Search results for: fast Fourier transform

Authors: Elmira Solati, Atousa Mehrani, Davoud Dorranian

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Generation of ZnO-Au nanocomposite under laser irradiation of a mixture of the ZnO and Au colloidal suspensions are experimentally investigated. In this work, firstly ZnO and Au nanoparticles are prepared by pulsed laser ablation of the corresponding metals in water using the 1064 nm wavelength of Nd:YAG laser. In a second step, the produced ZnO and Au colloidal suspensions were mixed in different volumetric ratio and irradiated using the second harmonic of a Nd:YAG laser operating at 532 nm wavelength. The changes in the size of the nanostructure and optical properties of the ZnO-Au nanocomposite are studied as a function of the volumetric ratio of ZnO and Au colloidal suspensions. The crystalline structure of the ZnO-Au nanocomposites was analyzed by X-ray diffraction (XRD). The optical properties of the samples were examined at room temperature by a UV-Vis-NIR absorption spectrophotometer. Transmission electron microscopy (TEM) was done by placing a drop of the concentrated suspension on a carbon-coated copper grid. To further confirm the morphology of ZnO-Au nanocomposites, we performed Scanning electron microscopy (SEM) analysis. Room temperature photoluminescence (PL) of the ZnO-Au nanocomposites was measured to characterize the luminescence properties of the ZnO-Au nanocomposites. The ZnO-Au nanocomposites were characterized by Fourier transform infrared (FTIR) spectroscopy. The X-ray diffraction pattern shows that the ZnO-Au nanocomposites had the polycrystalline structure of Au. The behavior observed by images of transmission electron microscope reveals that soldering of Au and ZnO nanoparticles include their adhesion. The plasmon peak in ZnO-Au nanocomposites was red-shifted and broadened in comparison with pure Au nanoparticles. By using the Tauc’s equation, the band gap energy for ZnO-Au nanocomposites is calculated to be 3.15–3.27 eV. In this work, the formation of ZnO-Au nanocomposites shifts the FTIR peak of metal oxide bands to higher wavenumbers. PL spectra of the ZnO-Au nanocomposites show that several weak peaks in the ultraviolet region and several relatively strong peaks in the visible region. SEM image indicates that the morphology of ZnO-Au nanocomposites produced in water was spherical. The TEM images of ZnO-Au nanocomposites demonstrate that with increasing the volumetric ratio of Au colloidal suspension the adhesion increased. According to the size distribution graphs of ZnO-Au nanocomposites with increasing the volumetric ratio of Au colloidal suspension the amount of ZnO-Au nanocomposites with the smaller size is further.

Keywords: Au nanoparticles, pulsed laser ablation, ZnO-Au nanocomposites, ZnO nanoparticles

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Authors: R. Rama Kishore, Sunesh

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This paper presents an optimized, robust, and secured watermarking technique. The methodology used in this work is the combination of entropy and chaotic grid map. The proposed methodology incorporates Discrete Cosine Transform (DCT) on the host image. To improve the imperceptibility of the method, the host image DCT blocks, where the watermark is to be embedded, are further optimized by considering the entropy of the blocks. Chaotic grid is used as a key to reorder the DCT blocks so that it will further increase security while selecting the watermark embedding locations and its sequence. Without a key, one cannot reveal the exact watermark from the watermarked image. The proposed method is implemented on four different images. It is concluded that the proposed method is giving better results in terms of imperceptibility measured through PSNR and found to be above 50. In order to prove the effectiveness of the method, the performance analysis is done after implementing different attacks on the watermarked images. It is found that the methodology is very strong against JPEG compression attack even with the quality parameter up to 15. The experimental results are confirming that the combination of entropy and chaotic grid map method is strong and secured to different image processing attacks.

Keywords: digital watermarking, discreate cosine transform, chaotic grid map, entropy

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Authors: Md. Refat Jahan Rakiba, M. Belal Hossaina, Rakesh Kumarc, Md. Akram Ullaha, Sultan Al Nahiand, Nazmun Naher Rimaa, Tasrina Rabia Choudhury, Samia Islam Libaf, Jimmy Yub, Mayeen Uddin Khandakerg, Abdelmoneim Suliemanh, Mohamed Mahmoud Sayedi

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Microplastics (MPs) have become an emerging global pollutant due to their wide spread and dispersion and potential threats to marine ecosystems. However, studies on MPs of estuarine and coastal ecosystems of Bangladesh are very limited or not available. In this study, we conducted the first study on the abundance, distribution, characteristics and potential risk assessment of microplastics in the sediment of Karnaphuli River estuary, Bangladesh. Microplastic particles were extracted from sediments of 30 stations along the estuary by density separation, and then enumerated and characterize by using steromicroscope and Fourier Transform Infrared (FT-IR) spectroscopy. In the collected sediment, the number of MPs varied from 22.29 - 59.5 items kg−1 of dry weight (DW) with an average of 1177 particles kg−1 DW. The mean abundance was higher in the downstream and left bank of estuary where the predominant shape, colour, and size of MPs were films (35%), white (19%), and >5000 μm (19%), respectively. The main polymer types were polyethylene terephthalate, polystyrene, polyethylene, cellulose, and nylon. MPs were found to pose risks (low to high) in the sediment of the estuary, with the highest risk occuring at one station near a sewage outlet, according to the results of risk analyses using the pollution risk index (PRI), polymer risk index (H), contamination factors (CFs), and pollution load index (PLI). The single value index, PLI clearly demonastated that all sampling sites were considerably polluted (as PLI >1) with microplastics. H values showed toxic polymers even in lower proportions possess higher polymeric hazard scores and vice versa. This investigation uncovered new insights on the status of MPs in the sediments of Karnaphuli River estuary, laying the groundwork for future research and control of microplastic pollution and management.

Keywords: microplastics, polymers, pollution risk assessment, Karnaphuli esttuary

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Authors: Héctor González Espinosa, Ricardo Ivan Cordova Chávez, Alejandra Contreras Ramos, Itzia Irene Padilla Martínez, José Guadalupe Trujillo Ferrara, Marvin Antonio Soriano Ursúa

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Boronic acids are able to create diester bonds with carbohydrates because of their hydroxyl groups; in nature, there are some organoborates with these characteristics, such as the calcium fructoborate, formed by the union of two fructose molecules and a boron atom, synthesized by plants. In addition, it has been observed that, in animal cells only the compounds with cis-diol functional groups are capable of linking to boric or boronic acids. The formation of these organoboron compounds could impair the physical and chemical properties of the precursors, even their acute toxicity. In this project, two carbohydrate-derived boron-containing compounds from D-fructose and D-arabinose and phenylboronic acid are analyzed by different spectroscopy techniques such as Raman, Infrared with Fourier Transform Infrared (FT-IR), Nuclear Magnetic Resonance (NMR) and X-ray diffraction crystallography to describe their chemical characteristics. Also, an acute toxicity test was performed to determine their LD50 using the Lorke’s method. It was confirmed by multiple spectra the formation of the adducts by the generation of the diester bonds with a β-D-pyranose of fructose and arabinose. The most prominent findings were the presence of signals corresponding to the formation of new bonds, like the stretching of B-O bonds, or the absence of signals of functional groups like the hydroxyls presented in the reagents used for the synthesis of the adducts. The NMR spectra yielded information about the stereoselectivity in the synthesis reaction, observed by the interaction of the protons and their vicinal atoms in the anomeric and second position carbons; but also, the absence of a racemic mix by the finding of just one signal in the range for the anomeric carbon in the 13C NMR spectra of both adducts. The acute toxicity tests by the Lorke’s method showed that the LD50 value for both compounds is 1265 mg/kg. Those results let us to propose these adducts as highly safe agents for further biological evaluation with medical purposes.

Keywords: acute toxicity, adduct, boron, carbohydrate, diester bond

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Authors: Surini Duthika Fernandopulle, Kalamba Arachchige Pramodya Wijesinghe

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Macrocapsules containing phase change material (PCM) PEG4000 as core and Calcium Alginate as the shell was synthesized by in-situ polymerization process, and their suitability for textile applications was studied. PCM macro-capsules were sandwiched between two polyurethane foams at regular intervals, and the sandwiched foams were subsequently covered with 100% cotton woven fabrics. According to the mathematical modelling and calculations 46 capsules were required to provide cooling for a period of 2 hours at 56ºC, so a panel of 10 cm x 10 cm area with 25 parts (having 5 capsules in each for 9 parts are 16 parts spaced for air permeability) were effectively merged into one textile material without changing the textile's original properties. First, the available cooling techniques related to textiles were considered and the best cooling techniques suiting the Sri Lankan climatic conditions were selected using a survey conducted for Sri Lankan Public based on ASHRAE-55-2010 standard and it consisted of 19 questions under 3 sections categorized as general information, thermal comfort sensation and requirement of Personal Cooling Garments (PCG). The results indicated that during daytime, majority of respondents feel warm and during nighttime also majority have responded as slightly warm. The survey also revealed that around 85% of the respondents are willing to accept a PCG. The developed panels were characterized using Fourier-transform infrared spectroscopy (FTIR) and Thermogravimetric Analysis (TGA) tests and the findings from FTIR showed that the macrocapsules consisted of PEG 4000 as the core material and Calcium Alginate as the shell material and findings from TGA showed that the capsules had the average weight percentage for core with 61,9% and shell with 34,7%. After heating both control samples and samples incorporating PCM panels, it was discovered that only the temperature of the control sample increased after 56ºC, whereas the temperature of the sample incorporating PCM panels began to regulate the temperature at 56ºC, preventing a temperature increase beyond 56ºC.

Keywords: phase change materials, thermal regulation, textiles, macrocapsules

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Authors: Xizhen Zhou, Yanjie Ji

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The charging behavior of drivers provides a reference for the planning and management of charging facilities. Based on the real trajectory data of electric vehicles, this study explored the influence of the surrounding environments of the parking spot on charging decisions. The built environment, the condition of vehicles, and the nearest charging station were all considered. And the mixed binary logit model was used to capture the impact of unobserved heterogeneity. The results show that the number of fast chargers in the charging station, parking price, dwell time, and shopping services all significantly impact the charging decision, while the leisure services, scenic spots, and mileage since the last charging are opposite. Besides, factors related to unobserved heterogeneity include the number of fast chargers, parking and charging prices, residential areas, etc. The interaction effects of random parameters further illustrate the complexity of charging choice behavior. The results provide insights for planning and managing charging facilities.

Keywords: charging decision, trajectory, electric vehicle, infrastructure, mixed logit

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Authors: Lucija Pustahija, Christine Bandl, Wolfgang Kern, Christian Mitterer

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Concerning today´s ecological demands, producing reliable materials from sustainable resources is a continuously developing topic. Such an example is the production of carbon materials via pyrolysis of natural gases or biomass. The amazing properties of pyrolytic carbon are utilized in various fields, where in particular the application in building industry is a promising way towards the utilization of pyrolytic carbon and composites based on pyrolytic carbon. For many applications, surface modification of carbon is an important step in tailoring its properties. Therefore, in this paper, an investigation of different oxidation methods was performed to prepare the carbon surface before functionalizing it with organosilanes, which act as coupling agents for epoxy and polyurethane resins. Made in such a way, a building material based on carbon composites could be used as a lightweight, durable material that can be applied where water or air filtration / purification is needed. In this work, both wet and dry oxidation were investigated. Wet oxidation was first performed in solutions of nitric acid (at 120 °C and 150 °C) followed by oxidation in hydrogen peroxide (80 °C) for 3 and 6 h. Moreover, a hydrothermal method (under oxygen gas) in autoclaves was investigated. Dry oxidation was performed under plasma and corona discharges, using different power values to elaborate optimum conditions. Selected samples were then (in preliminary experiments) subjected to a silanization of the surface with amino and glycidoxy organosilanes. The functionalized surfaces were examined by X-ray photon spectroscopy and Fourier transform infrared spectroscopy spectroscopy, and by scanning electron microscopy. The results of wet and dry oxidation methods indicated that the creation of functionalities was influenced by temperature, the concentration of the reagents (and gases) and the duration of the treatment. Sequential oxidation in aq. HNO₃ and H₂O₂ results in a higher content of oxygen functionalities at lower concentrations of oxidizing agents, when compared to oxidizing the carbon with concentrated nitric acid. Plasma oxidation results in non-permanent functionalization on the carbon surface, by which it´s necessary to find adequate parameters of oxidation treatments that could enable longer stability of functionalities. Results of the functionalization of the carbon surfaces with organosilanes will be presented as well.

Keywords: building materials, dry oxidation, organosilanes, pyrolytic carbon, resins, surface functionalization, wet oxidation

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Authors: Arijit Basuray, Saibal Chatterjee

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Pulsed Power in the form of Recurrent Surge Generator (RSG) can be used for testing various parameters of Motor or Transformer windings including inter-turn, interlayer insulation. Windings with solid insulation in motor and transformer have many interfaces and undesirable defects, and these defects can be exposed under this nondestructive testing methodology. Due to rapid development in power electronics variable frequency drives (VFD), Dry Type or cast resin Transformer used with PWM Sine wave inverters for solar power, solid insulation system used nowadays are shifting more and more to a high-frequency application. Authors have used the recurrent surge generator for testing winding integrity as well as Partial Discharge(PD) at fast rising voltage enabling PD measurement at closer situation under which the insulation system is supposed to work. Authors have discussed test results on a different system with recurrent surge voltages of different rise time.

Keywords: fast rising voltage, partial discharge, pulsed power, recurrent surge generator, solid insulation

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Authors: Aishik Deb, Rituparna Sinha

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We have developed an algorithm to detect the abnormal segment/"structural variation in the genome across a number of samples. We have worked on simulated as well as real data from the BAM Files and have designed a segmentation algorithm where abnormal segments are detected. This algorithm aims to improve the accuracy and performance of the existing CNV-CH algorithm. The next-generation sequencing (NGS) approach is very fast and can generate large sequences in a reasonable time. So the huge volume of sequence information gives rise to the need for Big Data and parallel approaches of segmentation. Therefore, we have designed a map-reduce approach for the existing CNV-CH algorithm where a large amount of sequence data can be segmented and structural variations in the human genome can be detected. We have compared the efficiency of the traditional and map-reduce algorithms with respect to precision, sensitivity, and F-Score. The advantages of using our algorithm are that it is fast and has better accuracy. This algorithm can be applied to detect structural variations within a genome, which in turn can be used to detect various genetic disorders such as cancer, etc. The defects may be caused by new mutations or changes to the DNA and generally result in abnormally high or low base coverage and quantification values.

Keywords: cancer detection, convex hull segmentation, map reduce, next generation sequencing

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Authors: Mahsa Ahmadi, Mehdi Mehdikhani-Nahrkhalaji, Jaleh Varshosaz, Shadi Farsaei

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Gelatin and hyaluronic acid are commonly used in skin tissue engineering scaffolds, but because of their low mechanical properties and high biodegradation rate, adding a synthetic polymer such as polycaprolactone could improve the scaffold properties. Therefore, we developed a gelatin-hyaluronic acid-polycaprolactone scaffold, containing 0.5 % atorvastatin loaded nanostructured lipid carriers (NLCs) for skin tissue engineering. The atorvastatin loaded NLCs solution was prepared by solvent evaporation method and freeze drying process. Synthesized atorvastatin loaded NLCs was added to the gelatin and hyaluronic acid solution, and a membrane was fabricated with solvent evaporation method. Thereafter it was coated by a thin layer of polycaprolactone via spine coating set. The resulting scaffolds were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analyses. Moreover, mechanical properties, in vitro degradation in 7 days period, and in vitro drug release of scaffolds were also evaluated. SEM images showed the uniform distributed NLCs with an average size of 100 nm in the scaffold structure. Mechanical test indicated that the scaffold had a 70.08 Mpa tensile modulus which was twofold of tensile modulus of normal human skin. A Franz-cell diffusion test was performed to investigate the scaffold drug release in phosphate buffered saline (pH=7.4) medium. Results showed that 72% of atorvastatin was released during 5 days. In vitro degradation test demonstrated that the membrane was degradated approximately 97%. In conclusion, suitable physicochemical and biological properties of membrane indicated that the developed gelatin-hyaluronic acid-polycaprolactone nanocomposite scaffold containing 0.5 % atorvastatin loaded NLCs could be used as a good candidate for skin tissue engineering applications.

Keywords: atorvastatin, gelatin, hyaluronic acid, nano lipid carriers (NLCs), polycaprolactone, skin tissue engineering, solvent casting, solvent evaporation

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Authors: Abe D. Desta

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This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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Authors: Fuad Abdullah Alatawi

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Microbial infections-based diseases are a significant public health issue around the world, mainly when antibiotic-resistant bacterium types evolve. In this research, we explored the anti-bacterial and anti-cancer potency of iron-oxide (Fe₂O₃) nanoparticles prepared from F. macrocarpa fruit extract. The chemical composition of F. macrocarpa fruit extract was used as a reducing and capping agent for nanoparticles’ synthesis was examined by GC-MS/MS analysis. Then, the prepared nanoparticles were confirmed by various biophysical techniques, including X-ray powder diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), UV-Vis Spectroscopy, and Transmission Electron Microscopy (TEM) and Energy Dispersive Spectroscopy (EDAX), and Dynamic Light Scattering (DLS). Also, the antioxidant capacity of fruit extract was determined through 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS), Fluorescence Recovery After Photobleaching (FRAP), Superoxide Dismutase (SOD) assays. Furthermore, the cytotoxicity activities of Fe₂O₃ NPs were determined using the (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) (MTT) test on MCF-7 cells. In the antibacterial assay, lethal doses of the Fe₂O₃NPs effectively inhibited the growth of gram-negative and gram-positive bacteria. The surface damage, ROS production, and protein leakage are the antibacterial mechanisms of Fe₂O₃NPs. Concerning antioxidant activity, the fruit extracts of F. macrocarpa had strong antioxidant properties, which were confirmed by DPPH, ABTS, FRAP, and SOD assays. In addition, the F. microcarpa-derived iron oxide nanomaterials greatly reduced the cell viability of (MCF-7). The GC-MS/MS analysis revealed the presence of 25 main bioactive compounds in the F. microcarpa extract. Overall, the finding of this research revealed that F. microcarpa-derived Fe₂O₃ nanoparticles could be employed as an alternative therapeutic agent to cure microbial infection and breast cancer in humans.

Keywords: ficus microcarpa, iron oxide, antibacterial activity, cytotoxicity

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Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

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All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features

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Authors: Uraib Sharaha, Guy Beck, Joseph Kapelushnik, Adam H. Agbaria, Itshak Lapidot, Shaul Mordechai, Ahmad Salman, Mahmoud Huleihel

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Infectious diseases cause a significant burden on the public health and the economic stability of societies all over the world for several centuries. A reliable detection of the causative agent of infection is not possible based on clinical features, since some of these infections have similar symptoms, including fever, sneezing, inflammation, vomiting, diarrhea, and fatigue. Moreover, physicians usually encounter difficulties in distinguishing between viral and bacterial infections based on symptoms. Therefore, there is an ongoing need for sensitive, specific, and rapid methods for identification of the etiology of the infection. This intricate issue perplex doctors and researchers since it has serious repercussions. In this study, we evaluated the potential of the mid-infrared spectroscopic method for rapid and reliable identification of bacterial and viral infections based on simple peripheral blood samples. Fourier transform infrared (FTIR) spectroscopy is considered a successful diagnostic method in the biological and medical fields. Many studies confirmed the great potential of the combination of FTIR spectroscopy and machine learning as a powerful diagnostic tool in medicine since it is a very sensitive method, which can detect and monitor the molecular and biochemical changes in biological samples. We believed that this method would play a major role in improving the health situation, raising the level of health in the community, and reducing the economic burdens in the health sector resulting from the indiscriminate use of antibiotics. We collected peripheral blood samples from young 364 patients, of which 93 were controls, 126 had bacterial infections, and 145 had viral infections, with ages lower than18 years old, limited to those who were diagnosed with fever-producing illness. Our preliminary results showed that it is possible to determine the infectious agent with high success rates of 82% for sensitivity and 80% for specificity, based on the WBC data.

Keywords: infectious diseases, (FTIR) spectroscopy, viral infections, bacterial infections.

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Authors: Hamdy Elgohary, Majid Assas

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Estimation of lateral displacement and interstory drifts represent a major step in multistory frames design. In the preliminary design stage, it is essential to perform a fast check for the expected values of lateral deformations. This step will help to ensure the compliance of the expected values with the design code requirements. Also, in some cases during or after the detailed design stage, it may be required to carry fast check of lateral deformations by design reviewer. In the present paper, a parametric study is carried out on the factors affecting in the lateral displacements of multistory frame buildings. Based on the results of the parametric study, simplified empirical equations are recommended for the direct determination of the lateral deflection of multistory frames. The results obtained using the recommended equations have been compared with the results obtained by finite element analysis. The comparison shows that the proposed equations lead to good approximation for the estimation of lateral deflection of multistory RC frame buildings.

Keywords: lateral deflection, interstory drift, approximate analysis, multistory frames

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Authors: Seda Yavuz, Anıl Çelebi, Aysun Taşyapı Çelebi, Oğuzhan Urhan

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Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption.

Keywords: binarization, hardware architecture, local binary pattern, motion estimation, two-bit transform

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Authors: Muhammad Ather Nadeem, Bilal Ahmad Khan, Tasawer Abbas

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Nanoherbicides utilize nanotechnology to enhance the delivery of biological or chemical herbicides using combinations of nanomaterials. The aim of this research was to examine the efficacy of chitosan nanoparticles containing MCPA herbicide as a potential eco-friendly alternative for weed control in wheat crops. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and ultraviolet absorbance were used to analyze the developed nanoparticles. The SEM analysis indicated that the average size of the particles was 35 nm, forming clusters with a porous structure. Both nanoparticles of fluroxyper + MCPA exhibited maximal absorption peaks at a wavelength of 320 nm. The compound fluroxyper +MCPA has a strong peak at a 2θ value of 30.55°, which correlates to the 78 plane of the anatase phase. The weeds, including Chenopodium album, Lathyrus aphaca, Angalis arvensis, and Melilotus indica, were sprayed with the nanoparticles while they were in the third or fourth leaf stage. There were seven distinct dosages used: doses (D0 (Check weeds), D1 (Recommended dose of traditional herbicide, D2 (Recommended dose of Nano-herbicide (NPs-H)), D3 (NPs-H with 05-fold lower dose), D4 ((NPs-H) with 10-fold lower dose), D5 (NPs-H with 15-fold lower dose), and D6 (NPs-H with 20-fold lower dose)). The chitosan-based nanoparticles of MCPA at the prescribed dosage of conventional herbicide resulted in complete death and visual damage, with a 100% fatality rate. The dosage that was 5-fold lower exhibited the lowest levels of plant height (3.95 cm), chlorophyll content (5.63%), dry biomass (0.10 g), and fresh biomass (0.33 g) in the broad-leaved weed of wheat. The herbicide nanoparticles, when used at a dosage 10-fold lower than that of conventional herbicides, had a comparable impact on the prescribed dosage. Nano-herbicides have the potential to improve the efficiency of standard herbicides by increasing stability and lowering toxicity.

Keywords: mortality, visual injury, chlorophyl contents, chitosan-based nanoparticles

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Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Shafaq Rubab

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The inclusion of special needs students in a classroom is prevailing gradually in developing countries. Digital game-based learning is one the most effective instructional methodology for special needs students. Digital game-based learning facilitates special needs students who actually face challenges and obstacles in their learning processes. This study aimed to evaluate the effectiveness of digital game-based learning on the educational progress of special needs students in developing countries. The quasi-experimental research was conducted by using purposively selected sample size of eight special needs students. Results of both experimental and control group showed that performance of the experimental group students was better than the control group students and there was a significant difference between both groups’ results. This research strongly recommended that digital game-based learning can help special needs students in an inclusive classroom. It also revealed that special needs students can learn efficiently by using pedagogically sound learning games and game-based learning helps a lot for the self-paced fast-track learning system.

Keywords: inclusive education, special needs, digital game-based learning, fast-track learning

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Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert

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Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.

Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT

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Authors: Omer Abdalla Ishag, Magdi Baker Amien

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Physicians used the stethoscope for listening patient heart sounds in order to make a diagnosis. However, the determination of heart conditions by acoustic stethoscope is a difficult task so it requires special training of medical staff. This study developed an accurate model for analyzing the phonocardiograph signal based on PC and DSP processor. The system has been realized into two phases; offline and real time phase. In offline phase, 30 cases of heart sounds files were collected from medical students and doctor's world website. For experimental phase (real time), an electronic stethoscope has been designed, implemented and recorded signals from 30 volunteers, 17 were normal cases and 13 were various pathologies cases, these acquired 30 signals were preprocessed using an adaptive filter to remove lung sounds. The background noise has been removed from both offline and real data, using wavelet transform, then graphical and statistics features vector elements were extracted, finally a look-up table was used for classification heart sounds cases. The obtained results of the implemented system showed accuracy of 90%, 80% and sensitivity of 87.5%, 82.4% for offline data, and real data respectively. The whole system has been designed on TMS320VC5509a DSP Platform.

Keywords: code composer studio, heart sounds, phonocardiograph, wavelet transform

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Authors: Reyhaneh Hashemi, Shahrooz Saviz

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In his study, we have survey the theory of gyrotron amplifier in a vane-loaded waveguide with inner dielectric material. Dispersion relation for electromagnetic waves emitted by a cylindrical waveguide that provided with wedge-shaped metal vanes projecting radially inward from the wall of the guide and exited in the transverse-electric mode was analysed. From numerical analysis of this dispersion relation, it is shown that the stability behavior of the fast-wave mode is dependent of the dielectric constant. With a small axial momentum spreed, a super bandwidth is shown to be attainable by a mixed mode operation. Also, with the utilization from the numeric analysis of relation dispersion. We show that in the –speed mode, the constant is independent de-electric. With the ratio of dispersion of smell, high –bandwith was obtained for the combined mode. And at the end, we were comparing the result of our work (vane-loaded) by the waveguide with a smooth wall.

Keywords: gyrotron amplifier, waveguide, vane-loaded waveguide, dielectric material, dispersion relation, cylindrical waveguide, fast-wave mode, mixed mode operation

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Authors: Abdelsalam A. Ahmed

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Fast speed drives for Permanent Magnet Synchronous Motor (PMSM) is a crucial performance for the electric traction systems. In this paper, PMSM is drived with a Model-based Predictive Control (MPC) technique. Fast speed tracking is achieved through optimization of the DC source utilization using MPC. The technique is based on predicting the optimum voltage vector applied to the driver. Control technique is investigated by comparing to the cascaded PI control based on Space Vector Pulse Width Modulation (SVPWM). MPC and SVPWM-based FOC are implemented with the TMS320F2812 DSP and its power driver circuits. The designed MPC for a PMSM drive is experimentally validated on a laboratory test bench. The performances are compared with those obtained by a conventional PI-based system in order to highlight the improvements, especially regarding speed tracking response.

Keywords: permanent magnet synchronous motor, model-based predictive control, DC source utilization, cascaded PI control, space vector pulse width modulation, TMS320F2812 DSP

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Authors: K. Larysz, E. Grochowska-Niedworok, M. Kardas, K. Brukalo, B. Calyniuk, R. Polaniak

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Eating behaviours and habits are one of the main factors affecting health. Abnormal nutritional status is a growing problem related to nutritional errors. The number of adolescents presenting excess body weight is also rising. The body's demand for all nutrients increases in the period of intensive development, i.e., during puberty. A varied, well-balanced diet and elimination of unhealthy habits are two of the key factors that contribute to the proper development of a young body. The aim of the study was to assess the nutritional status and selected eating behaviours/habits in adolescents attending middle school. An original questionnaire including 24 questions was conducted. A total of 401 correctly completed questionnaires were qualified for the assessment. Body mass index (BMI) was calculated. Furthermore, the frequency of breakfast consumption, the number of meals per day, types of snacks and sweetened beverages, as well as the frequency of consuming fruit and vegetables, dairy products and fast-foods were assessed. The obtained results were analysed statistically. The study showed that malnutrition was more of a problem than overweight or obesity among middle school students. More than 71% of middle school students have breakfast, whereas almost 30% of adolescents skip this meal. Up to 57.6% of respondents most often consume sweets at school. A total of 37% of adolescents consume sweetened beverages daily or almost every day. Most of the respondents consume an optimal number of meals daily. Only 24.7% of respondents consume fruit and vegetables more than once daily. The majority of respondents (49.40%) declared that they consumed fast food several times a month. Satisfactory frequency of consuming dairy products was reported by 32.7% of middle school students. Conclusions of our study: 1. Malnutrition is more of a problem than overweight or obesity among middle school students. They consume excessive amounts of sweets, sweetened beverages, and fast foods. 2. The consumption of fruit and vegetables was too low in the study group. The intake of dairy products was also low in some cases. 3. A statistically significant correlation was found between the frequency of fast food consumption and the intake of sweetened beverages. A low correlation was found between nutritional status and the number of meals per day. The number of meals consumed by these individuals decreased with increasing nutritional status.

Keywords: adolescent, malnutrition, nutrition, nutritional status, obesity

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Authors: Uttam Kumar Ghorai, Madhupriya Samanta, Subhajit Saha, Swati Das, Nilesh Mazumder, Kalyan Kumar Chattopadhyay

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Organic semiconductors have gained potential interest in the last few decades for their significant contributions in the various fields such as solar cell, non-volatile memory devices, field effect transistors and light emitting diodes etc. The most important advantages of using organic materials are mechanically flexible, light weight and low temperature depositing techniques. Recently with the advancement of nanoscience and technology, one dimensional organic and inorganic nanostructures such as nanowires, nanorods, nanotubes have gained tremendous interests due to their very high aspect ratio and large surface area for electron transport etc. Among them, self-assembled organic nanostructures like Copper, Zinc Phthalocyanine have shown good transport property and thermal stability due to their π conjugated bonds and π-π stacking respectively. Field emission properties of inorganic and carbon based nanostructures are reported in literatures mostly. But there are few reports in case of cold cathode emission characteristics of organic semiconductor nanostructures. In this work, the authors report the field emission characteristics of chemically and physically synthesized Copper Phthalocyanine (CuPc) nanostructures such as nanowires, nanotubes and nanotips. The as prepared samples were characterized by X-Ray diffraction (XRD), Ultra Violet Visible Spectrometer (UV-Vis), Fourier Transform Infra-red Spectroscopy (FTIR), and Field Emission Scanning Electron Microscope (FESEM) and Transmission Electron Microscope (TEM). The field emission characteristics were measured in our home designed field emission set up. The registered turn-on field and local field enhancement factor are found to be less than 5 V/μm and greater than 1000 respectively. The field emission behaviour is also stable for 200 minute. The experimental results are further verified by theoretically using by a finite displacement method as implemented in ANSYS Maxwell simulation package. The obtained results strongly indicate CuPc nanostructures to be the potential candidate as an electron emitter for field emission based display device applications.

Keywords: organic semiconductor, phthalocyanine, nanowires, nanotubes, field emission

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Authors: Shreyas Srinivas Rangan, Jurgis Porins

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The internet traffic has increased exponentially due to the high demand for data rates by the users, and the constantly increasing metro networks and access networks are focused on improving the maximum transmit distance of the long-reach optical networks. One of the common methods to improve the maximum transmit distance of the long-reach optical networks at the component level is to use broadband optical amplifiers. The Erbium Doped Fiber Amplifier (EDFA) provides high amplification with low noise figure but due to the characteristics of EDFA, its operation is limited to C-band and L-band. In contrast, the Raman amplifier exhibits a wide amplification spectrum, and negative noise figure values can be achieved. To obtain such results, high powered pumping sources are required. Operating Raman amplifiers with such high-powered optical sources may cause fire hazards and it may damage the optical system. In this paper, we implement a hybrid optical amplifier configuration. EDFA and Raman amplifiers are used in this hybrid setup to combine the advantages of both EDFA and Raman amplifiers to improve the reach of the system. Using this setup, we analyze the maximum transmit distance of the network by obtaining a correlation diagram between the length of the single-mode fiber (SMF) and the Bit Error Rate (BER). This hybrid amplifier configuration is implemented in a Wavelength Division Multiplexing (WDM) system with a BER of 10⁻⁹ by using NRZ modulation format, and the gain uniformity noise ratio (signal-to-noise ratio (SNR)), the efficiency of the pumping source, and the optical signal gain efficiency of the amplifier are studied experimentally in a mathematical modelling environment. Numerical simulations were implemented in RSoft OptSim simulation software based on the nonlinear Schrödinger equation using the Split-Step method, the Fourier transform, and the Monte Carlo method for estimating BER.

Keywords: Raman amplifier, erbium doped fibre amplifier, bit error rate, hybrid optical amplifiers

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Authors: Zahrasadat Hosseini, Jie Yuan

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Point-of-care (POC) diagnostic devices based on lab-on-a-chip (LOC) technology have the potential to revolutionize medical diagnostics. However, the development of an ideal microfluidic system based on LOC technology for diagnostics purposes requires overcoming several obstacles, such as improving sensitivity, selectivity, portability, cost-effectiveness, and prototyping methods. While numerous studies have introduced technologies and systems that advance these criteria, existing systems still have limitations. Electrochemical enzyme-linked immunosorbent assay (e-ELISA) in a LOC device offers numerous advantages, including enhanced sensitivity, decreased turnaround time, minimized sample and analyte consumption, reduced cost, disposability, and suitability for miniaturization, integration, and multiplexing. In this study, we present a novel design and fabrication method for a microfluidic diagnostic platform that integrates screen-printed electrochemical carbon/silver chloride electrodes on flexible printed circuit boards with flexible, multilayer, polydimethylsiloxane (PDMS) microfluidic networks to accurately manipulate and pre-immobilize analytes for performing electrochemical enzyme-linked immunosorbent assay (e-ELISA) for multiplexed quantification of blood serum biomarkers. We further demonstrate fast, cost-effective prototyping, as well as accurate and reliable detection performance of this device for quantification of interleukin-6-spiked samples through electrochemical analytics methods. We anticipate that our invention represents a significant step towards the development of user-friendly, portable, medical-grade, POC diagnostic devices.

Keywords: lab-on-a-chip, point-of-care diagnostics, electrochemical ELISA, biomarker quantification, fast prototyping

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Authors: Zahrasadat Hosseini, Jie Yuan

Abstract:

Point-of-care (POC) diagnostic devices based on lab-on-a-chip (LOC) technology have the potential to revolutionize medical diagnostics. However, the development of an ideal microfluidic system based on LOC technology for diagnostics purposes requires overcoming several obstacles, such as improving sensitivity, selectivity, portability, cost-effectiveness, and prototyping methods. While numerous studies have introduced technologies and systems that advance these criteria, existing systems still have limitations. Electrochemical enzyme-linked immunosorbent assay (e-ELISA) in a LOC device offers numerous advantages, including enhanced sensitivity, decreased turnaround time, minimized sample and analyte consumption, reduced cost, disposability, and suitability for miniaturization, integration, and multiplexing. In this study, we present a novel design and fabrication method for a microfluidic diagnostic platform that integrates screen-printed electrochemical carbon/silver chloride electrodes on flexible printed circuit boards with flexible, multilayer, polydimethylsiloxane (PDMS) microfluidic networks to accurately manipulate and pre-immobilize analytes for performing electrochemical enzyme-linked immunosorbent assay (e-ELISA) for multiplexed quantification of blood serum biomarkers. We further demonstrate fast, cost-effective prototyping, as well as accurate and reliable detection performance of this device for quantification of interleukin-6-spiked samples through electrochemical analytics methods. We anticipate that our invention represents a significant step towards the development of user-friendly, portable, medical-grade POC diagnostic devices.

Keywords: lab-on-a-chip, point-of-care diagnostics, electrochemical ELISA, biomarker quantification, fast prototyping

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Authors: Endris Yibru Hanurry, Wei-Hsin Hsu, Hsieh-Chih Tsai

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In recent years, the discovery of small interfering RNAs (siRNAs) has got great attention for the treatment of cancer and other diseases. However, the therapeutic efficacy of siRNAs has been faced with many drawbacks because of short half-life in blood circulation, poor membrane penetration, weak endosomal escape and inadequate release into the cytosol. To overcome these drawbacks, we designed a non-viral vector by conjugating polyamidoamine generation 4.5 dendrimer (PDG4.5) with diethylenetriamine (DETA)- and tetraethylenepentamine (TEPA) followed by binding with siRNA to form polyplexes through electrostatic interaction. The result of 1H nuclear magnetic resonance (NMR), 13C NMR, correlation spectroscopy, heteronuclear single–quantum correlation spectroscopy, and Fourier transform infrared spectroscopy confirmed the successful conjugation of DETA and TEPA with PDG4.5. Then, the size, surface charge, morphology, binding ability, stability, release assay, toxicity and cellular internalization were analyzed to explore the physicochemical and biological properties of PDG4.5-DETA and PDG4.5-TEPA polyplexes at specific N/P ratios. The polyplexes (N/P = 8) exhibited spherical nanosized (125 and 85 nm) particles with optimum surface charge (13 and 26 mV), showed strong siRNA binding ability, protected the siRNA against enzyme digestion and accepted biocompatibility to the HeLa cells. Qualitatively, the fluorescence microscopy image revealed the delocalization (Manders’ coefficient 0.63 and 0.53 for PDG4.5-DETA and PDG4.5-TEPA, respectively) of polyplexes and the translocation of the siRNA throughout the cytosol to show a decent cellular internalization and intracellular biodistribution of polyplexes in HeLa cells. Quantitatively, the flow cytometry result indicated that a significant (P < 0.05) amount of siRNA was internalized by cells treated with PDG4.5-DETA (68.5%) and PDG4.5-TEPA (73%) polyplexes. Generally, PDG4.5-DETA and PDG4.5-TEPA were ideal nanocarriers of siRNA in vitro and might be used as promising candidates for in vivo study and future pharmaceutical applications.

Keywords: non-viral carrier, oligoalkylamine, poly(amidoamine) dendrimer, polyplexes, siRNA

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Authors: Virginia Martin Torrejon, Binjie Wu

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Gelatine is a protein biopolymer obtained from the partial hydrolysis of animal tissues which contain collagen, the primary structural component in connective tissue. Gelatine hydrogels have attracted considerable research in recent years as an alternative to synthetic materials due to their outstanding gelling properties, biocompatibility and compostability. Surfactants, such as sodium dodecyl sulfate (SDS), are often used in hydrogels solutions as surface modifiers or solubility enhancers, and their incorporation can influence the hydrogel’s viscoelastic properties and, in turn, its processing and applications. Literature usually focuses on studying the impact of formulation parameters (e.g., gelatine content, gelatine strength, additives incorporation) on gelatine hydrogels properties, but processing parameters, such as curing temperature, are commonly overlooked. For example, some authors have reported a decrease in gel strength at lower curing temperatures, but there is a lack of research on systematic viscoelastic characterisation of high strength gelatine and gelatine-SDS systems at a wide range of curing temperatures. This knowledge is essential to meet and adjust the technological requirements for different applications (e.g., viscosity, setting time, gel strength or melting/gelling temperature). This work investigated the effect of curing temperature (10, 15, 20, 23 and 25 and 30°C) on the elastic modulus (G’) and melting temperature of high strength gelatine-SDS hydrogels, at 10 wt% and 20 wt% gelatine contents, by small-amplitude oscillatory shear rheology coupled with Fourier Transform Infrared Spectroscopy. It also correlates the gel strength obtained by rheological measurements with the gel strength measured by texture analysis. Gelatine and gelatine-SDS hydrogels’ rheological behaviour strongly depended on the curing temperature, and its gel strength and melting temperature can be slightly modified to adjust it to given processing and applications needs. Lower curing temperatures led to gelatine and gelatine-SDS hydrogels with considerably higher storage modulus. However, their melting temperature was lower than those gels cured at higher temperatures and lower gel strength. This effect was more considerable at longer timescales. This behaviour is attributed to the development of thermal-resistant structures in the lower strength gels cured at higher temperatures.

Keywords: gelatine gelation kinetics, gelatine-SDS interactions, gelatine-surfactant hydrogels, melting and gelling temperature of gelatine gels, rheology of gelatine hydrogels

Procedia PDF Downloads 89