Search results for: metal deep eutectic solvents

Authors: Shiyin He, Zheng Huang

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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

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Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

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We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

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Authors: Okoro Ikechukwu Ralph, Fuat Kara

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The discoveries of hydrocarbon reserves has clearly drifted offshore, and in deeper waters - areas where the industry still has limited knowledge; and that were hitherto, regarded as being out of reach. This shift presents significant and increased challenges in technology requirements needed to guarantee safety of personnel, environment and equipment; ensure high reliability of installed equipment; and provide high level of confidence in security of investment and company reputation. Nowhere are these challenges more apparent than on subsea well integrity and production performance. The past two decades has witnessed enormous rise in deep and ultra-deep water offshore field developments for the recovery of hydrocarbons. Subsea installed equipment at the seabed has been the technology of choice for these developments. This paper discusses the role of Subsea Control module (SCM) as a vital factor for deep-water well integrity and production performance. A case study for Deep-water well integrity and production performance is analysed.

Keywords: offshore reliability, production performance, subsea control module, well integrity

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Authors: Özge Yılmaz Gel, Berk Kılıç, Derin Dalgıç, Ela Mia Sevilla Levi, Ömer Aydın

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In this experiment, our goal was to remove heavy metals from water. Most recent studies have used removing toxic heavy elements: Cu⁺², Cr⁺³ and Fe⁺³ ions from aqueous solutions has been previously investigated with different kinds of plants like kiwi and tangerines. However, in this study, three different fruit peels were used. We tested banana, peach, and potato peels to remove heavy metal ions from their solution. The first step of the experiment was to wash the peels with distilled water and then dry the peels in an oven for 48 hrs at 80°C. Once the peels were washed and dried, 0.2 grams were weighed and added into 200 mL of %0.1 percent heavy metal solutions by mass. The mixing process was done via a magnetic stirrer. Each sample was taken in 15-minute intervals, and absorbance changes of the solutions were detected using a UV-Vis Spectrophotometer. Among the used waste products, banana peel was the most efficient one. Moreover, the amount of fruit peel, pH values of the initial heavy metal solution, and initial concentration of heavy metal solutions were investigated to determine the effect of fruit peels.

Keywords: absorbance, heavy metal, removal of heavy metals, fruit peels

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

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Authors: Neveen AlQasas, Daniel Johnson

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Membranes for water treatment are an established technology that attracts great attention due to its simplicity and cost effectiveness. However, membranes in operation suffer from the adverse effect of membrane fouling. Bio-fouling is a phenomenon that occurs at the water-membrane interface, and is a dynamic process that is initiated by the adsorption of dissolved organic material, including biomacromolecules, on the membrane surface. After initiation, attachment of microorganisms occurs, followed by biofilm growth. The biofilm blocks the pores of the membrane and consequently results in reducing the water flux. Moreover, the presence of a fouling layer can have a substantial impact on the membrane separation properties. Understanding the mechanism of the initiation phase of biofouling is a key point in eliminating the biofouling on membrane surfaces. The adhesion and attachment of different fouling materials is affected by the surface properties of the membrane materials. Therefore, surface properties of different polymeric materials had been studied in terms of their surface energies and Hansen solubility parameters (HSP). The difference between the combined HSP parameters (HSP distance) allows prediction of the affinity of two materials to each other. The possibilities of measuring the HSP of different polymer films via surface measurements, such as contact angle has been thoroughly investigated. Knowing the HSP of a membrane material and the HSP of a specific foulant, facilitate the estimation of the HSP distance between the two, and therefore the strength of attachment to the surface. Contact angle measurements using fourteen different solvents on five different polymeric films were carried out using the sessile drop method. Solvents were ranked as good or bad solvents using different ranking method and ranking was used to calculate the HSP of each polymeric film. Results clearly indicate the absence of a direct relation between contact angle values of each film and the HSP distance between each polymer film and the solvents used. Therefore, estimating HSP via contact angle alone is not sufficient. However, it was found if the surface tensions and viscosities of the used solvents are taken in to the account in the analysis of the contact angle values, a prediction of the HSP from contact angle measurements is possible. This was carried out via training of a neural network model. The trained neural network model has three inputs, contact angle value, surface tension and viscosity of solvent used. The model is able to predict the HSP distance between the used solvent and the tested polymer (material). The HSP distance prediction is further used to estimate the total and individual HSP parameters of each tested material. The results showed an accuracy of about 90% for all the five studied films

Keywords: surface characterization, hansen solubility parameter estimation, contact angle measurements, artificial neural network model, surface measurements

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Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

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The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: foot recognition, deep learning, knee rehabilitation, convolutional neural network

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Authors: Suriya

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Rapid socio-economic development and urbanization have led to an increasingly serious air pollution problem in Ulaanbaatar (UB), the capital of Mongolia. PM₂.₅ pollution has become the most pressing aspect of UB air pollution. Therefore, monitoring and predicting PM₂.₅ concentration in UB is of great significance for the health of the local people and environmental management. As of yet, very few studies have used models to predict PM₂.₅ concentrations in UB. Using data from 0:00 on June 1, 2018, to 23:00 on April 30, 2020, we proposed two deep learning models based on Bayesian-optimized LSTM (Bayes-LSTM) and CNN-LSTM. We utilized hourly observed data, including Himawari8 (H8) aerosol optical depth (AOD), meteorology, and PM₂.₅ concentration, as input for the prediction of PM₂.₅ concentrations. The correlation strengths between meteorology, AOD, and PM₂.₅ were analyzed using the gray correlation analysis method; the comparison of the performance improvement of the model by using the AOD input value was tested, and the performance of these models was evaluated using mean absolute error (MAE) and root mean square error (RMSE). The prediction accuracies of Bayes-LSTM and CNN-LSTM deep learning models were both improved when AOD was included as an input parameter. Improvement of the prediction accuracy of the CNN-LSTM model was particularly enhanced in the non-heating season; in the heating season, the prediction accuracy of the Bayes-LSTM model slightly improved, while the prediction accuracy of the CNN-LSTM model slightly decreased. We propose two novel deep learning models for PM₂.₅ concentration prediction in UB, Bayes-LSTM, and CNN-LSTM deep learning models. Pioneering the use of AOD data from H8 and demonstrating the inclusion of AOD input data improves the performance of our two proposed deep learning models.

Keywords: deep learning, AOD, PM2.5, prediction, Ulaanbaatar

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Authors: Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier, Léo Fréchier, Barthélémy Hermenault

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Deep Venous Thrombosis (DVT) occurs when a thrombus is formed within a deep vein (most often in the legs). This disease can be deadly if a part or the whole thrombus reaches the lung and causes a Pulmonary Embolism (PE). This disorder, often asymptomatic, has multifactorial causes: immobilization, surgery, pregnancy, age, cancers, and genetic variations. Our project aims to relate the thrombus epidemiology (origins, patient predispositions, PE) to its structure using ultrasound images. Ultrasonography and elastography were collected using Toshiba Aplio 500 at Brest Hospital. This manuscript compares two classification approaches: spectral clustering and scattering operator. The former is based on the graph and matrix theories while the latter cascades wavelet convolutions with nonlinear modulus and averaging operators.

Keywords: deep venous thrombosis, ultrasonography, elastography, scattering operator, wavelet, spectral clustering

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Authors: Loai Ben Naji, Osama M. Ibrahim, Khaled J. Al-Fadhalah

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The objective of this paper is to investigate the formation and adhesion of a protective aluminum-oxide (Al₂O₃, alumina) layer on the surface of Iron-Chromium-Aluminum Alloy (Fe-Cr-Al) sintered-metal-fibers. The oxide-scale layer was developed via multi-stage thermal oxidation at 930 ^oC for 1 hour, followed by 1 hour at 960 ^oC, and finally at 990 ^oC for 2 hours. Scanning Electron Microscope (SEM) images show that the multi-stage thermal oxidation resulted in the formation of predominantly Al₂O₃ platelets-like and whiskers. SEM images also reveal non-uniform oxide-scale growth on the surface of the fibers. Furthermore, peeling/spalling of the alumina protective layer occurred after minimum handling, which indicates weak adhesion forces between the protective layer and the base metal alloy.  Energy Dispersive Spectroscopy (EDS) analysis of the heat-treated Fe-Cr-Al sintered-metal-fibers confirmed the high aluminum content on the surface of the protective layer, and the low aluminum content on the exposed base metal alloy surface. In conclusion, the failure of the oxide-scale protective layer exposes the base metal alloy to further oxidation, and the fragile non-uniform oxide-scale is not suitable as a support for catalysts.

Keywords: high-temperature oxidation, iron-chromium-aluminum alloy, alumina protective layer, sintered-metal-fibers

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Authors: Victor Chinecherem Ejeke, Raphael Eze Nnam

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The main objective of this research is to produce biodiesel from waste vegetable oil using activated eggshell waste as solid catalysts. A transesterification reaction was performed for the conversion to biodiesel. Waste eggshells were calcined at 700°C, 800°C and 900°C for a time period of 3hrs for the preparation of the renewable catalyst. The calcined waste eggshell catalyst was characterized using X-Ray Florescence (XRF) Spectroscopy, which revealed CaO as the major constituent (90.86%); this was further confirmed by X-Ray Diffraction (XRD) and Fourier Transform Infrared (FTIR) analyses. The prepared catalyst was used for transesterification reaction and the effects of calcination temperature (700 to 900°C), Deep Eutectic Solvent DES loading (3 to 18 wt. %), Waste Egg Shell (WES) catalyst loading (6 to 14 wt. %) on the conversion to biodiesel were studied. The yield of biodiesel using a waste eggshell catalyst (91%) is comparable to conventional catalyst like sodium hydroxide with a yield of 80-90%. The maximum biodiesel production yield was obtained at a specific oil-to methanol molar ratio of 1:10, a temperature of 65°C and a catalyst loading of 14g-wt%. The biodiesel produced was characterized as being composed of methyl Tetradecanoate (C₁₄H₂₈O₂) 30.92% using the Gas Chromatographic (GC-MS) analysis. The fuel properties of the biodiesel (Flashpoint 138ᵒC) were comparable to commercial diesel, and hence it can be used in compression-ignition engines. The results indicated that the catalysts derived from waste eggshell had high potential to be used as biodiesel production catalysts in transesterification of waste vegetable oil with the advantage of reusability and also not requiring water washing steps.

Keywords: waste vegetable oil, catalyst , biodiesel , waste egg shell

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Authors: Ziad. Sh. Al Sarraf

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Ultrasonic metal welding has been the subject of ongoing research and development, most recently concentrating on metal joining in miniature devices, for example to allow solder-free wire bonding. As well as at the small scale, there are also opportunities to research the joining of thicker sheet metals and to widen the range of similar and dissimilar materials that can be successfully joined using this technology. This study presents the design, characterisation and test of a lateral-drive ultrasonic metal spot welding device. The ultrasonic metal spot welding horn is modelled using finite element analysis (FEA) and its vibration behaviour is characterised experimentally to ensure ultrasonic energy is delivered effectively to the weld coupon. The welding stack and fixtures are then designed and mounted on a test machine to allow a series of experiments to be conducted for various welding and ultrasonic parameters. Weld strength is subsequently analysed using tensile-shear tests. The results show how the weld strength is particularly sensitive to the combination of clamping force and ultrasonic vibration amplitude of the welding tip, but there are optimal combinations of these and also limits that must be clearly identified.

Keywords: ultrasonic welding, vibration amplitude, welding force, weld strength

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Authors: Mst. Tuhin Akter, Sharun Akter Khushbu, S. M. Shaqib

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A real-time system architecture is highly effective for monitoring and detecting various damaged products or fruits that may deteriorate over time or become infected with diseases. Deep learning models have proven to be effective in building such architectures. However, building a deep learning model from scratch is a time-consuming and costly process. A more efficient solution is to utilize deep neural network (DNN) based transfer learning models in the real-time monitoring architecture. This study focuses on using a novel strawberry dataset to develop effective transfer learning models for the proposed real-time monitoring system architecture, specifically for evaluating and detecting strawberry freshness. Several state-of-the-art transfer learning models were employed, and the best performing model was found to be Xception, demonstrating higher performance across evaluation metrics such as accuracy, recall, precision, and F1-score.

Keywords: strawberry freshness evaluation, deep neural network, transfer learning, image augmentation

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Authors: Dalila Chouder, Djaafer Benachour

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This work concerns the study of the adsorption of metal ions Ag +, Mg +, and Ni2+ in aqueous medium by polydibenzoether-ROWN based on three factors: Temperature, time and concentration. The polydibenzoether crown was synthesized by two means: Chemical and electrochemical. The behavior of the two polymers has been different, and turns out very interesting for chemical polydibenzoether crown has identified conditions. Chemical and électronique polydibenzoether crown have different extraction screw vi property of adsoption of ions fifférents, this study also shows that plyméres doped may have an advantageous electrical conductivity.

Keywords: polymerization, electrochemical, conductivity, complexing metal ions

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Authors: Megha, Diksha, Seema Rani, Balwinder Kaur, Harminder Kaur

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Fe₃O₄@SiO₂@SB functionalized magnetic nanoparticles were synthesized and used to detect heavy metal ions such as Pb²⁺, Hg²⁺, and Cd²⁺ in water. The formation of Fe₃O₄@SiO₂@SB nanocatalyst was confirmed by XRD, SEM, TEM, and IR. The simultaneous determination of analyte cations was carried out using square wave anodic stripping voltammetry (SWASV). Investigation and optimisation were done to study how experimental variables affected the performance of the modified magnetic electrode. Pb²⁺, Hg²⁺, and Cd²⁺ were successfully detected using the designed sensor in the presence of various possibly interfering ions. The recovery rate was found to be 97.5% for Pb²⁺, 96.2% for Hg²⁺, 103.5% for Cd²⁺. The electrochemical sensor was also employed to determine the presence of heavy metal ions in drinking water samples, which are well below the World Health Organization (WHO) guidelines.

Keywords: magnetic nanoparticles, heavy metal ions, electrochemical sensor, environmental water samples

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Authors: Pantip Kayee, Yuwadee Yaponha, Jiranit Pongtubthai

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This study focused on the determination of heavy metal concentration in wastewater and the investigation of heavy metal removal of wastewater treatment system of Suan Sunandha Rajabhat University. Heavy metals (Pb, Cu, Mn, Ni and Zn) were found in wastewater of Suan Sunandha Rajabhat University. Wastewater treatment systems of Suan Sunandha Rajabhat University showed the performance to remove heavy metals. However, heavy metals were still presented in effluent but these residue heavy metals were not over the standard for industrial wastewater. Wastewater treatment system can remove heavy metal by different process such as bioaccumulation by microorganism and biosorption on activated sludge.

Keywords: heavy metal, wastewater, bioaccumulation, biosorption

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Authors: Prima Khairunisa, Febriana Tri Kusumawati, Endah Luthfiana

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Background: Hypertension in elderly, caused by cardiovascular system cannot work normally, because the valves thickened and inelastic blood vessels. It causes vasoconstriction of the blood vessels. Hypertension exercise, increase cardiovascular function and the elasticity of the blood vessels. While slow deep breathing helps the body and mind feel relax. Combination both of them will decrease the blood pressure. Objective: To know the effect of hypertension exercise and slow deep breathing combination to blood pressure in elderly. Method: The study conducted with one group pre-post test experimental design. The samples were 10 elderly both male and female in a Village in Semarang, Central Java, Indonesia. The tool was manual sphygmomanometer to measure blood pressure. Result: Based on paired t-test between hypertension exercise and slow deep breathing with systole blood pressure showed sig (2-tailed) was 0.045, while paired t-test between hypertension exercise hypertension exercise and slow deep breathing with diastole blood pressure showed sig (2-tailed) was 0,343. The changes of systole blood pressure were 127.5 mmHg, and diastole blood pressure was 80 mmHg. Systole blood pressure decreases significantly because the average of systole blood pressure before implementation was 135-160 mmHg. While diastole blood pressure was not decreased significantly. It was influenced by the average of diastole blood pressure before implementation of hypertension exercise was not too high. It was between 80- 90 mmHg. Conclusion: There was an effect of hypertension exercise and slow deep breathing combination to the blood pressure in elderly after 6 times implementations.

Keywords: hypertension exercise, slow deep breathing, elderly, blood pressure

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Authors: Sait Ozsoy, Asude Gokmen, Mehtap Yondem, Hanife A. Alkan, Gulnaz T. Javan

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Deep neck infection often develops due to upper respiratory tract and odontogenic infections. Gastrointestinal System perforation can occur for many reasons and is in need of the early diagnosis and prompt surgical treatment. In both cases late or incorrect diagnosis may lead to increase morbidity and high mortality. A patient with a diagnosis of deep neck abscess died while under treatment due to sepsis and multiple organ failure. Autopsy finding showed duodenal ulcer and this is reported in the literature.

Keywords: peptic ulcer perforation, peritonitis, retropharyngeal abscess, sepsis

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Authors: Tshaiya Devi Thandauthapani, Adam J. Reeve, Adam S. Long, Ian J. Turner, James S. Sharp

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Fingermarks are a crucial form of evidence for identifying a person at a crime scene. However, visualising latent (hidden) fingermarks can be difficult, and the correct choice of techniques is essential to develop and preserve any fingermarks that might be present. Knives, firearms and other metal weapons have proven to be challenging substrates (stainless steel in particular) from which to reliably obtain fingermarks. In this study, time of flight secondary ion mass spectroscopy (ToF-SIMS) was used to image fingermarks on metal surfaces. This technique was compared to a conventional superglue based fuming technique that was accompanied by a series of contrast enhancing dyes (basic yellow 40 (BY40), crystal violet (CV) and Sudan black (SB)) on three different metal surfaces. The conventional techniques showed little to no evidence of fingermarks being present on the metal surfaces after a few days. However, ToF-SIMS images revealed fingermarks on the same and similar substrates with an exceptional level of detail demonstrating clear ridge definition as well as detail about sweat pore position and shape, that persist for over 26 days after deposition when the samples were stored under ambient conditions.

Keywords: conventional techniques, latent fingermarks, metal substrates, time of flight secondary ion mass spectroscopy

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Authors: Thuy Phuong Nhat Tran, Ashutosh Thakur, Toshiaki Taniike

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Recently, covalently linked graphene oxide frameworks (GOFs) have attracted considerable attention in gas absorbance and water purification as well-defined microporous materials. In spite of their potential advantages such as a controllable pore dimension, adjustable hydrophobicity, and structural stability, these materials have been scarcely employed in heterogeneous catalysis. Here we demonstrate a novel and facile method to synthesize Pd nanoparticles (NPs) confined in a GOF (Pd@GOF). The GOF with uniform interlayer space was obtained by the intercalation of diboronic acid between graphene oxide layers. It was found that Pd NPs were generated inside the graphitic gallery spaces of the GOF, and thus, formed Pd NPs were well-dispersed with a narrow particle size distribution. The synthesized Pd@GOF emerged as an efficient nanocatalyst based on its superior performance (product yield and recyclability) toward Suzuki-Miyaura cross-coupling reaction in both polar and apolar solvents, which has been hardly observed for previously reported graphene-based Pd nanocatalysts. Furthermore, the rational comparison of the catalytic performance between two kinds of Pd@GOF (Pd NPs encapsulated in a diboronic ester-intercalated GOF and in a monoboronic ester-intercalated GOF) firmly confirmed the essential role of a rigid framework design in the stabilization of Pd NPs. Based on these results, the covalently assembled GOF was proposed as a promising scaffold for hosting noble metal NPs to construct desired metal@GOF nanocatalysts with improved activity and durability.

Keywords: graphene oxide framework, palladium nanocatalyst, pore confinement, Suzuki-Miyaura cross-coupling reaction

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Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

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Time dependent settlement due to loading on soft saturated soils produces many problems such as high consolidation settlements and low consolidation rates. Also, long term consolidation settlement of soft soil underlying the embankment leads to unpredicted settlements and cracks on soil surface. Preloading method is an effective improvement method to solve this problem. Using vertical drains in preloading method is an effective method for improving soft soils. Applying deep soil mixing method on soft soils is another effective method for improving soft soils. There are little studies on using two methods of preloading and deep soil mixing simultaneously. In this paper, the concurrent effect of preloading with deep soil mixing by vertical drains is investigated through a finite element code, Plaxis2D. The influence of parameters such as deep soil mixing columns spacing, existence of vertical drains and distance between them, on settlement and stability factor of safety of embankment embedded on soft soil is investigated in this research.

Keywords: preloading, soft soil, vertical drains, deep soil mixing, consolidation settlement

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Authors: Byungsik Moon

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Electron beam inspection (EBI) has played an important role in detecting defects during the Fab process. The study focused on capturing buried Cu metal voids for 5nm technology nodes in Qualcomm Snapdragon mass production. This paper illustrates a case study where Cu metal voids can be detected without side effects with optimized EBI scanning conditions. The voids were buried in the VIA and not detected effectively by bright field inspection. EBI showed higher detectability, about 10 times that of bright fields, and a lower landing energy of EBI can avoid film damage. A comparison of detectability between EBI and bright field inspection was performed, and TEM confirmed voids that were detected by EBI. Therefore, a much higher detectability of buried Cu metal voids can be achieved without causing film damage.

Keywords: electron beam inspection, EBI, landing energy, Cu metal voids, bright field inspection

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Authors: Sharareh Mohseni

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Purpose: The objective of this study was to find a suitable solvent to produce saffron edible extract with improved chemical properties. Design/methodology/approach: Dried and pulverized stigmas of C. sativus L. (10g) was extracted with 300 ml of solvents including: distillated water (DW), ethanol/DW, methanol/DW, propylene glycol/DW, heptan/DW, and hexan/DW, for 3 days at 25°C and then centrifuged at 3000 rpm. Then the extracts were evaporated using rotary evaporator at 40°C. The fiber and solvent-free extracts were then analyzed by UV spectrophotometer to detect saffron quality parameters including crocin, picrocrocin and safranal. Findings: Distilled water/ethanol mixture as the extraction solvent, caused larger amounts of the plant constituents to diffuse out to the extract compared to other treatments and also control. Polar solvents including distilled water, ethanol, and propylene glycol (except methanol) were more effective in extracting crocin, picrocrocin, and saffranal than non-polar solvents. Social implications: Due to an enhancement of color and flavor, saffron extract is economical compared to natural saffron. Saffron Extract saves on preparation time and reduces the amount of saffron required for imparting the same flavor, as compared to dry saffron. Liquid extract is easier to use and standardize in food preparations compared to dry stamens and can be dosed precisely compared to natural saffron. Originality/value: No research had been done on production of saffron edible extract using the solvent studied in this survey. The novelty of this research is high and the results can be used industrially.

Keywords: Crocus sativus L., saffron extract, solvent extraction, distilled water

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Authors: A. Sakavičius, A. Lukša, V. Nargelienė, V. Bukauskas, G. Astromskas, A. Šetkus

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We investigate the influence of annealing on the properties of a contact between graphene and metal (Au and Ni), using circular transmission line model (CTLM) contact geometry. Kelvin probe force microscopy (KPFM) and Raman spectroscopy are applied for characterization of the surface and interface properties. Annealing causes a decrease of the metal-graphene contact resistance for both Ni and Au.

Keywords: Au/Graphene contacts, graphene, Kelvin force probe microscopy, NiC/Graphene contacts, Ni/Graphene contacts, Raman spectroscopy

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Authors: Komeil Valipourian

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Urban advances and the growing need for developing infrastructures has increased the importance of deep excavations. In this study, after the introducing probability analysis as an important issue, an attempt has been made to apply it for the deep excavation project of Bangkok’s Metro as a case study. For this, the numerical probability model has been developed based on the Finite Difference Method and Monte Carlo sampling approach. The results indicate that disregarding the issue of probability in this project will result in an inappropriate design of the retaining structure. Therefore, probabilistic redesign of the support is proposed and carried out as one of the applications of probability analysis. A 50% reduction in the flexural strength of the structure increases the failure probability just by 8% in the allowable range and helps improve economic conditions, while maintaining mechanical efficiency. With regard to the lack of efficient design in most deep excavations, by considering geometrical and geotechnical variability, an attempt was made to develop an optimum practical design standard for deep excavations based on failure probability. On this basis, a practical relationship is presented for estimating the maximum allowable horizontal displacement, which can help improve design conditions without developing the probability analysis.

Keywords: numerical probability modeling, deep excavation, allowable maximum displacement, finite difference method (FDM)

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Authors: M. Benhamida, Kh. Bouamama, P. Djemia

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We investigate by first-principles pseudo-potential calculations the composition dependence of lattice parameter, hardness and elastic properties of ternary disordered solid solutions Ti(1-x)Ta(x)N (1>=x>=0) with B1-rocksalt structure. Calculations use the coherent potential approximation with the exact muffin-tin orbitals (EMTO) and hardness formula for multicomponent covalent solid solution proposed. Bulk modulus B shows a nearly linear behaviour whereas not C44 and C’=(C11-C12)/2 that are not monotonous. Influences of vacancies on hardness of off-stoichiometric transition-metal nitrides TiN(1−x) and TaN(1−x) are also considered.

Keywords: transition metal nitride materials, elastic constants, hardness, EMTO

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Authors: Radha H. R., Krupakara P. V.

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Metal matrix composites are attracting today's manufacturers of many automobile parts so that they lost longer and their properties can be tailored according to the requirement. In this paper an attempt has been made to study the corrosion characteristics of Aluminium 6061 / quartz metal matrix composites in alkali medium like sodium hydroxide solutions. Metal matrix composites are heterogeneous mixtures of a matrix and reinforcement. In this work the matrix selected is Aluminium 6061 alloy which is commercially available and the reinforcement selected is quartz particulates of 50-80 micron size which is available in plenty in and around Bangalore district, India. Composites containing Aluminium 6061 with 2, 4 and 6 weight percent of quartz are manufactured by liquid melt metallurgy technique using vortex method. Corrosion tests like static weight loss and open circuit potential tests are conducted in different concentrated solutions of sodium hydroxide. To compare the results the matrix Aluminium 6061 is also casted in the same way. Specimens for the test are prepared according to ASTM standards. In all the tests the metal matrix composites showed better corrosion resistance than matrix alloy.

Keywords: aluminium 6061, corrosion, quartz, vortex

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Authors: Meysam Mousakhani, Reza Ziaie Moayed

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Considering the population growth and the needs of society, the improvement of problematic soils and the study of the application of different improvement methods have been considered. One of these methods is deep soil mixing, which has been developed in the past decade, especially in soft soils due to economic efficiency, simple implementation, and other benefits. The use of cement is criticized for its cost and the damaging environmental effects, so these factors lead us to use other additives along with cement in the deep soil mixing. Additives that are used today include fly ash, blast-furnace slag, glass powder, and potassium hydroxide. The present study provides a literature review on the application of different additives in deep soil mixing so that the best additives can be introduced from strength, economic, environmental and other perspectives. The results show that by replacing fly ash and slag with about 40 to 50% of cement, not only economic and environmental benefits but also a long-term strength comparable to cement would be achieved. The use of glass powder, especially in 3% mixing, results in desirable strength. In addition to the other benefits of these additives, potassium hydroxide can also be transported over longer distances, leading to wider soil improvement. Finally, this paper suggests further studies in terms of using other additives such as nanomaterials and zeolite, with different ratios, in different conditions and soils (silty sand, clayey sand, carbonate sand, sandy clay and etc.) in the deep mixing method.

Keywords: deep soil mix, soil stabilization, fly ash, ground improvement

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Authors: Nurul Huda Baharuddin, Nik Meriam Nik Sulaiman, Mohammed Kheireddine Aroua

Abstract:

The effects of pH, polymer concentration, and metal ions feed concentration for four selected heavy metals Zn (II), Pb (II), Cr (III) and Cr (VI) were tested by using Polymer Enhanced Ultrafiltration (PEUF). An alternative biopolymer namely unmodified starch is proposed as a binding reagent in consequences, as compared to commonly used water-soluble polymers namely polyethylene glycol (PEG) and polyethyleneimine (PEI) in the removal of selected four heavy metal ions. The speciation species profiles of four selected complexes ions namely Zn (II), Pb (II), Cr (III) and Cr (VI) and the present of hydroxides ions (OH-) in variously charged ions were investigated by available software at certain pH range. In corresponds to identify the potential of complexation behavior between metal ion-polymers, potentiometric titration studies were obtained at first before carried out experimental works. Experimental works were done using ultrafiltration systems obtained by laboratory ultrafiltration bench scale equipped with 10 kDa polysulfone hollow fiber membrane. Throughout the laboratory works, the rejection coefficient and permeate flux were found to be significantly affected by the main operating parameter, namely the effects of pH, polymer composition and metal ions concentrations. The interaction of complexation between two binding polymers namely unmodified starch and PEG were occurred due to physical attraction of metal ions to the polymer on the molecular surface with high possibility of chemical occurrence. However, these selected metal ions are mainly complexes by polymer functional groups whenever there is interaction with PEI polymer. For study of single metal ions solutions, Zn (II) ions' rejections approaching over 90% were obtained at pH 7 for each tested polymer. This behavior was similar to Pb (II), Cr (III) and Cr (VI); where the rejections were obtained at lower acidic pH and increased at neutral pH of 7. Different behavior was found by Cr (VI) ions where a high rejection was only achieved at acidic pH region with PEI. Polymer concentration and metal ions concentration are found to have a significant effect on rejections. For mixed metal ion solutions, the behavior of metal ion rejections was similar to single metal ion solutions for investigation on the effects of pH. Rejection values were high at pH 7 for Zn (II) pH 7 for Zn (II) and Cr (III) ions, corresponding to higher rejections with unmodified starch. Pb (II) ions obtained high rejections when tested with PEG whenever carried out in mixed metal ion solutions. High Cr (VI) ions' rejection was found with PEI in single and mixed metal ions solutions at neutral pH range. The influence of starch’s granule structure towards the rejections of these four selected metal ions is found to be attracted in a non-ionic manner. No significant effects on permeate flux were obtained when tested at different pH ranges, polymer concentrations and metal ions feed either by single or mixtures metal ions solutions. Canizares Model was employed as the theoretical model to predict permeate flux and metal ions retention on the study of heavy metal ions removal.

Keywords: polyethyleneimine, polyethylene glycol, polymer-enhanced ultrafiltration, unmodified starch

Procedia PDF Downloads 139

Authors: Shaik Jilani Basha, Inavolu Avinash, Alla Venu Sai Reddy, Bitragunta Taraka Ramu

Abstract:

We can use the neural style transfer technique to build a picture with the same "content" as the beginning image but the "style" of the picture we've chosen. Neural style transfer is a technique for merging the style of one image into another while retaining its original information. The only change is how the image is formatted to give it an additional artistic sense. The content image depicts the plan or drawing, as well as the colors of the drawing or paintings used to portray the style. It is a computer vision programme that learns and processes images through deep convolutional neural networks. To implement software, we used to train deep learning models with the train data, and whenever a user takes an image and a styled image, the output will be as the style gets transferred to the original image, and it will be shown as the output.

Keywords: neural networks, computer vision, deep learning, convolutional neural networks

Procedia PDF Downloads 63