Search results for: magnetic solvent extraction

Authors: Natalia Fijol, Aji P. Mathew

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We present the processing and characterisation of three-dimensional (3D) monolith filters based on polylactic acid (PLA) reinforced with various nature-derived nanospecies such as hydroxyapatite, modified cellulose fibers and chitin fibers. The nanospecies of choice were dispersed in PLA through Thermally Induced Phase Separation (TIPS) method. The biocomposites were developed via solvent-assisted blending and the obtained pellets were further single-screw extruded into 3D-printing filaments and processed into various geometries using Fused Deposition Modelling (FDM) technique. The printed prototypes included cubic, cylindrical and hour-glass shapes with diverse patterns of printing infill as well as varying pore structure including uniform and multiple level gradual pore structure. The pores and channel structure as well as overall shape of the prototypes were designed in attempt to optimize the flux and maximize the adsorption-active time. FDM is a cost and energy-efficient method, which does not require expensive tools and elaborated post-processing maintenance. Therefore, FDM offers the possibility to produce customized, highly functional water purification filters with tuned porous structures suitable for removal of wide range of common water pollutants. Moreover, as 3D printing becomes more and more available worldwide, it allows producing portable filters at the place and time where they are most needed. The study demonstrates preparation route for the PLA-based, fully biobased composite and their processing via FDM technique into water purification filters, addressing water treatment challenges on an industrial scale.

Keywords: fused deposition modelling, water treatment, biomaterials, 3D printing, nanocellulose, nanochitin, polylactic acid

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Authors: Jarek Krajewski, Andre Wittenborn, Martin Sauerland

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This abstract describes a promising approach for estimating post-traumatic stress disorder (PTSD) based on prosodic speech characteristics. It illustrates the validity of this method by briefly discussing results from an Arabic refugee sample (N= 47, 32 m, 15 f). A well-established standardized self-report scale “Reaction of Adolescents to Traumatic Stress” (RATS) was used to determine the ground truth level of PTSD. The speech material was prompted by telling about autobiographical related sadness inducing experiences (sampling rate 16 kHz, 8 bit resolution). In order to investigate PTSD-induced speech changes, a self-developed set of 136 prosodic speech features was extracted from the .wav files. This set was adapted to capture traumatization related speech phenomena. An artificial neural network (ANN) machine learning model was applied to determine the PTSD level and reached a correlation of r = .37. These results indicate that our classifiers can achieve similar results to those seen in speech-based stress research.

Keywords: speech prosody, PTSD, machine learning, feature extraction

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Authors: Umme Hani, H. G. Shivakumar, M. D. Younus Pasha

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The purpose of this work was to design and optimize a novel vaginal drug delivery system for more effective treatment against vaginal candidiasis. To achieve a better therapeutic efficacy and patient compliance in the treatment for vaginal candidiasis, herbal antifungal agent Curcumin which is 2.5 fold more potent than fluconazole at inhibiting the adhesion of candida albicans has been formulated in a bio-adhesive vaginal film. Curcumin was formulated in bio-adhesive film formulations that could be retained in the vagina for prolonged intervals. The polymeric films were prepared by solvent evaporation and optimized for various physicodynamic and aesthetic properties. Curcumin HPβCD (Hydroxypropyl β Cyclodextrin) was first developed to increase the solubility of curcumin. The formation of the Curcumin HPβCD complex was characterized by scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and FT-IR and evaluated for its solubility. Curcumin HPβCD complex was formulated in a bio-adhesive film using hydroxypropyl methyl cellulose (HPMC) and Carbopol 934P and characterized. DSC and FT-IR data of Curcumin HPβCD indicate there was complex formation between the drug and HPβCD. The little moisture content (8.02±0.34% w/w) was present in the film, which helps them to remain stable and kept them from being completely dry and brittle. The mechanical properties, tensile strength, and percentage elongation at break reveal that the formulations were found to be soft and tough. The films showed good peelability, relatively good swelling index, and moderate tensile strength and retained vaginal mucosa up to 8 h. The developed Curcumin vaginal film could be a promising safe herbal medication and can ensure longer residence at the vagina and provide an efficient therapy for vaginal candidiasis.

Keywords: curcumin, curcumin-HPβCD complex, bio-adhesive vaginal film, vaginal candidiasis, 23 factorial design

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Authors: Lee Myung-Won, Kwak Keun-Chang

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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation

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Authors: Jagadeshvaran P. L., Kamlesh Panwar, Indumathi Ramakrishnan, Suryasarathi Bose

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The surge in the usage of wireless electronics and communication devices has engendered a different form of pollution, viz. the electromagnetic (EM) pollution and yet another serious issue, electromagnetic interference (EMI). There is a legitimate need to develop strategies and materials to combat this issue, otherwise leading to dreadful consequences. Functional textiles have emerged as the modern materials to help attenuate EM waves due to the numerous advantages – flexibility being the most important. In addition to this, there is an inherent advantage of multiple interfaces in coated fabrics that can engender significant attenuation. Herein we report a coating having multifunctional properties – capable of blocking both UV and EM radiation (predominantly of the microwave frequencies) with flame-retarding properties. The layer described here comprises iron titanate(FT) synthesized from its sustainable precursor – ilmenite sand and carbon nanotubes (CNT) dispersed in waterborne polyurethane. It is worth noting that FT's use as a multifunctional material is being reported for the first time. It was observed that a single layer of coated fabric shows EMI shielding effectiveness of -40 dB translating to 99.99% attenuation and similarly a UV blocking of 99.99% in the wavelength ranging from 200-400 nm. The microwave shielding properties of the fabric were demonstrated using a Bluetooth module – where the coated fabric was able to block the incoming Bluetooth signals to the module from a mobile phone. Besides, the coated fabrics exhibited phenomenal enhancement in thermal stability - a five percent increase in the limiting oxygen index (LOI) was observed upon the application of the coating. Such exceptional properties complement cotton fabrics' existing utility, thereby extending their use to specialty applications.

Keywords: multifunctional coatings, EMI shielding, UV blocking, iron titanate, CNT, waterborne polyurethane, cotton fabrics

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Authors: Rajkumar Ghosh

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Water scarcity is a significant challenge in urban areas, even in smart cities (Lucknow, Bangalore, Jaipur, etc.) where efficient resource management is prioritized. The depletion of groundwater resources in Gomti Nagar, Lucknow, Uttar Pradesh, India is particularly severe, posing a significant challenge for sustainable development in the region. This study focuses on addressing the water shortage by investigating the effectiveness of rooftop rainwater harvesting systems (RTRWHs) as a sustainable approach to bridge the gap between groundwater recharge and extraction. The aim of this study is to assess the effectiveness of RTRWHs in reducing aquifer depletion and addressing the water scarcity issue in the Gomti Nagar region. The research methodology involves the utilization of RTRWHs as the primary method for collecting rainwater. RTRWHs will be implemented in residential and commercial buildings to maximize the collection of rainwater. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. Statistical analysis and modelling techniques were employed to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The study reveals that the installation of RTRWHs in the Gomti Nagar region has a positive impact on addressing the water scarcity issue. Currently, RTRWHs cover only a small percentage of the total rainfall collected in the region. However, when RTRWHs are installed in all buildings, their influence on increasing water availability and reducing aquifer depletion will be significantly greater. The study also highlights the significant water imbalance in the region, emphasizing the urgent need for sustainable water management practices. This research contributes to the theoretical understanding of sustainable water management systems in smart cities. By highlighting the effectiveness of RTRWHs in reducing aquifer depletion, it emphasizes the importance of implementing such systems in urban areas. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. The collected data were then analysed using statistical analysis and modelling techniques to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The findings of this study demonstrate that the implementation of RTRWHs can effectively mitigate the water scarcity crisis in Gomti Nagar. By reducing aquifer depletion and bridging the gap between groundwater recharge and extraction, RTRWHs offer a sustainable solution to the region's water scarcity challenges. Widespread adoption of RTRWHs in all buildings and integration into urban planning and development processes are crucial for efficient water management in smart cities like Gomti Nagar. These findings can serve as a basis for policymakers, urban planners, and developers to prioritize and incentivize the installation of RTRWHs as a potential solution to the water shortage crisis.

Keywords: water scarcity, urban areas, smart cities, resource management, groundwater depletion, rooftop rainwater harvesting systems, sustainable development, sustainable water management, mitigating water scarcity

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Authors: Lanre Oluwafemi Akinyemi

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The reduction of limestone to cement in Nigeria is expensive and requires huge amounts of energy. This significantly affects the cost of cement. Concrete is heavy: a cubic foot of it weighs about 150 lbs. and a cubic yard is about 4000 lbs. Thus a ready-mix truck with 9 cubic yards is carrying 36,000 lbs excluding the weight of the truck itself, thereby accumulating cost for also manufacturers. Therein lies the need to find a substitute for cement by using the polystyrene paste that benefits both the manufactures and the consumers. Polystyrene Paste Constructional Cement (PPCC), a patented material obtained by dissolving Waste EPS in volatile organic solvent, has recently been identified as a suitable binder/cement for construction and building material production. This paper illustrates the procedures of a test experiment undertaken to determine the splitting tensile strength of PPCC mortar compared to that of OPC (Ordinary Portland Cement). Expanded polystyrene was dissolved in gasoline to form a paste referred to as Polystyrene Paste Constructional Cement (PPCC). Mortars of mix ratios 1:4, 1:5, 1:6, 1:7 (PPCC: fine aggregate) batched by volume were used to produce 50mm x 100mm cylindrical PPCC mortar splitting tensile strength specimens. The control experiment was done by creating another series of cylindrical OPC mortar splitting tensile strength specimens following the same mix ratio used earlier. The PPCC cylindrical splitting tensile strength specimens were left to air-set, and the ones made with Ordinary Portland Cement (OPC) were demoded after 24 hours and cured in water. The cylindrical PPCC splitting tensile strength specimens were tested at 28 days and compared with those of the Ordinary Portland cement splitting tensile strength specimens. The result shows that hence for this two mixes, PPCC exhibits a better binding property than the OPC. With this my new invention I recommend the use of PPCC as a substitute for a Portland cement.

Keywords: polystyrene paste, Portland cement, construction, mortar

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Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Wu Yufeng, Gu Yifan, Wang Hengguang, Gongyu, Zuo Tieyong

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Indium is one the scarce resources which can be only used less than 30 years, and more than 70% of the indium is used for the production of the LCD. The benefit of recycling Indium from waste LCD is large. Take the LCD-TV for example, the yield of which was close to 90 million units in 2010. If it was available to recycle the indium effectively, the yield of the secondary-indium could reach up to 110 metric ton, which accounted for one third of the primary indium production in China. And compared with the dispersion and long process extraction of the primary indium resources, secondary indium concentrates in the waste LCD, the exploitation has great economic and environmental benefits. However, the potential benefits were indefinite, resulting in China’s government did not pay enough attention to the indium recycling industry. In our study, an estimation model was constructed to analyze the potential of the indium in the waste LCD. The different types of LCD were detected to find out the content of indium. Then, the potential of the indium in the waste LCD was estimated in China. Furthermore, the pollution emissions of the product process of the primary and secondary indium was analyzed respectively to calculate the economic and environmental benefits of the indium recycling from the waste LCD in China.

Keywords: indium recycling, waste liquid crystal displays, benefits, China

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Authors: Ruomeng Xiao, Zhulin Zong, Longfa Yang

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Aiming at the problem that the target signal is difficult to detect under the strong ground clutter environment, this paper proposes a clutter suppression algorithm based on the combination of singular value decomposition and the Mallat fast wavelet algorithm. The method first carries out singular value decomposition on the radar echo data matrix, realizes the initial separation of target and clutter through the threshold processing of singular value, and then carries out wavelet decomposition on the echo data to find out the target location, and adopts the discard method to select the appropriate decomposition layer to reconstruct the target signal, which ensures the minimum loss of target information while suppressing the clutter. After the verification of the measured data, the method has a significant effect on the target extraction under low SCR, and the target reconstruction can be realized without the prior position information of the target and the method also has a certain enhancement on the output SCR compared with the traditional single wavelet processing method.

Keywords: clutter suppression, singular value decomposition, wavelet transform, Mallat algorithm, low SCR

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Authors: Stella C. Okenu, Stephen O. Adikwu, Martins E. Okoro

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The geothermal energy resource potential of the Lower Benue Trough (LBT) in Nigeria was evaluated in this study using spectral analysis of high-resolution aeromagnetic (HRAM) data. The reduced to the equator aeromagnetic data was divided into sixteen (16) overlapping blocks, and each of the blocks was analyzed to obtain the radial averaged power spectrum which enabled the computation of the top and centroid depths to magnetic sources. The values were then used to assess the Curie Point Depth (CPD), geothermal gradients, and heat flow variations in the study area. Results showed that CPD varies from 7.03 to 18.23 km, with an average of 12.26 km; geothermal gradient values vary between 31.82 and 82.50°C/km, with an average of 51.21°C/km, while heat flow variations range from 79.54 to 206.26 mW/m², with an average of 128.02 mW/m². Shallow CPD zones that run from the eastern through the western and southwestern parts of the study area correspond to zones of high geothermal gradient values and high subsurface heat flow distributions. These areas signify zones associated with anomalous subsurface thermal conditions and are therefore recommended for detailed geothermal energy exploration studies.

Keywords: geothermal energy, curie-point depth, geothermal gradient, heat flow, aeromagnetic data, LBT

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Authors: K. Fellah, H. Benmehdi, A. Amrouche, H. Malainine, F. Memmou, H. Dalile, W. Siata

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This work aims to evaluate the antioxidant of flavonoids extracted from the leaves of Prunus persica L. A phytochemical screening allowed us to highlight the different phytochemicals present in the leaves of the studied plant. The selective extraction of flavonoids gave yields of 0.71, 1.5, and 4.8% for the fractions ethyl ether, ethyl acetate and n- butanol, respectively. The reading of the antioxidant activity of different extracts of flavonoids by HPLTC method revealed positive reaction (yellow spots) on the TLC plates sprayed with DPPH. Using the DPPH method, the fractions of flavonoids (bunanol, ethyl acetate and Diethyl ether) showed a potent scavenging activity with IC50 = 0.22; 0.27 and 0.76 mg / ml, respectively. Furthermore, our findings revealed the extracts under study exhibited higher reducing potential which depends upon extract concentration. These results obtained from this investigation confirm that the Prunus persica remains a major resource of bioactive molecules.

Keywords: Prunus persica L., phytochemical study, flavonoids, antioxidant activity, TLC bioautographic, FRAP, DPPH

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Authors: E. Younsi, H. Andriamboavonjy, A. David, S. Dokou, B. Lemrabet

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Software and time optimization are very important factors in financial markets, which are competitive fields, and emergence of new computer tools further stresses the challenge. In this context, any improvement of technical indicators which generate a buy or sell signal is a major issue. Thus, many tools have been created to make them more effective. This worry about efficiency has been leading in present paper to seek best (and most innovative) way giving largest improvement in these indicators. The approach consists in attaching a signature to frequent market configurations by application of frequent patterns extraction method which is here most appropriate to optimize investment strategies. The goal of proposed trading algorithm is to find most accurate signatures using back testing procedure applied to technical indicators for improving their performance. The problem is then to determine the signatures which, combined with an indicator, outperform this indicator alone. To do this, the FP-Tree algorithm has been preferred, as it appears to be the most efficient algorithm to perform this task.

Keywords: quantitative analysis, back-testing, computational models, apriori algorithm, pattern recognition, data mining, FP-tree

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Authors: Hanan Moawad, Naglaa M. Abd EL-Rahman

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Erwinia carotovora var. carotovora is the main cause of soft rot in potatoes. Hyphaene thebaica was studied for biocontrol of E. carotovora which inhibited growth of E. carotovora on solid medium, a comparative study of classical and ultrasound-assisted extractions of Hyphaene thebaica fruit. The use of ultrasound decreased significant the total time of treatment and increase the total amount of crude extract. The crude extract was subjected to determine the in vitro, by a bioassay technique revealed that the treatment of paper disks with ultrasound extraction of Hyphaene thebaica reduced the growth of pathogen and produced inhibition zones up to 38mm in diameter. The antioxidant activity of ultrasound-ethanolic extract of Doum fruits (Hyphaene thebaica) was determined. Data obtained showed that the extract contains the secondary metabolites such as Tannins, Saponin, Flavonoids, Phenols, Steroids, Terpenoids, Glycosides and Alkaloids.

Keywords: ultrasound, classical extract, biological control, Erwinia carotovora, Hyphaene thebaica

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Authors: Mohammad Mardi

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Generally, the resistivity is high in oil layer and low in water layer. Yet there are intervals of oil-bearing zones showing low resistivity, high porosity, and low resistance. In the typical example, well A (depth: 4341.5-4372.0m), both Spectral Gamma Ray (SGR) and Corrected Gamma Ray (CGR) are relatively low; porosity varies from 12-22%. Above 4360 meters, the reservoir shows the conventional positive difference between deep and shallow resistivity with high resistance; below 4360m, the reservoir shows a negative difference with low resistance, especially at depths of 4362.4 meters and 4371 meters, deep resistivity is only 2Ω.m, and the CAST-V imaging map shows that there are low resistance substances contained in the pores or matrix in the reservoirs of this interval. The rock slice analysis data shows that the pyrite volume is 2-3% in the interval 4369.08m-4371.55m. A comprehensive analysis on the volume of shale (Vsh), porosity, invasion features of resistivity, mud logging, and mineral volume indicates that the possible causes for the negative difference between deep and shallow resistivities with relatively low resistance are erosional pores, caves, micritic texture and the presence of pyrite. Full-bore Drill Stem Test (DST) verified 4991.09 bbl/d in this interval. To identify and thoroughly characterize low resistivity intervals coring, Nuclear Magnetic Resonance (NMR) logging and further geological evaluation are needed.

Keywords: low resistivity pay, carbonates petrophysics, microporosity, porosity

Procedia PDF Downloads 154

Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

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Authors: Navab Karimi, Tohid Alizadeh

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An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively.

Keywords: sun-dried organic raisin, genetic algorithm, feature extraction, ann regression, linear regression, support vector machine, south azerbaijan.

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Authors: Juliane P. De Oliveira, Carlos H. Dos Santos, Marcia Shoji, Maria E. C. Ferreira, Natalia U. Yamaguchi

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The construction sector is considered a major generator of environmental impacts due to the high consumption of natural resources and waste generation. Thus, this article aims to evaluate the performance of a concrete produced by the partial and total replacement of natural coarse aggregate by recycled coarse aggregate, derived from the concrete residue of buildings and demolitions. The study was made by comparing the compressive strength and absorption of three different concrete traces, keeping the water/cement factor of 0.60 and changing only the proportions of recycled coarse aggregate between 0%, 50% and 100%. Traces 50% and 100% obtained good results by comparing the actual specific mass, because the material used is lighter to the natural coarse aggregate. It was concluded that the concrete produced with recycled aggregates, even with inferior results, can be used where it is not needed a structural function, giving an adequate destination to the construction and demolition waste and consequently reducing the extraction and consumption of natural resources.

Keywords: green concrete, recycled aggregate, recycling, sustainable development

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Authors: Dita Mayasari, Zahrina Mardina, Riki Siswanto, Agresta Ifada, Ova Oktavina, Prihartini Widiyanti

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Heart failure is a serious major health problem with high number of mortality per year. Bypass is one of the solutions that has often been taken. Natural vascular graft (xenograft) as the substitute in bypass is inconvenient due to ethic problems and the risk of infection transmission caused by the usage of another species transgenic vascular. Nowadays, synthetic materials have been fabricated from polymers. The aim of this research is to make a synthetic vascular graft with great physical strength, high biocompatibility, and good affordability. The method of this research was mixing PLGA and collagen by magnetic stirrer. This composite were shaped by spinneret with water as coagulant. Then it was coated by chitosan with 3 variations of weight (1 gram, 2 grams, and 3 grams) to increase hemo and cytocompatibility, proliferation, and cell attachment in order for the vascular graft candidates to be more biocompatible. Mechanical strength for each variation was 5,306 MPa (chitosan 1 gram), 3,433 MPa (chitosan 2 grams) and 3,745 MPa (chitosan 3 grams). All the tensile values were higher than human vascular tensile strength. Toxicity test showed that the living cells in all variations were more than 60% in number, thus the vascular graft is not toxic.

Keywords: chitosan, collagen, PLGA, spinneret

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Authors: Andrew R. Winters, Gregor J. Gassner

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A high-order numerical magentohydrodynamics (MHD) solver built upon a non-linear entropy stable numerical flux function that supports eight traveling wave solutions will be described. The method is designed to treat the divergence-free constraint on the magnetic field in a similar fashion to a hyperbolic divergence cleaning technique. The solver is especially well-suited for flows involving strong discontinuities due to its strong stability without the need to enforce artificial low density or energy limits. Furthermore, a new formulation of the numerical algorithm to guarantee positivity of the pressure during the simulation is described and presented. By construction, the solver conserves mass, momentum, and energy and is entropy stable. High spatial order is obtained through the use of a third order limiting technique. High temporal order is achieved by utilizing the family of strong stability preserving (SSP) Runge-Kutta methods. Main attributes of the solver are presented as well as details on an implementation of the new solver into the multi-physics, multi-scale simulation code FLASH. The accuracy, robustness, and computational efficiency is demonstrated with a variety of numerical tests. Comparisons are also made between the new solver and existing methods already present in FLASH framework.

Keywords: entropy stability, finite volume scheme, magnetohydrodynamics, pressure positivity

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Authors: Reynaldo Esquivel, Pedro Hernandez, Aaron Martinez-Higareda, Sergio Tena-Cano, Enrique Alvarez-Ramos, Armando Lucero-Acuna

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Stimuli-responsive nanomaterials play an essential role in loading, transporting and well-distribution of anti-cancer compounds in the cellular surroundings. The outstanding properties as the Lower Critical Solution Temperature (LCST), hydrolytic cleavage and protonation/deprotonation cycle, govern the release and delivery mechanisms of payloads. In this contribution, we experimentally determine the load efficiency and release of antineoplastic Vincristine Sulfate into PNIPAM-Interpenetrated-Chitosan (PIntC) nanoparticles. Structural analysis was performed by Fourier Transform Infrared Spectroscopy (FT-IR) and Proton Nuclear Magnetic Resonance (1HNMR). ζ-Potential (ζ) and Hydrodynamic diameter (DH) measurements were monitored by Electrophoretic Mobility (EM) and Dynamic Light scattering (DLS) respectively. Mathematical analysis of the release pharmacokinetics reveals a three-phase model above LCST, while a monophasic of Vincristine release model was observed at 32 °C. Cytotoxic essays reveal a noticeable enhancement of Vincristine effectiveness at low drug concentration on HeLa cervix cancer and MDA-MB-231 breast cancer.

Keywords: nanoparticles, vincristine, drug delivery, PNIPAM

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Authors: Ali Abdrhman M. Ukasha

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Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression-salt- peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption

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Authors: Jasneet Kaur, Swapandeep Singh Chimni

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The unfavorable use of metal-based catalysts that are often extortionate and toxic can be overcome by using small organic molecules known as organocatalysts. A variety of small organic molecules, including Brønsted/Lewis bases and acids, based on sulfonic acids, phosphoric acids, amines, phosphines or carbenes, Cinchona alkaloids, have been used as organocatalysts. One of the key reasons for using organocatalysis is their ability to be effectively removed from the final product in comparison to the metallic counterparts, which are exceedingly difficult to remove. The present investigation seeks to explore the catalytic nature of Cinchona alkaloids as an organocatalyst for enantioselective synthesis of 3-substituted-3-aminooxindole, which is known to exhibit a variety of biological activities and pharmacological activities. In this context, an organocatalytic asymmetric route for the synthesis of 3-aminooxindoles via reaction of isatin imine with α-acetoxy-β-ketoesters has been developed. The bifunctional Cinchona derived thiourea catalyzed the reaction of α-acetoxy-β-ketoesters derivatives with isatin imine to afford 3-substituted-aminooxindole derivatives in up to 93% yield, 95% enantiomeric excess and >20:1 diastereomeric ratio. The reaction was performed at room temperature for two hours using 10 mol% of catalyst, in the presence of 4Å molecular sieves in tetrahydrofuran as a solvent at ambient temperature. After the completion of the reaction, the pure product could be easily separated by using column chromatography using hexane and ethyl acetate as solvents. In conclusion, the catalytic potential of Cinchona derived chiral thiourea-tertiary amine catalyst was explored for an organocatalytic enantioselective Mannich reaction of β-ketoester derivatives with various isatin imine derivatives under mild conditions.

Keywords: asymmetric synthesis, aminooxindoles, enantioselective, isatin imine

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Authors: Salmin K. Alshalmani, Nada H. Zobi, Ismaeel H. Bozakouk

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Marine organisms are potentially prolific sources of highly bio active secondary metabolites that might represent useful leads in the development of new pharmaceutical agents. The Libyan marine biodiversity including macroalgae remains partially unexplored in term of their potential bio activities. The phytochemical analysis of the alcoholic extracts of some commonly occurring seaweed Cystoseira compressa, enteromorpha intestinals, corallina, and Ulva lactuca and their evaluated for antibacterial activity by well diffusion assay were studied. Four different solvents namely water, ethanol 99 %, methanol 99 %, and methylated spirit 95 % were used for extraction. The phytochemical analysis revealed the presence of carbohydrates, steroids, tannin & phenols, saponins, proteins, and glycosides. The extracts were subjected for study of antibacterial activity. The zone of inhibition ranged between 8 to 16 mm in aqueous extract and up to 16 mm in methanol extract. The maximum activity (16 mm) was recorded from methanol extract of Ulva lactuca against Staphylococcus aureus and, minimum activity (8mm) recorded by Cystoseira compressa against S. aureus.

Keywords: macroalgae, phytochemicals, antibacterial activity, methanolic extract

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Authors: Pachari Chuenta, Suwat Nanan

Abstract:

ZnO nanostructures have been synthesized successfully in high yield via catalyst-free chemical precipitation technique by varying zinc source (either zinc nitrate or zinc acetate) and oxygen source (either oxalic acid or urea) without using any surfactant, organic solvent or capping agent. The ZnO nanostructures were characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray diffractometry (XRD), scanning electron microscopy (SEM), thermal gravimetric analysis (TGA), UV-vis diffuse reflection spectroscopy (UV-vis DRS), and photoluminescence spectroscopy (PL). The FTIR peak in the range of 450-470 cm-1 corresponded to Zn-O stretching in ZnO structure. The synthesized ZnO samples showed well crystalized hexagonal wurtzite structure. SEM micrographs displayed spherical droplet of about 50-100 nm. The band gap of prepared ZnO was found to be 3.4-3.5 eV. The presence of PL peak at 468 nm was attributed to surface defect state. The photocatalytic activity of ZnO was studied by monitoring the photodegradation of reactive red (RR141) azo dye under ultraviolet (UV) light irradiation. Blank experiment was also separately carried out by irradiating the aqueous solution of the dye in absence of the photocatalyst. The initial concentration of the dye was fixed at 10 mgL-1. About 50 mg of ZnO photocatalyst was dispersed in 200 mL dye solution. The sample was collected at a regular time interval during the irradiation and then was analyzed after centrifugation. The concentration of the dye was determined by monitoring the absorbance at its maximum wavelength (λₘₐₓ) of 544 nm using UV-vis spectroscopic analysis technique. The sources of Zn and O played an important role on photocatalytic performance of the ZnO photocatalyst. ZnO nanoparticles which prepared by zinc acetate and oxalic acid at molar ratio of 1:1 showed high photocatalytic performance of about 97% toward photodegradation of reactive red azo dye (RR141) under UV light irradiation for only 60 min. This work demonstrates the promising potential of ZnO nanomaterials as photocatalysts for environmental remediation.

Keywords: azo dye, chemical precipitation, photocatalytic, ZnO

Procedia PDF Downloads 139

Authors: Md. Shah Alam

Abstract:

Mushfiq Ahmad has defined a Mixed Number, which is the sum of a scalar and a Cartesian vector. He has also defined the elementary group operations of Mixed numbers i.e. the norm of Mixed numbers, the product of two Mixed numbers, the identity element and the inverse. It has been observed that Mixed Number is consistent with Pauli matrix algebra and a handy tool to work with Dirac electron theory. Its use as a mathematical method in Physics has been studied. (1) We have applied Mixed number in Quantum Mechanics: Mixed Number version of Displacement operator, Vector differential operator, and Angular momentum operator has been developed. Mixed Number method has also been applied to Klein-Gordon equation. (2) We have applied Mixed number in Electrodynamics: Mixed Number version of Maxwell’s equation, the Electric and Magnetic field quantities and Lorentz Force has been found. (3) An associative transformation of Mixed Number numbers fulfilling Lorentz invariance requirement is developed. (4) We have applied Mixed number algebra as an extension of Complex number. Mixed numbers and the Quaternions have isomorphic correspondence, but they are different in algebraic details. The multiplication of unit Mixed number and the multiplication of unit Quaternions are different. Since Mixed Number has properties similar to those of Pauli matrix algebra, Mixed Number algebra is a more convenient tool to deal with Dirac equation.

Keywords: mixed number, special relativity, quantum mechanics, electrodynamics, pauli matrix

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Authors: Umit Candan, Kadir Dogan, Ozkan Akin

Abstract:

In this study, the use of a modified rotor 6/4 Switched Reluctance Motor (SRM) and a Brushless Direct Current Motor (BLDC) in pan-tilt systems is compared. Pan-tilt systems are critical mechanisms that enable the precise orientation of cameras and sensors, and their performance largely depends on the characteristics of the motors used. The aim of the study is to determine how the performance of the SRM can be improved through rotor modifications and how these improvements can compete with BLDC motors. Using Finite Element Method (FEM) analyses, the design characteristics and magnetic performance of the 6/4 Switched Reluctance Motor are examined in detail. The modified SRM is found to offer increased torque capacity and efficiency while standing out with its simple construction and robustness. FEM analysis results of SRM indicate that considering its cost-effectiveness and performance improvements achieved through modifications, the SRM is a strong alternative for certain pan-tilt applications. This study aims to provide engineers and researchers with a performance comparison of the modified rotor 6/4 SRM and BLDC motors in pan-tilt systems, helping them make more informed and effective motor selections.

Keywords: reluctance machines, switched reluctance machines, pan-tilt application, comparison, FEM analysis

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Authors: Junkyeong Kim, Jooyoung Park, Aoqi Zhang, Seunghee Park

Abstract:

The tensile force of Pre-Stressed Concrete (PSC) girder is the most important factor for evaluating the performance of PSC girder bridges. To measure the tensile force of PSC girder, several NDT methods were studied. However, conventional NDT method cannot be applied to the real-size PSC girder because the PS tendons could not be approached. To measure the tensile force of real-size PSC girder, this study proposed embedded EM sensor based tensile force estimation method. The embedded EM sensor could be installed inside of PSC girder as a sheath joint before the concrete casting. After curing process, the PS tendons were installed, and the tensile force was induced step by step using hydraulic jacking machine. The B-H loop was measured using embedded EM sensor at each tensile force steps and to compare with actual tensile force, the load cell was installed at each end of girder. The magnetization energy loss, that is the closed area of B-H loop, was decreased according to the increase of tensile force with regular pattern. Thus, the tensile force could be estimated by the tracking the change of magnetization energy loss of PS tendons. Through the experimental result, the proposed method can be used to estimate the tensile force of the in-situ real-size PSC girder bridge.

Keywords: tensile force estimation, embedded EM sensor, magnetization energy loss, PSC girder

Procedia PDF Downloads 326

Authors: Jay L. Fu

Abstract:

Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

Procedia PDF Downloads 133