respectively. Driving performance was analysed with the help of vehicle control performance indicators such as mean acceleration and mean brake pedal force of the participants. Preliminary analysis reported an increase in mean acceleration and mean brake pedal force with increasing BAC levels. Generalized linear mixed models were developed to quantify the effect of different alcohol levels and explanatory variables such as driver’s age, gender and other driver characteristic variables on the driving performance indicators. Alcohol use was reported as a significant factor affecting the accelerating and braking performance of the drivers. The acceleration model results indicated that mean acceleration of the drivers increased by 0.013 m/s², 0.026 m/s² and 0.027 m/s² for the BAC levels of 0.03%, 0.05% and 0.08% respectively. Results of the brake pedal force model reported that mean brake pedal force of the drivers increased by 1.09 N, 1.32 N and 1.44 N for the BAC levels of 0.03%, 0.05% and 0.08% respectively. Age was a significant factor in both the models where one year increase in drivers’ age resulted in 0.2% reduction in mean acceleration and 19% reduction in mean brake pedal force of the drivers. It shows that driving experience could compensate for the negative effects of alcohol to some extent while driving. Female drivers were found to accelerate slower and brake harder as compared to the male drivers which confirmed that female drivers are more conscious about their safety while driving. It was observed that drivers who were regular exercisers had better control on their accelerator pedal as compared to the non-regular exercisers during drunken driving. The findings of the present study revealed that drivers tend to be more aggressive and impulsive under the influence of alcohol which deteriorates their driving performance. Drunk driving state can be differentiated from sober driving state by observing the accelerating and braking behaviour of the drivers. The conclusions may provide reference in making countermeasures against drinking and driving and contribute to traffic safety.

Keywords: alcohol, acceleration, braking behaviour, driving simulator

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Authors: Luo Jiaoyang, Yu Hongyang

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In this paper, we explore a method that can be used in the working scene of intelligent industrial robots to confirm the identity information of operators to ensure that the robot executes instructions in a sufficiently safe environment. This approach uses three information modalities, namely visible light, depth, and sound. We explored a variety of fusion modes for the three modalities and finally used the joint feature learning method to improve the performance of the model in the case of noise compared with the single-modal case, making the maximum noise in the experiment. It can also maintain an accuracy rate of more than 90%.

Keywords: multimodal, kinect, machine learning, distance image

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Authors: Ionel Botef

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Aerospace products operate in very aggressive environments characterized by high temperature, high pressure, large stresses on individual components, the presence of oxidizing and corroding atmosphere, as well as internally created or externally ingested particulate materials that induce erosion and impact damage. Consequently, during operation, the materials of individual components degrade. In addition, the impact of maintenance costs for both civil and military aircraft was estimated at least two to three times greater than initial purchase values, and this trend is expected to increase. As a result, for viable product realisation and maintenance, a spectrum of issues regarding novel processing technologies, innovation of new materials, performance, costs, and environmental impact must constantly be addressed. One of these technologies, namely the cold-gas dynamic-spray process has enabled a broad range of coatings and applications, including many that have not been previously possible or commercially practical, hence its potential for new aerospace applications. Therefore, the purpose of this paper is to summarise the state of the art of this technology alongside its theoretical and experimental studies, and explore how the cold-gas dynamic-spray process could be integrated within a framework that finally could lead to more efficient aircraft maintenance. Based on the paper's qualitative findings supported by authorities, evidence, and logic essentially it is argued that the cold-gas dynamic-spray manufacturing process should not be viewed in isolation, but should be viewed as a component of a broad framework that finally leads to more efficient aerospace operations.

Keywords: aerospace, aging aircraft, cold spray, materials

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Authors: Adrian Keith Caamino, Sina Shakibania, Lena Sunqvist-Öqvist, Jan Rosenkranz, Yousef Ghorbani

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Feldspar minerals are one of the main components of the earth’s crust. They are tectosilicate, meaning that they mainly contain aluminum and silicon. Besides aluminum and silicon, they contain either potassium, sodium, or calcium. Accordingly, feldspar minerals are categorized into three main groups: K-feldspar, Na-feldspar, and Ca-feldspar. In recent years, the trend to use K-feldspar has grown tremendously, considering its potential to produce potash and alumina. However, the feldspar minerals, in general, are difficult to decompose for the dissolution of their metallic components. Several methods, including intensive milling, leaching under elevated pressure and temperature, thermal pretreatment, and the use of corrosive leaching reagents, have been proposed to improve its low dissolving efficiency. In this study, as part of the POTASSIAL EU project, to overcome the low dissolution efficiency of the K-feldspar components, mechanical activation using intensive milling followed by leaching using hydrochloric acid (HCl) was practiced. Grinding operational parameters, namely time, rotational speed, and ball-to-sample weight ratio, were studied using the Taguchi optimization method. Then, the mineralogy of the grinded samples was analyzed using a scanning electron microscope (SEM) equipped with automated quantitative mineralogy. After grinding, the prepared samples were subjected to HCl leaching. In the end, the dissolution efficiency of the main elements and impurities of different samples were correlated to the mineralogical characterization results. K-feldspar component dissolution is correlated with ore mineralogy, which provides insight into how to best optimize leaching conditions for selective dissolution. Further, it will have an effect on purifying steps taken afterward and the final value recovery procedures

Keywords: K-feldspar, grinding, automated mineralogy, impurity, leaching

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Authors: Kanit Aroonrat, Somchai Wongwises

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A heat exchanger is one of the vital parts in a wide variety of applications. The tube with surface modification is generally referred to as an enhanced tube. With this, the thermal performance of the heat exchanger is improved. A dimpled tube is one of many kinds of enhanced tube. The heat transfer and pressure drop of two-phase flow inside dimpled tubes have received little attention in the literature, despite of having an important role in the development of refrigeration and air conditioning systems. As a result, the main aim of this study is to investigate the condensation heat transfer and pressure drop of refrigerant-134a flowing inside dimpled tubes. The test section is a counter-flow double-tube heat exchanger, which the refrigerant flows in the inner tube and water flows in the annulus. The inner tubes are one smooth tube and three dimpled tubes with different helical pitches. All test tubes are made from copper with an inside diameter of 8.1 mm and length of 1500 mm. The experiments are conducted over mass fluxes ranging from 300 to 500 kg/m²s, heat flux ranging from 10 to 20 kW/m², and condensing temperature ranging from 40 to 50 ˚C. The results show that all dimpled tubes provide higher heat transfer coefficient and frictional pressure drop compared to the smooth tube. In addition, the heat transfer coefficient and frictional pressure drop increase with decreasing of helical pitch. It can be observed that the dimpled tube with lowest helical pitch yields the heat transfer enhancement in the range of 60-89% with the frictional pressure drop increase of 289-674% in comparison to the smooth tube.

Keywords: condensation, dimpled tube, heat transfer, pressure drop

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Authors: Jae-Yong Park, Yeo-Kyeong Lee, Hee-Sun Kim

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Purpose: This study aims at investigating the mechanical behaviors of mastication, according to various teeth movement. There are three masticatory cases which are general case and 2 cases of teeth movement. General case includes the common arrange of all teeth and 2 cases of teeth movement are that one is the half movement location case of molar teeth in no. 14 tooth seat after extraction of no. 14 tooth and the other is no. 14 tooth seat location case of molar teeth after extraction in the same case before. Materials and Methods: In order to analyze these cases, 3 dimensional finite element (FE) model of the skull were generated based on computed tomography images, 964 dicom files of 38 year old male having normal occlusion status. An FE model in general occlusal case was used to develop CAE procedure. This procedure was applied to FE models in other occlusal cases. The displacement controls according to loading condition were applied effectively to simulate occlusal behaviors in all cases. From the FE analyses, von Mises stress distribution of skull and teeth was observed. The von Mises stress, effective stress, had been widely used to determine the absolute stress value, regardless of stress direction and yield characteristics of materials. Results: High stress was distributed over the periodontal area of mandible under molar teeth when the mandible was transmitted to the coronal-apical direction in the general occlusal case. According to the stress propagation from teeth to cranium, stress distribution decreased as the distribution propagated from molar teeth to infratemporal crest of the greater wing of the sphenoid bone and lateral pterygoid plate in general case. In 2 cases of teeth movement, there were observed that high stresses were distributed over the periodontal area of mandible under teeth where they are located under the moved molar teeth in cranium. Conclusion: The predictions of the mechanical behaviors of general case and 2 cases of teeth movement during the masticatory process were investigated including qualitative validation. The displacement controls as the loading condition were applied effectively to simulate occlusal behaviors in 2 cases of teeth movement of molar teeth.

Keywords: cranium, finite element analysis, mandible, masticatory action, occlusal force

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Authors: Hamid Reza Shariatmadari

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The Muslims who believe in twelve Imams and believe that their twelfth Imam is now hidden, because of their kind of consideration of immune Imam as their unique canonical authority for interpretation of Islam, are subject of these important questions; how can you be democratic? And can you speak of democracy as the best model of governing? Answering this question, we can talk firstly about the nature of democracy and realize it as a way and mechanism not as a philosophy of identity and secondly we can refer to the nature and functions of Imam in Shiism and thirdly we will focus on the age of Ghaybah (Or concealment of Imam). In such a time we can or have to combine domination of Islamic Faqis (Islamic Jurists) and democracy which is known in Shiite Iran for instance as religious democracy.

Keywords: Shiism, concealment of Imam, Islamic Jurists, Democracy

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Authors: Alaa Morsy, Youssef Ibrahim

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Earthquake is one of the most catastrophic events, which makes enormous harm to properties and human lives. As a piece of a safe building configuration, reinforced concrete walls are given in structures to decrease horizontal displacements under seismic load. Shear walls are additionally used to oppose the horizontal loads that might be incited by the impact of wind. Reinforced concrete walls in residential buildings might have openings that are required for windows in outside walls or for doors in inside walls or different states of openings due to architectural purposes. The size, position, and area of openings may fluctuate from an engineering perspective. Shear walls can encounter harm around corners of entryways and windows because of advancement of stress concentration under the impact of vertical or horizontal loads. The openings cause a diminishing in shear wall capacity. It might have an unfavorable impact on the stiffness of reinforced concrete wall and on the seismic reaction of structures. Finite Element Method using software package ‘ANSYS ver. 12’ becomes an essential approach in analyzing civil engineering problems numerically. Now we can make various models with different parameters in short time by using ANSYS instead of doing it experimentally, which consumes a lot of time and money. Finite element modeling approach has been conducted to study the effect of opening shape, size and position in RC wall with different thicknesses under axial and lateral static loads. The proposed finite element approach has been verified with experimental programme conducted by the researchers and validated by their variables. A very good correlation has been observed between the model and experimental results including load capacity, failure mode, and lateral displacement. A parametric study is applied to investigate the effect of opening size, shape, position on different reinforced concrete wall thicknesses. The results may be useful for improving existing design models and to be applied in practice, as it satisfies both the architectural and the structural requirements.

Keywords: Ansys, concrete walls, openings, out of plane behavior, seismic, shear wall

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Authors: A. Douara, N. Kermas, B. Djellouli

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In this study, we report calculations of gate capacitance of AlGaN/GaN HEMTs with nextnano device simulation software. We have used a physical gate capacitance model for III-V FETs that incorporates quantum capacitance and centroid capacitance in the channel. These simulations explore various device structures with different values of barrier thickness and channel thickness. A detailed understanding of the impact of gate capacitance in HEMTs will allow us to determine their role in future 10 nm physical gate length node.

Keywords: gate capacitance, AlGaN/GaN, HEMTs, quantum capacitance, centroid capacitance

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Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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Authors: Tridipa Biswas, Kamal Pandey

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A Digital Elevation Model (DEM) is a simple representation of a surface in 3 dimensional space with elevation as the third dimension along with X (horizontal coordinates) and Y (vertical coordinates) in rectangular coordinates. DEM has wide applications in various fields like disaster management, hydrology and watershed management, geomorphology, urban development, map creation and resource management etc. Cartosat-1 or IRS P5 (Indian Remote Sensing Satellite) is a state-of-the-art remote sensing satellite built by ISRO (May 5, 2005) which is mainly intended for cartographic applications.Cartosat-1 is equipped with two panchromatic cameras capable of simultaneous acquiring images of 2.5 meters spatial resolution. One camera is looking at +26 degrees forward while another looks at –5 degrees backward to acquire stereoscopic imagery with base to height ratio of 0.62. The time difference between acquiring of the stereopair images is approximately 52 seconds. The high resolution stereo data have great potential to produce high-quality DEM. The high-resolution Cartosat-1 stereo image data is expected to have significant impact in topographic mapping and watershed applications. The objective of the present study is to generate high-resolution DEM, quality evaluation in different elevation strata, generation of ortho-rectified image and associated accuracy assessment from CARTOSAT-1 data based Ground Control Points (GCPs) for Aglar watershed (Tehri-Garhwal and Dehradun district, Uttarakhand, India). The present study reveals that generated DEMs (10m and 30m) derived from the CARTOSAT-1 stereo pair is much better and accurate when compared with existing DEMs (ASTER and CARTO DEM) also for different terrain parameters like slope, aspect, drainage, watershed boundaries etc., which are derived from the generated DEMs, have better accuracy and results when compared with the other two (ASTER and CARTO) DEMs derived terrain parameters.

Keywords: ASTER-DEM, CARTO-DEM, CARTOSAT-1, digital elevation model (DEM), ortho-rectified image, photogrammetry, RPC, stereo pair, terrain parameters

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Authors: S. Sadallah

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In this paper, dynamic programming is used to determine the optimal management of financial resources in company. Solution of the problem by consider into simpler substructures is constructed. The optimal management of internal capital of company are simulated. The tools applied in this development are based on graph theory. The software of given problems is built by using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: management, software, optimal, greedy algorithm, graph-diagram

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

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This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

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Authors: Dharmit Viroja, Prerakkumar Shah, Rajanikant Gajera, Ruchit Shah

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With present scenario of aging oil and gas fields with high water cuts, volatile oil prices and increasing greenhouse gas emission, the need for alleviating such issues has necessitated for oil and gas industry to make the maximum out of available assets, infrastructure and reserves in mother Earth. Study undertaken emphasizes on utilizing Geothermal Energy under specific reservoir conditions for Enhanced oil Recovery (EOR) to boost up production. Allied benefits of this process include mitigation of electricity problem in remote fields and controlled CO-emission. Utilization of this energy for EOR and increasing economic life of field could surely be rewarding. A new way to value oil lands would be considered if geothermal co-production is integrated in the field development program. Temperature profile of co-produced fluid across its journey is a pivotal issue which has been studied. Geo pressured reservoirs resulting from trapped brine under an impermeable bed is also a frontier for exploitation. Hot geothermal fluid is a by-product of large number of oil and gas wells, historically this hot water has been seen as an inconvenience; however, it can be looked at as a useful resource. The production of hot fluids from abandoned and co-production of hot fluids from producing wells has potential to prolong life of oil and gas fields. The study encompasses various factors which are required for use of this technology and application of this process across various phases of oil and gas value chain. Interdisciplinary approach in oil and gas value chain has shown potential for economic production of estimated oil and gas reserves.

Keywords: enhanced oil recovery, geo-pressured reservoirs, geothermal energy, oil and gas value chain

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Authors: Felipe Azocar Simonet, Luis Acosta Espejo

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In this article, we will try to find an efficient boundary approximation for the bi-objective location problem with coherent coverage for two levels of hierarchy (CCLP). We present the mathematical formulation of the model used. Supported efficient solutions and unsupported efficient solutions are obtained by solving the bi-objective combinatorial problem through the weights method using a Lagrangean heuristic. Subsequently, the results are validated through the DEA analysis with the GEM index (Global efficiency measurement).

Keywords: coherent covering location problem, efficient frontier, lagragian relaxation, data envelopment analysis

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Authors: Md. Shadab, Mariyam N. Nashid, Venkata Srikanth Meka, Thiagarajan Madheswaran

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Naringenin (NAR), is a naturally occurring plant flavonoid, found predominantly in citrus fruits, that possesses a wide range of pharmacological properties including anti-oxidant, anti-inflammatory behaviour, cholesterol-lowering and anticarcinogenic activities. However, despite the therapeutic potential of naringenin shown in a number of animal models, its clinical development has been hindered due to its low aqueous solubility, slow dissolution rate and inefficient transport across biological membranes resulting in low bioavailability. Naringenin nanosuspension were produced using stabilizers Tween® 80 by high pressure homogenization techniques. The nanosuspensions were characterized with regard to size (photon correlation spectroscopy (PCS), size distribution, charge (zeta potential measurements), morphology, short term physical stability, dissolution profile and antioxidant potential. A nanocrystal PCS size of about 500 nm was obtained after 20 homogenization cycles at 1500 bar. The short-term stability was assessed by storage of the nanosuspensions at 4 ◦C, room temperature and 40 ◦C. Result showed that naringenin nanosuspension was physically unstable due to large fluctuations in the particle size and zeta potential after 30 days. Naringenin nanosuspension demonstrated higher drug dissolution (97.90%) compared to naringenin powder (62.76%) after 120 minutes of testing. Naringenin nanosuspension showed increased antioxidant activity compared to naringenin powder with a percentage DPPH radical scavenging activity of 49.17% and 31.45% respectively at the lowest DPPH concentration.

Keywords: bioavailability, naringenin, nanosuspension, oral delivery

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Authors: Breanna Macumber, Victor A. Huayamave, Emir A. Vela, Wangdo Kim, Tamara T. Chamber, Esteban Centeno

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Spina bifida is a type of neural tube defect that affects the nervous system and can lead to problems such as total leg paralysis. Treatment requires physical therapy and rehabilitation. Robotic exoskeletons have been used for rehabilitation to train muscle movement and assist in injury recovery; however, current models focus on the adult populations and not on the infant population. The proposed framework aims to couple a musculoskeletal infant model with a robotic exoskeleton using vacuum-powered artificial muscles to provide rehabilitation to infants affected by spina bifida. The study that drove the input values for the robotic exoskeleton used motion capture technology to collect data from the spontaneous kicking movement of a 2.4-month-old infant lying supine. OpenSim was used to develop the musculoskeletal model, and Inverse kinematics was used to estimate hip joint angles. A total of 4 kicks (A, B, C, D) were selected, and the selection was based on range, transient response, and stable response. Kicks had at least 5° of range of motion with a smooth transient response and a stable period. The robotic exoskeleton used a Vacuum-Powered Artificial Muscle (VPAM) the structure comprised of cells that were clipped in a collapsed state and unclipped when desired to simulate infant’s age. The artificial muscle works with vacuum pressure. When air is removed, the muscle contracts and when air is added, the muscle relaxes. Bench testing was performed using a 6-month-old infant mannequin. The previously developed exoskeleton worked really well with controlled ranges of motion and frequencies, which are typical of rehabilitation protocols for infants suffering with spina bifida. However, the random kicking motion in this study contained high frequency kicks and was not able to accurately replicate all the investigated kicks. Kick 'A' had a greater error when compared to the other kicks. This study has the potential to advance the infant rehabilitation field.

Keywords: musculoskeletal modeling, soft robotics, rehabilitation, pediatrics

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Authors: Hounyèmè Romuald, Maxime Logez, Mama Daouda, Argillier Christine

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In view of the very strong degradation of aquatic ecosystems, it is urgent to set up monitoring systems that are best able to report on the effects of the stresses they undergo. This is particularly true in developing countries, where specific and relevant quality standards and funding for monitoring programs are lacking. The objective of this study was to make a relevant and objective choice of physicochemical parameters informative of the main stressors occurring on African lakes and to identify their alteration thresholds. Based on statistical analyses of the relationship between several driving forces and the physicochemical parameters of the Nokoué lagoon, relevant Physico-chemical parameters were selected for its monitoring. An innovative method based on Bayesian statistical modeling was used. Eleven Physico-chemical parameters were selected for their response to at least one stressor and their threshold quality standards were also established: Total Phosphorus (<4.5mg/L), Orthophosphates (<0.2mg/L), Nitrates (<0.5 mg/L), TKN (<1.85 mg/L), Dry Organic Matter (<5 mg/L), Dissolved Oxygen (>4 mg/L), BOD (<11.6 mg/L), Salinity (7.6 .), Water Temperature (<28.7 °C), pH (>6.2), and Transparency (>0.9 m). According to the System for the Evaluation of Coastal Water Quality, these thresholds correspond to” good to medium” suitability classes, except for total phosphorus. One of the original features of this study is the use of the bounds of the credibility interval of the fixed-effect coefficients as local weathering standards for the characterization of the Physico-chemical status of this anthropized African ecosystem.

Keywords: driving forces, alteration thresholds, acadjas, monitoring, modeling, human activities

Procedia PDF Downloads 78