Search results for: performance prism model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25985

Search results for: performance prism model

12725 ORR Activity and Stability of Pt-Based Electrocatalysts in PEM Fuel Cell

Authors: S. Limpattayanate, M. Hunsom

Abstract:

A comparison of activity and stability of the as-formed Pt/C, Pt-Co, and Pt-Pd/C electrocatalysts, prepared by a combined approach of impregnation and seeding, was performed. According to the activity test in a single proton exchange membrane (PEM) fuel cell, the oxygen reduction reaction (ORR) activity of the Pt-M/C electro catalyst was slightly lower than that of Pt/C. The j0.9 V and E10 mA/cm2 of the as-prepared electrocatalysts increased in the order of Pt/C>Pt-Co/C>Pt-Pd/C. However, in the medium-to-high current density region, Pt-Pd/C exhibited the best performance. With regard to their stability in a 0.5 M H2SO4 electrolyte solution, the electro chemical surface area decreased as the number of rounds of repetitive potential cycling increased due to the dissolution of the metals within the catalyst structure. For long-term measurement, Pt-Pd/C was the most stable than the other three electrocatalysts.

Keywords: ORR activity, stability, Pt-based electrocatalysts, PEM fuel cell

Procedia PDF Downloads 434
12724 CERD: Cost Effective Route Discovery in Mobile Ad Hoc Networks

Authors: Anuradha Banerjee

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A mobile ad hoc network is an infrastructure less network, where nodes are free to move independently in any direction. The nodes have limited battery power; hence, we require energy efficient route discovery technique to enhance their lifetime and network performance. In this paper, we propose an energy-efficient route discovery technique CERD that greatly reduces the number of route requests flooded into the network and also gives priority to the route request packets sent from the routers that has communicated with the destination very recently, in single or multi-hop paths. This does not only enhance the lifetime of nodes but also decreases the delay in tracking the destination.

Keywords: ad hoc network, energy efficiency, flooding, node lifetime, route discovery

Procedia PDF Downloads 330
12723 Attentional Differences in Musical Recall and Improvisation

Authors: Krzysztof T. Piotrowski

Abstract:

The main goal of the research was to investigate differences in attention in two kinds of musical performance - recall and improvisation. Musical recall is a sample of convergent production that requires intensively focused attention. Inversely, musical improvisation is a divergent task and probably requires a different way of attentional control. The study was designed in dual task paradigm. Participants were to remember a simple melody and then recall or improvise, simultaneously performing the spatial attentional test on computer screen. The result shows that improvising participants find spatial goals in more disperse way. The conclusion is that musical improvisation requires extensification of attention to occur.

Keywords: attention, creativity, divergent task, musical improvisation

Procedia PDF Downloads 218
12722 Design, Analysis and Obstacle Avoidance Control of an Electric Wheelchair with Sit-Sleep-Seat Elevation Functions

Authors: Waleed Ahmed, Huang Xiaohua, Wilayat Ali

Abstract:

The wheelchair users are generally exposed to physical and psychological health problems, e.g., pressure sores and pain in the hip joint, associated with seating posture or being inactive in a wheelchair for a long time. Reclining Wheelchair with back, thigh, and leg adjustment helps in daily life activities and health preservation. The seat elevating function of an electric wheelchair allows the user (lower limb amputation) to reach different heights. An electric wheelchair is expected to ease the lives of the elderly and disable people by giving them mobility support and decreasing the percentage of accidents caused by users’ narrow sight or joystick operation errors. Thus, this paper proposed the design, analysis and obstacle avoidance control of an electric wheelchair with sit-sleep-seat elevation functions. A 3D model of a wheelchair is designed in SolidWorks that was later used for multi-body dynamic (MBD) analysis and to verify driving control system. The control system uses the fuzzy algorithm to avoid the obstacle by getting information in the form of distance from the ultrasonic sensor and user-specified direction from the joystick’s operation. The proposed fuzzy driving control system focuses on the direction and velocity of the wheelchair. The wheelchair model has been examined and proven in MSC Adams (Automated Dynamic Analysis of Mechanical Systems). The designed fuzzy control algorithm is implemented on Gazebo robotic 3D simulator using Robotic Operating System (ROS) middleware. The proposed wheelchair design enhanced mobility and quality of life by improving the user’s functional capabilities. Simulation results verify the non-accidental behavior of the electric wheelchair.

Keywords: fuzzy logic control, joystick, multi body dynamics, obstacle avoidance, scissor mechanism, sensor

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12721 Impact of Drainage Defect on the Railway Track Surface Deflections; A Numerical Investigation

Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman

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The railwaytransportation network in the UK is over 100 years old and is known as one of the oldest mass transit systems in the world. This aged track network requires frequent closure for maintenance. One of the main reasons for closure is inadequate drainage due to the leakage in the buried drainage pipes. The leaking water can cause localised subgrade weakness, which subsequently can lead to major ground/substructure failure.Different condition assessment methods are available to assess the railway substructure. However, the existing condition assessment methods are not able to detect any local ground weakness/damageand provide details of the damage (e.g. size and location). To tackle this issue, a hybrid back-analysis technique based on artificial neural network (ANN) and genetic algorithm (GA) has been developed to predict the substructurelayers’ moduli and identify any soil weaknesses. At first, afinite element (FE) model of a railway track section under Falling Weight Deflection (FWD) testing was developed and validated against field trial. Then a drainage pipe and various scenarios of the local defect/ soil weakness around the buried pipe with various geometriesand physical properties were modelled. The impact of the soil local weaknesson the track surface deflection wasalso studied. The FE simulations results were used to generate a database for ANN training, and then a GA wasemployed as an optimisation tool to optimise and back-calculate layers’ moduli and soil weakness moduli (ANN’s input). The hybrid ANN-GA back-analysis technique is a computationally efficient method with no dependency on seed modulus values. The modelcan estimate substructures’ layer moduli and the presence of any localised foundation weakness.

Keywords: finite element (FE) model, drainage defect, falling weight deflectometer (FWD), hybrid ANN-GA

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12720 Microstructure of Hydrogen Permeation Barrier Coatings

Authors: Motonori Tamura

Abstract:

Ceramics coatings consisting of fine crystal grains, with diameters of about 100 nm or less, provided superior hydrogen-permeation barriers. Applying TiN, TiC or Al₂O₃ coatings on a stainless steel substrate reduced the hydrogen permeation by a factor of about 100 to 5,000 compared with uncoated substrates. Effect of the microstructure of coatings on hydrogen-permeation behavior is studied. The test specimens coated with coatings, with columnar crystals grown vertically on the substrate, tended to exhibit higher hydrogen permeability. The grain boundaries of the coatings became trap sites for hydrogen, and microcrystalline structures with many grain boundaries are expected to provide effective hydrogen-barrier performance.

Keywords: hydrogen permeation, tin coating, microstructure, crystal grain, stainless steel

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12719 The Impact of Gestational Weight Gain on Subclinical Atherosclerosis, Placental Circulation and Neonatal Complications

Authors: Marina Shargorodsky

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Aim: Gestational weight gain (GWG) has been related to altering future weight-gain curves and increased risks of obesity later in life. Obesity may contribute to vascular atherosclerotic changes as well as excess cardiovascular morbidity and mortality observed in these patients. Noninvasive arterial testing, such as ultrasonographic measurement of carotid IMT, is considered a surrogate for systemic atherosclerotic disease burden and is predictive of cardiovascular events in asymptomatic individuals as well as recurrent events in patients with known cardiovascular disease. Currently, there is no consistent evidence regarding the vascular impact of excessive GWG. The present study was designed to investigate the impact of GWG on early atherosclerotic changes during late pregnancy, using intima-media thickness, as well as placental vascular circulation and inflammatory lesions and pregnancy outcomes. Methods: The study group consisted of 59 pregnant women who gave birth and underwent a placental histopathological examination at the Department of Obstetrics and Gynecology, Edith Wolfson Medical Center, Israel, in 2019. According to the IOM guidelines the study group has been divided into two groups: Group 1 included 32 women with pregnancy weight gain within recommended range; Group 2 included 27 women with excessive weight gain during pregnancy. The IMT was measured from non-diseased intimal and medial wall layers of the carotid artery on both sides, visualized by high-resolution 7.5 MHz ultrasound (Apogee CX Color, ATL). Placental histology subdivided placental findings to lesions consistent with maternal vascular and fetal vascular malperfusion according to the criteria of the Society for Pediatric Pathology, subdividing placental findings to lesions consistent with maternal vascular and fetal vascular malperfusion, as well as the inflammatory response of maternal and fetal origin. Results: IMT levels differed between groups and were significantly higher in Group 1 compared to Group 2 (0.7+/-0.1 vs 0.6+/-0/1, p=0.028). Multiple linear regression analysis of IMT included variables based on their associations in univariate analyses with a backward approach. Included in the model were pre-gestational BMI, HDL cholesterol and fasting glucose. The model was significant (p=0.001) and correctly classified 64.7% of study patients. In this model, pre-pregnancy BMI remained a significant independent predictor of subclinical atherosclerosis assessed by IMT (OR 4.314, 95% CI 0.0599-0.674, p=0.044). Among placental lesions related to fetal vascular malperfusion, villous changes consistent with fetal thrombo-occlusive disease (FTOD) were significantly higher in Group 1 than in Group 2, p=0.034). In Conclusion, the present study demonstrated that excessive weight gain during pregnancy is associated with an adverse effect on early stages of subclinical atherosclerosis, placental vascular circulation and neonatal complications. The precise mechanism for these vascular changes, as well as the overall clinical impact of weight control during pregnancy on IMT, placental vascular circulation as well as pregnancy outcomes, deserves further investigation.

Keywords: obesity, pregnancy, complications, weight gain

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12718 Using Machine Learning to Classify Different Body Parts and Determine Healthiness

Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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12717 Ammonia Bunkering Spill Scenarios: Modelling Plume’s Behaviour and Potential to Trigger Harmful Algal Blooms in the Singapore Straits

Authors: Bryan Low

Abstract:

In the coming decades, the global maritime industry will face a most formidable environmental challenge -achieving net zero carbon emissions by 2050. To meet this target, the Maritime Port Authority of Singapore (MPA) has worked to establish green shipping and digital corridors with ports of several other countries around the world where ships will use low-carbon alternative fuels such as ammonia for power generation. While this paradigm shift to the bunkering of greener fuels is encouraging, fuels like ammonia will also introduce a new and unique type of environmental risk in the unlikely scenario of a spill. While numerous modelling studies have been conducted for oil spills and their associated environmental impact on coastal and marine ecosystems, ammonia spills are comparatively less well understood. For example, there is a knowledge gap regarding how the complex hydrodynamic conditions of the Singapore Straits may influence the dispersion of a hypothetical ammonia plume, which has different physical and chemical properties compared to an oil slick. Chemically, ammonia can be absorbed by phytoplankton, thus altering the balance of the marine nitrogen cycle. Biologically, ammonia generally serves the role of a nutrient in coastal ecosystems at lower concentrations. However, at higher concentrations, it has been found to be toxic to many local species. It may also have the potential to trigger eutrophication and harmful algal blooms (HABs) in coastal waters, depending on local hydrodynamic conditions. Thus, the key objective of this research paper is to support the development of a model-based forecasting system that can predict ammonia plume behaviour in coastal waters, given prevailing hydrodynamic conditions and their environmental impact. This will be essential as ammonia bunkering becomes more commonplace in Singapore’s ports and around the world. Specifically, this system must be able to assess the HAB-triggering potential of an ammonia plume, as well as its lethal and sub-lethal toxic effects on local species. This will allow the relevant authorities to better plan risk mitigation measures or choose a time window with the ideal hydrodynamic conditions to conduct ammonia bunkering operations with minimal risk. In this paper, we present the first part of such a forecasting system: a jointly coupled hydrodynamic-water quality model that can capture how advection-diffusion processes driven by ocean currents influence plume behaviour and how the plume interacts with the marine nitrogen cycle. The model is then applied to various ammonia spill scenarios where the results are discussed in the context of current ammonia toxicity guidelines, impact on local ecosystems, and mitigation measures for future bunkering operations conducted in the Singapore Straits.

Keywords: ammonia bunkering, forecasting, harmful algal blooms, hydrodynamics, marine nitrogen cycle, oceanography, water quality modeling

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12716 Inputs and Outputs of Innovation Processes in the Colombian Services Sector

Authors: Álvaro Turriago-Hoyos

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Most research tends to see innovation as an explanatory factor in achieving high levels of competitiveness and productivity. More recent studies have begun to analyze the determinants of innovation in the services sector as opposed to the much-discussed industrial sector of a country’s economy. This research paper focuses on the services sector in Colombia, one of Latin America’s fastest growing and biggest economies. Over the past decade, much of Colombia’s economic expansion has relied on commodity exports (mainly oil and coffee) whilst the industrial sector has performed relatively poorly. Such developments highlight the potential of the innovative role played by the services sector of the Colombian economy and its future growth prospects. This research paper analyzes the relationship between inputs, which at the same time are internal sources of innovation (such as R&D activities), and external sources that are improved by technology acquisition. The outputs are basically the four kinds of innovation that the OECD Oslo Manual recognizes: product, process, marketing and organizational innovations. The instrument used to measure this input-output relationship is based on Knowledge Production Function approaches. We run Probit models in order to identify the existing relationships between the above inputs and outputs, but also to identify spill-overs derived from interactions of the components of the value chain of the services firms analyzed: customers, suppliers, competitors, and complementary firms. Data are obtained from the Colombian National Administrative Department of Statistics for the period 2008 to 2013 published in the II and III Colombian National Innovation Survey. A short summary of the results obtained lead to conclude that firm size and a firm’s level of technological development turn out to be important discriminating factors for the description of the innovative process at the firm level. The model’s outcomes show a positive impact on the probability of introducing any kind of innovation both on R&D and Technology Acquisition investment. Also, cooperation agreements with customers, research institutes, competitors, and the suppliers are significant. Belonging to a particular industrial group is an important determinant but only to product and organizational innovation. It is possible to establish that Health Services, Education, Computer, Wholesale trade, and Financial Intermediation are the ISIC sectors, which report the highest number of frequencies of the considered set of firms. Those five sectors of the sixteen considered, in all cases, explained more than half of the total of all kinds of innovations. Product Innovation, which is followed by Marketing Innovation, gets the highest results. Displaying the same set of firms distinguishing by size, and belonging to high and low tech services sector shows that the larger the firms the larger a number of innovations, but also that always high-tech firms show a better innovation performance.

Keywords: Colombia, determinants of innovation, innovation, services sector

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12715 Behavioral Effects of Oxidant and Reduced Chemorepellent on Mutant and Wild-Type Tetrahymena thermophila

Authors: Ananya Govindarajan

Abstract:

Tetrahymena thermophila is a single-cell, eukaryotic organism that belongs to the Protozoa Kingdom. Tetrahymena thermophila is often used in signal transduction pathway studies because of its ability to model sensory input and the effects of environmental conditions such as chemicals and temperature. The recently discovered G37 chemorepellent receptor showed increased responsiveness to all chemorepellents. Investigating the mutant G37 Tetrahymena gene in various test solutions, including ferric chloride, ferrous sulfate, hydrogen peroxide, tetrazolium blue, potassium chloride, and dithiothreitol were performed to determine the role of oxidants and reducing agents with the mutant and wild-type cells (CU427) to assess the role of the receptor. Behavioral assays and recordings processed by ImageJ indicated that ferric chloride, hydrogen peroxide, and tetrazolium blue yielded little to no chemorepellent responses from G37 cells (<20% ARs). CU427 cells were over-responsive based on the mean percent of cells (>50% ARs). Reducing agents elicited chemorepellent responses from both G37 and CU427, in addition to potassium chloride. Cell responses were classified as over-responsive (>50% ARs). Dithiothreitol yielded unexpected results as G37 (37.0% ARs) and CU427 (38.1% ARs) had relatively similar responses and were only responsive and not over-responsive to the reducing agent test chemical solution. Ultimately, this indicates that the G37 receptor is more interactive with molecules that are reducing agents or non-oxidant compounds; G37 may be unable to sense and respond to oxidants effectively, further elucidating the pathways of the G37 strain and nature of this receptor. Results also indicate that the CSF most likely contained an oxidant, like ferric chloride. This research can be further applied to neuronal influences and how specific compounds may affect human neurons individually and their excitability as the responses model action potentials and membrane potential.

Keywords: tetrahymena thermophila, signal transduction, chemosensory, oxidant, reducing agent

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12714 Design and Production of Thin-Walled UHPFRC Footbridge

Authors: P. Tej, P. Kněž, M. Blank

Abstract:

The paper presents design and production of thin-walled U-profile footbridge made of UHPFRC. The main structure of the bridge is one prefabricated shell structure made of UHPFRC with dispersed steel fibers without any conventional reinforcement. The span of the bridge structure is 10 m and the clear width of 1.5 m. The thickness of the UHPFRC shell structure oscillated in an interval of 30-45 mm. Several calculations were made during the bridge design and compared with the experiments. For the purpose of verifying the calculations, a segment of 1.5 m was first produced, followed by the whole footbridge for testing. After the load tests were done, the design was optimized to cast the final footbridge.

Keywords: footbridge, non-linear analysis, shell structure, UHPFRC, Ultra-High Performance Fibre Reinforced Concrete

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12713 The Development of OTOP Web Application: Case of Samut Songkhram Province

Authors: Satien Janpla, Kunyanuth Kularbphettong

Abstract:

This paper aims to present the development of a web‑based system to serve the need of selling OTOP products in Samut Songkhram, Thailand. This system was designed to promote and sell OTOP products on website. We describe the design approaches and functional components of this system. The system was developed by PHP and JavaScript and MySQL database System. To evaluate the system performance, questionnaires were used to measure user satisfaction with system usability by specialists and users. The results were satisfactory as followed: Means for specialists and users were 4.05 and 3.97, and standard deviation for specialists and users were 0.563 and 0.644 respectively. Further analysis showed that the quality of One Tambon One Product (OTOP) Website was also at a good level as well.

Keywords: web-based system, OTOP, product, website

Procedia PDF Downloads 300
12712 Training for Digital Manufacturing: A Multilevel Teaching Model

Authors: Luís Rocha, Adam Gąska, Enrico Savio, Michael Marxer, Christoph Battaglia

Abstract:

The changes observed in the last years in the field of manufacturing and production engineering, popularly known as "Fourth Industry Revolution", utilizes the achievements in the different areas of computer sciences, introducing new solutions at almost every stage of the production process, just to mention such concepts as mass customization, cloud computing, knowledge-based engineering, virtual reality, rapid prototyping, or virtual models of measuring systems. To effectively speed up the production process and make it more flexible, it is necessary to tighten the bonds connecting individual stages of the production process and to raise the awareness and knowledge of employees of individual sectors about the nature and specificity of work in other stages. It is important to discover and develop a suitable education method adapted to the specificities of each stage of the production process, becoming an extremely crucial issue to exploit the potential of the fourth industrial revolution properly. Because of it, the project “Train4Dim” (T4D) intends to develop complex training material for digital manufacturing, including content for design, manufacturing, and quality control, with a focus on coordinate metrology and portable measuring systems. In this paper, the authors present an approach to using an active learning methodology for digital manufacturing. T4D main objective is to develop a multi-degree (apprenticeship up to master’s degree studies) and educational approach that can be adapted to different teaching levels. It’s also described the process of creating the underneath methodology. The paper will share the steps to achieve the aims of the project (training model for digital manufacturing): 1) surveying the stakeholders, 2) Defining the learning aims, 3) producing all contents and curriculum, 4) training for tutors, and 5) Pilot courses test and improvements.

Keywords: learning, Industry 4.0, active learning, digital manufacturing

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12711 Data Clustering Algorithm Based on Multi-Objective Periodic Bacterial Foraging Optimization with Two Learning Archives

Authors: Chen Guo, Heng Tang, Ben Niu

Abstract:

Clustering splits objects into different groups based on similarity, making the objects have higher similarity in the same group and lower similarity in different groups. Thus, clustering can be treated as an optimization problem to maximize the intra-cluster similarity or inter-cluster dissimilarity. In real-world applications, the datasets often have some complex characteristics: sparse, overlap, high dimensionality, etc. When facing these datasets, simultaneously optimizing two or more objectives can obtain better clustering results than optimizing one objective. However, except for the objectives weighting methods, traditional clustering approaches have difficulty in solving multi-objective data clustering problems. Due to this, evolutionary multi-objective optimization algorithms are investigated by researchers to optimize multiple clustering objectives. In this paper, the Data Clustering algorithm based on Multi-objective Periodic Bacterial Foraging Optimization with two Learning Archives (DC-MPBFOLA) is proposed. Specifically, first, to reduce the high computing complexity of the original BFO, periodic BFO is employed as the basic algorithmic framework. Then transfer the periodic BFO into a multi-objective type. Second, two learning strategies are proposed based on the two learning archives to guide the bacterial swarm to move in a better direction. On the one hand, the global best is selected from the global learning archive according to the convergence index and diversity index. On the other hand, the personal best is selected from the personal learning archive according to the sum of weighted objectives. According to the aforementioned learning strategies, a chemotaxis operation is designed. Third, an elite learning strategy is designed to provide fresh power to the objects in two learning archives. When the objects in these two archives do not change for two consecutive times, randomly initializing one dimension of objects can prevent the proposed algorithm from falling into local optima. Fourth, to validate the performance of the proposed algorithm, DC-MPBFOLA is compared with four state-of-art evolutionary multi-objective optimization algorithms and one classical clustering algorithm on evaluation indexes of datasets. To further verify the effectiveness and feasibility of designed strategies in DC-MPBFOLA, variants of DC-MPBFOLA are also proposed. Experimental results demonstrate that DC-MPBFOLA outperforms its competitors regarding all evaluation indexes and clustering partitions. These results also indicate that the designed strategies positively influence the performance improvement of the original BFO.

Keywords: data clustering, multi-objective optimization, bacterial foraging optimization, learning archives

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12710 Effects of Gamma-Tocotrienol Supplementation on T-Regulatory Cells in Syngeneic Mouse Model of Breast Cancer

Authors: S. Subramaniam, J. S. A. Rao, P. Ramdas, K. R. Selvaduray, N. M. Han, M. K. Kutty, A. K. Radhakrishnan

Abstract:

Immune system is a complex system where the immune cells have the capability to respond against a wide range of immune challenges including cancer progression. However, in the event of cancer development, tumour cells trigger immunosuppressive environment via activation of myeloid-derived suppressor cells and T regulatory (Treg) cells. The Treg cells are subset of CD4+ T lymphocytes, known to have crucial roles in regulating immune homeostasis and promoting the establishment and maintenance of peripheral tolerance. Dysregulation of these mechanisms could lead to cancer progression and immune suppression. Recently, there are many studies reporting on the effects of natural bioactive compounds on immune responses against cancer. It was known that tocotrienol-rich-fraction consisting 70% tocotrienols and 30% α-tocopherol is able to exhibit immunomodulatory as well as anti-cancer properties. Hence, this study was designed to evaluate the effects of gamma-tocotrienol (G-T3) supplementation on T-reg cells in a syngeneic mouse model of breast cancer. In this study, female BALB/c mice were divided into two groups and fed with either soy oil (vehicle) or gamma-tocotrienol (G-T3) for two weeks followed by inoculation with tumour cells. All the mice continued to receive the same supplementation until day 49. The results showed a significant reduction in tumour volume and weight in G-T3 fed mice compared to vehicle-fed mice. Lung and liver histology showed reduced evidence of metastasis in tumour-bearing G-T3 fed mice. Besides that, flow cytometry analysis revealed T-helper cell population was increased, and T-regulatory cell population was suppressed following G-T3 supplementation. Moreover, immunohistochemistry analysis showed that there was a marked decrease in the expression of FOXP3 in the G-T3 fed tumour bearing mice. In conclusion, the G-T3 supplementation showed good prognosis towards breast cancer by enhancing the immune response in tumour-bearing mice. Therefore, gamma-T3 can be used as immunotherapy agent for the treatment of breast cancer.

Keywords: breast cancer, gamma tocotrienol, immune suppression, supplement

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12709 Detecting Local Clusters of Childhood Malnutrition in the Island Province of Marinduque, Philippines Using Spatial Scan Statistic

Authors: Novee Lor C. Leyso, Maylin C. Palatino

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Under-five malnutrition continues to persist in the Philippines, particularly in the island Province of Marinduque, with prevalence of some forms of malnutrition even worsening in recent years. Local spatial cluster detection provides a spatial perspective in understanding this phenomenon as key in analyzing patterns of geographic variation, identification of community-appropriate programs and interventions, and focused targeting on high-risk areas. Using data from a province-wide household-based census conducted in 2014–2016, this study aimed to determine and evaluate spatial clusters of under-five malnutrition, across the province and within each municipality at the individual level using household location. Malnutrition was defined as weight-for-age z-score that fall outside the 2 standard deviations from the median of the WHO reference population. The Kulldorff’s elliptical spatial scan statistic in binomial model was used to locate clusters with high-risk of malnutrition, while adjusting for age and membership to government conditional cash transfer program as proxy for socio-economic status. One large significant cluster of under-five malnutrition was found southwest of the province, in which living in these areas at least doubles the risk of malnutrition. Additionally, at least one significant cluster were identified within each municipality—mostly located along the coastal areas. All these indicate apparent geographical variations across and within municipalities in the province. There were also similarities and disparities in the patterns of risk of malnutrition in each cluster across municipalities, and even within municipality, suggesting underlying causes at work that warrants further investigation. Therefore, community-appropriate programs and interventions should be identified and should be focused on high-risk areas to maximize limited government resources. Further studies are also recommended to determine factors affecting variations in childhood malnutrition considering the evidence of spatial clustering found in this study.

Keywords: Binomial model, Kulldorff’s elliptical spatial scan statistic, Philippines, under-five malnutrition

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12708 Increased Circularity in Metals Production Using the Ausmelt TSL Process

Authors: Jacob Wood, David Wilson, Stephen Hughes

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The Ausmelt Top Submerged Lance (TSL) Process has been widely applied for the processing of both primary and secondary copper, nickel, lead, tin, and zinc-bearing feed materials. Continual development and evolution of the technology over more than 30 years has resulted in a more intense smelting process with higher energy efficiency, improved metal recoveries, lower operating costs, and reduced fossil fuel consumption. This paper covers a number of recent advances to the technology, highlighting their positive impacts on smelter operating costs, environmental performance, and contribution towards increased circularity in metals production.

Keywords: ausmelt TSL, smelting, circular economy, energy efficiency

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12707 Spatial Planning and Tourism Development with Sustainability Model of the Territorial Tourist with Land Use Approach

Authors: Mehrangiz Rezaee, Zabih Charrahi

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In the last decade, with increasing tourism destinations and tourism growth, we are witnessing the widespread impacts of tourism on the economy, environment and society. Tourism and its related economy are now undergoing a transformation and as one of the key pillars of business economics, it plays a vital role in the world economy. Activities related to tourism and providing services appropriate to it in an area, like many economic sectors, require the necessary context on its origin. Given the importance of tourism industry and tourism potentials of Yazd province in Iran, it is necessary to use a proper procedure for prioritizing different areas for proper and efficient planning. One of the most important goals of planning is foresight and creating balanced development in different geographical areas. This process requires an accurate study of the areas and potential and actual talents, as well as evaluation and understanding of the relationship between the indicators affecting the development of the region. At the global and regional level, the development of tourist resorts and the proper distribution of tourism destinations are needed to counter environmental impacts and risks. The main objective of this study is the sustainable development of suitable tourism areas. Given that tourism activities in different territorial areas require operational zoning, this study deals with the evaluation of territorial tourism using concepts such as land use, fitness and sustainable development. It is essential to understand the structure of tourism development and the spatial development of tourism using land use patterns, spatial planning and sustainable development. Tourism spatial planning implements different approaches. However, the development of tourism as well as the spatial development of tourism is complex, since tourist activities can be carried out in different areas with different purposes. Multipurpose areas have great important for tourism because it determines the flow of tourism. Therefore, in this paper, by studying the development and determination of tourism suitability that is related to spatial development, it is possible to plan tourism spatial development by developing a model that describes the characteristics of tourism. The results of this research determine the suitability of multi-functional territorial tourism development in line with spatial planning of tourism.

Keywords: land use change, spatial planning, sustainability, territorial tourist, Yazd

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12706 Microwave Imaging by Application of Information Theory Criteria in MUSIC Algorithm

Authors: Majid Pourahmadi

Abstract:

The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.

Keywords: microwave imaging, time reversal, MUSIC algorithm, minimum description length (MDL)

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12705 Bayesian Reliability of Weibull Regression with Type-I Censored Data

Authors: Al Omari Moahmmed Ahmed

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In the Bayesian, we developed an approach by using non-informative prior with covariate and obtained by using Gauss quadrature method to estimate the parameters of the covariate and reliability function of the Weibull regression distribution with Type-I censored data. The maximum likelihood seen that the estimators obtained are not available in closed forms, although they can be solved it by using Newton-Raphson methods. The comparison criteria are the MSE and the performance of these estimates are assessed using simulation considering various sample size, several specific values of shape parameter. The results show that Bayesian with non-informative prior is better than Maximum Likelihood Estimator.

Keywords: non-informative prior, Bayesian method, type-I censoring, Gauss quardature

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12704 A Design for Supply Chain Model by Integrated Evaluation of Design Value and Supply Chain Cost

Authors: Yuan-Jye Tseng, Jia-Shu Li

Abstract:

To design a product with the given product requirement and design objective, there can be alternative ways to propose the detailed design specifications of the product. In the design modeling stage, alternative design cases with detailed specifications can be modeled to fulfill the product requirement and design objective. Therefore, in the design evaluation stage, it is required to perform an evaluation of the alternative design cases for deciding the final design. The purpose of this research is to develop a product evaluation model for evaluating the alternative design cases by integrated evaluating the criteria of functional design, Kansei design, and design for supply chain. The criteria in the functional design group include primary function, expansion function, improved function, and new function. The criteria in the Kansei group include geometric shape, dimension, surface finish, and layout. The criteria in the design for supply chain group include material, manufacturing process, assembly, and supply chain operation. From the point of view of value and cost, the criteria in the functional design group and Kansei design group represent the design value of the product. The criteria in the design for supply chain group represent the supply chain and manufacturing cost of the product. It is required to evaluate the design value and the supply chain cost to determine the final design. For the purpose of evaluating the criteria in the three criteria groups, a fuzzy analytic network process (FANP) method is presented to evaluate a weighted index by calculating the total relational values among the three groups. A method using the technique for order preference by similarity to ideal solution (TOPSIS) is used to compare and rank the design alternative cases according to the weighted index using the total relational values of the criteria. The final decision of a design case can be determined by using the ordered ranking. For example, the design case with the top ranking can be selected as the final design case. Based on the criteria in the evaluation, the design objective can be achieved with a combined and weighted effect of the design value and manufacturing cost. An example product is demonstrated and illustrated in the presentation. It shows that the design evaluation model is useful for integrated evaluation of functional design, Kansei design, and design for supply chain to determine the best design case and achieve the design objective.

Keywords: design for supply chain, design evaluation, functional design, Kansei design, fuzzy analytic network process, technique for order preference by similarity to ideal solution

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12703 Complexity in a Leslie-Gower Delayed Prey-Predator Model

Authors: Anuraj Singh

Abstract:

The complex dynamics is explored in a prey predator system with multiple delays. The predator dynamics is governed by Leslie-Gower scheme. The existence of periodic solutions via Hopf bifurcation with respect to delay parameters is established. To substantiate analytical findings, numerical simulations are performed. The system shows rich dynamic behavior including chaos and limit cycles.

Keywords: chaos, Hopf bifurcation, stability, time delay

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12702 Triassic Magmatism in Southern Beishan Orogen, Northwest China: Zircon U–Pb Geochronology, Petrogenesis and Tectonic Implications

Authors: Zengda Li

Abstract:

The tectonic evolution of the Beishan orogen, which forms part of the Central Asian Orogenic Belt, remains debated. This study reports the identification of three Triassic granitic plutons representing two distinct stages of magmatism in southern Beishan orogen. Zircon U–Pb dating constrains the early stage as 238–237 Ma and the late stage as 229–227 Ma. The granitoids belong to high-K calc-alkaline and shoshonitic series and exhibit alkalic-calcic and calc-alkalic features, and are weakly peraluminous rocks. Most of these granitoids are highly fractionated I-type and A-type granites. They have relatively high Isr values (0.7049–0.7086) and weak negative εNd(t) values of −1.5 to −2.1, with young Nd model ages of 1.04–0.91 Ga, indicating a crustal contribution. They also show markedly positive zircon εHf(t) values (+3.4 to +11.8) and two-stage Hf model ages of 1.06–0.69 Ga, indicating a mixture of mantle and crustal components. The lithospheric mantle beneath this region incorporating older subducted materials was metasomatized by fluids or melts. Partial melting of the metasomatized lithospheric mantle resulted in underplated magmas, which provided the heat and material input to generate the granitoids. The Middle Triassic granitic plutons show moderate negative Eu anomalies, enrichment of LILEs and depletion in Nb, Ta, and Ti suggesting partial melting of crustal components in response to the underplated mantle-derived magmas, probably linked to lithospheric delamination and asthenospheric upwelling. The Late Triassic granitic plutons show characteristics of post-orogenic granite with strong negative anomalies of Eu, Ba, Nb, Sr, P, and Ti, indicating fractional crystallization and crustal contamination during the emplacement process.

Keywords: Triassic, magmatism, geochronology, petrogenesis, Beishan orogen

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12701 Microbial Contamination of Haemolymph of Honeybee (Apis mellifera intermissa) Parasitized by Varroa Destructor

Authors: Messaouda Belaid, Salima Kebbouche-Gana

Abstract:

The negative effect of the Varroa bee colony is very important. They cause morphological and physiological changes, causing a decrease in performance of individuals and long-term death of the colony. Indirectly, they weaken the bees become much more sensitive to the different pathogenic organisms naturally present in the colony. This work aims to research secondary infections of microbial origin occurred in the worker bee nurse due to parasitism by Varroa destructor. The feeding behaviour of Varroa may causes damaging host integument. The results show that the microbial contamination enable to be transmitted into honeybee heamocoel are Bacillus sp, Pseudomonas sp, Enterobacter, Aspergillus.

Keywords: honeybee, Apis mellifera intermissa, microbial contamination, Varroa destructor

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12700 A General Form of Characteristics Method Applied on Minimum Length Nozzles Design

Authors: Merouane Salhi, Mohamed Roudane, Abdelkader Kirad

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In this work, we present a new form of characteristics method, which is a technique for solving partial differential equations. Typically, it applies to first-order equations; the aim of this method is to reduce a partial differential equation to a family of ordinary differential equations along which the solution can be integrated from some initial data. This latter developed under the real gas theory, because when the thermal and the caloric imperfections of a gas increases, the specific heat and their ratio do not remain constant anymore and start to vary with the gas parameters. The gas doesn’t stay perfect. Its state equation change and it becomes for a real gas. The presented equations of the characteristics remain valid whatever area or field of study. Here we need have inserted the developed Prandtl Meyer function in the mathematical system to find a new model when the effect of stagnation pressure is taken into account. In this case, the effects of molecular size and intermolecular attraction forces intervene to correct the state equation, the thermodynamic parameters and the value of Prandtl Meyer function. However, with the assumptions that Berthelot’s state equation accounts for molecular size and intermolecular force effects, expressions are developed for analyzing the supersonic flow for thermally and calorically imperfect gas. The supersonic parameters depend directly on the stagnation parameters of the combustion chamber. The resolution has been made by the finite differences method using the corrector predictor algorithm. As results, the developed mathematical model used to design 2D minimum length nozzles under effect of the stagnation parameters of fluid flow. A comparison for air with the perfect gas PG and high temperature models on the one hand and our results by the real gas theory on the other of nozzles shapes and characteristics are made.

Keywords: numerical methods, nozzles design, real gas, stagnation parameters, supersonic expansion, the characteristics method

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12699 Interplay of Material and Cycle Design in a Vacuum-Temperature Swing Adsorption Process for Biogas Upgrading

Authors: Federico Capra, Emanuele Martelli, Matteo Gazzani, Marco Mazzotti, Maurizio Notaro

Abstract:

Natural gas is a major energy source in the current global economy, contributing to roughly 21% of the total primary energy consumption. Production of natural gas starting from renewable energy sources is key to limit the related CO2 emissions, especially for those sectors that heavily rely on natural gas use. In this context, biomethane produced via biogas upgrading represents a good candidate for partial substitution of fossil natural gas. The upgrading process of biogas to biomethane consists in (i) the removal of pollutants and impurities (e.g. H2S, siloxanes, ammonia, water), and (ii) the separation of carbon dioxide from methane. Focusing on the CO2 removal process, several technologies can be considered: chemical or physical absorption with solvents (e.g. water, amines), membranes, adsorption-based systems (PSA). However, none emerged as the leading technology, because of (i) the heterogeneity in plant size, ii) the heterogeneity in biogas composition, which is strongly related to the feedstock type (animal manure, sewage treatment, landfill products), (iii) the case-sensitive optimal tradeoff between purity and recovery of biomethane, and iv) the destination of the produced biomethane (grid injection, CHP applications, transportation sector). With this contribution, we explore the use of a technology for biogas upgrading and we compare the resulting performance with benchmark technologies. The proposed technology makes use of a chemical sorbent, which is engineered by RSE and consists of Di-Ethanol-Amine deposited on a solid support made of γ-Alumina, to chemically adsorb the CO2 contained in the gas. The material is packed into fixed beds that cyclically undergo adsorption and regeneration steps. CO2 is adsorbed at low temperature and ambient pressure (or slightly above) while the regeneration is carried out by pulling vacuum and increasing the temperature of the bed (vacuum-temperature swing adsorption - VTSA). Dynamic adsorption tests were performed by RSE and were used to tune the mathematical model of the process, including material and transport parameters (i.e. Langmuir isotherms data and heat and mass transport). Based on this set of data, an optimal VTSA cycle was designed. The results enabled a better understanding of the interplay between material and cycle tuning. As exemplary application, the upgrading of biogas for grid injection, produced by an anaerobic digester (60-70% CO2, 30-40% CH4), for an equivalent size of 1 MWel was selected. A plant configuration is proposed to maximize heat recovery and minimize the energy consumption of the process. The resulting performances are very promising compared to benchmark solutions, which make the VTSA configuration a valuable alternative for biomethane production starting from biogas.

Keywords: biogas upgrading, biogas upgrading energetic cost, CO2 adsorption, VTSA process modelling

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12698 The Governance of UK Museums and Art Galleries: Implications for Accountability

Authors: Aminah Abdullah, Iqbal Khadaroo

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This paper investigates to what ends, how and by whom museums and art galleries in the UK are governed, and to whom they provide accounts to justify their behavior and activities. A theoretical framework is developed by drawing from the governance and accountability literature and is fleshed out by using empirical data from secondary sources. The findings show that the governance model used, informed by the new public management (NPM) philosophy, and has created tensions between the managerial and social forms of accountability. Museums and art galleries have adopted a managerial culture of getting done what gets measured.

Keywords: governance, accountability, UK museums and art galleries, public sector

Procedia PDF Downloads 315
12697 Emotion Expression of the Leader and Collective Efficacy: Pride and Guilt

Authors: Hsiu-Tsu Cho

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Collective efficacy refers to a group’s sense of its capacity to complete a task successfully or to reach objectives. Little effort has been expended on investigating the relationship between the emotion expression of a leader and collective efficacy. In this study, we examined the impact of the different emotions and emotion expression of a group leader on collective efficacy and explored whether the emotion–expressive effects differed under conditions of negative and positive emotions. A total of 240 undergraduate and graduate students recruited using Facebook and posters at a university participated in this research. The participants were separated randomly into 80 groups of four persons consisting of three participants and a confederate. They were randomly assigned to one of five conditions in a 2 (pride vs. guilt) × 2 (emotion expression of group leader vs. no emotion expression of group leader) factorial design and a control condition. Each four-person group was instructed to get the reward in a group competition of solving the five-disk Tower of Hanoi puzzle and making decisions on an investment case. We surveyed the participants by employing the emotional measure revised from previous researchers and collective efficacy questionnaire on a 5-point scale. To induce an emotion of pride (or guilt), the experimenter announced whether the group performance was good enough to have a chance of getting the reward (ranking the top or bottom 20% among all groups) after group task. The leader (confederate) could either express or not express a feeling of pride (or guilt) following the instruction according to the assigned condition. To check manipulation of emotion, we added a control condition under which the experimenter revealed no results regarding group performance in maintaining a neutral emotion. One-way ANOVAs and post hoc pairwise comparisons among the three emotion conditions (pride, guilt, and control condition) involved assigning pride and guilt scores (pride: F(1,75) = 32.41, p < .001; guilt: F(1,75) = 6.75, p < .05). The results indicated that manipulations of emotion were successful. A two-way between-measures ANOVA was conducted to examine the predictions of the main effects of emotion types and emotion expression as well as the interaction effect of these two variables on collective efficacy. The experimental findings suggest that pride did not affect collective efficacy (F(1,60) = 1.90, ns.) more than guilt did and that the group leader did not motivate collective efficacy regardless of whether he or she expressed emotion (F(1,60) = .89, ns.). However, the interaction effect of emotion types and emotion expression was statistically significant (F(1,60) = 4.27, p < .05, ω2 = .066); the effects accounted for 6.6% of the variance. Additional results revealed that, under the pride condition, the leader enhanced group efficacy when expressing emotion, whereas, under the guilt condition, an expression of emotion could reduce collective efficacy. Overall, these findings challenge the assumption that the effect of expression emotion are the same on all emotions and suggest that a leader should be cautious when expressing negative emotions toward a group to avoid reducing group effectiveness.

Keywords: collective efficacy, group leader, emotion expression, pride, guilty

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12696 Protective Effect of Bexarotene, a Selective RXRα Agonist, against Hypotension Associated with Inflammation and Tissue Injury Linked to Decreased Circulating iNOS Levels in A Rat Model of Septic Shock

Authors: Bahar Tunctan, Sefika Pinar Kucukkavruk, Meryem Temiz-Resitoglu, Demet Sinem Guden, Ayse Nihal Sari, Seyhan Sahan-Firat

Abstract:

We hypothesized that rexinoids such as bexarotene, a selective retinoid X receptor α (RXRα) agonist, may be beneficial for preventing mortality due to inflammation associated with increased expression/activity of inducible nitric oxide synthase (iNOS) induced by lipopolysaccharide (LPS). Therefore, we investigated effects of bexarotene on the changes in circulating protein levels of iNOS (an index for systemic iNOS expression), myeloperoxidase (MPO) (an index for systemic inflammation), and lactate dehydrogenase (LDH) (an index for systemic tissue injury) in LPS-induced systemic inflammation model resulting in septic shock in rats. Rats were injected with saline (4 ml/kg; i.p.), LPS (10 mg/kg; i.p.), dimethylsulphoxide (4 ml/kg, 0.1%; s.c.) at time 0. Mean arterial blood pressure and heart rate were measured using a tail-cuff device. Bexarotene (0.03, 0.1, 0.3, and 1 mg/kg; s.c.) was administered to separate groups of rats 1 h after injection of saline or LPS. The rats were sacrificed 4 h after saline or LPS injection and blood was collected for measurement of serum iNOS, MPO, and LDH protein levels. Blood pressure decreased by 31 mmHg and heart rate increased by 63 bpm in the LPS-treated rats. Bexarotene at 0.3 and 1 mg/kg doses caused 20% mortality 4 h after LPS injection. In the LPS-treated rats, serum iNOS, MPO, and LDH protein levels were increased. Bexarotene only at 0.1 mg/kg dose prevented the LPS-induced hypotension and increased in iNOS, MPO, and LDH protein levels. These data are consistent with the view that a decrease in systemic iNOS levels contributes to the beneficial effect of bexarotene to prevent the hypotension associated with inflammation and tissue injury during rat endotoxemia. [This work was financially supported by The Scientific and Technological Research Council of Turkey (SBAG-109S121)].

Keywords: bexarotene, inflammation, iNOS, lipopolisaccharide, RXRa

Procedia PDF Downloads 302