Search results for: mixed shape morphology

Authors: Khamael M. Abualnaja, Lidija Šiller, Ben R. Horrocks

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The structural characterization of silicon nano crystals (SiNCs) have been carried out using transmission electron microscope (TEM) and atomic force microscopy (AFM). SiNCs are crystalline with an average diameter of 65 nm. Erbium trichloride was added to silicon nano crystals using a simple chemical procedure. Erbium is useful in this context because it has a narrow emission band at ⋍1536 nm which corresponds to a standard optical telecommunication wavelength. The optical properties of SiNCs and erbium-mixed SiNCs samples have been characterized using UV-vis spectroscopy, confocal Raman spectroscopy and photoluminescence spectroscopy (PL). SiNCs and erbium-mixed SiNCs samples exhibit an orange PL emission peak at around 595 nm that arise from radiative recombination of Si. Erbium-mixed SiNCs also shows a weak PL emission peak at ⋍1536 nm that attributed to the intra-4f transition in erbium ions. The intensity of the PL peak of Si in erbium-mixed SiNCs is increased in the intensity up to ×3 as compared to pure SiNCs. It was observed that intensity of 1536 nm peak decreased dramatically in the presence of silicon nano crystals and the PL emission peak of silicon nano crystals is increased. Therefore, the resulted data present that the energy transfer from erbium ions to SiNCs due to the chemical mixing method which used in this work.

Keywords: Silicon Nanocrystals (SiNCs), Erbium Ion, photoluminescence, energy transfer

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Authors: Tahmina Sultana, Yasser Hassan

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Vehicle technologies rapidly evolving due to their multifaceted advantages. Adapted different vehicle technologies like connectivity and automation on the same roads with conventional vehicles controlled by human drivers may increase speed disparity in mixed vehicle technologies. Identifying relationships between speed distribution measures of different vehicles and road geometry can be an indicator of speed disparity in mixed technologies. Previous studies proved that speed disparity measures and traffic accidents are inextricably related. Horizontal curves from three geographic areas were selected based on relevant criteria, and speed data were collected at the midpoint of the preceding tangent and starting, ending, and middle point of the curve. Multiple linear mixed effect models (LME) were developed using the instantaneous speed measures representing the speed of vehicles at different points of horizontal curves to recognize relationships between speed variance (standard deviation) and road geometry. A simulation-based framework (Monte Carlo) was introduced to check the speed disparity on horizontal curves in mixed vehicle technologies when consideration is given to the interactions among connected vehicles (CVs), autonomous vehicles (AVs), and non-connected vehicles (NCVs) on horizontal curves. The Monte Carlo method was used in the simulation to randomly sample values for the various parameters from their respective distributions. Theresults show that NCVs had higher speed variation than CVs and AVs. In addition, AVs and CVs contributed to reduce speed disparity in the mixed vehicle technologies in any penetration rates.

Keywords: autonomous vehicles, connected vehicles, non-connected vehicles, speed variance

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Authors: Rajni Kant Panik

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The aim of the present study was to develop and evaluate mupirocin loaded nanoparticle incorporated into hydrogel as an infected wound healer. Incorporated Nanoparticle in hydrogel provides a barrier that effectively prevents the contamination of the wound and further progression of infection to deeper tissues. Hydrogel creates moist healing environment on wound space with good fluid absorbance. Nanoparticles were prepared by double emulsion solvent evaporation method using different ratios of PLGA polymer and the hydrogels was developed using sodium alginate and gelatin. Further prepared nanoparticles were then incorporated into the hydrogels. The formulations were characterized by FT-IR and DSC for drug and polymer compatibility and surface morphology was studied by TEM. Nanoparticle hydrogel were evaluated for their size, shape, encapsulation efficiency and for in vitro studies. The FT-IR and DSC confirmed the absence of any drug polymer interaction. The average size of Nanoparticle was found to be in range of 208.21-412.33 nm and shape was found to be spherical. The maximum encapsulation efficiency was found to be 69.03%. The in vitro release profile of Nanoparticle incorporated hydrogel formulation was found to give sustained release of drug. Antimicrobial activity testing confirmed that encapsulated drug preserve its effectiveness. The stability study confirmed that the formulation prepared were stable. Present study complements our finding that mupirocin loaded Nanoparticle incorporated into hydrogel has the potential to be an effective and safe novel addition for the release of mupirocin in sustained manner, which may be a better option for the management of wound. These finding also supports the progression of antibiotic via hydrogel delivery system is a novel topical dosage form for the management of wound.

Keywords: hydrogel, nanoparticle, PLGA, wound healing

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Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

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This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

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Authors: Fatma Zehra Doğru, Olcay Arslan

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In this paper, we propose alternative robust estimators for the shape parameters of the Burr XII distribution. We provide a small simulation study and a real data example to illustrate the performance of the proposed estimators over the ML and the LS estimators.

Keywords: burr xii distribution, robust estimator, m-estimator, least squares

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Authors: Pooja Mongia Raj, Rakesh Raj, Alpana Ram

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Background: The use of multiparticulate drug delivery systems in preference to single unit dosage forms for colon targeting purposes dates back to 1985 when Hardy and co-workers showed that multiparticulate systems enabled the drug to reach the colon quickly and were retained in the ascending colon for a relatively long period of time. Methods: Site-specific colonic drug delivery system (nanoparticles) of 5-ASA were prepared and coated with pH sensitive polymer. Chitosan nanoparticles (CTNP) bearing 5-Amino salicylic acid (5-ASA) were prepared, by ionotropic gelation method. Nanoparticulate dosage form consisting of a hydrophobic core enteric coated with pH-dependent polymer Eudragit S-100 by solvent evaporation method, for the effective delivery of drug to the colon for treatment of ulcerative colitis. Results: The mean diameter of CTNP and ECTNP formulations were 159 and 661 nm, respectively. Also optimum value of polydispersity index was found to be 0.249 [count rate (kcps) was 251.2] and 0.170 [count rate (kcps) was 173.9] was obtained for both the formulations respectively. Conclusion: CTNP and Eudragit chitosan nanoparticles (ECTNP) was characterized for shape and surface morphology by scanning electron microscopy (SEM) appeared to be spherical in shape. The in vitro drug release was investigated using USP dissolution test apparatus in different simulated GIT fluids showed promising release. In vivo experiments are in further proceeding for fruitful results.

Keywords: colon targeting, nanoparticles, polymer, 5-amino salicylic acid, edragit

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Authors: I. Yalcin Enis, J. Vojtech, T. Gok Sadikoglu

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In this study, polycaprolactone (PCL) was dissolved in chloroform: ethanol solvent system at a concentration of 18 w/v %. 1, 2, 4, and 6 droplets of formic acid were added to the prepared 10ml PCL-chloroform:ethanol solutions separately. Fibrous webs were produced by electrospinning technique. Morphology of the webs was investigated by using scanning electron microscopy (SEM) whereas fiber diameters were measured by Image J Software System. The effect of formic acid addition to the mostly used chloroform solvent on fiber morphology was examined.

Keywords: chloroform, electrospinning, formic acid polycaprolactone, fiber

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Authors: M. Zareh, H. Mohammadi, B. Naser

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Atherosclerotic plaque rupture is the main trigger of heart attack and brain stroke which are the leading cause of death in developed countries. Better understanding of rupture-prone plaque can help clinicians detect vulnerable plaques- rupture prone or instable plaques- and apply immediate medical treatment to prevent these life-threatening cardiovascular events. Therefore, there are plenty of studies addressing disclosure of vulnerable plaques properties. Necrotic core and fibrous tissue are two major tissues constituting atherosclerotic plaque; using histopathological and numerical approaches, many studies have demonstrated that plaque rupture is strongly associated with a large necrotic core and a thin fibrous cap, two morphological characteristic which can be acquired by two-dimensional imaging of atherosclerotic plaque present in coronary and carotid arteries. Plaque rupture is widely considered as a mechanical failure inside plaque tissue; this failure occurs when the stress within plaque excesses the strength of tissue material; hence, finite element method, a strong numerical approach, has been extensively applied to estimate stress distribution within plaques with different compositions which is then used for assessment of various vulnerability characteristics including plaque morphology, material properties and blood pressure. This study aims to evaluate significance of three-dimensional morphology on vulnerability degree of atherosclerotic plaque. To reach this end, different two-dimensional geometrical models of atherosclerotic plaques are considered based on available data and named Main 2D Models (M2M). Then, for each of these M2Ms, two three-dimensional idealistic models are created. These two 3D models represent two possible three-dimensional morphologies which might exist for a plaque with similar 2D morphology to one of M2Ms. Finite element method is employed to estimate stress, von-Mises stress, within each 3D models. Results indicate that for each M2Ms stress can significantly varies due to possible 3D morphological changes in that plaque. Also, our results show that an atherosclerotic plaque with thick cap may experience rupture if it has a critical 3D morphology. This study highlights the effect of 3D geometry of plaque on its instability degree and suggests that 3D morphology of plaque might be necessary to more effectively and accurately assess atherosclerotic plaque vulnerability.

Keywords: atherosclerotic plaque, plaque rupture, finite element method, 3D model

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Authors: Pavel Kotin, Sergey Dotofeev, Daniil Kozlov, Alexey Garshev

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We propose the investigation of CdSe quantum dots which were synthesized in the presence of silver halides. To understand a process of nanoparticle formation in more detail, we varied the silver halide amount in the synthesis and proposed a sampling during colloidal growth. The attempts were focused on the investigation of shape, structure and optical properties of nanoparticles. We used the colloidal method of synthesis. Cadmium oleate, tri-n-octylphosphine selenide (TOPSe) and AgHal in TOP were precursors of cadmium, selenium and silver halides correspondingly. The molar Ag/Cd ratio in synthesis was varied from 1/16 to 1/1. The sampling was basically realized in 20 sec, 5 min, and 30 min after the beginning of quantum dots nucleation. To investigate nanoparticles we used transmission electron microscopy (including high resolution one), X-ray diffraction, and optical spectroscopy. It was established that silver halides lead to obtaining tetrapods with different leg length and large ellipsoidal nanoparticles possessing an intensive near IR photoluminescence. The change of the amount of silver halide in synthesis and the selection of an optimal growth time allows controlling the shape and the share of tetrapods or ellipsoidal nanoparticles in the product. Our main attempts were focused on a detailed investigation of the quantum dots structure and shape evolution and, finally, on mechanisms of such nanoparticle formation.

Keywords: colloidal quantum dots, shape evolution, silver doping, tetrapods

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Authors: Yunjia Wang, Zhihong Zhao, Erxiang Song

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Rockfills are widely used in civil engineering, such as dams, railways, and airport foundations in mountain areas. A significant long-term post-construction settlement may affect the serviceability or even the safety of rockfill infrastructures. The creep behavior of rockfills is influenced by a number of factors, such as particle size, strength and shape, water condition and stress level. However, the effect of particle shape on rockfill creep still remains poorly understood, which deserves a careful investigation. Particle-based discrete element method (DEM) was used to simulate the creep behavior of rockfills under different boundary conditions. Both angular and rounded particles were considered in this numerical study, in order to investigate the influence of particle shape. The preliminary results showed that angular particles experience more breakages and larger creep strains under one-dimensional compression than rounded particles. On the contrary, larger creep strains were observed in he rounded specimens in the direct shear test. The mechanism responsible for this difference is that the possibility of the existence of key particle in rounded particles is higher than that in angular particles. The above simulations demonstrate that the influence of particle shape on the creep behavior of rockfills can be simulated by DEM properly. The method of DEM simulation may facilitate our understanding of deformation properties of rockfill materials.

Keywords: rockfills, creep behavior, particle crushing, discrete element method, boundary conditions

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Authors: Armin Shirbazo, Mohammad Vahab, Hamed Lamei Ramandi, Jalal Fahimpour

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One of the most effective ways for increasing production in wells that are faced with problems such as pressure depletion and low rate is hydraulic fracturing. Hydraulic fracturing is creating a high permeable path through the reservoir and simulated area around the wellbore. This is very important for low permeability reservoirs, which their production is uneconomical. In this study, the influence of the fracturing pattern in multi-stage fractured horizontal wells is analyzed for a tight, heavy oil reservoir to explore the impact of fracturing patterns on improving oil recovery. The horizontal well has five transverse fractures with the same fracture length, width, height, and conductivity properties. The fracture patterns are divided into four distinct shapes: uniform shape, diamond shape, U shape, and W shape. The results show that different fracturing patterns produce various cumulative production after ten years, and the best pattern can be selected based on the most cumulative production. The result also illustrates that optimum design in fracturing can boost the production up to 3% through the permeability distribution around the wellbore and reservoir.

Keywords: multi-stage fracturing, horizontal well, fracture patterns, fracture length, number of stages

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Authors: Yousif Mohamed Y. Abdallah, Mommen A. Alkhir, Amel S. Algaddal

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This was experimental study conducted to study segmentation of brain in MRI images using edge detection and morphology filters. For brain MRI images each film scanned using digitizer scanner then treated by using image processing program (MatLab), where the segmentation was studied. The scanned image was saved in a TIFF file format to preserve the quality of the image. Brain tissue can be easily detected in MRI image if the object has sufficient contrast from the background. We use edge detection and basic morphology tools to detect a brain. The segmentation of MRI images steps using detection and morphology filters were image reading, detection entire brain, dilation of the image, filling interior gaps inside the image, removal connected objects on borders and smoothen the object (brain). The results of this study were that it showed an alternate method for displaying the segmented object would be to place an outline around the segmented brain. Those filters approaches can help in removal of unwanted background information and increase diagnostic information of Brain MRI.

Keywords: improvement, brain, matlab, markers, boundaries

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Authors: Sang Hwan Bak, Min Jung Kim, Dong Bok Lee

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Fe-2%Mn-0.5%Si-0.2C steel was welded and corroded at 600, 700 and 800oC for 20 h in 1 atm of N2/H2S/H2O-mixed gas in order to characterize the high-temperature corrosion behavior of the welded joint. Corrosion proceeded fast and almost linearly. It increased with an increase in the corrosion temperature. H2S formed FeS owing to sulfur released from H2S. The scales were fragile and nonadherent.

Keywords: Fe-Mn-Si steel, corrosion, welding, sulfidation, H2S gas

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Authors: Partha Sarathi Mondal, Srabani Sanyal

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Different geomorphic agents produce a different landforms pattern. Similarly rivers also have a distinct and diverse landforms pattern. And even, within a river course different and distinct assemblage of landforms i.e. morphological variability are seen. These morphological variability are produced by different river processes. Channel and floodplain morphology helps to interpret river processes. Consequently morphological variability can be used as an important tool for assessing river processes, hydrological connectivity and river health, which will help us to draw inference about river processes and therefore, management of river health. The present study is documented on West Rapti river, a trans-boundary river flowing through Nepal and India, from its source to confluence with Ghaghra river in India. The river shows a significant morphological variability throughout its course. The present study tries to find out factors and processes responsible for the morphological variability of the river and in which way it can be applied in river management practices. For this purpose channel and floodplain morphology of West Rapti river was mapped as accurately as possible and then on the basis of process-form interactions, inferences are drawn to understand factors of morphological variability. The study shows that the valley setting of West Rapti river, in the Himalayan region, is confined and somewhere partly confined whereas, channel of the West Rapti river is single thread in most part of Himalayan region and braided in valley region. In the foothill region valley is unconfined and channel is braided, in middle part channel is meandering and valley is unconfined, whereas, channel is anthropogenically altered in the lower part of the course. Due to this the morphology of West Rapti river is highly diverse. These morphological variability are produced by different geomorphic processes. Therefore, for any river management it is essential to sustain these morphological variability so that the river could not cross the geomorphic threshold and environmental flow of the river along with the biodiversity of riparian region is maintained.

Keywords: channel morphology, environmental flow, floodplain morphology, geomorphic threshold

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Authors: Ebert Brea

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We propose a novel direct search algorithm for identifying at least a local minimum of mixed integer nonlinear unconstrained optimization problems. The Mixed Integer Randomized Pattern Search Algorithm (MIRPSA), so-called by the author, is based on a randomized pattern search, which is modified by the MIRPSA for finding at least a local minimum of our problem. The MIRPSA has two main operations over the randomized pattern search: moving operation and shrinking operation. Each operation is carried out by the algorithm when a set of conditions is held. The convergence properties of the MIRPSA is analyzed using a Markov chain approach, which is represented by an infinite countable set of state space λ, where each state d(q) is defined by a measure of the qth randomized pattern search Hq, for all q in N. According to the algorithm, when a moving operation is carried out on the qth randomized pattern search Hq, the MIRPSA holds its state. Meanwhile, if the MIRPSA carries out a shrinking operation over the qth randomized pattern search Hq, the algorithm will visit the next state, this is, a shrinking operation at the qth state causes a changing of the qth state into (q+1)th state. It is worthwhile pointing out that the MIRPSA never goes back to any visited states because the MIRPSA only visits any qth by shrinking operations. In this article, we describe the MIRPSA for mixed integer nonlinear unconstrained optimization problems for doing a deep study of its convergence properties using Markov chain viewpoint. We herein include a low dimension case for showing more details of the MIRPSA, when the algorithm is used for identifying the minimum of a mixed integer quadratic function. Besides, numerical examples are also shown in order to measure the performance of the MIRPSA.

Keywords: direct search, mixed integer optimization, random search, convergence, Markov chain

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Authors: Chun-Ying Lee, Mei-Wen Wu, Li-Yi Cheng, Chiang-Ho Cheng

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This research studies the electroplating of zinc coating in the zinc chloride bath mixed with supercritical CO2. The sodium fluoride (NaF) was used as the bath additive to change the structure and property of the coating, and therefore the roughness and corrosion resistance of the zinc coating was investigated. The surface characterization was performed using optical microscope (OM), X-ray diffractometer (XRD), and α-step profilometer. Moreover, the potentiodynamic polarization measurement in 3% NaCl solution was employed in the corrosion resistance evaluation. Because of the emulsification of the electrolyte mixed in Sc-CO2, the electroplated zinc produced the coating with smoother surface, smaller grain, better throwing power and higher corrosion resistance. The main role played by the NaF was to reduce the coating’s roughness and grain size. In other words, the CO2 mixed with the electrolyte under the supercritical condition performed the similar function as brighter and leveler in zinc electroplating to enhance the throwing power and corrosion resistance of the coating.

Keywords: supercritical CO2, zinc-electroplating, sodium fluoride, electroplating

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Authors: Kotchamon Yodkhum, Thawatchai Phaechamud

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Hydrophobic chitosan-based materials have been developed as controlled drug delivery system. This study was aimed to prepare and evaluate chitosan-aluminum monostearate composite dispersion (CLA) as fabricating liquid for construct a hydrophobic, controlled-release solid drug delivery matrix. This work was attempted to blend hydrophobic substance, aluminum monostearate (AMS), with chitosan in acidic aqueous medium without using any surfactants or grafting reaction, and high temperature during mixing that are normally performed when preparing hydrophobic chitosan system. Lactic acid solution (2%w/v) was employed as chitosan solvent. CLA dispersion was prepared by dispersing different amounts of AMS (1-20% w/w) in chitosan solution (4% w/w) with continuous agitation using magnetic stirrer for 24 h. Effect of AMS amount on physicochemical properties of the dispersion such as viscosity, rheology and particle size was evaluated. Morphology of chitosan-AMS complex (dispersant) was observed under inverted microscope and atomic force microscope. Stability of CLA dispersions was evaluated after preparation within 48 h. CLA dispersions containing AMS less than 5 % w/w exhibited rheological behavior as Newtonian while that containing higher AMS amount exhibited as pseudoplastic. Particle size of the dispersant was significantly smaller when AMS amount was increased up to 5% w/w and was not different between the higher AMS amount system. Morphology of the dispersant under inverted microscope displayed irregular shape and their size exhibited the same trend with particle size measurement. Observation of the dispersion stability revealed that phase separation occurred faster in the system containing higher AMS amount which indicated lower stability of the system. However, the dispersions were homogeneous and stable more than 12 hours after preparation that enough for fabrication process. The prepared dispersions had ability to be fabricated as a porous matrix via lyophilization technique.

Keywords: chitosan, aluminum monostearate, dispersion, controlled-release

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Authors: Zellagui Rahima, Chaumont Denis, Boughelout Abderrahman, Adnane Mohamed

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Thin films of CdxZn1-xS were deposed by chemical bath deposition on glass substrates for photovoltaic applications. The thin films CdZnS were synthesized by chemical bath (CBD) with different deposition protocols for optimized the parameter of deposition as the temperature, time of deposition, concentrations of ion and pH. Surface morphology, optical and chemical composition properties of thin film CdZnS were investigated by SEM, EDAX, spectrophotometer. The transmittance is 80% in visible region 300 nm – 1000 nm; it has been observed in that films the grain size is between 50nm and 100nm measured by SEM image and we also note that the shape of particle is changing with the change in concentration. This result favors of application these films in solar cells; the chemical analysis with EDAX gives information about the presence of Cd, Zn and S elements and investigates the stoichiometry.

Keywords: thin film, solar cells, transmition, cdzns

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Authors: Hira Lal Gope, Hidekazu Fukai

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The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: convolutional neural networks, coffee bean, peaberry, sorting, support vector machine

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Authors: Eldar Mammadov, Konul Mammadova, Aytaj Ilyaszada

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Background: According to many studies, it is known that H. pylori transform into the coccoid form, which cannot be cultured and has poor metabolic activity.In this study, we succeeded in preserving the spiral shape of H.pylori for a long time by preparing a biphase transport medium with a hard bottom (Muller Hinton with 7% HRBC (horse red blood cells) agar 5ml) and liquid top part (BH (brain heart) broth + HS (horse serum)+7% HRBC+antibiotics (Vancomycin 5 mg, Trimethoprim lactate 25 mg, Polymyxin B 1250 I.U.)) in cell culture flasks with filter caps. For comparison, we also used a BH broth medium with 7% HRBC used for the transport of H.pylori. Methods: Rapid urease test positive 7 biopsy specimens were also inoculated into biphasic and BH broth medium with 7% HRBC, then put in CO2 Gaspak packages and sent to the laboratory. Then both mediums were kept in the thermostat at 37 °C for 1 day. After microscopic, PCR and urease test diagnosis, they were transferred to Columbia Agar with 7% HRBC. Incubated at 37°C for 5-7 days, cultures were examined for colony characteristics and bacterial morphology. E-test antimicrobial susceptibility test was performed. Results: There were 3 growths from biphasic transport medium passed to Columbia agar with 7% HRBC and only 1 growth from BH broth medium with 7% HRBC. It was also observed that after the first 3 days in BH broth medium with 7%, H.pylori passed into coccoid form and its biochemical activity weakened, while its spiral shape did not change for 2-3 weeks in the biphase transport medium. Conclusions: By using the biphase transport medium we have prepared; we can culture the bacterium by preventing H.pylori from spiraling into the coccoid form. In our opinion, this may result in the wide use of culture method for diagnosis of H.pylori, study of antibiotic susceptibility and molecular genetic analysis.

Keywords: clinical trial, H.pylori, coccoid form, transport medium

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Authors: Rama Shanker, Anil Kumar Sachan

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Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.

Keywords: aggregate proportions, artificial neural network, concrete grade, concrete mix design

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Authors: Areej R. Banjar, Abraham G. Campbell

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The use of Mixed Reality (MR) in teaching and training is growing popular and can improve students’ ability to perform technical procedures. This short paper outlines the creation of an interactive educational MR 3D application that aims to improve the quality of instruction for dentistry students. This application is called MRImplantology and aims to teach the fundamentals and preoperative planning of dental implant placement. MRImplantology uses cone-beam computed tomography (CBCT) images as the source for 3D dental models that dentistry students will be able to freely manipulate within a 3D MR world to aid their learning process.

Keywords: augmented reality, education, dentistry, cone-beam computed tomography CBCT, head mounted display HMD, mixed reality

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Authors: Katielly Vianna Polkowski, Rodrigo Denizarte de Oliveira Polkowski, Cristiano Grings Herbert

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The use of nanomaterials in the formulation of polymeric materials modifies their molecular structure, offering an infinite range of possibilities for the development of smart products, being of great importance for science and contemporary industry. Shape memory polymers are generally lightweight, have high shape recovery capabilities, they are easy to process and have properties that can be adapted for a variety of applications. Shape memory materials are active materials that have attracted attention due to their superior damping properties when compared to conventional structural materials. The development of methodologies capable of preparing new materials, which use graphene in their structure, represents technological innovation that transforms low-cost products into advanced materials with high added value. To obtain an improvement in the shape memory effect (SME) of polymeric materials, it is possible to use graphene in its composition containing low concentration by mass of graphene nanoplatelets (GNP), graphene oxide (GO) or other functionalized graphene, via different mixture process. As a result, there was an improvement in the SME, regarding the increase in the values of maximum strain. In addition, the use of graphene contributes to obtaining nanocomposites with superior electrical properties, greater crystallinity, as well as resistance to material degradation. The methodology used in the research is Systematic Review, scientific investigation, gathering relevant studies on influence of nanomaterials on the properties of shape memory polymeric, using the literature database as a source and study methods. In the present study, a systematic reviewwas performed of all papers published from 2014 to 2022 regarding graphene and shape memory polymeric througha search of three databases. This study allows for easy identification of themost relevant fields of study with respect to graphene and shape memory polymeric, as well as the main gaps to beexplored in the literature. The addition of graphene showed improvements in obtaining higher values of maximum deformation of the material, attributed to a possible slip between stacked or agglomerated nanostructures, as well as an increase in stiffness due to the increase in the degree of phase separation that results in a greater amount physical cross-links, referring to the formation of shortrange rigid domains.

Keywords: graphene, shape memory, smart materials, polymers, nanomaterials

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Authors: Sakshi Gupta, Seema Joshi

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Thiosemicarbazones (TSCs) have garnered significant attention in coordination chemistry due to their versatile coordination modes and pharmacological properties. Mixed ligand complexes of TSCs represent a promising area of research, offering enhanced antimicrobial activities compared to their parent compounds. This review provides an overview of the synthesis, characterization, and antimicrobial properties of mixed ligand complexes incorporating thiosemicarbazones. The synthesis of mixed ligand complexes typically involves the reaction of a metal salt with TSC ligands and additional ligands, such as nitrogen- or oxygen-based ligands. Various transition metals, including copper, nickel, and cobalt, have been employed to form mixed ligand complexes with TSCs. Characterization techniques such as spectroscopy, X-ray crystallography, and elemental analysis are commonly utilized to confirm the structures of these complexes. One of the key advantages of mixed ligand complexes is their enhanced antimicrobial activity compared to pure TSC compounds. The synergistic effect between the TSC ligands and additional ligands contributes to increased efficacy, possibly through improved metal-ligand interactions or enhanced membrane permeability. Furthermore, mixed ligand complexes offer the potential for selective targeting of microbial species while minimizing toxicity to mammalian cells. This selectivity arises from the specific interactions between the metal center, TSC ligands, and biological targets within microbial cells. Such targeted antimicrobial activity is crucial for developing effective treatments with minimal side effects. Moreover, the versatility of mixed ligand complexes allows for the design of tailored antimicrobial agents with optimized properties. By varying the metal ion, TSC ligands, and additional ligands, researchers can fine-tune the physicochemical properties and biological activities of these complexes. This tunability opens avenues for the development of novel antimicrobial agents with improved efficacy and reduced resistance. In conclusion, mixed ligand complexes of thiosemicarbazones represent a promising class of compounds with potent antimicrobial activities. Further research in this field holds great potential for the development of novel therapeutic agents to combat microbial infections effectively.

Keywords: metal complex, thiosemicarbazones, mixed ligand, selective targeting, antimicrobial activity

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Authors: Ladaporn Pithuk

Abstract:

This study aims to investigate the marketing mixed factors that affecting on expectations about commercial transactions through social networks. The research method will using quantitative research, data was collected by questionnaires to person have experience access to trading over the internet for 400 sample by purposive sampling method. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and using quality function deployment for hypothesis testing. Finding the most significant interrelationship between marketing mixed factors and commercial transactions expectations through social networks are product and place the relationship of five ties product and place (location) is involved in almost all will make the site a model that meets the needs of the user visit. In terms of price, the promotion, privacy, personalization and providing a process technical. This will make operations more efficient, reduce confusion, duplication, delays in data transmission, including the creation of different elements in products and services.

Keywords: commercial transactions expectations, marketing mixed factors, social networks, consumer behavior

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Authors: Ruby Priya, Om Parkash Pandey

Abstract:

Eu doped Gd₂O₃ phosphors are synthesized via co-precipitation method using ammonia as a precipitating agent. The concentration of the Eu was set as 4 mol% for all the samples. The effect of the surfactants (CTAB, PEG, and SDS) on the structural, morphological and luminescent properties has been studied in details. The as-synthesized phosphors were characterized by X-ray diffraction technique, Field emission scanning electron microscopy, Fourier transformed infrared spectroscopy and photoluminescence technique. It was observed that the surfactants have not changed the crystal structure, but influenced the morphology of as-synthesized phosphors to a great extent. The as-synthesized phosphors are expected to be promising candidates for optoelectronic devices, biosensors, MRI contrast agents and various biomedical applications.

Keywords: co-precipitation, Europium, photoluminescence, surfactants

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Authors: Vineeth Siripuram, Abhineet Nigam

Abstract:

A bioreactor is an engineered system that supports a biologically active environment. Along the years, the advancements in bioreactors have been widely accepted all over the world for varied applications ranging from sewage treatment to tissue cloning. Driven by tissue and organ shortage, tissue engineering has emerged as an alternative to transplantation for the reconstruction of lost or damaged organs. In this study, Computational fluid dynamics (CFD) has been used to model porous medium flow in scaffolds (taken from the literature) with different flow patterns. A detailed analysis of different scaffold geometries and their influence on cell deposition in the perfusion system is been carried out using Computational fluid dynamics (CFD). Considering the fact that, the scaffold should mimic the organs or tissues structures in a three-dimensional manner, certain assumptions were made accordingly. The research on scaffolds has been extensively carried out in different bioreactors. However, there has been less focus on the morphology of the scaffolds and the flow patterns in which the perfusion system is laid upon. The objective of this paper is to employ a computational approach using CFD simulation to determine the optimal morphology and the anisotropic measurements of the various samples of scaffolds. Using predictive computational modelling approach, variables which exert dominant effects on the cell deposition within the scaffold were prioritised and corresponding changes in morphology of scaffold and flow patterns in the perfusion systems are made. A Eulerian approach was carried on in multiple CFD simulations, and it is observed that the morphological and topological changes in the scaffold perfusion system are of great importance in the commercial applications of scaffolds.

Keywords: cell seeding, CFD, flow patterns, modelling, perfusion systems, scaffold

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Authors: Lay Poh Tan, Chor Yong Tay, Haiyang Yu

Abstract:

Micro-contact printing is a form of soft lithography that uses the relief patterns on a master polydimethylsiloxane (PDMS) stamp to form patterns of self-assembled monolayers (SAMs) of ink on the surface of a substrate through conformal contact technique. Here, we adopt this method to print proteins of different dimensions on our biodegradable polymer substrates. We started off with printing 20-500 μm scale lanes of fibronectin to engineer the shape of bone marrow derived human mesenchymal stem cell (hMSCs). After 8 hours of culture, the hMSCs adopted elongated shapes, and upon analysis of the gene expressions, genes commonly associated with myogenesis (GATA-4, MyoD1, cTnT and β-MHC) and neurogenesis (NeuroD, Nestin, GFAP, and MAP2) were up-regulated but gene expression associated to osteogenesis (ALPL, RUNX2, and SPARC) were either down modulated or remained at the nominal level. This is the first evidence that cellular morphology control via micropatterning could be used to modulate stem cell fate without external biochemical stimuli. We further our studies to modulate the focal adhesion (FA) instead of the macro shape of cells. Micro-contact printed islands of different smaller dimensions were investigated. We successfully regulated the FAs into dense FAs and elongated FAs by micropatterning. Additionally, the combined effects of hard (40.4 kPa), and intermediate (10.6 kPa) PA gel and FAs patterning on hMSCs differentiation were studied. Results showed that FA and matrix compliance plays an important role in hMSCs differentiation, and there is a cross-talk between different physical stimulants and the significance of these stimuli can only be realized if they are combined at the optimum level.

Keywords: micro-contact printing, polymer substrate, cell-material interaction, stem cell differentiation

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Authors: Vijaykumar Patel, P. Bahadur

Abstract:

Microstructural evolution of a cationic gemini surfactant 12-4-12 micelles in the presence of bile salts has been investigated using different techniques. A negative value of interaction parameter evaluated from surface tension measurements is a signature of strong synergistic interaction between oppositely charged surfactants. Both the bile salts compete with each other in inducing the micellar transition of 12-4-12 micelles depending on their hydrophobicity. Viscosity measurements disclose that loading of bile salts induces morphological changes in 12-4-12 micelles; sodium deoxycholate is more efficient in altering the aggregation behaviour of 12-4-12 micelles compared to sodium cholate and presents pronounced increase in viscosity and micellar growth which is suppressed at elevated temperatures. A remarkable growth of 12-4-12 micelles in the presence of sodium deoxycholate at low pH has been ascribed to the solubilization of bile acids formed in acidic medium. Small angle neutron scattering experiments provided size and shape of 12-4-12/bile salt mixed micelles are explicated on the basis of hydrophobicity of bile salts. The location of bile salts in micelle was determined from nuclear overhauser effect spectroscopy. The present study characterizes 12-4-12 gemini-bile salt mixed systems which significantly enriches our knowledge, and such a structural transition provides an opportunity to use these bioamphiphiles as delivery vehicles and in some pharmaceutical formulations.

Keywords: gemini surfactants, bile salts, SANS (small angle neutron scattering), NOESY (nuclear overhauser effect spectroscopy)

Procedia PDF Downloads 127

Authors: Chaitanya Varma, Arpan Mehar

Abstract:

The present study demonstrates the procedure to analyse speed data collected on various four-lane divided sections in India. Field data for the study was collected at different straight and curved sections on rural highways with the help of radar speed gun and video camera. The data collected at the sections were analysed and parameters pertain to speed distributions were estimated. The different statistical distribution was analysed on vehicle type speed data and for mixed traffic speed data. It was found that vehicle type speed data was either follows the normal distribution or Log-normal distribution, whereas the mixed traffic speed data follows more than one type of statistical distribution. The most common fit observed on mixed traffic speed data were Beta distribution and Weibull distribution. The separate operating speed model based on traffic and roadway geometric parameters were proposed in the present study. The operating speed model with traffic parameters and curve geometry parameters were established. Two different operating speed models were proposed with variables 1/R and Ln(R) and were found to be realistic with a different range of curve radius. The models developed in the present study are simple and realistic and can be used for forecasting operating speed on four-lane highways.

Keywords: highway, mixed traffic flow, modeling, operating speed

Procedia PDF Downloads 432