Search results for: deep injection well

Authors: Madhujit Deb, G. R. K. Sastry, R. S. Panua, Rahul Banerjee, P. K. Bose

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The present work attempts to investigate the combustion, performance and emission characteristics of an existing single-cylinder four-stroke compression-ignition engine operated in dual-fuel mode with hydrogen as an alternative fuel. Environmental concerns and limited amount of petroleum fuels have caused interests in the development of alternative fuels like hydrogen for internal combustion (IC) engines. In this experimental investigation, a diesel engine is made to run using hydrogen in dual fuel mode with diesel, where hydrogen is introduced into the intake manifold using an LPG-CNG injector and pilot diesel is injected using diesel injectors. A Timed Manifold Injection (TMI) system has been developed to vary the injection strategies. The optimized timing for the injection of hydrogen was 100 CA after top dead center (ATDC). From the study it was observed that with increasing hydrogen rate, enhancement in brake thermal efficiency (BTHE) of the engine has been observed with reduction in brake specific energy consumption (BSEC). Furthermore, Soot contents decrease with an increase in indicated specific NOx emissions with the enhancement of hydrogen flow rate.

Keywords: diesel engine, hydrogen, BTHE, BSEC, soot, NOx

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Authors: A. Shabib-Asl, M. Abdalla Ayoub Mohammed, A. F. Alta’ee, I. Bin Mohd Saaid, P. Paulo Jose Valentim

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In the last few decades, much focus has been placed on enhancing oil recovery from existing fields. This is accomplished by the study and application of various methods. As for recent cases, the study of fluid mobility control and sweep efficiency in gas injection process as well as water alternating gas (WAG) method have demonstrated positive results on oil recovery and thus gained wide interest in petroleum industry. WAG injection application results in an increased oil recovery. Its mechanism consists in reduction of gas oil ratio (GOR). However, there are some problems associated with this which includes poor volumetric sweep efficiency due to its low density and high mobility when compared with oil. This has led to the introduction of foam assisted water alternating gas (FAWAG) technique, which in contrast with WAG injection, acts in improving the sweep efficiency and reducing the gas oil ration therefore maximizing the production rate from the producer wells. This paper presents a comprehensive review of FAWAG process from perspective of Snorre field experience. In addition, some comparative results between FAWAG and the other EOR methods are presented including their setbacks. The main aim is to provide a solid background for future laboratory research and successful field application-extend.

Keywords: GOR, mobility ratio, sweep efficiency, WAG

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Ahmed Gaber Abdel Raheem, Nashwa Ahmed Mohamed

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Introduction: Sensorineural hearing loss (SNHL) is largely caused by the degeneration of the cochlea. Therapeutic options for SNHL are limited to hearing aids and cochlear implants. The cell transplantation approach to the regeneration of hair cells has gained considerable attention because stem cells are believed to accumulate in the damaged sites and have the potential for the repair of damaged tissues. The aim of the work: was to assess the use of bone marrow transplantation in repair of damaged inner ear hair cells in rats after the damage had been inflicted by Amikacin injection. Material and Methods: Thirty albino rats were used in this study. They were divided into three groups. Each group ten rats. Group I: used as control. Group II: Were given Amikacin- intratympanic injection till complete loss of hearing function. This could be assessed by Distortion product Otoacoustic Emission (DPOAEs) and / or auditory brain stem evoked potential (ABR). GroupIII: were given intra-peritoneal injection of bone marrow stem cell after complete loss of hearing caused by Amikacin. Clinical assessment was done using DPOAEs and / or auditory brain stem evoked potential (ABR), before and after bone marrow injection. Histological assessment of the inner ear was done by light and electron microscope. Also, Detection of stem cells in the inner ear by immunohistochemistry. Results: Histological examination of the specimens showed promising improvement in the structure of cochlea that may be responsible for the improvement of hearing function in rats detected by DPOAEs and / or ABR. Conclusion: Bone marrow stem cells transplantation might be useful for the treatment of SNHL.

Keywords: amikacin, hair cells, sensorineural hearing loss, stem cells

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Jun Ming Moey, Zhiyaun Chen, David Nicholson

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Bad actors are often hard to detect in data that imprints their behaviour patterns because they are comparatively rare events embedded in non-bad actor data. An unsupervised machine learning framework is applied here to detect bad actors in financial crime datasets that record millions of transactions undertaken by hundreds of actors (<0.01% bad). Specifically, the framework combines ‘shallow’ (PCA, Isolation Forest) and ‘deep’ (Autoencoder) methods to detect outlier patterns. Detection performance analysis for both the individual methods and their combination is reported.

Keywords: detection, machine learning, deep learning, unsupervised, outlier analysis, data science, fraud, financial crime

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Authors: Haozhe Xiang

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With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

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Authors: Fernanda Pinheiro Martins, Pedro Teixeira Lacava

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The objective of this research is to analyze the effects of different spark plug conditions in engine-like conditions by applying computational fluid dynamics analysis. The 3D models applied consist of 3-Zones Extended Coherent Flame (ECFM-3Z) and Imposed Stretch Spark Ignition Model (ISSIM), respectively, for the combustion and the spark plug modelling. For this study, it was applied direct injection fuel system in a single cylinder engine operating with E0. The application of realistic operating conditions (load and speed) to the different cases studied will provide a deeper understanding of the effects of the spark plug gap, a result of parts outwearing in most of the cases, to the development of the combustion in engine-like conditions.

Keywords: engine, CFD, direct injection, combustion, spark plug

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Authors: Wen Luo, Phil J. Vardon, Anne-Catherine Dieudonne

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One key process that partly controls the success of geothermal projects is fluid reinjection, which benefits in dealing with waste water, maintaining reservoir pressure, and supplying heat-exchange media, etc. Thus, sustaining the injectivity is of great importance for the efficiency and sustainability of geothermal production. However, the injectivity is sensitive to the reinjection process. Field experiences have illustrated that the injectivity can be damaged or improved. In this paper, the focus is on how the injectivity is improved. Since the injection pressure is far below the formation fracture pressure, hydraulic fracturing cannot be the mechanism contributing to the increase in injectivity. Instead, thermal stimulation has been identified as the main contributor to improving the injectivity. For low-enthalpy geothermal reservoirs, which are not fracture-controlled, thermal fracturing, instead of thermal shearing, is expected to be the mechanism for increasing injectivity. In this paper, field data from the sedimentary low-enthalpy geothermal reservoirs in the Netherlands were analysed to show the occurrence of thermal fracturing due to the cooling shock during reinjection. Injection data were collected and compared to show the effects of the thermal fractures on injectivity. Then, a thermo-hydro-mechanical (THM) model for the near field formation was developed and solved by finite element method to simulate the observed thermal fractures. It was then compared with the HM model, decomposed from the THM model, to illustrate the thermal effects on thermal fracturing. Finally, the effects of operational parameters, i.e. injection temperature and pressure, on the changes in injectivity were studied on the basis of the THM model. The field data analysis and simulation results illustrate that the thermal fracturing occurred during reinjection and contributed to the increase in injectivity. The injection temperature was identified as a key parameter that contributes to thermal fracturing.

Keywords: injectivity, reinjection, thermal fracturing, thermo-hydro-mechanical model

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Authors: Gaokai Liu

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Automatic defect detection for nanomaterial images is widely required in industrial scenarios. Deep learning approaches are considered as the most effective solutions for the great majority of image-based tasks. In this paper, an edge guidance network for defect segmentation is proposed. First, the encoder path with multiple convolution and downsampling operations is applied to the acquisition of shared features. Then two decoder paths both are connected to the last convolution layer of the encoder and supervised by the edge and segmentation labels, respectively, to guide the whole training process. Meanwhile, the edge and encoder outputs from the same stage are concatenated to the segmentation corresponding part to further tune the segmentation result. Finally, the effectiveness of the proposed method is verified via the experiments on open nanofibrous datasets.

Keywords: deep learning, defect detection, image segmentation, nanomaterials

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Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

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In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

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Authors: Rania Hanafi Mahmoud Said, Rasha Mohamed Taha

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Background: The use of nanoparticles for medication delivery offers the possibility of avoiding the negative effects of systemic antibiotic dosing as well as antibiotic resistance in bacteria. Aim of the study: The goal of this study was to see the efficiency of local administration of tetracycline loaded on nano chitosan in the treatment of the induced infection of the albino rats gingiva with Porphyromonas gingivalis through Immunohistochemical localization of Interleukin-1beta (IL-1β) as a proinflammatory cytokine.Material and methods: Fifty adult male albino rats 150 - 180 grams body weight used in this investigation. Any changes in rats’ weights were detected. The male albino rats were divided haphazardly into five groups as Group I involved ten rats; they served as a normal negative control group. Group II involved ten rats; they were infected once with P.gingivalis that was injected into the interdental gingiva. Group III involved ten rats; they were subjected to the same procedure as group II and then to daily injection at the site of infection with diluted tetracycline powder. Group IV involved ten rats; they were subjected to the same procedure as group II and then to daily injection of nano Chitosan at the site of injection. Group V involved ten rats; they were subjected to the same procedure as group II and then to daily injection of tetracycline loaded on nano Chitosan at the site of injection. After rats had been euthanized, the extraction and preparation of their gingiva were carried out in order to examine histologically and immunohistochemically. Results: The light microscopic results of groups II, III, and IV showed degeneration represented by swollen epithelial cells, collagen fibers dissociation of the connective tissue of lamina propria, and areas of basement membrane discontinuation, while groups I and V showed an almost normal histological picture of gingival tissue. Immunohistochemical results showed a significant difference in Group II and III when compared to control. No significant difference appears in group V when compared to the control (group I). Conclusion: Using nanochitosan as a carrier for tetracycline is a new technology to get over the increasing resistance of tetracycline.

Keywords: immunohistochemistry, P.gingivalis, nano-chitosan, tetracycline, periodontitis

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Authors: Seyedeh Zeinab Peighambarzadeh, Mehdi Tavana

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Cataract is the most common cause of blindness worldwide and its incidence will increase as the World’s population ages. Even in modern ophthalmology, there is no effective medical treatment for cataract except surgery. Development of a drug which could prevent or delay the onset of cataract will lessen this burden and reduce the number of blind patients waiting for cataract surgery. This study was undertaken to evaluate the protective effect of vitamin E on Selenite-induced Cataract in Sprague-dawely rats. Cataracts were induced in rats by administration of sodium selenite. On postpartum day ten, in group I, saline was injected subcutaneously. Group II rat pups received subcutaneous injection of vitamin E (60mg/kg B.W.) at day 8 postpartum and every other day thereafter. Group III and IV rat pups received a subcutaneous injection of sodium selenite (13mg/kg B.W.) at day 10 postpartum. Group IV also received subcutaneous injection of vitamin E (60mg/kg B.W.) at day 8 postpartum and every other day thereafter. The development of cataract in rats was assessed clinically by slit-lamp biomicroscope from day 14 up to postpartum day 28. After sacrifice, extricated pup lenses were analyzed for total and soluble protein concentrations and eletrophoretic pattern (SDS-PAGE). There was no opacification of lens in Group I and II. There was mature cataract in 95% of Group III. In group IV, 55% of rats developed sub capsular or cortical cataract. Cataractous and biochemical changes of the crystalline lens proteins due to selenite can be retard or prevented by vitamin E.

Keywords: preventive effect, selenite-induced cataract, vitamin E, rat

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Authors: Agoubi Belgacem, Adel Kharroubi

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Geothermal groundwater is the main water source to supply various sectors in El Hamma city, southeastern Tunisia. This region was long the destination of thousands of people from Tunisia and neighboring countries for care and bathing. The main objective of this study is to understand the groundwater mineralization origins and factors that control. The second goal is the appraisal of radon in geothermal groundwater in the study area. For this aim, geothermal groundwater was sampled and collected from different locations (thermal baths and deep wells). Physical parameters were measured and major ions were analyzed. Results reveal three water types. The water first type has Na-Mg-Ca-SO4-Cl facies and T>55°C. The second water type dominated by Na-Ca-Cl-SO4 facies with a temperature < 45 °C. However the third water type is dominated by Ca-SO4-Na-Cl-Mg. The three water types may be controlled by depth and geology. The first represent groundwater from deep aquifer (lower cretaceous), the second type was the shallow aquifer and the first is mixed water from deep and shallow water with a temperature ranging from 45 to 55°C. Measured Radon shows that shallow aquifer has a higher 222Rn concentration (677 to 2903 Bq.m-3) than deep water (203 to 1100 Bq.m-3). R-222 in El Hamma thermal aquifer was controlled by structures, porosity and permeability of aquifers. Geostatistical analyses of hydrogeological data and radon activities confirm the vertical flow and communication between deep and shallow aquifers through vertical faults system.

Keywords: Radon-222, geothermal, water, environment, Tunisia

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Authors: Mehdi Tavana, Seyedeh Zeinab Peighambarzadeh

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Excretory urography is used for morphologic and especially functional studies of the urinary tracts. There are many indications for excretory urography in humans and animals. Intravenous urography is the most practical method, other urography techniques were manipulated because of difficulties for finding veins in small size of the patients. At the best of times, the combination of small veins and abundant subcutaneous tissue make vascular access difficult or impossible, therefore, another methods of administration of contrast media is desired. This study was performed to evaluate the feasibility of intraosseous injection of iodixanol in providing a safe and diagnostic urogram in Persian squirrel. Fourteen hundreds mg iodine per kilogram body weight of iodixanol were injected subcutaneously over tibial tuberosity on ten clinically healthy adult Persian squirrels with no signs of urinary system disorder. Lateral and ventrodorsal radiographs were taken every 2 minutes until the pyelogram was finished. Intraosseous injection of iodixanol was successful to show nephrogram, pyelogram, uretrogram and cystogram clearly. There were no abnormal clinical signs after one week of experiments. Biochemical and hematological profiles were in normal ranges. It is concluded that intraosseous urography is an effective and reliable method for urography studies in squirrel. Microscopic examinations of the kidneys and the site of injection after one week were normal.

Keywords: intraosseous urography, iodixanol, Persian squirrel, morphologic

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Authors: Faisal A. Salih

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Verapamil hydrochloride (Ver) is a drug used in medicine for arrythmia, angina and hypertension as a calcium channel blocker. For the quantitative determination of Ver in dosage forms, the HPLC method is most often used. A convenient alternative to the chromatographic method is potentiometry using a Verselective electrode, which does not require expensive equipment, can be used without separation from the matrix components, which significantly reduces the analysis time, and does not use toxic organic solvents, being a "green", "environmentally friendly" technique. It has been established in this study that the rational choice of the membrane plasticizer and the preconditioning and measurement algorithms, which prevent nonexchangeable extraction of Ver into the membrane phase, makes it possible to achieve excellent analytical characteristics of Ver-selective electrodes based on commercially available components. In particular, an electrode with the following membrane composition: PVC (32.8 wt %), ortho-nitrophenyloctyl ether (66.6 wt %), and tetrakis-4-chlorophenylborate (0.6 wt % or 0.01 M) have the lower detection limit 4 × 10−8 M and potential reproducibility 0.15–0.22 mV. Both direct potentiometry (DP) and potentiometric titration (PT) methods can be used for the determination of Ver in tablets and injection solutions. Masses of Ver per average tablet weight determined by the methods of DP and PT for the same set of 10 tablets were (80.4±0.2 and80.7±0.2) mg, respectively. The masses of Ver in solutions for injection, determined by DP for two ampoules from one set, were (5.00±0.015 and 5.004±0.006) mg. In all cases, good reproducibility and excellent correspondence with the declared quantities were observed.

Keywords: verapamil, potentiometry, ion-selective electrode, pharmaceutical analysis

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Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao

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Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.

Keywords: artificial intelligence and office, NLP, deep learning, text classification

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Authors: Brinda Sharma, Saakshi S. Sarpotdar

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Deep-fat frying is popular standard method that has been studied basically to clarify the complicated mechanisms of fat decomposition at high temperatures and to assess their effects on human health. The aim of this paper is to point out the application of method engineering that has been recently improved our understanding of the fundamental principles and mechanisms concerned at different scales and different times throughout the process: pretreatment, frying, and cooling. It covers the several aspects of deep-fat drying. New results regarding the understanding of the frying method that are obtained as a results of major breakthroughs in on-line instrumentation (heat, steam flux, and native pressure sensors), within the methodology of microstructural and imaging analysis (NMR, MRI, SEM) and in software system tools for the simulation of coupled transfer and transport phenomena. Such advances have opened the approach for the creation of significant information of the behavior of varied materials and to the event of latest tools to manage frying operations via final product quality in real conditions. Lastly, this paper promotes an integrated approach to the frying method as well as numerous competencies like those of chemists, engineers, toxicologists, nutritionists, and materials scientists also as of the occupation and industrial sectors.

Keywords: frying, cooling, imaging analysis (NMR, MRI, SEM), deep-fat frying

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Authors: T. Zaki, Fathi S. Soliman

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Desulfurization process is required by most, if not all refineries, to achieve ultra-low sulfur fuel, that contains less than 10 ppm sulfur. A lot of research works and many effective technologies have been studied to achieve deep desulfurization process in moderate reaction environment, such as adsorption desulfurization (ADS), oxidative desulfurization (ODS), biodesulfurization and extraction desulfurization (EDS). Extraction desulfurization using deep eutectic solvents (DESs) is considered as simple, cheap, highly efficient and environmentally friend process. In this work, four DESs were designed and synthesized. Choline chloride (ChCl) was selected as typical hydrogen bond acceptors (HBA), and ethylene glycol (EG), glycerol (Gl), urea (Ur) and thiourea (Tu) were selected as hydrogen bond donors (HBD), from which a series of deep eutectic solvents were synthesized. The experimental data showed that the synthesized DESs showed desulfurization affinities towards the thiophene species in cyclohexane solvent. Ethylene glycol molecules showed more affinity to create hydrogen bond with thiophene instead of choline chloride. Accordingly, ethylene glycol choline chloride DES has the highest extraction efficiency.

Keywords: DES, desulfurization, green solvent, extraction

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Authors: Gizem Eser Erdek

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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

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Authors: Lina Liang, Kai Xu, Jing Zhang

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Purpose: Age-related macular degeneration (AMD) is a major leading cause of visual impairment and blindness with no cure currently established. Cell replacement is discussed as a potential therapy for AMD. Besides intravitreal injection and subretinal injection, intravenous administration has been explored as an alternative route. This study is to observe the effect of BSYJ, a traditional Chinese medicine on the homing and differentiation of mesenchymal stem cells transplanted via tail vein injection in an age-related macular degeneration mouse model. Methods: Four-week-old C57BL/6J mice were injected with 40 mg/kg NaIO₃ to induce age-related macular degeneration model. At the second day after NaIO₃ injection, 1×10⁷ GFP labeled bone marrow-derived mesenchymal stem cells (GFP-MSCs) were transplanted via tali vein injection into the experimental mice. Then the mice were randomly divided into two groups, gavaged with either BSYJ solution (BSYJ group, n=12) or distilled water (DW group, n=12). 12 age-matched healthy C57BL/6J mice were fed regularly as normal control. At day 7, day 14, and day 28 after treatment, retina flat mounting was used to detect the homing of mesenchymal stem cells at the retina. Double-labeling immunofluorescence was used to determine the differentiation of mesenchymal stem cells. Results: At 7, 14, 28 days after treatment, the numbers of GFP-MSCs detected by retina flatmount were 10.2 ± 2.5, 14.5 ± 3.4 and 18.7 ± 5.8, respectively in the distilled water group, while 15.7 ± 3.8, 32.3 ± 3.5 and 77.3 ± 6.4 in BSYJ group, the differences between the two groups were significant (p < 0.05). At 28 days after treatment, it was shown by double staining immunofluorescence that there were more GFP positive cells in the retina of BSYJ group than that of the DW group, but none of the cells expressed RPE specific genes such as RPE65 and CRALBP, or photoreceptor genes such as recoverin and rhodopsin either in BSYJ group or DW group. However, GFAP positive cells were found among the cells labeled with GFP, and the double labeling cells were much more in the BSYJ group than the distilled water group. Conclusion: BSYJ could promote homing of mesenchymal stem cells at the retina of age-related macular degeneration model mice induced by NaIO₃, and the differentiation towards to glial cells. Acknowledgement: National Natural Foundation of China (No: 81473736, 81674033,81973912).

Keywords: BSYJ, differentiation, homing, mesenchymal stem cells

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Authors: Marcelo Lopes Dias Kolling, Felipe Ferreira Laranjeira, Guilherme Augusto Hettwer, Pedro Salomão Piccinini, Marwan Masri, Carlos Oscar Uebel

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Introduction: Injectable fillers are among the most common nonsurgical cosmetic procedures, with significant growth yearly. Knowledge of rheological and mechanical characteristics of fillers, facial anatomy, and injection technique is essential for safety. Concepts such as the use of cannula versus needle, aspiration before injection, and facial danger zones have been well discussed. In case of an accidental intravascular puncture, the pressure inside the vessel may not be sufficient to push blood into the syringe due to the characteristics of the filler product; this is especially true for calcium hydroxyapatite (CaHA) or hyaluronic acid (HA) fillers with high G’. Since viscoelastic properties of normal saline are much lower than those of fillers, aspiration with saline prior to filler injection may decrease the risk of a false negative aspiration and subsequent catastrophic effects. We discuss a technique to add an additional safety step to the procedure with saline aspiration prior to injection, a ‘’reverse Seldinger’’ technique for intravascular access, which we term SANIT: Saline Aspiration Negative Intravascular Test. Objectives: To demonstrate the author’s (PSP) technique which adds an additional safety step to the process of filler injection, with both CaHA and HA, in order to decrease the risk of intravascular injection. Materials and Methods: Normal skin cleansing and topical anesthesia with prilocaine/lidocaine cream are performed; the facial subunits to be treated are marked. A 3mL Luer lock syringe is filled with 2mL of 0.9% normal saline and a 27G needle, which is turned one half rotation. When a cannula is to be used, the Luer lock syringe is attached to a 27G 4cm single hole disposable cannula. After skin puncture, the 3mL syringe is advanced with the plunger pulled back (negative pressure). Progress is made to the desired depth, all the while aspirating. Once the desired location of filler injection is reached, the syringe is exchanged for the syringe containing a filler, securely grabbing the hub of the needle and taking care to not dislodge the needle tip. Prior to this, we remove 0.1mL of filler to allow for space inside the syringe for aspiration. We again aspirate and inject retrograde. SANIT is especially useful for CaHA, since the G’ is much higher than HA, and thus reflux of blood into the syringe is less likely to occur. Results: The technique has been used safely for the past two years with no adverse events; the increase in cost is negligible (only the cost of 2mL of normal saline). Over 100 patients (over 300 syringes) have been treated with this technique. The risk of accidental intravascular puncture has been calculated to be between 1:6410 to 1:40882 syringes among expert injectors; however, the consequences of intravascular injection can be catastrophic even with board-certified physicians. Conclusions: While the risk of intravascular filler injection is low, the consequences can be disastrous. We believe that adding the SANIT technique can help further mitigate risk with no significant untoward effects and could be considered by all performing injectable fillers. Further follow-up is ongoing.

Keywords: injectable fillers, safety, saline aspiration, injectable filler complications, hyaluronic acid, calcium hydroxyapatite

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Authors: Bashiru Abdullahi, Isah Bala Yabo, Ibrahim Yakubu Seini

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In this paper, the steady/transient MHD heat transfer within radiative porous channel due to convective boundary conditions is considered. The solution of the steady-state and that of the transient version were conveyed by Perturbation and Finite difference methods respectively. The heat transfer mechanism of the present work ascertains the influence of Biot number〖(B〗_i1), magnetizing parameter (M), radiation parameter(R), temperature difference, suction/injection(S) Grashof number (Gr) and time (t) on velocity (u), temperature(θ), skin friction(τ), and Nusselt number (Nu). The results established were discussed with the help of a line graph. It was found that the velocity, temperature, and skin friction decay with increasing suction/injection and magnetizing parameters while the Nusselt number upsurges with suction/injection at y = 0 and falls at y =1. The steady-state solution was in perfect agreement with the transient version for a significant value of time t. It is interesting to report that the Biot number has a cogent influence consequently, as its values upsurge the result of the present work slant the extended literature.

Keywords: heat transfer, thermal radiation, porous channel, MHD, transient, convective boundary condition

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Authors: Dingyang Hu, Dan Liu

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DNN (Deep Neural Network) deep learning models are widely used in classification, prediction, and other task scenarios. To address the difficulties of generic adversarial perturbation generation for deep learning models under black-box conditions, a generic adversarial ingestion generation method based on a saliency map (CJsp) is proposed to obtain salient image regions by counting the factors that influence the input features of an image on the output results. This method can be understood as a saliency map attack algorithm to obtain false classification results by reducing the weights of salient feature points. Experiments also demonstrate that this method can obtain a high success rate of migration attacks and is a batch adversarial sample generation method.

Keywords: adversarial sample, gradient, probability, black box

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

Abstract:

In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Nur Dayana Khairunnisa Rosli, Seripah Awang Kechil

Abstract:

Swirling flows with velocity slip are important in nature and industrial processes. The present work considers the effects of velocity slip, temperature jump and suction/injection on the flow and heat transfer of power-law fluids due to a rotating disk in the presence of magnetic field. The system of the partial differential equations is highly non-linear. The number of independent variables is reduced by transforming the system into a system of coupled non-linear ordinary differential equations using similarity transformations. The effects of suction/injection, velocity slip and temperature jump on the flow rates are investigated for various cases of shear thinning and shear thickening power law fluids. The thermal and velocity jump strongly reduce the heat transfer rate and skin friction coefficient. Suction decreases the radial and tangential skin friction coefficient and the rate of heat transfer. It is also observed that the effects are more pronounced in the case of shear thinning fluids as compared to shear thickening fluids.

Keywords: heat transfer, power-law fluids, rotating disk, suction or injection, temperature jump, velocity slip

Procedia PDF Downloads 237

Authors: Mohammad Javad Mehrabanpour, Mohammad Hosein Hosseini, Ali Shirazi, Dorsa Mehrabanpour

Abstract:

Respiratory infections are the most important diseases that affect poultry. Ornithobacterium rhinotracheale is a bacterium that causes respiratory infections including alveolar inflation and pneumonia in birds. The aim of this study was to evaluated antibody titer against Ornitobacterium rhinotracheal in layer chicken sera after vaccination with an experimental ORT vaccine that produced in Razi Vaccine and Serum Research Institute. Cultured bacteria were inactivated by formalin, and controlled tests were conducted on it. The obtained antigens were formulated using Montanide oil and were homogenized using homogenizer. Eighty SPF chickens were kept until the age of 14 days under existing standards for temperature, humidity, and light. At the age of 14 days, chickens were divided into 3 groups. The first group included 50 chickens injected with prepared ORT vaccine, the second group, as control group, included 15 chickens injected with sterile PBS to get stress of infection and the third group included 15 chickens with no injection performed to them. All 3 groups were kept in separate cages at same room. Blood samples were regularly taken from the chickens every week for serum separation and evaluation of antibody titer. During the fifth week post vaccination, booster vaccine was injected into the chickens of vaccinated group. The chickens were inspected every day in terms of mortality as well as any injection site reactions. Three weeks after the booster injection, blood samples were taken from all chickens of all groups, and sera were isolated. The sera of immunized (vaccinated) SPF chickens with ORT vaccine as well as that of SPF chickens in the control groups were reviewed according to the recommendations of ELISA kit manufacturer to examine the chicken’s humeral immune response to the studied vaccine. Potency, stability and sterility tests were also performed on the above mentioned vaccine. Results obtained indicate high antibody titer in sera of chickens vaccinated with experimental ORT vaccine as compared with the control groups that emphasize the ability of experimentally prepared ORT vaccine to stimulate humoral immune response of chicken. After the second injection, antibody titer increased and remained almost stable up to 9 weeks after the injection. ORT vaccine can cause potency in chickens and can protect them against disease.

Keywords: antibody, layer chicken, Ornithobactrium rhinotracitis, vaccine

Procedia PDF Downloads 387

Authors: Changyeop Lee, Sewon Kim, Jongho Lee

Abstract:

Reburning technology has been developed to adopt various commercial combustion systems. Fuel lean reburning is an advanced reburning method to reduce NOx economically without using burnout air, however it is not easy to get high NOx reduction efficiency. In the fuel lean reburning system, the localized fuel rich eddies are used to establish partial fuel rich regions so that the NOx can react with hydrocarbon radical restrictively. In this paper, a new advanced reburning method which supplies reburn fuel with oscillatory motion is introduced to increase NOx reduction rate effectively. To clarify whether forced oscillating injection of reburn fuel can effectively reduce NOx emission, experimental tests were conducted in vertical combustion furnace. Experiments were performed in flames stabilized by a gas burner, which was mounted at the bottom of the furnace. The natural gas is used as both main and reburn fuel and total thermal input is about 40kW. The forced oscillating injection of reburn fuel is realized by electronic solenoid valve, so that fuel rich region and fuel lean region is established alternately. In the fuel rich region, NOx is converted to N2 by reburning reaction, however unburned hydrocarbon and CO is oxidized in fuel lean zone and mixing zone at downstream where slightly fuel lean region is formed by mixing of two regions. This paper reports data on flue gas emissions and temperature distribution in the furnace for a wide range of experimental conditions. All experimental data has been measured at steady state. The NOx reduction rate increases up to 41% by forced oscillating reburn motion. The CO emissions were shown to be kept at very low level. And this paper makes clear that in order to decrease NOx concentration in the exhaust when oscillating reburn fuel injection system is adopted, the control of factors such as frequency and duty ratio is very important.

Keywords: NOx, CO, reburning, pollutant

Procedia PDF Downloads 267

Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long

Abstract:

In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.

Keywords: agricultural object detection, deep learning, machine vision, YOLO family

Procedia PDF Downloads 169

Authors: Mrityunjay Kumar Sinha, Mayank Srivastava

Abstract:

The position of interface and temperature variation of phase change thermal energy storage system under constant heat injection and radiative heat injection is analysed during charging/discharging process by Heat balance integral method. The charging/discharging process is solely governed by conduction. Phase change material is kept inside a rectangular cavity. Time-dependent fixed temperature and radiative boundary condition applied on one wall, all other walls are thermally insulated. Interface location and temperature variation are analysed by using MATLAB.

Keywords: conduction, melting/solidification, phase change materials, Stefan’s number

Procedia PDF Downloads 365