Search results for: ultra high precision grinding

Authors: Wang Xiaoqing, Fang Youyuan, Zheng Yanxing, Gu Tianyang, Zong Jianjian, Tong Jinrong

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Compared with traditional distributed environment, the net-centric environment brings on more demanding challenges for information sharing with the characteristics of ultra-large scale and strong distribution, dynamic, autonomy, heterogeneity, redundancy. This paper realizes an information sharing model and a series of core services, through which provides an open, flexible and scalable information sharing platform.

Keywords: net-centric environment, information sharing, metadata registry and catalog, cross-domain data access control

Procedia PDF Downloads 546

Authors: M. R. Rouhi, S. Shafiei, A. Taghavipour, H. Adibi-Asl, A. Doosthoseini

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This research targets at alleviating the problem of range anxiety associated with the battery electric vehicles (BEVs) by considering mechanical and control aspects of the powertrain. In this way, all the energy consuming components and their effect on reducing the range of the BEV and battery life index are identified. On the other hand, an appropriate control strategy is designed to guarantee the performance of the BEV and the extended electric range which is evaluated by an extensive simulation procedure and a real-world driving schedule.

Keywords: battery, electric vehicles, ultra-capacitor, model predictive control

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Authors: Hoda Mahgoub, Abeer Hanafy

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Linagliptin (LNG) belongs to dipeptidyl-peptidase-4 (DPP-4) inhibitor class. DPP-4 inhibitors represent a new therapeutic approach for the treatment of type 2 diabetes in adults. The aim of this work was to develop and validate an accurate and reproducible HPLC method for the determination of LNG with high sensitivity in rat plasma. The method involved separation of both LNG and pindolol (internal standard) at ambient temperature on a Zorbax Eclipse XDB C18 column and a mobile phase composed of 75% methanol: 25% formic acid 0.1% pH 4.1 at a flow rate of 1.0 mL.min-1. UV detection was performed at 254nm. The method was validated in compliance with ICH guidelines and found to be linear in the range of 5–1000ng.mL-1. The limit of quantification (LOQ) was found to be 5ng.mL-1 based on 100µL of plasma. The variations for intra- and inter-assay precision were less than 10%, and the accuracy values were ranged between 93.3% and 102.5%. The extraction recovery (R%) was more than 83%. The method involved a single extraction step of a very small plasma volume (100µL). The assay was successfully applied to an in-vivo pharmacokinetic study of LNG in rats that were administered a single oral dose of 10mg.kg-1 LNG. The maximum concentration (Cmax) was found to be 927.5 ± 23.9ng.mL-1. The area under the plasma concentration-time curve (AUC0-72) was 18285.02 ± 605.76h.ng.mL-1. In conclusion, the good accuracy and low LOQ of the bioanalytical HPLC method were suitable for monitoring the full pharmacokinetic profile of LNG in rats. The main advantages of the method were the sensitivity, small sample volume, single-step extraction procedure and the short time of analysis.

Keywords: HPLC, linagliptin, pharmacokinetic study, rat plasma

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Authors: Anil P. Dewani, Ravindra L. Bakal, Anil V. Chandewar

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Present work demonstrates the applicability of high-performance liquid chromatography (HPLC) with UV detection for the determination of malondialdehyde as malondialdehyde-thiobarbituric acid complex (MDA-TBA) in-vivo in rats. The HPLC-UV method for MDA-TBA was achieved by isocratic mode on a reverse-phase C18 column (250mm×4.6mm) at a flow rate of 1.0mLmin−1 followed by UV detection at 278 nm. The chromatographic conditions were optimized by varying the concentration and pH followed by changes in percentage of organic phase optimal mobile phase consisted of mixture of water (0.2% Triethylamine pH adjusted to 2.3 by ortho-phosphoric acid) and acetonitrile in ratio (80:20 % v/v). The retention time of MDA-TBA complex was 3.7 min. The developed method was sensitive as limit of detection and quantification (LOD and LOQ) for MDA-TBA complex were (standard deviation and slope of calibration curve) 110 ng/ml and 363 ng/ml respectively. The method was linear for MDA spiked in plasma and subjected to derivatization at concentrations ranging from 100 to 1000 ng/ml. The precision of developed method measured in terms of relative standard deviations for intra-day and inter-day studies was 1.6–5.0% and 1.9–3.6% respectively. The HPLC method was applied for monitoring MDA levels in rats subjected to chronic treatment of ciprofloxacin (CFL) (5mg/kg/day) for 21 days. Results were compared by findings in control group rats. Mean peak areas of both study groups was subjected for statistical treatment to unpaired student t-test to find p-values. The p value was < 0.001 indicating significant results and suggesting increased MDA levels in rats subjected to chronic treatment of CFL of 21 days.

Keywords: MDA, TBA, ciprofloxacin, HPLC-UV

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Authors: Mohammadreza Akbari, Pooya Soleimani Besheli, Reza Khalili, Davood Domiri Danji

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In this conference, our aims are accuracy, capabilities and power at solving of the complicated non-linear partial differential. Our purpose is to enhance the ability to solve the mentioned nonlinear differential equations at basic science and engineering field and similar issues with a simple and innovative approach. As we know most of engineering system behavior in practical are nonlinear process (especially basic science and engineering field, etc.) and analytical solving (no numeric) these problems are difficult, complex, and sometimes impossible like (Fluids and Gas wave, these problems can't solve with numeric method, because of no have boundary condition) accordingly in this symposium we are going to exposure an innovative approach which we have named it Akbari-Ganji's Method or AGM in engineering, that can solve sets of coupled nonlinear differential equations (ODE, PDE) with high accuracy and simple solution and so this issue will emerge after comparing the achieved solutions by Numerical method (Runge-Kutta 4th). Eventually, AGM method will be proved that could be created huge evolution for researchers, professors and students in whole over the world, because of AGM coding system, so by using this software we can analytically solve all complicated linear and nonlinear partial differential equations, with help of that there is no difficulty for solving all nonlinear differential equations. Advantages and ability of this method (AGM) as follow: (a) Non-linear Differential equations (ODE, PDE) are directly solvable by this method. (b) In this method (AGM), most of the time, without any dimensionless procedure, we can solve equation(s) by any boundary or initial condition number. (c) AGM method always is convergent in boundary or initial condition. (d) Parameters of exponential, Trigonometric and Logarithmic of the existent in the non-linear differential equation with AGM method no needs Taylor expand which are caused high solve precision. (e) AGM method is very flexible in the coding system, and can solve easily varieties of the non-linear differential equation at high acceptable accuracy. (f) One of the important advantages of this method is analytical solving with high accuracy such as partial differential equation in vibration in solids, waves in water and gas, with minimum initial and boundary condition capable to solve problem. (g) It is very important to present a general and simple approach for solving most problems of the differential equations with high non-linearity in engineering sciences especially at civil engineering, and compare output with numerical method (Runge-Kutta 4th) and Exact solutions.

Keywords: new approach, AGM, sets of coupled nonlinear differential equation, exact solutions, numerical

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Authors: Vasanth C. Shunmugasamy, Bilal Mansoor

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Magnesium alloys are increasingly being considered for structural systems across different industrial sectors, including precision components of biomedical devices, owing to their high specific strength, stiffness and biodegradability. However, Mg alloys exhibit a high corrosion rate that restricts their application as a biomaterial. For safe use as biomaterial, it is essential to control their corrosion rates. Mg alloy corrosion is influenced by several factors, such as grain size, precipitates and texture. In Mg alloys, microgalvanic coupling between the α-Mg matrix and secondary precipitates can exist, which results in an increased corrosion rate. The present research addresses this challenge by engineering the microstructure of a biodegradable Mg–Zn–RE–Zr alloy by friction stir processing (FSP), a severe plastic deformation process. The FSP-processed Mg alloys showed improved corrosion resistance and mechanical properties. FSPed Mg alloy showed refined grains, a strong basal texture and broken and uniformly distributed secondary precipitates in the stir zone. Mg, alloy base material, exposed to In vitro corrosion medium showed micro galvanic coupling between precipitate and matrix, resulting in the unstable passive layer. However, FS processed alloy showed uniform corrosion owing to stable surface film formation. The stable surface film is attributed to refined grains, preferred texture and distribution of precipitates. The research results show promising potential for Mg alloy to be developed as a biomaterial.

Keywords: biomaterials, severe plastic deformation, magnesium alloys, corrosion

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Authors: Ivan P. Pozdnyakov, Alexey A. Melnikov, Nikolai V. Tkachenko

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Photochemical reactions with participation of iron (III) carboxylates are important for environmental photochemistry and have a great potential of application in water purification (Advanced Oxidation Processes, photo-Fenton and Fenton-like processes). In spite of this information about excited states and primary intermediates in photochemistry of Fe(III) complexes with carboxylic acids is scarce. This talk presents and discusses the results of several recent authors' publications in a field of ultra fast spectroscopy of natural Fe(III) carboxylates.

Keywords: carboxylates, iron complexes, photochemistry, radical complexes, ultrafast processes

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Authors: Aptullah Karakas, Murat Baydogan

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The hot dip aluminizing (HDA) process involves immersing a metallic substrate into a molten aluminum bath for several minutes, and removed from the bath and cooled down to room temperature. After the HDA process, various aluminide layers are formed as a result of interdiffusion between the substrate and the molten aluminum and between the aluminide layers. In order to form a uniform aluminide layer, the specimen must be covered and wet well by the molten aluminum. Surface roughness plays an important role in wettability, and thus, surface preparation is an important stage in determining the final surface roughness. In this study, different roughness values were achieved by grinding the surface with emery papers as 180, 320 and 600 grids. After the surface preparation, the HDA process was performed in a molten Al-Si bath at 700 ᴼC for 10 minutes. After the HDA process, a microstructural examination of the coating was carried out to evaluate the uniformity of the coating and adhesion between the substrate and the coating. According to the results, the best adhesion at the interface was observed on the specimen, which was prepared by 320 grid emery paper having a mean surface roughness (Ra) of 0.097 µm.

Keywords: hot-dip aluminizing, microstructure, surface roughness, coating

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Authors: Sisi Xia, Dezhuan Tao, Junyan Yang, Weiting Xiong

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Under the background of Chinese urbanization changing from incremental development to stock development, the completion of urban public service facilities is essential to urban spatial quality. As public services facilities is a huge and complicated system, clarifying the various types of internal rules associated with the land market price is key to optimizing spatial layout. This paper takes Wuxi City as a representative sample location and establishes the digital analysis platform using urban price and several high-precision big data acquisition methods. On this basis, it analyzes the coupling relationship between different public service categories and land price, summarizing the coupling patterns of urban public facilities distribution and urban land price fluctuations. Finally, the internal mechanism within each of the two elements is explored, providing the reference of the optimum layout of urban planning and public service facilities.

Keywords: public service facilities, land price, urban spatial morphology, big data

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Authors: Rasha Saad, Jean Frederic Weber, Fatimah Bebe, Sadia Sultan

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The goal of study was to screen the effects of candesartan and four endophytic fungi for their potential in microbial biotransformation. In this experiment, four types of unidentified fungi with the codes of TH2L1, TH2R10, TH1P35 and TH1S46 were used in screening process by MECFUS (Microtiter plate, Elicitors, Combination, Freeze-drying, UHPLC, Statistical analysis) protocol. The experiment was carried out by using 96-well microtiter plate (MTP) with different media and elicitors. Various media with two concentrations of Potato Dextrose Broth (PDB) and elicitors used were to induce the production of secondary metabolites from the fungi as well as the biotransformation of the drug compound. After incubation, cultures were extracted by freeze drying method and finally analyzed by ultra-High performance Liquid Chromatography (uHPLC). The extracts analyzed by uHPLC followed by LC/Ms, demonstrated the presence of biotransformation products from the drug compound and elicitation of the secondary metabolism from the fungi by the occurrence of the additional peaks. From the four fungi, TH1S46 showed highly potential produced secondary metabolites as well as the biotransformation of candesartan. For other fungi, they responded when candesartan was introduced. Moreover, the additional peaks produced in uHPLC need to be further investigation by using LC-MS or NMR.

Keywords: biotransformation, candesartan, endophytes, secondary metabolites

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Authors: Somayeh Komeylian

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Array signal processing techniques have been recently developing in a variety application of the performance enhancement of receivers by refraining the power of jamming and interference signals. In this scenario, biases induced to the antenna array receiver degrade significantly the accurate estimation of the carrier phase. Owing to the integration of frequency becomes the carrier phase, we have obtained the unbiased doppler frequency for the high precision estimation of carrier phase. The unbiased characteristic of Doppler frequency to the power jamming and the other interference signals allows achieving the highly accurate estimation of phase carrier. In this study, we have rigorously investigated the unbiased characteristic of Doppler frequency to the variation of the antenna array geometries. The simulation results have efficiently verified that the Doppler frequency remains also unbiased and accurate to the variation of antenna array geometries.

Keywords: array signal processing, unbiased doppler frequency, GNSS, carrier phase, and slowly fluctuating point target

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Authors: Seham Samir Soliman, Ahmed A.Suliman, Khaled Fathy, Ahmed A. Sedik

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Cyclophosphamide (CP), an antineoplastic drug, has been found to induce reproductive damage. It is essential to develop approaches aimed at safeguarding ovarian tissue integrity in women experiencing reproductive toxicity as a result of chemotherapy. The current study was conducted to assess the impact of an extract derived from Moringa oleifera (M. oleifera) leaves on ovarian damage produced by CP. A total of 32 female Wistar Albino rats, which were in a healthy cycling state, were randomly separated into 4 groups, with every group contains 8 rats. The first group was administered intraperitoneal (i.p.) saline. The second group was administered a solitary intraperitoneal dosage of cyclophosphamide (200 mg/kg). The third one received M. oleifera extract (150 mg/kg orally) for 20 days, followed by i.p. of CP on the last day of the experiment. The fourth group received M. oleifera extract (250 mg/kg orally) for 20 days, followed by i.p. of CP on the last day of the experiment. Hormonal assessments, including luteinizing hormone (LH), estrogen (ES), and follicle-stimulating hormone (FSH), were performed 24 hours after CP administration. In addition, evaluating the antioxidant status and inflammatory response against CP. Moreover, conducting detailed histopathological and ultra-structural pictures of the ovary. Our findings reported that rats intoxicated with CP exhibited elevated levels of FSH, LH, malondialdehyde (MDA), tumor necrosis factor-alpha (TNF-α), and a decrease in E₂, and glutathione (GSH) levels. Pre-treatment with M. oleifera extract (250 mg/kg orally) ameliorated the disturbance in hormonal changes, oxidative stress indices, and the levels of pro-inflammatory mediators. Also, the histopathological and ultra-structural pictures of the ovaries were improved significantly in rats. In conclusion, M. oleifera extract possesses a significant protective role against CP-induced acute reproductive toxicity via modulating the values of FSH, LH, E₂ and quenching the release of reactive oxygen species and inflammatory mediators in female rats.

Keywords: cyclophosphamide, Moringa oleifera, ovarian function, oxidative stress, pro-inflammatory mediators

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Authors: Yash Jain

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The US Center for Disease Control has recommended wearing masks to slow the spread of the virus. The research uses a video feed from a camera to conduct real-time classifications of whether or not a human is correctly wearing a mask, incorrectly wearing a mask, or not wearing a mask at all. Utilizing two distinct datasets from the open-source website Kaggle, a mask detection network had been trained. The first dataset that was used to train the model was titled 'Face Mask Detection' on Kaggle, where the dataset was retrieved from and the second dataset was titled 'Face Mask Dataset, which provided the data in a (YOLO Format)' so that the TinyYoloV3 model could be trained. Based on the data from Kaggle, two machine learning models were implemented and trained: a Tiny YoloV3 Real-time model and a two-stage neural network classifier. The two-stage neural network classifier had a first step of identifying distinct faces within the image, and the second step was a classifier to detect the state of the mask on the face and whether it was worn correctly, incorrectly, or no mask at all. The TinyYoloV3 was used for the live feed as well as for a comparison standpoint against the previous two-stage classifier and was trained using the darknet neural network framework. The two-stage classifier attained a mean average precision (MAP) of 80%, while the model trained using TinyYoloV3 real-time detection had a mean average precision (MAP) of 59%. Overall, both models were able to correctly classify stages/scenarios of no mask, mask, and incorrectly worn masks.

Keywords: datasets, classifier, mask-detection, real-time, TinyYoloV3, two-stage neural network classifier

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Authors: Zhang Pinliang, Chen Chuan, Song Guangming, Wu Qiang, Gong Zizheng, Li Ming

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The active removal of space debris and asteroid defense are important issues in human space activities. Both of them need a detumbling process, for almost all space debris and asteroid are in a rotating state, and it`s hard and dangerous to capture or remove a target with a relatively high tumbling rate. So it`s necessary to find a method to reduce the angular rate first. The laser ablation method is an efficient way to tackle this detumbling problem, for it`s a contactless technique and can work at a safe distance. In existing research, a laser rotational control strategy based on the estimation of the instantaneous angular velocity of the target has been presented. But their calculation of control torque produced by a laser, which is very important in detumbling operation, is not accurate enough, for the method they used is only suitable for the plane or regularly shaped target, and they did not consider the influence of irregular shape and the size of the spot. In this paper, based on the triangulation reconstruction of the target surface, we propose a new method to calculate the impulse of the irregularly shaped target under both the covered irradiation and spot irradiation of the laser and verify its accuracy by theoretical formula calculation and impulse measurement experiment. Then we use it to study the process of detumbling cylinder and asteroid by laser. The result shows that the new method is universally practical and has high precision; it will take more than 13.9 hours to stop the rotation of Bennu with 1E+05kJ laser pulse energy; the speed of the detumbling process depends on the distance between the spot and the centroid of the target, which can be found an optimal value in every particular case.

Keywords: detumbling, laser ablation drive, space target, space debris remove

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Authors: Jun Yang, Norbert Schulz, Claude Canizares

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Knowing the dust content in the interstellar matter is necessary to understand the composition and evolution of the interstellar medium (ISM). The metal composition of the ISM enables us to study the cooling and heating processes that dominate the star formation rates in our Galaxy. The Chandra High Energy Transmission Grating (HETG) Spectrometer provides a unique opportunity to measure element dust compositions through X-ray edge absorption structure. We measure gas to dust optical depth ratios towards 9 bright Low-Mass X-ray Binaries (LMXBs) in the Galactic Bulge with the highest precision so far. Well calibrated and pile-up free optical depths are measured with the HETG spectrometer with respect to broadband hydrogen equivalent absorption in bright LMXBs: 4U 1636-53, Ser X-1, GX 3+1, 4U 1728-34, 4U 1705-44, GX 340+0, GX 13+1, GX 5-1, and GX 349+2. From the optical depths results, we deduce gas to dust ratios for various silicates in the ISM and present our results for the Si K edge in different lines of sight towards the Galactic Bulge.

Keywords: low-mass X-ray binaries, interstellar medium, gas to dust ratio, spectrometer

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Authors: Somayeh Lotfi, Manuel Eggimann, Eckhard Wagner, Radosław Mróz, Jan Deja

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One of the main environmental challenges in the construction industry is a strong social force to decrease the bulk transport of the building materials in urban environments. Considering this fact, applying more in-situ recycling technologies for Construction and Demolition Waste (CDW) is an urgent need. The European C2CA project develops a novel concrete recycling technology that can be performed purely mechanically and in situ. The technology consists of a combination of smart demolition, gentle grinding of the crushed concrete in an autogenous mill, and a novel dry classification technology called ADR to remove the fines. The feasibility of this recycling process was examined in demonstration projects involving in total 20,000 tons of End of Life (EOL) concrete from two office towers in Groningen, The Netherlands. This paper concentrates on the second demonstration project of C2CA, where EOL concrete was recycled on an industrial site. After recycling, the properties of the produced Recycled Aggregate (RA) were investigated, and results are presented. An experimental study was carried out on mechanical and durability properties of produced Recycled Aggregate Concrete (RAC) compared to those of the Natural Aggregate Concrete (NAC). The aim was to understand the importance of RA substitution, w/c ratio and type of cement to the properties of RAC. In this regard, two series of reference concrete with strength classes of C25/30 and C45/55 were produced using natural coarse aggregates (rounded and crushed) and natural sand. The RAC series were created by replacing parts of the natural aggregate, resulting in series of concrete with 0%, 20%, 50% and 100% of RA. Results show that the concrete mix design and type of cement have a decisive effect on the properties of RAC. On the other hand, the substitution of RA even at a high percentage replacement level has a minor and manageable impact on the performance of RAC. This result is a good indication towards the feasibility of using RA in structural concrete by modifying the mix design and using a proper type of cement.

Keywords: C2CA, ADR, concrete recycling, recycled aggregate, durability

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Authors: Trad Khodja Rafik, Mahtout Amine, Ghoul Rachid, Benbouali Amine, Boulahlib Amine, Hariza Abdelmalik

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Cranioplasty with custom implant realized using 3D printing technology. Cranioplasty is a surgical act that aims restoring cranial bone losses in order to protect the brain from external aggressions and to improve the patient aesthetic appearance. This objective can be achieved with taking advantage of the current technological development in computer science and biomechanics. The objective of this paper it to present an approach for the realization of high precision biocompatible cranial implants using new 3D printing technologies at the lowest cost. The proposed method is to reproduce the missing part of the skull by referring to its healthy contralateral part. Once the model is validated by the neurosurgeons, a mold is 3D printed for the production of a biocompatible implant in Poly-Methyl-Methacrylate (PMMA) acrylic cement. Using this procedure four patients underwent this procedure with excellent aesthetic results.

Keywords: cranioplasty, cranial bone loss, 3D printing technology, custom-made implants, PMMA

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Authors: Behnam Madadnia

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For several years, 3D-shaped electronics have been rising, with many uses in home appliances, automotive, and manufacturing. One of the biggest challenges in the fabrication of 3D shape electronics, which are made by thermoforming, is repeatable and accurate component positioning, and typically there is no control over the final position of the component. This paper aims to address this issue and present a reliable approach for guiding the electronic components in the desired place during thermoforming. We have proposed a heat-control mask in the thermoforming machine to control the heating of the polymer, not allowing specific parts to be formable, which can assure the conductive traces' mechanical stability during thermoforming of the substrate. We have verified our approach's accuracy by applying our method on a real industrial semi-sphere mold for positioning 7 LEDs and one touch sensor. We measured the LEDs' position after thermoforming to prove the process's repeatability. The experiment results demonstrate that the proposed method is capable of positioning electronic components in thermoformed 3D electronics with high precision.

Keywords: 3D-shaped electronics, electronic components, thermoforming, component positioning

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Authors: Talha A. Al-Dubai, Rashad A. Bantan, Ramadan H. Abu-Zied, Brian G. Jones, Aaid G. Al-Zubieri

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Contemporary foraminiferal samples sediments were collected from the intertidal sabkha of Al-Kharrar Lagoon, Saudi Arabia, to study the vertical distribution of Foraminifera and, based on a modern training set, their potential to develop a predictor of former sea-level changes in the area. Based on hierarchical cluster analysis, the intertidal sabkha is divided into three vertical zones (A, B & C) represented by three foraminiferal assemblages, where agglutinated species occupied Zone A and calcareous species occupied the other two zones. In Zone A (high intertidal), Agglutinella compressa, Clavulina angularis and C. multicamerata are dominant species with a minor presence of Peneroplis planatus, Coscinospira hemprichii, Sorites orbiculus, Quinqueloculina lamarckiana, Q. seminula, Ammonia convexa and A. tepida. In contrast, in Zone B (middle intertidal) the most abundant species are P. planatus, C. hemprichii, S. orbiculus, Q. lamarckiana, Q. seminula and Q. laevigata, while Zone C (low intertidal) is characterised by C. hemprichii, Q. costata, S. orbiculus, P. planatus, A. convexa, A. tepida, Spiroloculina communis and S. costigera. A transfer function for sea-level reconstruction was developed using a modern dataset of 75 contemporary sediment samples and 99 species collected from several transects across the sabkha. The model provided an error of 0.12m, suggesting that intertidal foraminifers are able to predict the past sea-level changes with high precision in Al-Kharrar Lagoon, and thus the future prediction of those changes in the area.

Keywords: Lagoonal foraminifers, intertidal sabkha, vertical zonation, transfer function, sea level

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Authors: Seyedmahdi Mousavihashemi

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Natural Akermanite (NAM) has been successfully prepared by a modified sol-gel method. Optimization in calcination temperature and mechanical ball milling resulted in a pure and nano-sized powder which characterized by means of scanning electron microscopy (SEM), X-ray diffraction (XRD), transmission electron microscopy (TEM) and Fourier transform infrared Spectroscopy (FT–IR). We hypothesized that nano-sized Akermanite (AM) would mimic more efficiently the nanocrystal structure and function of natural bone apatite, owing to the higher surface area, compare to conventional micron-size Akermanite (AM). Accordingly, we used the unique advantage of nanotechnology to improve novel nano akermanite particles as a potential candidate for bone tissue regeneration whether as a per implant filling powder or in combination with other biomaterials as a composite scaffold. Pure Akermanite (PAM) powders were successfully obtained via a simple sol-gel method followed by calcination at 1250 °C. Mechanical grinding in a ceramic ball mill for 7 hours resulted in akermanite (AM) nanoparticles in the range of about 30- 45 nm.

Keywords: biomedical engineering, nano composite, SEM, TEM

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Authors: Milad Abbasi

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Carbon fiber-reinforced polymer (CFRP) composite structures are increasingly being utilized in the automotive industry due to their lightweight and specific energy absorption capabilities. Although it is impossible to predict composite mechanical properties directly using theoretical methods, various research has been conducted so far in the literature for accurate simulation of CFRP structures' energy-absorbing behavior. In this research, axial compression experiments were carried out on hand lay-up unidirectional CFRP composite tubes. The fabrication method allowed the authors to extract the material properties of the CFRPs using ASTM D3039, D3410, and D3518 standards. A neural network machine learning algorithm was then utilized to build a robust prediction model to forecast the axial compressive properties of CFRP tubes while reducing high-cost experimental efforts. The predicted results have been compared with the experimental outcomes in terms of load-carrying capacity and energy absorption capability. The results showed high accuracy and precision in the prediction of the energy-absorption capacity of the CFRP tubes. This research also demonstrates the effectiveness and challenges of machine learning techniques in the robust simulation of composites' energy-absorption behavior. Interestingly, the proposed method considerably condensed numerical and experimental efforts in the simulation and calibration of CFRP composite tubes subjected to compressive loading.

Keywords: CFRP composite tubes, energy absorption, crushing behavior, machine learning, neural network

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Authors: Khavieya Anandhan, Soundarapandian Santhanakrishnan, Vijayaraghavan Laxmanan

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In general, measurement of surfaces is carried out by using traditional methods such as contact type stylus instruments. This prevalent approach is challenged by using non-contact instruments such as optical profiler, co-ordinate measuring machine, laser triangulation sensors, machine vision system, etc. Recently, confocal sensor is trying to be used in the surface metrology field. This sensor, such as a confocal sensor, is explored in this study to determine the surface roughness value for various turned surfaces. Turning is a crucial machining process to manufacture products such as grooves, tapered domes, threads, tapers, etc. The roughness value of turned surfaces are in the range of range 0.4-12.5 µm, were taken for analysis. Three instruments were used, namely, perthometer, optical profiler, and confocal sensor. Among these, in fact, a confocal sensor is least explored, despite its good resolution about 5 nm. Thus, such a high-precision sensor was used in this study to explore the possibility of measuring turned surfaces. Further, using this data, measurement uncertainty was also studied.

Keywords: confocal sensor, optical profiler, surface roughness, turned surfaces

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Authors: Thidarat Duangyod, Chanida Palanuvej, Nijsiri Ruangrungsi

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Pentace burmanica Kurz., belonging to the Malvaceae family, is commonly used for anti-diarrhea in Thai traditional medicine. A method for quantification of (+)-catechin and (-)-epicatechin in P. burmanica stem bark from 12 different Thailand markets by reverse-phase high performance liquid chromatography (HPLC) was investigated and validated. The analysis was performed by a Shimadzu DGU-20A3 HPLC equipped with a Shimadzu SPD-M20A photo diode array detector. The separation was accomplished with an Inersil ODS-3 column (5 µm x 4.6 x 250 mm) using 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B) as mobile phase at the flow rate of 1 ml/min. The isocratic was set at 20% B for 15 min and the column temperature was maintained at 40 ºC. The detection was at the wavelength of 280 nm. Both (+)-catechin and (-)-epicatechin existed in the ethanolic extract of P. burmanica stem bark. The content of (-)-epicatechin was found as 59.74 ± 1.69 µg/mg of crude extract. In contrast, the quantitation of (+)-catechin content was omitted because of its small amount. The method was linear over a range of 5-200 µg/ml with good coefficients (r2 > 0.99) for (+)-catechin and (-)-epicatechin. Limit of detection values were found to be 4.80 µg/ml for (+)-catechin and 5.14 µg/ml for (-)-epicatechin. Limit of quantitation of (+)-catechin and (-)-epicatechin were of 14.54 µg/ml and 15.57 µg/ml respectively. Good repeatability and intermediate precision (%RSD < 3) were found in this study. The average recoveries of both (+)-catechin and (-)-epicatechin were obtained with good recovery in the range of 91.11 – 97.02% and 88.53 – 93.78%, respectively, with the %RSD less than 2. The peak purity indices of catechins were more than 0.99. The results suggested that HPLC method proved to be precise and accurate and the method can be conveniently used for (+)-catechin and (-)-epicatechin determination in ethanolic extract of P. burmanica stem bark. Moreover, the stem bark of P. burmanica was found to be a rich source of (-)-epicatechin.

Keywords: pentace burmanica, (+)-catechin, (-)-epicatechin, high performance liquid chromatography

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Authors: Ismaila Olabisi Ogundiji, Hakeem Mayowa Olujide, Qasim Usamot

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The main reasons for site-specific management for agricultural inputs are to increase the profitability of crop production, to protect the environment and to improve products’ quality. Information about the variability of different soil attributes within a field is highly essential for the decision-making process. Lack of fast and accurate acquisition of soil characteristics remains one of the biggest limitations of precision agriculture due to being expensive and time-consuming. Adaptive sampling has been proven as an accurate and affordable sampling technique for planning within a field for site-specific management of agricultural inputs. This study employed spatial uncertainty of soil apparent electrical conductivity (ECa) estimates to identify adaptive re-survey areas in the field. The original dataset was grouped into validation and calibration groups where the calibration group was sub-grouped into three sets of different measurements pass intervals. A conditional simulation was performed on the field ECa to evaluate the ECa spatial uncertainty estimates by the use of the geostatistical technique. The grouping of high-uncertainty areas for each set was done using image segmentation in MATLAB, then, high and low area value-separate was identified. Finally, an adaptive re-survey was carried out on those areas of high-uncertainty. Adding adaptive re-surveying significantly minimized the time required for resampling whole field and resulted in ECa with minimal error. For the most spacious transect, the root mean square error (RMSE) yielded from an initial crude sampling survey was minimized after an adaptive re-survey, which was close to that value of the ECa yielded with an all-field re-survey. The estimated sampling time for the adaptive re-survey was found to be 45% lesser than that of all-field re-survey. The results indicate that designing adaptive sampling through spatial uncertainty models significantly mitigates sampling cost, and there was still conformity in the accuracy of the observations.

Keywords: soil electrical conductivity, adaptive sampling, conditional simulation, spatial uncertainty, site-specific management

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Authors: Mohammad Syed Ali Molla, Mohammed Azim, Mohammad Esharuzzaman

Abstract:

Centrifugal-casting machine is used in manufacturing special machine components like multi-layer journal bearing used in all internal combustion engine, steam, gas turbine and air craft turboengine where isotropic properties and high precisions are desired. Moreover, this machine can be used in manufacturing thin wall hightech machine components like cylinder liners and piston rings of IC engine and other machine parts like sleeves, and bushes. Heavy-duty machine component like railway wheel can also be prepared by centrifugal casting. A lot of technological developments are required in casting process for production of good casted machine body and machine parts. Usually defects like blowholes, surface roughness, chilled surface etc. are found in sand casted machine parts. But these can be removed by centrifugal casting machine using rotating metallic die. Moreover, die rotation, its temperature control, and good pouring practice can contribute to the quality of casting because of the fact that the soundness of a casting in large part depends upon how the metal enters into the mold or dies and solidifies. Poor pouring practice leads to variety of casting defects such as temperature loss, low quality casting, excessive turbulence, over pouring etc. Besides these, handling of molten metal is very unsecured and dangerous for the workers. In order to get rid of all these problems, the need of an automatic pouring device arises. In this research work, a robot assisted pouring device and a centrifugal casting machine are designed, developed constructed and tested experimentally which are found to work satisfactorily. The robot assisted pouring device is further modified and developed for using it in actual metal casting process. Lot of settings and tests are required to control the system and ultimately it can be used in automation of centrifugal casting machine to produce high-tech machine parts with desired precision.

Keywords: bearing, centrifugal casting, cylinder liners, robot

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Authors: A. Soria-Verdugo, A. Morato-Godino, L. M. García-Gutiérrez, N. García-Hernando

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The evolution of the pyrolysis of sewage sludge in a fixed and a fluidized bed was analyzed using a novel measuring technique. This original measuring technique consists of installing the whole reactor over a precision scale, capable of measuring the mass of the complete reactor with enough precision to detect the mass released by the sewage sludge sample during its pyrolysis. The inert conditions required for the pyrolysis process were obtained supplying the bed with a nitrogen flowrate, and the bed temperature was adjusted to either 500 ºC or 600 ºC using a group of three electric resistors. The sewage sludge sample was supplied through the top of the bed in a batch of 10 g. The measurement of the mass released by the sewage sludge sample was employed to determine the evolution of the reaction rate during the pyrolysis, the total amount of volatile matter released, and the pyrolysis time. The pyrolysis tests of sewage sludge in the fluidized bed were conducted using two different bed materials of the same size but different densities: silica sand and sepiolite particles. The higher density of silica sand particles induces a flotsam behavior for the sewage sludge particles which move close to the bed surface. In contrast, the lower density of sepiolite produces a neutrally-buoyant behavior for the sewage sludge particles, which shows a proper circulation throughout the whole bed in this case. The analysis of the evolution of the pyrolysis process in both fluidized beds show that the pyrolysis is faster when buoyancy effects are negligible, i.e. in the bed conformed by sepiolite particles. Moreover, sepiolite was found to show an absorbent capability for the volatile matter released during the pyrolysis of sewage sludge.

Keywords: bubbling fluidized bed, pyrolysis, reaction rate, segregation effects, sewage sludge

Procedia PDF Downloads 337

Authors: A. El Hamdouni, J. Zbitou, A. Tajmouati, L. El Abdellaoui, A. Errkik, A. Tribak, M. Latrach

Abstract:

This paper presents a novel fractal antenna structure proposed for UWB (Ultra – Wideband) applications. The frequency band 3.1-10.6 GHz released by FCC (Federal Communication Commission) as the commercial operation of UWB has been chosen as frequency range for this antenna based on coplanar waveguide (CPW) feed and circular shapes fulfilled according to fractal geometry. The proposed antenna is validated and designed by using an FR4 substrate with overall area of 34 x 43 mm2. The simulated results performed by CST-Microwave Studio and compared by ADS (Advanced Design System) show good matching input impedance with return loss less than -10 dB between 2.9 GHz and 11 GHz.

Keywords: Fractal antenna, Fractal Geometry, CPW Feed, UWB, FCC

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Authors: Deepanjali Gurav, Kun Qian

Abstract:

In-vitro metabolic diagnosis relies on designed materials-based analytical platforms for detection of selected metabolites in biological samples, which has a key role in disease detection and therapeutic evaluation in clinics. However, the basic challenge deals with developing a simple approach for metabolic analysis in bio-samples with high sample complexity and low molecular abundance. In this work, we report a designer plasmonic nanoshells based platform for direct detection of small metabolites in clinical samples for in-vitro metabolic diagnostics. We first synthesized a series of plasmonic core-shell particles with tunable nanoshell structures. The optimized plasmonic nanoshells as new matrices allowed fast, multiplex, sensitive, and selective LDI MS (Laser desorption/ionization mass spectrometry) detection of small metabolites in 0.5 μL of bio-fluids without enrichment or purification. Furthermore, coupling with isotopic quantification of selected metabolites, we demonstrated the use of these plasmonic nanoshells for disease detection and therapeutic evaluation in clinics. For disease detection, we identified patients with postoperative brain infection through glucose quantitation and daily monitoring by cerebrospinal fluid (CSF) analysis. For therapeutic evaluation, we investigated drug distribution in blood and CSF systems and validated the function and permeability of blood-brain/CSF-barriers, during therapeutic treatment of patients with cerebral edema for pharmacokinetic study. Our work sheds light on the design of materials for high-performance metabolic analysis and precision diagnostics in real cases.

Keywords: plasmonic nanoparticles, metabolites, fingerprinting, mass spectrometry, in-vitro diagnostics

Procedia PDF Downloads 118

Authors: Bitewulign Mekonnen

Abstract:

Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Moses Basitere, Marshal Sherene Sheldon, Seteno Karabo Obed Ntwampe, Debbie Dejager

Abstract:

In South Africa, Poultry slaughterhouses consume largest amount of freshwater and discharges high strength wastewater, which can be treated successfully at low cost using anaerobic digesters. In this study, the performance of bench-scale mesophilic Static Granular Bed Reactor (SGBR) containing fully anaerobic granules coupled with ultra-filtration (UF) membrane as a post-treatment for poultry slaughterhouse wastewater was investigated. The poultry slaughterhouse was characterized by chemical oxygen demand (COD) range between 2000 and 6000 mg/l, average biological oxygen demand (BOD) of 2375 mg/l and average fats, oil and grease (FOG) of 554 mg/l. A continuous SGBR anaerobic reactor was operated for 6 weeks at different hydraulic retention time (HRT) and an Organic loading rate. The results showed an average COD removal was greater than 90% for both the SGBR anaerobic digester and ultrafiltration membrane. The total suspended solids and fats oil and grease (FOG) removal was greater than 95%. The SGBR reactor coupled with UF membrane showed a greater potential to treat poultry slaughterhouse wastewater.

Keywords: chemical oxygen demand, poultry slaughterhouse wastewater, static granular bed reactor, ultrafiltration, wastewater

Procedia PDF Downloads 364