Search results for: malaria cells images

Authors: Divya Pradip Roy, Md. Zahirul Alam Chowdhury

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Electromyography (EMG) sensors are generally used to record the electrical activity produced by skeletal muscles. The conventional EMG sensors available in the market are expensive. This research suggests a low cost EMG sensor design which can be built with simple devices within our reach. In this research, one instrumentation amplifier, two high pass filters, two low pass filters and an inverting amplifier is connected sequentially. The output from the circuit exhibits electrical potential generated by the muscle cells when they are neurologically activated. This electromyography signal is used to control prosthetic devices, identifying neuromuscular diseases and for various other purposes.

Keywords: EMG, high pass filter, instrumentation amplifier, inverting amplifier, low pass filter, neuromuscular

Procedia PDF Downloads 175

Authors: Ajish Sreedharan

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With the fast evolution of digital data exchange, security information becomes much important in data storage and transmission. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. As encryption process is applied to the whole image in AES ,it is difficult to improve the efficiency. In this paper, wavelet decomposition is used to concentrate the main information of image to the low frequency part. Then, AES encryption is applied to the low frequency part. The high frequency parts are XORed with the encrypted low frequency part and a wavelet reconstruction is applied. Theoretical analysis and experimental results show that the proposed algorithm has high efficiency, and satisfied security suits for image data transmission.

Keywords: discrete wavelet transforms, AES, dynamic SBox

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Authors: Manoj Gupta, Nirmendra Singh Bhadauria

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Most of the applications in image processing require high spatial and high spectral resolution in a single image. For example satellite image system, the traffic monitoring system, and long range sensor fusion system all use image processing. However, most of the available equipment is not capable of providing this type of data. The sensor in the surveillance system can only cover the view of a small area for a particular focus, yet the demanding application of this system requires a view with a high coverage of the field. Image fusion provides the possibility of combining different sources of information. In this paper, we have decomposed the image using DTCWT and then fused using average and hybrid of (maxima and average) pixel level techniques and then compared quality of both the images using PSNR.

Keywords: image fusion, DWT, DT-CWT, PSNR, average image fusion, hybrid image fusion

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Pallab Datta, Jyotirmoy Chatterjee, Santanu Dhara

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Over the past few years, phosphorous containing polymers have received widespread attention for applications such as high performance optical fibers, flame retardant materials, drug delivery and tissue engineering. Being pentavalent, phosphorous can exist in different chemical environments in these polymers which increase their versatility. In human biochemistry, phosphorous based compounds exert their functions both in soluble and insoluble form occurring as inorganic or as organophosphorous compounds. Specifically in case of biomacromolecules, phosphates are critical for functions of DNA, ATP, phosphoproteins, phospholipids, phosphoglycans and several coenzymes. Inspired by the role of phosphorous in functional biomacromolecules, design and synthesis of biomimetic materials are thus carried out by several authors to study macromolecular function or as substitutes in clinical tissue regeneration conditions. In addition, many regulatory signals of the body are controlled by phoshphorylation of key proteins present either in form of growth factors or matrix-bound scaffold proteins. This inspires works on synthesis of phospho-peptidomimetic amino acids for understanding key signaling pathways and this is extended to obtain molecules with potentially useful biological properties. Apart from above applications, phosphate groups bound to polymer backbones have also been demonstrated to improve function of osteoblast cells and augment performance of bone grafts. Despite the advantages of phosphate grafting, however, there is limited understanding on effect of degree of phosphorylation on macromolecular physicochemical and/or biological properties. Such investigations are necessary to effectively translate knowledge of macromolecular biochemistry into relevant clinical products since they directly influence processability of these polymers into suitable scaffold structures and control subsequent biological response. Amongst various techniques for fabrication of biomimetic scaffolds, nanofibrous scaffolds fabricated by electrospinning technique offer some special advantages in resembling the attributes of natural extracellular matrix. Understanding changes in physico-chemical properties of polymers as function of phosphorylation is therefore going to be crucial in development of nanofiber scaffolds based on phosphorylated polymers. The aim of the present work is to investigate the effect of phosphorous grafting on the electrospinning behavior of polymers with aim to obtain biomaterials for bone regeneration applications. For this purpose, phosphorylated derivatives of two polymers of widely different electrospinning behaviors were selected as starting materials. Poly(vinyl alcohol) is a conveniently electrospinnable polymer at different conditions and concentrations. On the other hand, electrospinning of chitosan backbone based polymers have been viewed as a critical challenge. The phosphorylated derivatives of these polymers were synthesized, characterized and electrospinning behavior of various solutions containing these derivatives was compared with electrospinning of pure poly (vinyl alcohol). In PVA, phosphorylation adversely impacted electrospinnability while in NMPC, higher phosphate content widened concentration range for nanofiber formation. Culture of MG-63 cells on electrospun nanofibers, revealed that degree of phosphate modification of a polymer significantly improves cell adhesion or osteoblast function of cultured cells. It is concluded that improvement of cell response parameters of nanofiber scaffolds can be attained as a function of controlled degree of phosphate grafting in polymeric biomaterials with implications for bone tissue engineering applications.

Keywords: bone regeneration, chitosan, electrospinning, phosphorylation

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Authors: Man N. M. Cheung

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In judging the attractiveness of female body shape, visual sense is one of the important means. The ratio and proportion of body shape influence the perception of female physical attractiveness. This study aims to examine visual perception of digital textile prints on a virtual 3D model in judging the attractiveness of the body shape. Also, investigate the influences when using different shape parameters and their relationships. Participants were asked to conduct a set of questionnaires with images to rank the attractiveness of the female body shape. Results showed that morphing the fabric prints with a certain ratio and combination of shape parameters - waist and hip, can enhance the attractiveness of the female body shape.

Keywords: digital printing, 3D body modeling, fashion print design, body shape attractiveness

Procedia PDF Downloads 179

Authors: Achiron Anat, Mathilda Mandel, Mayust Sue, Achiron Reuven, Gurevich Michael

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Introduction: As coronavirus disease 2019 (COVID-19) vaccination is currently spreading around the world, it is of importance to assess the ability of multiple sclerosis (MS) patients to mount an appropriate immune response to the vaccine in the context of disease-modifying treatments (DMT’s). Objectives: Evaluate immunity generated following COVID-19 vaccination in MS patients, and assess factors contributing to protective humoral and cellular immune responses in MS patients vaccinated against severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) virus infection. Methods: Review our recent data related to (1) the safety of PfizerBNT162b2 COVID-19 mRNA vaccine in adult MS patients; (2) the humoral post-vaccination SARS-CoV2 IgG response in MS vaccinees using anti-spike protein-based serology; and (3) the cellular immune response of memory B-cells specific for SARS-CoV-2 receptor-binding domain (RBD) and memory T-cells secreting IFN-g and/or IL-2 in response to SARS-CoV2 peptides using ELISpot/Fluorospot assays in MS patients either untreated or under treatment with fingolimod, cladribine, or ocrelizumab; (4) covariate parameters related to mounting protective immune responses. Results: COVID-19 vaccine proved safe in MS patients, and the adverse event profile was mainly characterised by pain at the injection site, fatigue, and headache. Not any increased risk of relapse activity was noted and the rate of patients with acute relapse was comparable to the relapse rate in non-vaccinated patients during the corresponding follow-up period. A mild increase in the rate of adverse events was noted in younger MS patients, among patients with lower disability, and in patients treated with DMTs. Following COVID-19 vaccination protective humoral immune response was significantly decreased in fingolimod- and ocrelizumab- treated MS patients. SARS-CoV2 specific B-cell and T-cell cellular responses were respectively decreased. Untreated MS patients and patients treated with cladribine demonstrated protective humoral and cellular immune responses, similar to healthy vaccinated subjects. Conclusions: COVID-19 BNT162b2 vaccine proved as safe for MS patients. No increased risk of relapse activity was noted post-vaccination. Although COVID-19 vaccination is new, accumulated data demonstrate differences in immune responses under various DMT’s. This knowledge can help to construct appropriate COVID-19 vaccine guidelines to ensure proper immune responses for MS patients.

Keywords: covid-19, vaccination, multiple sclerosis, IgG

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Authors: Umut Kokbas, Mustafa Nisari

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Immunoglobulins, also known as antibodies, are glycoprotein molecules produced by activated B cells that transform into plasma cells and result in them. Antibodies are critical molecules of the immune response to fight, which help the immune system specifically recognize and destroy antigens such as bacteria, viruses, and toxins. Immunoglobulin classes differ in their biological properties, structures, targets, functions, and distributions. Five major classes of antibodies have been identified in mammals: IgA, IgD, IgE, IgG, and IgM. Evaluation of the immunoglobulin isotype can provide a useful insight into the complex humoral immune response. Evaluation and knowledge of immunoglobulin structure and classes are also important for the selection and preparation of antibodies for immunoassays and other detection applications. The immunoglobulin test measures the level of certain immunoglobulins in the blood. IgA, IgG, and IgM are usually measured together. In this way, they can provide doctors with important information, especially regarding immune deficiency diseases. Hypogammaglobulinemia (HGG) is one of the main groups of primary immunodeficiency disorders. HGG is caused by various defects in B cell lineage or function that result in low levels of immunoglobulins in the bloodstream. This affects the body's immune response, causing a wide range of clinical features, from asymptomatic diseases to severe and recurrent infections, chronic inflammation and autoimmunity Transient infant hypogammaglobulinemia (THGI), IgM deficiency (IgMD), Bruton agammaglobulinemia, IgA deficiency (SIgAD) HGG samples are a few. Most patients can continue their normal lives by taking prophylactic antibiotics. However, patients with severe infections require intravenous immune serum globulin (IVIG) therapy. The IgE level may rise to fight off parasitic infections, as well as a sign that the body is overreacting to allergens. Also, since the immune response can vary with different antigens, measuring specific antibody levels also aids in the interpretation of the immune response after immunization or vaccination. Immune deficiencies usually occur in childhood. In Immunology and Allergy clinics, apart from the classical methods, it will be more useful in terms of diagnosis and follow-up of diseases, if it is fast, reliable and especially in childhood hypogammaglobulinemia, sampling from children with a method that is more convenient and uncomplicated. The antibodies were attached to the electrode surface via the poly hydroxyethyl methacrylamide cysteine nanopolymer. It was used to evaluate the anodic peak results obtained in the electrochemical study. According to the data obtained, immunoglobulin determination can be made with a biosensor. However, in further studies, it will be useful to develop a medical diagnostic kit with biomedical engineering and to increase its sensitivity.

Keywords: biosensor, immunosensor, immunoglobulin, infection

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Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

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Authors: Roza Dzierzak, Waldemar Wojcik, Piotr Kacejko

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Analysis of the texture of medical images consists of determining the parameters and characteristics of the examined tissue. The main goal is to assign the analyzed area to one of two basic groups: as a healthy tissue or a tissue with pathological changes. The CT images of the thoracic lumbar spine from 15 healthy patients and 15 with confirmed osteoporosis were used for the analysis. As a result, 120 samples with dimensions of 50x50 pixels were obtained. The set of features has been obtained based on the histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model, and Haar wavelet. As a result of the image analysis, 290 descriptors of textural features were obtained. The dimension of the space of features was reduced by the use of three selection methods: Fisher coefficient (FC), mutual information (MI), minimization of the classification error probability and average correlation coefficients between the chosen features minimization of classification error probability (POE) and average correlation coefficients (ACC). Each of them returned ten features occupying the initial place in the ranking devised according to its own coefficient. As a result of the Fisher coefficient and mutual information selections, the same features arranged in a different order were obtained. In both rankings, the 50% percentile (Perc.50%) was found in the first place. The next selected features come from the co-occurrence matrix. The sets of features selected in the selection process were evaluated using six classification tree methods. These were: decision stump (DS), Hoeffding tree (HT), logistic model trees (LMT), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). In order to assess the accuracy of classifiers, the following parameters were used: overall classification accuracy (ACC), true positive rate (TPR, classification sensitivity), true negative rate (TNR, classification specificity), positive predictive value (PPV) and negative predictive value (NPV). Taking into account the classification results, it should be stated that the best results were obtained for the Hoeffding tree and logistic model trees classifiers, using the set of features selected by the POE + ACC method. In the case of the Hoeffding tree classifier, the highest values of three parameters were obtained: ACC = 90%, TPR = 93.3% and PPV = 93.3%. Additionally, the values of the other two parameters, i.e., TNR = 86.7% and NPV = 86.6% were close to the maximum values obtained for the LMT classifier. In the case of logistic model trees classifier, the same ACC value was obtained ACC=90% and the highest values for TNR=88.3% and NPV= 88.3%. The values of the other two parameters remained at a level close to the highest TPR = 91.7% and PPV = 91.6%. The results obtained in the experiment show that the use of classification trees is an effective method of classification of texture features. This allows identifying the conditions of the spongy tissue for healthy cases and those with the porosis.

Keywords: classification, feature selection, texture analysis, tree algorithms

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Authors: H. Al-Khalifa, A. Al-Nasser

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The main immune organs in poultry are the thymus, spleen and bursa of Fabricius. During an immune response, mature lymphocytes and other immune cells interact with antigens in these tissues. Consequently, the mass of these organs can in some cases indicate immune status. The objective of the current study was to investigate the effect of feeding flaxseed on immune tissue weights. Cobb 500 broiler chickens were fed flaxseed at 15%, the control diet did not contain any flaxseed. Results showed that dietary supplementation with flaxseed did not affect the weights of the spleens of broiler chickens. However, it significantly lowered bursa weights (p<0.01), compared to the control diet. In addition, the bursae were thinner in appearance compared with bursii from chickens fed the control diets.

Keywords: bursa of fabricius, flaxseed, spleen, thymus

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Authors: Stoyan Nedeltchev, Markus Schubert

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By means of the ultrafast X-ray tomography facility, data were obtained at different superficial gas velocities U_G in a bubble column (0.1 m in ID) operated with an air-deionized water system at ambient conditions. Raw reconstructed images were treated by both the information entropy (IE) and the reconstruction entropy (RE) algorithms in order to identify the main transition velocities in a bubble column. The IE values exhibited two well-pronounced minima at U_G=0.025 m/s and U_G=0.085 m/s identifying the boundaries of the homogeneous, transition and heterogeneous regimes. The RE extracted from the central region of the column’s cross-section exhibited only one characteristic peak at U_G=0.03 m/s, which was attributed to the transition from the homogeneous to the heterogeneous flow regime. This result implies that the transition regime is non-existent in the core of the column.

Keywords: bubble column, ultrafast X-ray tomography, information entropy, reconstruction entropy

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Authors: Mustafa Öztas, Metin Bedir, Yahya Özdemir

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Boron doped of In2O3 films were prepared by spray pyrolysis technique at 350 °C substrate temperature, which is a low cost and large area technique to be well-suited for the manufacture of solar cells, using boric acid (H3BO3) as dopant source, and their properties were investigated as a function of doping concentration. X-ray analysis showed that the films were polycrystalline fitting well with a hexagonal structure and have preferred orientation in (220) direction. The changes observed in the energy band gap and structural properties of the films related to the boric acid concentration are discussed in detail.

Keywords: spray pyrolysis, In2O3, boron, optical properties, boric acid

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Authors: Khaled Harrar, Rachid Jennane

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The purpose of this study is the discrimination of 28 postmenopausal with osteoporotic femoral fractures from an age-matched control group of 28 women using texture analysis based on fractals. Two pre-processing approaches are applied on radiographic images; these techniques are compared to highlight the choice of the pre-processing method. Furthermore, the values of the fractal dimension are compared to those of the fractal signature in terms of the classification of the two populations. In a second analysis, the BMD measure at proximal femur was compared to the fractal analysis, the latter, which is a non-invasive technique, allowed a better discrimination; the results confirm that the fractal analysis of texture on calcaneus radiographs is able to discriminate osteoporotic patients with femoral fracture from controls. This discrimination was efficient compared to that obtained by BMD alone. It was also present in comparing subgroups with overlapping values of BMD.

Keywords: osteoporosis, fractal dimension, fractal signature, bone mineral density

Procedia PDF Downloads 425

Authors: Gaweł Magdalena, Lipkowska Anna, Olbert Magdalena, Frąckiewicz Ewelina, Librowski Tadeusz, Nowak Gabriel, Pilc Andrzej

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Heme oxygenase-1 (HO-1), also known as heat shock protein 32 (HSP32), has been shown to be implicated in cytoprotection in various organs. Its activation plays a significant role in acute and chronic inflammation, protecting cells from oxidative injury and apoptosis. This inducible isoform of HO catalyzes the first and rate-limiting step in heme degradation to produce equimolar quantities of biologically active products: carbon monoxide (CO), free iron and biliverdin. CO has been reported to possess anti-apoptotic properties. Moreover, it inhibits the production of proinflammatory cytokines and stimulates the synthesis of the anti-inflammatory interleukin-10 (IL-10), as well as promotes vasodilatation at sites of inflammation. The second product of catalytic HO-1 activity, free cytotoxic iron, is promptly sequestered into the iron storage protein ferritin, which lowers the pro-oxidant state of the cell. The third product, biliverdin, is subsequently converted by biliverdin reductase into the bile pigment bilirubin, the most potent endogenous antioxidant among the constituents of human serum, which modulates immune effector functions and suppresses inflammatory response. Furthermore, being one of the so-called stress proteins, HO-1 adaptively responds to different stressors, such as reactive oxygen species (ROS), inflammatory cytokines and heavy metals and thus protects cells against such conditions as ischemia, hemorrhagic shock, heat shock or hypoxia. It is suggested that pharmacologic modulation of HO-1 may represent an effective strategy for prevention of stress and drug-induced gastrointestinal toxicity. HO-1 is constitutively expressed in normal gastric, intestinal and colonic mucosa and up-regulated during inflammation. It has been proven that HO-1 up-regulated by hemin, heme and cobalt-protoporphyrin ameliorates experimental colitis. In addition, the up-regulation of HO-1 partially explains the mechanism of action of 5-aminosalicylic acid (5-ASA), which is used clinically as an anti-colitis agent. In 2009 Ueda et al. has reported for the first time that mucosal protection by Polaprezinc, a chelate compound of zinc and L-carnosine used as an anti-ulcer drug in Japan, is also attributed to induction of HO-1 in the stomach. Since then, inducers of HO-1 are desired subject of research, as they may constitute therapeutically effective anti-ulcer drugs.

Keywords: heme oxygenase-1, gastric lesions, gastroprotection, Polaprezinc

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Authors: Abdelaziz Moujane, Abedelali Boulli, Abdellah Ouigmane

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The present work focuses on the assessment of forestlandscape changes in the region of ZaouitAhansal, usingmultitemporal satellite images at high spatial resolution.Severalremotesensingmethodswereappliednamely: The supervised classification algorithm and NDVI whichwerecombined in a GIS environment to quantify the extent and change in density of forest stands (holmoak, juniper, thya, Aleppo pine, crops, and others).The resultsobtainedshowedthat the forest of ZaouitAhansal has undergonesignificantdegradationresulting in a decrease in the area of juniper, cedar, and zeenoak, as well as an increase in the area of baresoil and agricultural land. The remotesensing data providedsatisfactoryresults for identifying and quantifying changes in forestcover. In addition, thisstudycould serve as a reference for the development of management strategies and restoration programs.

Keywords: remote sensing, GIS, satellite image, NDVI, deforestation, zaouit ahansal

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Authors: Melissa Chavez Portillo, Mauricio Pacio Castillo, Hector Juarez Santiesteban, Oscar Portillo Moreno

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Chemical bath deposited PbS:Bi3+ as an electron collection layer is introduced between the silicon wafer and the Ag electrode the performance of the PbS heterojunction thin film solar thin film solar cells with 1 cm2 active area. We employed Bi-doping to transform it into an n-type semiconductor. The experimental results reveal that the cell response parameters depend critically on the deposition procedures in terms of bath temperature, deposition time. The device achieves an open-circuit voltage of 0.4 V. The simple and low-cost deposition method of PbS:Bi3+ films is promising for the fabrication.

Keywords: Bi doping, PbS, thin films, solar cell

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Authors: Bouzaki Mohammed Moustafa, Benyoucef Boumediene, Benouaz Tayeb, Benhamou Amina

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The ambient temperature and the defects density in the Hetero-junction with Intrinsic Thin layers solar cells (HIT) strongly influence their performances. In first part, we presented the bands diagram on the front/back simulated solar cell based on a-Si: H / c-Si (p)/a-Si:h. In another part, we modeled the following layers structure: ZnO/a-Si:H(n)/a-Si:H(i)/c-Si(p)/a-Si:H(p)/Ag where we studied the effect of the ambient temperature and the defects density in the gap of the crystalline silicon layer on the performance of the heterojunction solar cell with intrinsic layer (HIT).

Keywords: heterojunction solar cell, solar cell performance, bands diagram, ambient temperature, defect density

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Minakshi Mainaji Sonawane, Bharti W. Gawali, Sudhir Mendhekar, Ramesh R. Manza

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People's lives and health are severely impacted by skin diseases. A new study proposes an effective method for identifying the different forms of skin diseases. Image denoising is a technique for improving image quality after it has been harmed by noise. The proposed technique is based on the usage of the wavelet transform. Wavelet transform is the best method for analyzing the image due to the ability to split the image into the sub-band, which has been used to estimate the noise ratio at the noisy image. According to experimental results, the proposed method presents the best values for MSE, PSNR, and Entropy for denoised images. we can found in Also, by using different types of wavelet transform filters is make the proposed approach can obtain the best results 23.13, 20.08, 50.7 for the image denoising process

Keywords: MSE, PSNR, entropy, Gaussian filter, DWT

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Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: Ankita Singh, Chandan Gorain, Amirul I. Mallick

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Successful adherence of the mucosal epithelial cells is the key early step for Campylobacter jejuni pathogenesis (C. jejuni). A set of Surface Exposed Colonization Proteins (SECPs) are among the major factors involved in host cell adherence and invasion of C. jejuni. Among them, constitutively expressed surface-exposed lipoprotein adhesin of C. jejuni, JlpA, interacts with intestinal heat shock protein 90 (hsp90α) and contributes in disease progression by triggering pro-inflammatory response via activation of NF-κB and p38 MAP kinase pathway. Together with its ability to express in the bacterial surface, higher sequence conservation and predicted predominance of several B cells epitopes, JlpA protein reserves its potential to become an effective vaccine candidate against wide range of Campylobacter sps including C. jejuni. Given that chickens are the primary sources for C. jejuni and persistent gut colonization remain as major cause for foodborne pathogenesis to humans, present study explicitly used chickens as model to test the immune-protective efficacy of JlpA protein. Taking into account that gastrointestinal tract is the focal site for C. jejuni colonization, to extrapolate the benefit of mucosal (intragastric) delivery of JlpA protein, a food grade Nisin inducible Lactic acid producing bacteria, Lactococcus lactis (L. lactis) was engineered to express recombinant JlpA protein (rJlpA) in the surface of the bacteria. Following evaluation of optimal surface expression and functionality of recombinant JlpA protein expressed by recombinant L. lactis (rL. lactis), the immune-protective role of intragastric administration of live rL. lactis was assessed in commercial broiler chickens. In addition to the significant elevation of antigen specific mucosal immune responses in the intestine of chickens that received three doses of rL. lactis, marked upregulation of Toll-like receptor 2 (TLR2) gene expression in association with mixed pro-inflammatory responses (both Th1 and Th17 type) was observed. Furthermore, intragastric delivery of rJlpA expressed by rL. lactis, but not the injectable form, resulted in a significant reduction in C. jejuni colonization in chickens suggesting that mucosal delivery of live rL. lactis expressing JlpA serves as a promising vaccine platform to induce strong immune-protective responses against C. jejuni in chickens.

Keywords: chickens, lipoprotein adhesion of Campylobacter jejuni, immuno-protection, Lactococcus lactis, mucosal delivery

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Authors: H. Yousefnia, S. Zolghadri, AR. Jalilian, A. Mirzaei, A. Bahrami-Samani, M. Erfani

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The objective of this study is the preparation of 111In-DOTMP as a new bone imaging agent. 111In was produced at the Agricultural, Medical and Industrial Research School (AMIRS) by means of 30 MeV cyclotron via natCd(p,x)111In reaction. Complexion of In‐111 with DOTMP was carried out by adding 0.1 ml of the stock solution (50 mg/ml in 2 N NaoH) to the vial containing 1 mCi of 111In. pH of the mixture was adjusted to 7-8 by means of phosphate buffer. The radiochemical purity of the complex at the optimized condition was higher than 98% (by using whatman No.1 paper in NH4OH:MeOH: H2O (0.2:2:4)). Both the biodistribution studies and SPECT imaging indicated high bone uptake. The ratio of bone to other soft tissue accumulation was significantly high which permit to observe high quality images. The results show that 111In-DOTMP can be used as a suitable tracer for diagnosis of bone metastases by SPECT imaging.

Keywords: biodistribution, DOTMP, 111In, SPECT

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Authors: Zuzana Poborilova, Anna B. Ohlsson, Torkel Berglund, Anna Vildova, Petr Babula

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Lawsone is a pigment that occurs naturally in plants. It has been used as a skin and hair dye for a long time. Moreover, its different biological activities have been reported. The present study focused on the effect of lawsone on a plant cell model represented by tobacco BY-2 cell suspension culture, which is used as a model comparable with the HeLa cells. It has been shown that lawsone inhibits the cell growth in the concentration-dependent manner. In addition, changes in DNA methylation level have been determined. We observed decreasing level of DNA methylation in the presence of increasing concentrations of lawsone. These results were accompanied with overproduction of reactive oxygen species (ROS). Since epigenetic modifications can be caused by different stress factors, there could be a connection between the changes in the level of DNA methylation and ROS production caused by lawsone.

Keywords: DNA methylation, lawsone, naphthoquinone, reactive oxygen species

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Authors: Alisa Salimova, Jiane Zuo, Christopher Homer

Abstract:

The objective of this study is to analyse the North Canal riparian zone land use with the help of remote sensing analysis in ArcGis using 30 cloudless Landsat8 open-source satellite images from May to August of 2013 and 2017. Land cover, urban construction, heat island effect, vegetation cover, and water system change were chosen as the main parameters and further analysed to evaluate its impact on the North Canal water quality. The methodology involved the following steps: firstly, 30 cloudless satellite images were collected from the Landsat TM image open-source database. The visual interpretation method was used to determine different land types in a catchment area. After primary and secondary classification, 28 land cover types in total were classified. Visual interpretation method was used with the help ArcGIS for the grassland monitoring, US Landsat TM remote sensing image processing with a resolution of 30 meters was used to analyse the vegetation cover. The water system was analysed using the visual interpretation method on the GIS software platform to decode the target area, water use and coverage. Monthly measurements of water temperature, pH, BOD, COD, ammonia nitrogen, total nitrogen and total phosphorus in 2013 and 2017 were taken from three locations of the North Canal in Tongzhou district. These parameters were used for water quality index calculation and compared to land-use changes. The results of this research were promising. The vegetation coverage of North Canal riparian zone in 2017 was higher than the vegetation coverage in 2013. The surface brightness temperature value was positively correlated with the vegetation coverage density and the distance from the surface of the water bodies. This indicates that the vegetation coverage and water system have a great effect on temperature regulation and urban heat island effect. Surface temperature in 2017 was higher than in 2013, indicating a global warming effect. The water volume in the river area has been partially reduced, indicating the potential water scarcity risk in North Canal watershed. Between 2013 and 2017, urban residential, industrial and mining storage land areas significantly increased compared to other land use types; however, water quality has significantly improved in 2017 compared to 2013. This observation indicates that the Tongzhou Water Restoration Plan showed positive results and water management of Tongzhou district had been improved.

Keywords: North Canal, land use, riparian vegetation, river ecology, remote sensing

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Authors: Z. Razi, S. M. J. Mortazavi, N. Shokrpour, Z. Shayan, F. Amiri

Abstract:

Long-term exposure to low doses of ionizing radiation occurs in radiation health care workplaces. Although doses in health professions are generally very low, there are still matters of concern. The radiation safety program promotes occupational radiation safety through accurate and reliable monitoring of radiation workers in order to effectively manage radiation protection. To achieve this goal, it has become mandatory to implement health examination periodically. As a result, based on the hematological alterations, working populations with a common occupational radiation history are screened. This paper calls into question the effectiveness of blood component analysis as a screening program which is mandatory for medical radiation workers in some countries. This study details the distribution and trends of changes in blood components, including white blood cells (WBCs), red blood cells (RBCs) and platelets as well as received cumulative doses from occupational radiation exposure. This study was conducted among 199 participants and 100 control subjects at the medical imaging departments at the central hospital of Shiraz University of Medical Sciences during the years 2006–2010. Descriptive and analytical statistics, considering the P-value<0.05 as statistically significance was used for data analysis. The results of this study show that there is no significant difference between the radiation workers and controls regarding WBCs and platelet count during 4 years. Also, we have found no statistically significant difference between the two groups with respect to RBCs. Besides, no statistically significant difference was observed with respect to RBCs with regards to gender, which has been analyzed separately because of the lower reference range for normal RBCs levels in women compared to men and. Moreover, the findings confirm that in a separate evaluation between WBCs count and the personnel’s working experience and their annual exposure dose, results showed no linear correlation between the three variables. Since the hematological findings were within the range of control levels, it can be concluded that the radiation dosage (which was not more than 7.58 mSv in this study) had been too small to stimulate any quantifiable change in medical radiation worker’s blood count. Thus, use of more accurate method for screening program based on the working profile of the radiation workers and their accumulated dose is suggested. In addition, complexity of radiation-induced functions and the influence of various factors on blood count alteration should be taken into account.

Keywords: blood cell count, mandatory testing, occupational exposure, radiation

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Authors: Jaehong Kim, Sunhee Park, HongSeop Shin, Kyongho Lim, Suhyun Kwon, Don-Gyou Lee, Pureum Kim, Moojong Lim, JongSang Baek

Abstract:

Transparent displays with OLEDs are the most commonly produced forms of see-through displays on the market or in development. In order to block the visual interruption caused by the light coming from the background, the special panel is combined with transparent displays with OLEDs. There is, however, few studies performance of optical shutter panel for transparent displays until now. This paper, therefore, describes the performance of optical shutter panels. The novel evaluation method was developed by measuring the amount of light which can form a transmitted background image. The new proposed method could tell how recognizable transmitted background images cannot be seen, and is consistent with viewer’s perception.

Keywords: optical shutter panel, optical performance, transparent display, visual interruption

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Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

Abstract:

In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: segmentation, color-texture, neural networks, fractal, watershed

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Authors: Ibrahim Elnour Abdelrahman Eltayeb

Abstract:

Computational modelling is a method used to investigate joint forces during a movement. It can get high accuracy in the joint forces via subject-specific models. However, the construction of subject-specific models remains time-consuming and expensive. The purpose of this paper was to identify what alterations we can make to generic computational models to get a better estimation of the joint forces. It appraised the impact of these alterations on the accuracy of the estimated joint forces. It found different strategies of alterations: joint model, muscle model, and an optimisation problem. All these alterations affected joint contact force accuracy, so showing the potential for improving the model predictions without involving costly and time-consuming medical images.

Keywords: joint force, joint model, optimisation problem, validation

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Authors: Amdy Moustapha Drame, Ilya V. Germashev, E. A. Markushevskaya

Abstract:

Among the main problems of medicine is breast cancer, from which a significant number of women around the world are constantly dying. Therefore, the detection of malignant breast tumors is an urgent task. For many years, various technologies for detecting these tumors have been used, in particular, in thermal imaging in order to determine different levels of breast cancer development. These periodic screening methods are a diagnostic tool for women and may have become an alternative to older methods such as mammography. This article proposes a model for the identification of malignant neoplasms of the mammary glands by the asymmetry of internal and external thermal imaging fields.

Keywords: asymmetry, breast cancer, tumors, deep learning, thermogram, convolutional transformation, classification

Procedia PDF Downloads 60