Search results for: VFA membrane extraction

Authors: Bouchenak Fatima, Lmegharbi Abdelbaki, Houssem Degaichia, Benrebiha Fatima

Abstract:

The essential oil composition of the leaf of Artemisia absinthium from region of Cherchell (The south of Algeria) was investigated by GC, GC-MS. 27 constituents were identified correspond to 84, 63% of the total oil. The major components are Thujone (60, 82%), Chamazulènel (16, 62%), ρ-cymène (4, 29%) and 2-carène (4.25%). The antimicrobial activity of oil was tested in vitro by two methods (agar diffusion and microdilution) on three plant pathogenic fungi. This oil has been tested for antimicrobial activity against three pathogenic fungi (Botrytis cinerea, Fusarium culmorum and Helminthosporium Sp.).The study of activity was evaluated by two methods: Method of diffusion in gelose and the minimum inhibitory concentration MIC. This oil exhibited an interesting antimicrobial activity. A preliminary study showed that this oil presented high toxicity against this fungus. These results, although preliminary show a good antifungal activity, to limit and inhibit stop the development of those pathogen agent.

Keywords: artemisia absinthian, extraction process, chemical study, antifungal activity

Procedia PDF Downloads 467

Authors: Saji George, Eng Khuan Seng, Christof Luda

Abstract:

Nanotechnology has been recognized as an important tool for modern agriculture and has the potential to overcome some of the pressing challenges faced by aquaculture industry. A strategy for optimizing nanotechnology-based therapeutic delivery platform for immunizing farmed fish was developed. Accordingly, a compositional library of nanomaterials of natural chemistry (Halloysite (clay), Chitosan, Hydroxyapatite, Mesoporous Silica and a composite material of clay-chitosan) was screened for their toxicity and efficiency in delivering models antigens in cellular and zebrafish embryo models using high throughput screening platforms. Through multi-parametric optimization, chitosan modified halloysite (clay) nanomaterial was identified as an optimal vaccine delivery platform. Further, studies conducted in juvenile seabass showed the potential of clay-chitosan in delivering outer membrane protein of Tenacibaculum maritimum- TIMA (pathogenic bacteria) to and its efficiency in eliciting immune responses in fish. In short, as exemplified by this work, the strategy of using compositional nanomaterial libraries and their biological profiling using high-throughput screening platform could fasten the discovery process of nanomaterials with potential applications in food and agriculture.

Keywords: nanotechnology, fish-vaccine, drug-delivery, halloysite-chitosan

Procedia PDF Downloads 271

Authors: Elyta Widyaningrum

Abstract:

The LiDAR data acquisition has been recognizable as one of the fastest solution to provide the basis data for topographic base mapping in Indonesia. The challenges to accelerate the provision of large-scale topographic base maps as a development plan basis gives the opportunity to implement the automated scheme in the map production process. The one stop processing will also contribute to accelerate the map provision especially to conform with the Indonesian fundamental spatial data catalog derived from ISO 19110 and geospatial database integration. Thus, the automated LiDAR classification, DTM generation and feature extraction will be conducted in one GIS-software environment to form all layers of topographic base maps. The quality of automated topographic base map will be assessed and analyzed based on its completeness, correctness, contiguity, consistency and possible customization.

Keywords: automation, GIS environment, LiDAR processing, map quality

Procedia PDF Downloads 356

Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

Abstract:

In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: text mining, topic extraction, independent, incremental, independent component analysis

Procedia PDF Downloads 294

Authors: Ahmed M. Haddad, Hadeel S. El-Shaal, Gadallah M. Abu-Elreesh

Abstract:

Some of filamentous fungi can be used for biodiesel production as they are able to accumulate high amounts of intracellular lipids when grown at stress conditions. Aspergillus fumigatus sp. was isolated from Nile delta soil in Egypt. The fungus was primarily screened for its capacity to accumulate lipids using Nile red staining assay. The fungus could accumulate more than 20% of its biomass as lipids when grown at optimized minimal medium. After lipid extraction, we could use fungal cell debris to remove some heavy metals from contaminated waste water. The fungal cell debris could remove Cd, Cr, and Zn with absorption efficiency of 73%, 83.43%, and 69.39% respectively. In conclusion, the Aspergillus fumigatus isolate may be considered as a promising biodiesel producer, and its biomass waste can be further used for bioremediation of wastewater contaminated with heavy metals.

Keywords: biodiesel, bioremediation, fungi, heavy metals, lipids, oleaginous

Procedia PDF Downloads 211

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 32

Authors: Khalil Khan, Ikram Syed, Muhammad Ehsan Mazhar, Iran Uddin, Nasir Ahmad

Abstract:

Face parts labeling is the process of assigning class labels to each face part. A face parts labeling method (FPL) which divides a given image into its constitutes parts is proposed in this paper. A database FaceD consisting of 564 images is labeled with hand and make publically available. A supervised learning model is built through extraction of features from the training data. The testing phase is performed with two semantic segmentation methods, i.e., pixel and super-pixel based segmentation. In pixel-based segmentation class label is provided to each pixel individually. In super-pixel based method class label is assigned to super-pixel only – as a result, the same class label is given to all pixels inside a super-pixel. Pixel labeling accuracy reported with pixel and super-pixel based methods is 97.68 % and 93.45% respectively.

Keywords: face labeling, semantic segmentation, classification, face segmentation

Procedia PDF Downloads 242

Authors: So Youn Park, Yi Sle Lee, Ki Whan Hong, Chi Dae Kim

Abstract:

The role of metabolism in the pathogenesis of osteoarthritis is an emerging field. Metabolic alterations may be a role in osteoarthritis (OA) pathogenesis, and these changes influence joint destruction via several cytokine. Especially, in OA patients, levels of IL-1β are elevated in the synovial fluid, synovial membrane, subchondral bone, and cartilage. The IL-1β is activated by NLRP3 inflammasomes, and NLRP3 inflammasomes are cytosolic complexes that drive the production of other inflammatory cytokines, including IL-1β. In this study, we examined that SIRT1 suppresses IL-1β through inhibiting NLRP3 inflammasomes and SIRT1 ameliorates osteoarthritis. OA fibroblasts were isolated from synovium of OA patients. IL-1β and NLRP3 were detected in synovium of OA patients by immunohistochemistry. Lipopolysaccharides (LPS) stimulated the expression of active IL-1β mRNA in OA fibroblasts and combination of LPS, and adenosine triphosphate increased more the expression of active IL-1β in OA fibroblasts. The level of IL-1β was measured by western blot and ELISA assay. NLRP3 inflammasomes complex were measured by western blot. SIRT1 did not inhibit expression of NLRP3 inflammasome. So caspase-1, apoptotic speck-like protein containing a caspase recruitment domain (ASC) and NLRP3 protein were expressed in OA fibroblasts. But SIRT1 suppressed activation of IL-1β by inhibiting activity of caspase-1 via NLRP3 inflammasome in OA fibroblasts under LPS plus ATP stimulation. These results suggest that SIRT1 is a modulator of NLRP3 inflammasomes in OA fibroblasts and ameliorate IL-1β, so expression of SIRT1 in OA fibroblast may be a potential strategy for OA inflammation treatment.

Keywords: osteoarthritis, inflammasome, SIRT1, IL-1beta

Procedia PDF Downloads 188

Authors: Suhadiyana Hanapi, Alhassan Salami Tijani, W. A. N Wan Mohamed

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In this paper, a prototype PEM fuel cell vehicle integrated with a 1 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack as a main power sources has been developed for a lightweight cruising vehicle. The test vehicle is equipped with a PEM fuel cell system that provides electric power to a brushed DC motor. This vehicle was designed to compete with industrial lightweight vehicle with the target of consuming least amount of energy and high performance. Individual variations in driving style have a significant impact on vehicle energy efficiency and it is well established from the literature. The primary aim of this study was to assesses the power and fuel consumption of a hydrogen fuel cell vehicle operating at three difference driving technique (i.e. 25 km/h constant speed, 22-28 km/h speed range, 20-30 km/h speed range). The goal is to develop the best driving strategy to maximize performance and minimize fuel consumption for the vehicle system. The relationship between power demand and hydrogen consumption has also been discussed. All the techniques can be evaluated and compared on broadly similar terms. Automatic intelligent controller for driving prototype fuel cell vehicle on different obstacle while maintaining all systems at maximum efficiency was used. The result showed that 25 km/h constant speed was identified for optimal driving with less fuel consumption.

Keywords: prototype fuel cell electric vehicles, energy efficient, control/driving technique, fuel economy

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Authors: Ikram Kamal, Mohamed Blaghen

Abstract:

Biosurfactants are amphiphilic biological compounds consisting of hydrophobic and hydrophilic domains produced extracellularly or as part of the cell membrane by a variety of yeast, bacteria and filamentous fungi. Biosurfactant applications in the environmental industries are promising due to their biodegradability, low toxicity, and effectiveness in enhancing biodegradation and solubilization of low solubility compounds. Currently, the main application is for enhancement of oil recovery and hydrocarbon bioremediation due to their biodegradability and low critical micelle concentration (CMC). The use of biosurfactants has also been proposed for various industrial applications, such as in food additives, cosmetics, detergent formulations and in combinations with enzymes for wastewater treatment. In this study, we have investigated the potential of bacterial strains: Mannheimia haemolytica, Burkholderia cepacia and Serratia ficaria were collected aseptically from the lagoon Marchika (water and soil) in Nador, Morocco; for the production of biosurfactants. This study also aimed to optimize the biosurfactant production process by changing the variables that influence the type and amount of biosurfactant produced by these microorganisms such as: carbon sources and also other physical and chemical parameters such as temperature and pH. Emulsification index, methylene blue test, and thin layer chromatography (TLC) revealed the ability of strains used in this study to produce compounds that could emulsify gasoline. In addition, a GC/MS was used to separate and identify different biosurfactants purified.

Keywords: biosurfactants, Mannheimia haemolytica, biodegradability, Burkholderia cepacia, Serratia ficaria

Procedia PDF Downloads 249

Authors: Erol Bayraktarov, Asya Ilgun, Thomas Schickl, Alexandre Campo, Nicolis Stamatios

Abstract:

Traditional means of harvesting honey are often stressful for honeybees. Each time honey is collected a portion of the colony can die. In consequence, the colonies’ resilience to environmental stressors will decrease and this ultimately contributes to the global problem of honeybee colony losses. As part of the project HIVEOPOLIS, we design and build a different kind of beehive, incorporating technology to reduce negative impacts of beekeeping procedures, including honey harvesting. A first step in maintaining more sustainable honey harvesting practices is to design honey storage frames that can automate the honey collection procedures. This way, beekeepers save time, money, and labor by not having to open the hive and remove frames, and the honeybees' nest stays undisturbed.This system shows promising features, e.g., high reliability which could be a key advantage compared to current honey harvesting technologies.Our original concept of fractional honey harvesting has been to encourage the removal of honey only from "safe" locations and at levels that would leave the bees enough high-nutritional-value honey. In this abstract, we describe the current state of our honey harvester, its technology and areas to improve. The honey harvester works by separating the honeycomb cells away from the comb foundation; the movement and the elastic nature of honey supports this functionality. The honey sticks to the foundation, because of the surface tension forces amplified by the geometry. In the future, by monitoring the weight and therefore the capped honey cells on our honey harvester frames, we will be able to remove honey as soon as the weight measuring system reports that the comb is ready for harvesting. Higher viscosity honey or crystalized honey cause challenges in temperate locations when a smooth flow of honey is required. We use resistive heaters to soften the propolis and wax to unglue the moving parts during extraction. These heaters can also melt the honey slightly to the needed flow state. Precise control of these heaters allows us to operate the device for several purposes. We use ‘Nitinol’ springs that are activated by heat as an actuation method. Unlike conventional stepper or servo motors, which we also evaluated throughout development, the springs and heaters take up less space and reduce the overall system complexity. Honeybee acceptance was unknown until we actually inserted a device inside a hive. We not only observed bees walking on the artificial comb but also building wax, filling gaps with propolis and storing honey. This also shows that bees don’t mind living in spaces and hives built from 3D printed materials. We do not have data yet to prove that the plastic materials do not affect the chemical composition of the honey. We succeeded in automatically extracting stored honey from the device, demonstrating a useful extraction flow and overall effective operation this way.

Keywords: honey harvesting, honeybee, hiveopolis, nitinol

Procedia PDF Downloads 99

Authors: Olusegun Solomon

Abstract:

This paper describes the concept for the design and maximum power point tracking control for an interior permanent magnet synchronous generator wind turbine system. Two design concepts are compared to outline the effect of magnet design on the performance of the interior permanent magnet synchronous generator. An approximate model that includes the effect of core losses has been developed for the machine to simulate the dynamic performance of the wind energy system. An algorithm for Maximum Power Point Tracking control is included to describe the process for maximum power extraction.

Keywords: permanent magnet synchronous generator, wind power system, wind turbine

Procedia PDF Downloads 210

Authors: Young Sik Kim, Tae Kwon Ha

Abstract:

This article considers the problems of economic growth and Russian energy strategy. Also in this paper, the issues related to the economic growth prospects of Russian were discussed. Russian energy strategy without standing Russia`s stature in global energy markets, at the current production and extraction rates, will not be able to sustain its own production as well as fulfil its energy strategy. Indeed, Russia’s energy sector suffers from a chronic lack of investments which are necessary to modernize its energy supply system. In recent years, especially since the international financial crisis, Russia-EU energy cooperation has made substantive progress. Recently the break-through progress has been made, resulting mainly from long-term contributing factors between the countries and recent international economic and political situation changes. Analytical material presented in the article is intended for a more detailed or substantive analysis related to foreign economic relations of the countries and Russia as well.

Keywords: Russia, energy strategy, economic growth, cooperation

Procedia PDF Downloads 304

Authors: Mohammad Hossein Modarressi, Mozhgan Mondeali, Khabat Barkhordari, Ali Etemadi

Abstract:

The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant concerns worldwide due to its catastrophic effects on public health. The SARS-CoV-2 infection is initiated with the binding of the receptor-binding domain (RBD) in its spike protein to the ACE2 receptor in the host cell membrane. Due to the error-prone entity of the viral RNA-dependent polymerase complex, the virus genome, including the coding region for the RBD, acquires new mutations, leading to the appearance of multiple variants. These variants can potentially impact transmission, virulence, antigenicity and evasive immune properties. S477N mutation located in the RBD has been observed in the SARS-CoV-2 omicron (B.1.1. 529) variant. In this study, we investigated the consequences of S477N mutation at the molecular level using computational approaches such as molecular dynamics simulation, protein-protein interaction analysis, immunoinformatics and free energy computation. We showed that displacement of Ser with Asn increases the stability of the spike protein and its affinity to ACE2 and thus increases the transmission potential of the virus. This mutation changes the folding and secondary structure of the spike protein. Also, it reduces antibody neutralization, raising concern about re-infection, vaccine breakthrough and therapeutic values.

Keywords: S477N, COVID-19, molecular dynamic, SARS-COV2 mutations

Procedia PDF Downloads 161

Authors: Sree Vennela P., V. Samyuktha Bhardwaj

Abstract:

Hyponatremia is an electrolyte disturbance in which the sodium ion concentration in the serum is lower than normal. Sodium is the dominant extracellular cation (positive ion) and cannot freely cross from the interstitial space through the cell membrane, into the cell. Its homeostasis (stability of concentration) inside the cell is vital to the normal function of any cell. Normal serum sodium levels are between 135 and 145 mEq/L. Hyponatremia is defined as a serum level of less than 135 mEq/L and is considered severe when the serum level is below 125 mEq/L. In the vast majority of cases, Hyponatremia occurs as a result of excess body water diluting the serum sodium (salt level in the blood). Hyponatremia is often a complication of other medical illnesses in which excess water accumulates in the body at a higher rate than can be excreted (for example in congestive heart failure, syndrome of inappropriate antidiuretic hormone, SIADH, or polydipsia). Sometimes it may be a result of over-hydration (drinking too much water).Lack of sodium (salt) is very rarely the cause of Hyponatremia, although it can promote Hyponatremia indirectly. In particular, sodium loss can lead to a state of volume depletion (loss of blood volume in the body), with volume depletion serving as a signal for the release of ADH (anti-diuretic hormone). As a result of ADH-stimulated water retention (too much water in the body), blood sodium becomes diluted and Hyponatremia results.

Keywords: Tolvaptan, hyponatremia, syndrome of insufficient anti diuretic hormone (SIADH), euvolemic hyponatremia

Procedia PDF Downloads 252

Authors: P. Subbuthai, S. Muruganand

Abstract:

Diabetic Retinopathy is one of the complicated diseases and it is caused by the changes in the blood vessels of the retina. Extraction of retina image through Fundus camera sometimes produced poor contrast and noises. Because of this noise, detection of blood vessels in the retina is very complicated. So preprocessing is needed, in this paper, a novel algorithm is implemented to remove the noisy pixel in the retina image. The proposed algorithm is Extended Median Filter and it is applied to the green channel of the retina because green channel vessels are brighter than the background. Proposed extended median filter is compared with the existing standard median filter by performance metrics such as PSNR, MSE and RMSE. Experimental results show that the proposed Extended Median Filter algorithm gives a better result than the existing standard median filter in terms of noise suppression and detail preservation.

Keywords: fundus retina image, diabetic retinopathy, median filter, microaneurysms, exudates

Procedia PDF Downloads 330

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 32

Authors: Kyung-Soon Choi, Ji-Young Hwang, Young-Hee Pyo

Abstract:

Vinegars have been used as an alternative remedy for treating gout, but the scientific basis remains to be elucidated. In this study, acetic acid fermentation was applied for the first time to Monascus-fermented soybeans to examine its effect on the bioactive components together with the xanthine oxidase inhibitory (XOI) activity of the soy vinegar. The content of total phenols (0.47~0.97 mg gallic acid equivalents/mL) and flavonoids (0.18~0.39 mg quercetin equivallents/mL) were spectrophotometrically determined, and the content of organic acid (10.22~59.76 mg/mL) and isoflavones (6.79~7.46 mg/mL) were determined using HPLC-UV. The analytical method for ubiquinones (0.079~0.276 μg/mL) employed saponification before solvent extraction and quantification using LC-MS. Soy vinegar also showed significant XOI (95.3%) after 20 days of acetic acid fermentation at 30 °C. The results suggest that soy vinegar has potential as a novel medicinal food.

Keywords: acetic acid fermentation, bioactive component, soy vinegar, xanthine oxidase inhibitory activity

Procedia PDF Downloads 376

Authors: Luc Conti, Dimitry Dumont-Fillon, Harald van Lintel, Eric Chappel

Abstract:

Flow control valves comprise a silicon flexible membrane that deflects against a substrate, usually made of glass, containing pillars, an outlet hole, and anti-stiction features. However, there is a strong interest in using silicon instead of glass as substrate material, as it would simplify the process flow by allowing the use of well controlled anisotropic etching. Moreover, specific devices demanding a bending of the substrate would also benefit from the inherent outstanding mechanical strength of monocrystalline silicon. Unfortunately, direct Si-Si bonding is not easily achieved with highly structured wafers since residual stress may prevent the good adhesion between wafers. Using a thermoplastic polymer, such as parylene, as intermediate layer is not well adapted to this design as the wafer-to-wafer alignment is critical. An alternative anodic bonding method using an intermediate borosilicate layer has been successfully tested. This layer has been deposited onto the silicon substrate. The bonding recipe has been adapted to account for the presence of the SOI buried oxide and intermediate glass layer in order not to exceed the breakdown voltage. Flow control valves dedicated to infusion of viscous fluids at very high pressure have been made and characterized. The results are compared to previous data obtained using the standard anodic bonding method.

Keywords: anodic bonding, evaporated glass, flow control valve, drug delivery

Procedia PDF Downloads 194

Authors: Xingguo Feng, Hui Zhou, Kaifeng Zhang, Zhao Jiang, Hanjun Hu, Jun Zheng, Hong Hao

Abstract:

TiN and TiC films have been prepared on Ti6Al4V alloy substrates by plasma-based ion implantation. The effect of N+C and Ti+N hybrid ion implantation at 50 kV, and Ti+C hybrid ion implantation at 20 kV, 35 kV and 50 kV extraction voltages on mechanical properties at a dose of 2×10¹⁷ ions / cm² was studied. The chemical states and microstructures of the implanted samples were investigated using X-ray photoelectron (XPS), and X-ray diffraction (XRD), together with the mechanical and tribological properties of the samples were characterized using nano-indentation and ball-on-disk tribometer. It was found that the modified layer by Ti+C implanted at 50 kV was composed of mainly TiC and Ti-O bond and the layer of Ti+N implanted at 50 kV was observed to be TiN and Ti-O bond. Hardness tests have shown that the hardness values for N+C, Ti+N, and Ti+C hybrid ion implantation samples were much higher than the un-implanted ones. The results of wear tests showed that both Ti+C and Ti+N ion implanted samples had much better wear resistance compared un-implanted sample. The wear rate of Ti+C implanted at 50 kV sample was 6.7×10⁻⁵mm³ / N.m, which was decreased over one order than unimplanted samples.

Keywords: plasma ion implantation, x-ray photoelectron (XPS), hardness, wear

Procedia PDF Downloads 398

Authors: Boussoualim Nacira, Aklouf Youcef

Abstract:

Software as a Service (SaaS) is a software delivery paradigm in which the product is not installed on-premise, but it is available on Internet and Web. The customers do not pay to possess the software itself but rather to use it. This concept of pay per use is very attractive. Hence, we see increasing number of organizations adopting SaaS. However, each customer is unique, which leads to a very large variation in the requirements off the software. As several suppliers propose SaaS products, the choice of this latter becomes a major issue. When multiple criteria are involved in decision making, we talk about a problem of «Multi-Criteria Decision-Making» (MCDM). Therefore, this paper presents a method to help customers to choose a better SaaS product satisfying most of their conditions and alternatives. Also, we know that a good method of adaptive selection should be based on the correct definition of the different parameters of choice. This is why we started by extraction and analysis the various parameters involved in the process of the selection of a SaaS application.

Keywords: cloud computing, business operation, Multi-Criteria Decision-Making (MCDM), Software as a Service (SaaS)

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

Abstract:

Epilepsy is a common neurological disorders characterized by sudden recurrent seizures. Electroencephalogram (EEG) is widely used to diagnose possible epileptic seizure. Many research works have been devoted to predict epileptic seizure by analyzing EEG signal. Seizure prediction by analyzing EEG signals are challenging task due to variations of brain signals of different patients. In this paper, we propose a new approach for feature extraction based on phase correlation in EEG signals. In phase correlation, we calculate relative change between two consecutive segments of an EEG signal and then combine the changes with neighboring signals to extract features. These features are then used to classify preictal/ictal and interictal EEG signals for seizure prediction. Experiment results show that the proposed method carries good prediction rate with greater consistence for the benchmark data set in different brain locations compared to the existing state-of-the-art methods.

Keywords: EEG, epilepsy, phase correlation, seizure

Procedia PDF Downloads 300

Authors: Mehmet Ali Topçu, Aydın Ruşen

Abstract:

Çinkur is the only plant in Turkey that produces zinc from primary ore containing zinc carbonate from its establishment until 1997. After this year, zinc concentrate coming from Iran was used in this plant. Therefore, there are two different leach residues namely Turkish leach residue (TLR) and Iranian leach residue (ILR), in Çinkur stock piles. This paper describes zinc recovery by sulphuric acid (H2SO4) treatment for each leach residue and includes comparison of blended of TLR and ILR. Before leach experiments; chemical, mineralogical and thermal analysis of three different leach residues was carried out by using atomic absorption spectrometry (AAS), X-Ray diffraction (XRD) and differential thermal analysis (DTA), respectively. Leaching experiments were conducted at optimum conditions; 100 oC, 150 g/L H2SO4 and 2 hours. In the experiments, stirring rate was kept constant at 600 r/min which ensures complete mixing in leaching solution. Results show that zinc recovery for Iranian LR was higher than Turkish LR due to having different chemical composition from each other.

Keywords: hydrometallurgy, leaching, metal extraction, metal recovery

Procedia PDF Downloads 343

Authors: D. Pugazhenthi, B. Sree Vidya

Abstract:

Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

Procedia PDF Downloads 246

Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

Abstract:

Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: basketball, deep learning, feature extraction, single-camera, tracking

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Authors: Boris G. German, Edward Jiménez, Sebastián Espinoza, Andrés G. Chico, Ricardo A. Narváez

Abstract:

The unique flora and fauna of The Galapagos Islands has leveraged a tourism-driven growth in the islands. Nonetheless, such development is energy-intensive and requires thousands of gallons of diesel each year for thermoelectric electricity generation. The needed transport of fossil fuels from the continent has generated oil spillages and affectations to the fragile ecosystem of the islands. The Zero Fossil Fuels initiative for The Galapagos proposed by the Ecuadorian government as an alternative to reduce the use of fossil fuels in the islands, considers the replacement of diesel in thermoelectric generators, by Jatropha curcas vegetable oil. However, the Jatropha oil supply cannot entirely cover yet the demand for electricity generation in Galapagos. Within this context, the present work aims to provide an optimization model that can be used as a selection criterion for approving new Jatropha Curcas collection points in rural areas of Manabi-Ecuador. For this purpose, existing Jatropha collection points in Manabi were grouped under three regions: north (7 collection points), center (4 collection points) and south (9 collection points). Field work was carried out in every region in order to characterize the collection points, to establish local Jatropha supply and to determine transportation costs. Data collection was complemented using GIS software and an objective function was defined in order to determine the profit associated to Jatropha oil production. The market price of both Jatropha oil and residual cake, were considered for the total revenue; whereas Jatropha price, transportation and oil extraction costs were considered for the total cost. The tonnes of Jatropha fruit and seed, transported from collection points to the extraction plant, were considered as variables. The maximum and minimum amount of the collected Jatropha from each region constrained the optimization problem. The supply chain was optimized using linear programming in order to maximize the profits. Finally, a sensitivity analysis was performed in order to find a profit-based criterion for the acceptance of future collection points in Manabi. The maximum profit reached a value of $ 4,616.93 per year, which represented a total Jatropha collection of 62.3 tonnes Jatropha per year. The northern region of Manabi had the biggest collection share (69%), followed by the southern region (17%). The criteria for accepting new Jatropha collection points in the rural areas of Manabi can be defined by the current maximum profit of the zone and by the variation in the profit when collection points are removed one at a time. The definition of new feasible collection points plays a key role in the supply chain associated to Jatropha oil production. Therefore, a mathematical model that assists decision makers in establishing new collection points while assuring profitability, contributes to guarantee a continued Jatropha oil supply for Galapagos and a sustained economic growth in the rural areas of Ecuador.

Keywords: collection points, Jatropha curcas, linear programming, supply chain

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Authors: Sawsan Dacrory, Hussein Abou-Yousef, Samir Kamel, Ragab E. Abou-Zeid, Mohamed S. Abdel-Aziz, Mohamed Elbadry

Abstract:

A considerable amount of lignocellulosic by-product could be obtained from olive pulp during olive oil extraction industry. The major constituents of the olive pulp are husks and seeds. The separation of each portion of olive pulp (seeds and husks) was carried out by water flotation where seeds were sediment in the bottom. Both seeds and husks were dignified by 15% NaOH followed by complete lignin removal by using sodium chlorite in acidic medium. The isolated holocellulose, α-cellulose, hydrogel and CMC which prepared from cellulose of both seeds and husk fractions were characterized by FTIR and SEM. The present study focused on the investigation of the chemical components of the lignocellulosic fraction of olive pulp. Biofunctionlization of hydrogel was achieved through loading of silver nanoparticles AgNPs in to the prepared hydrogel. The antimicrobial activity of the loaded silver hydrogel against G-ve, and G+ve, and candida was demonstrated.

Keywords: cellulose, carboxymethyle cellulose, olive pulp, hydrogel

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Authors: Abujnah Dukali

Abstract:

Natural honey was assessed in cell culture system for its anticancer activity. Human leukemic cell line HL 60 was treated with honey and cultured for 5 days and cytotoxicity was calculated by MTT assay. Honey showed cytotoxicity with CC50 value of 174.20 µg/ml. Radical modulation activities was assessed by lipid peroxidation assay using egg lecithin. Honey showed antioxidant activity with EC50 value of 159.73 µg/ml. In addition, treatment with HL60 cells also resulted in nuclear DNA fragmentation, as seen in agarose gel electrophoresis. This is a hallmark of cells undergoing apoptosis. Confirmation of apoptosis was performed by staining the cells with Annexin V and FACS analysis. Apoptosis is an active, genetically regulated disassembly of the cell form within. Disassembly creates changes in the phospholipid content of the cytoplasmic membrane outer leaflet. Phosphatidylserine (PS) is translocated from the inner to the outer surface of the cell for phagocytic cell recognition. The human anticoagulant, annexin V, is a Ca2+-dependent phospholipid protein with a high affinity for PS. Annexin V labeled with fluorescein can identify apoptotic cells in the population It is a confirmatory test for apoptosis. Annexin V-positive cells were defined as apoptotic cells. Since honey shows both antioxidant activity and cytotoxicity at almost the same concentration, it can prevent the free radical induced cancer as prophylactic agent and kill the cancer cells by apoptotic process as a chemotherapeutic agent. Everyday intake of honey can prevent the cancer induction.

Keywords: anticancer, cells, DNA, honey

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Authors: Mahdiye Khorasani, Arjun Vijay, Ali Mashayekh, Christian Trapp

Abstract:

The performance of Proton Exchange Membrane Fuel Cell (PEMFC) is highly dependent on the pressure and mass flow of media (Hydrogen and air) throughout the cells and the stack. Higher pressure, on the one hand, results in higher output power of the stack but, on the other hand, increases the electrical power demand of the compressor. In this work, a simulation model of a PEMFC system for vehicle and airplane applications is developed. With this new model, the effect of different pressures and air mass flow rates are investigated to discover the optimum operating point in a PEMFC system, and innovative operation strategies are implemented to optimize reactants flow while minimizing electrical power demand of the compressor for optimum performance. Additionally, a fuel cell system test bench is set up, which contains not only all the auxiliary components for conditioning the gases, reactants, and flows but also a dynamic titling table for testing different orientations of the stack to simulate the flight conditions during take-off and landing and off-road-vehicle scenarios. The results of simulation will be tested and validated on the test bench for future works.

Keywords: air mass flow effect, optimization of operation, pressure effect, PEMFC system, PEMFC system simulation

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Authors: Sadia Munir, Diana White, Aya Albahri, Pratiwi Hastania, Eltahir Mohamed, Mahmood Khan, Fathima Mohamed, Ayat Kadhi, Haila Saleem

Abstract:

Preeclampsia is a major complication of pregnancy. Prediction and management of preeclampsia is a challenge for obstetricians. To our knowledge, no major progress has been achieved in the prevention and early detection of preeclampsia. There is very little known about the clear treatment path of this disorder. Preeclampsia puts both mother and baby at risk of several short term- and long term-health problems later in life. There is huge health service cost burden in the health care system associated with preeclampsia and its complications. Preeclampsia is divided into two different types. Early onset preeclampsia develops before 34 weeks of gestation, and late onset develops at or after 34 weeks of gestation. Different genetic and environmental factors, prognosis, heritability, biochemical and clinical features are associated with early and late onset preeclampsia. Prevalence of preeclampsia greatly varies all over the world and is dependent on ethnicity of the population and geographic region. To authors best knowledge, no published data on preeclampsia exist in Qatar. In this study, we are reporting the incidence of preeclampsia in Qatar. The purpose of this study is to compare the incidence and risk factors of both early onset and late onset preeclampsia in Qatar. This retrospective longitudinal cohort study was conducted using data from the hospital record of Women’s Hospital, Hamad Medical Corporation (HMC), from May 2014-May 2016. Data collection tool, which was approved by HMC, was a researcher made extraction sheet that included information such as blood pressure during admission, socio demographic characteristics, delivery mode, and new born details. A total of 1929 patients’ files were identified by the hospital information management when they apply codes of preeclampsia. Out of 1929 files, 878 had significant gestational hypertension without proteinuria, 365 had preeclampsia, 364 had severe preeclampsia, and 188 had preexisting hypertension with superimposed proteinuria. In this study, 78% of the data was obtained by hospital electronic system (Cerner) and the remaining 22% was from patient’s paper records. We have gone through detail data extraction from 560 files. Initial data analysis has revealed that 15.02% of pregnancies were complicated with preeclampsia from May 2014-May 2016. We have analyzed difference in the two different disease entities in the ethnicity, maternal age, severity of hypertension, mode of delivery and infant birth weight. We have identified promising differences in the risk factors of early onset and late onset preeclampsia. The data from clinical findings of preeclampsia will contribute to increased knowledge about two different disease entities, their etiology, and similarities/differences. The findings of this study can also be used in predicting health challenges, improving health care system, setting up guidelines, and providing the best care for women suffering from preeclampsia.

Keywords: preeclampsia, incidence, risk factors, maternal

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