Search results for: malaria cells images

Authors: Md. Danish Eqbal, Venkat Gundabala

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Microparticles and microcapsules are basically used as a carrier for cells, tissues, drugs, and chemicals. Due to its biocompatibility, non-toxicity and biodegradability, alginate based microparticles have numerous applications in drug delivery, tissue engineering, organ repair and transplantation, etc. The production of uniform monodispersed microparticles was a challenge for the past few decades. However, emergence of microfluidics has provided controlled methods for the generation of the uniform monodispersed microparticles. In this work, we present a successful method for the generation of both microparticles and microcapsules (single and double core) using merging approach of two droplets, completely inside the microfluidic device. We have fabricated hybrid glass- PDMS (polydimethylsiloxane) based microfluidic device which has coflow geometry as well as the T junction channel. Coflow is used to generate the single as well as double oil-alginate emulsion in oil and T junction helps to form the calcium chloride droplets in oil. The basic idea is to match the frequency of the alginate droplets and calcium chloride droplets perfectly for controlled generation. Using the merging of droplets technique, we have successfully generated the microparticles and the microcapsules having single core as well as double and multiple cores. The cores in the microcapsules are very stable, well separated from each other and very intact as seen through cross-sectional confocal images. The size and the number of the cores along with the thickness of the shell can be easily controlled by controlling the flowrate of the liquids.

Keywords: double-core, droplets, microcapsules, microparticles

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Authors: Abdelmajid Timoumi, Salah Alamri, Hatem Alamri

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TiO₂ Graphene Oxide (TiO₂-GO) nanocomposite was prepared using the spin coating technique of suspension of Graphene Oxide (GO) nanosheets and Titanium Tetra Isopropoxide (TIP). The prepared nanocomposites samples were characterized by X-ray diffractometer, Scanning Electron Microscope and Atomic Force Microscope to examine their structures and morphologies. UV-vis transmittance and reflectance spectroscopy was employed to estimate band gap energies. From the TiO₂-GO samples, a 0.25 μm thin layer on a piece of glass 2x2 cm was created. The X-ray diffraction analysis revealed that the as-deposited layers are amorphous in nature. The surface morphology images demonstrate that the layers grew in distributed with some spherical/rod-like and partially agglomerated TiGO on the surface of the composite. The Atomic Force Microscopy indicated that the films are smooth with slightly larger surface roughness. The analysis of optical absorption data of the layers showed that the values of band gap energy decreased from 3.46 eV to 1.40 eV, depending on the grams of GO doping. This reduction might be attributed to electron and/or hole trapping at the donor and acceptor levels in the TiO₂ band structure. Observed results have shown that the inclusion of GO in the TiO₂ matrix have exhibited significant and excellent properties, which would be promising for application in the photovoltaic application.

Keywords: titanium dioxide, graphene oxide, thin films, solar cells

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Authors: Avatharam Ganivada, Krishna Shah

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The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.

Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision

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Authors: Meenal Surawar, Rajashree Kotharkar

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Urban Heat Island (UHI) is found more pronounced as a prominent urban environmental concern in developing cities. To study the UHI effect in the Indian context, the Nagpur urban area has been explored in this paper using Landsat 7 ETM+ satellite images through Remote Sensing and GIS techniques. This paper intends to study the effect of LU/LC pattern on daytime Land Surface Temperature (LST) variation, contributing UHI formation within the Nagpur Urban area. Supervised LU/LC area classification was carried to study urban Change detection using ENVI 5. Change detection has been studied by carrying Normalized Difference Vegetation Index (NDVI) to understand the proportion of vegetative cover with respect to built-up ratio. Detection of spectral radiance from the thermal band of satellite images was processed to calibrate LST. Specific representative areas on the basis of urban built-up and vegetation classification were selected for observation of point LST. The entire Nagpur urban area shows that, as building density increases with decrease in vegetation cover, LST increases, thereby causing the UHI effect. UHI intensity has gradually increased by 0.7°C from 2000 to 2006; however, a drastic increase has been observed with difference of 1.8°C during the period 2006 to 2013. Within the Nagpur urban area, the UHI effect was formed due to increase in building density and decrease in vegetative cover.

Keywords: land use/land cover, land surface temperature, remote sensing, urban heat island

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Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

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In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

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Authors: R. Mofeed, N. Elgendy

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Cinema constructs mind-spaces that reflect inherent human thoughts and emotions. As a representational art, Cinema would introduce comprehensive images of life phenomena in different ways. The term “represent” suggests verity of meanings; bring into presence, replace or typify. In that sense, Cinema may present a phenomenon through direct embodiment, or introduce a substitute image that replaces the original phenomena, or typify it by relating the produced image to a more general category through a process of abstraction. This research is interested in questioning the type of images that Egyptian Cinema introduces to informal urbanism and how these images were conditioned and reshaped in the last twenty years. The informalities/slums phenomenon first appeared in Egypt and, particularly, Cairo in the early sixties, however, this phenomenon was completely ignored by the state and society until the eighties, and furthermore, its evident representation in Cinema was by the mid-nineties. The Informal City represents the illegal housing developments, and it is a fast growing form of urbanization in Cairo. Yet, this expanding phenomenon is still depicted as the minority, exceptional and marginal through the Cinematic lenses. This paper aims at tracing the forms of representations of the urban informalities in the Egyptian Cinema between 1994 and 2014, and how did that affect the popular mind and its perception of these areas. The paper runs two main lines of inquiry; the first traces the phenomena through a chronological and geographical mapping of the informal urbanism has been portrayed in films. This analysis is based on an academic research work at Cairo University in Fall 2014. The visual tracing through maps and timelines allowed a reading of the phases of ignorance, presence, typifying and repetition in the representation of this huge sector of the city through more than 50 films that has been investigated. The analysis clearly revealed the “portrayed image” of informality by the Cinema through the examined period. However, the second part of the paper explores the “perceived image”. A designed questionnaire is applied to highlight the main features of that image that is perceived by both inhabitants of informalities and other Cairenes based on watching selected films. The questionnaire covers the different images of informalities proposed in the Cinema whether in a comic or a melodramatic background and highlight the descriptive terms used, to see which of them resonate with the mass perceptions and affected their mental images. The two images; “portrayed” and “perceived” are then to be encountered to reflect on issues of repetitions, stereotyping and reality. The formulated stereotype of informal urbanism is finally outlined and justified in relation to both production consumption mechanisms of films and the State official vision of informalities.

Keywords: cinema, informal urbanism, popular mind, representation

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Authors: Agustinus Rudatyo Himamunanto, Anastasia Rita Widiarti

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Transliteration using Javanese manuscripts is one of methods to preserve and legate the wealth of literature in the past for the present generation in Indonesia. The transliteration manual process commonly requires philologists and takes a relatively long time. The automatic transliteration process is expected to shorten the time so as to help the works of philologists. The preprocessing and segmentation stage firstly done is used to manage the document images, thus obtaining image script units that will compile input document images free from noise and have the similarity in properties in the thickness, size, and slope. The next stage of characteristic extraction is used to find unique characteristics that will distinguish each Javanese script image. One of characteristics that is used in this research is the number of black pixels in each image units. Each image of Java scripts contained in the data training will undergo the same process similar to the input characters. The system testing was performed with the data of the book Hamong Tani. The book Hamong Tani was selected due to its content, age and number of pages. Those were considered sufficient as a model experimental input. Based on the results of random page automatic transliteration process testing, it was determined that the maximum percentage correctness obtained was 81.53%. The percentage of success was obtained in 32x32 pixel input image size with the 5x5 image window. With regard to the results, it can be concluded that the automatic transliteration model offered is relatively good.

Keywords: Javanese script, character recognition, statistical, automatic transliteration

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Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela

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Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.

Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution

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Authors: Abdu Zakari, Said Jibrin, Fatope Majekodunmi Oladeji, Mohammed Hassan Shagga, Andrew Sule

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From the Stems of Bark of Echinaceae angustifolia DC three known triterpenes 3a,5,5b,8,8,11a-hexamethyl-1-(prop-1-en-2-yl)icosahydro-1H-cyclopenta[a]chrysene-9-yl acetate (lupeol acetate), 4,4,6a,6b,8a,10,11,14b,octamethyl1,1,2,3,4,4a,5,6,6a,6b,7,8,8a, 9,10, 11,12,12a,14,14a,14b-icosahydropicen-3-yl acetate (derivative of β-amyrin and 9- hydroxy-1-isopropenyl-5a,5b,8,8,11a-pentamethyl-icosahydro-cyclopenta[a]chrysene- 3a-carboxylic acid (betulinic acid), labelled as Ea-7-38, Ea-9-10 and Ea-12-85) were isolated and characterized. All isolates were tested for their cytotoxicities against Artemia salina (brine shrimp larvae). Compound Ea-12-85 exhibited potent cytotoxic activity against the Artemia salina, Ea-7-38, Ea-9-10 were found to be non-toxic in the cytotoxicity test. The result of the study has justified the claim of the traditional medicine practitioners in Girei for the treatment of complicated malaria disease using the stem bark of E. angustifolia DC.

Keywords: cytotoxic, terpenes, Echinaceae angustifolia, brine shrimp, artemia salina

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Authors: Gagik Ayvazyan, Levon Hakhoyan, Surik Khudaverdyan, Laura Lakhoyan

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Black Si (b-Si) is a nano-structured Si surface formed by a self-organized, maskless process with needle-like surfaces discernible by their black color. The combination of low reflectivity and the semi-conductive properties of Si found in b-Si make it a prime candidate for application in solar cells as an antireflection surface. However, surface recombination losses significantly reduce the efficiency of b-Si solar cells. Surface passivation using suitable dielectric films can minimize these losses. Nowadays some works have demonstrated that excellent passivation of b-Si nanostructures can be reached using Al₂O₃ films. However, the negative fixed charge present in Al₂O₃ films should provide good field effect passivation only for p- and p+-type Si surfaces. HfO2 thin films have not been practically tested for passivation of b-Si. HfO₂ could provide an alternative for n- and n+- type Si surface passivation since it has been shown to exhibit positive fixed charge. Using optical simulation by Finite-Difference Time Domain (FDTD) method, the possibility of b-Si passivation by HfO2 films has been analyzed. The FDTD modeling revealed that b-Si layers with HfO₂ films effectively suppress reflection in the wavelength range 400–1000 nm and across a wide range of incidence angles. The light-trapping performance primarily depends on geometry of the needles and film thickness. With the decrease of periodicity and increase of height of the needles, the reflectance decrease significantly, and the absorption increases significantly. Increase in thickness results in an even greater decrease in the calculated reflection coefficient of model structures and, consequently, to an improvement in the antireflection characteristics in the visible range. The excellent surface passivation and low reflectance results prove the potential of using the combination of the b-Si surface and the HfO₂ film for solar cells applications.

Keywords: antireflection, black silicon, HfO₂, passivation, simulation, solar cell

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Authors: Juan Sebastian Huertas Piedrahita, Jaime Arturo Lopez Duque, Eduardo Luis Perez Londoño, Julián S. Rodríguez

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The process of generating computer vision is called artificial vision. The artificial vision is a branch of artificial intelligence that allows the obtaining, processing, and analysis of any type of information especially the ones obtained through digital images. Actually the artificial vision is used in manufacturing areas for quality control and production, as these processes can be realized through counting algorithms, positioning, and recognition of objects that can be measured by a single camera (or more). On the other hand, the companies use assembly lines formed by conveyor systems with actuators on them for moving pieces from one location to another in their production. These devices must be previously programmed for their good performance and must have a programmed logic routine. Nowadays the production is the main target of every industry, quality, and the fast elaboration of the different stages and processes in the chain of production of any product or service being offered. The principal base of this project is to program a computer that recognizes geometric figures (circle, square, and triangle) through a camera, each one with a different color and link it with a group of conveyor systems to organize the mentioned figures in cubicles, which differ from one another also by having different colors. This project bases on artificial vision, therefore the methodology needed to develop this project must be strict, this one is detailed below: 1. Methodology: 1.1 The software used in this project is QT Creator which is linked with Open CV libraries. Together, these tools perform to realize the respective program to identify colors and forms directly from the camera to the computer. 1.2 Imagery acquisition: To start using the libraries of Open CV is necessary to acquire images, which can be captured by a computer’s web camera or a different specialized camera. 1.3 The recognition of RGB colors is realized by code, crossing the matrices of the captured images and comparing pixels, identifying the primary colors which are red, green, and blue. 1.4 To detect forms it is necessary to realize the segmentation of the images, so the first step is converting the image from RGB to grayscale, to work with the dark tones of the image, then the image is binarized which means having the figure of the image in a white tone with a black background. Finally, we find the contours of the figure in the image to detect the quantity of edges to identify which figure it is. 1.5 After the color and figure have been identified, the program links with the conveyor systems, which through the actuators will classify the figures in their respective cubicles. Conclusions: The Open CV library is a useful tool for projects in which an interface between a computer and the environment is required since the camera obtains external characteristics and realizes any process. With the program for this project any type of assembly line can be optimized because images from the environment can be obtained and the process would be more accurate.

Keywords: artificial intelligence, artificial vision, binarized, grayscale, images, RGB

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Authors: Navdeep Goel, Salvador Gabarda

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Digital images are widely used in computer applications. To store or transmit the uncompressed images requires considerable storage capacity and transmission bandwidth. Image compression is a means to perform transmission or storage of visual data in the most economical way. This paper explains about how images can be encoded to be transmitted in a multiplexing time-frequency domain channel. Multiplexing involves packing signals together whose representations are compact in the working domain. In order to optimize transmission resources each 4x4 pixel block of the image is transformed by a suitable polynomial approximation, into a minimal number of coefficients. Less than 4*4 coefficients in one block spares a significant amount of transmitted information, but some information is lost. Different approximations for image transformation have been evaluated as polynomial representation (Vandermonde matrix), least squares + gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev polynomials or singular value decomposition (SVD). Results have been compared in terms of nominal compression rate (NCR), compression ratio (CR) and peak signal-to-noise ratio (PSNR) in order to minimize the error function defined as the difference between the original pixel gray levels and the approximated polynomial output. Polynomial coefficients have been later encoded and handled for generating chirps in a target rate of about two chirps per 4*4 pixel block and then submitted to a transmission multiplexing operation in the time-frequency domain.

Keywords: chirp signals, image multiplexing, image transformation, linear canonical transform, polynomial approximation

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Authors: Devadrita Dey Sarkar

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Regardless of the many technologic advances in the past decade, increased training and experience, and the obvious benefits of uniform standards, the false-negative rate in screening mammography remains unacceptably high .A computer aided neural network classification of regions of suspicion (ROS) on digitized mammograms is presented in this abstract which employs features extracted by a new technique based on independent component analysis. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral breast images has the potential to improve the overall performance in the detection of breast lumps. Because breast lumps can be detected reliably by computer on lateral breast mammographs, radiologists’ accuracy in the detection of breast lumps would be improved by the use of CAD, and thus early diagnosis of breast cancer would become possible. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for breast CAD may include the computerized detection of breast nodules, as well as the computerized classification of benign and malignant nodules. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with these CAD systems, which would be reliable and useful method for quantifying the similarity of a pair of images for visual comparison by radiologists.

Keywords: CAD(computer-aided design), lesions, neural network, ROS(region of suspicion)

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Authors: Cut Maisyarah Karyati, Aries Muslim, Sulardi

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Digital image processing techniques to obtain detailed information from an image have been used in various fields, including in civil engineering, where the use of solid beam profiles in buildings and bridges has often been encountered since the early development of beams. Along with this development, the founded castellated beam profiles began to be more diverse in shape, such as the shape of a hexagon, triangle, pentagon, circle, ellipse and oval that could be a practical solution in optimizing a construction because of its characteristics. The purpose of this research is to create a computer application to edge detect the profile of various shapes of the castella beams hole. The digital image segmentation method has been used to obtain the grayscale images and represented in 2D and 3D formats. This application has been successfully made according to the desired function, which is to provide information on the type of castella beam hole.

Keywords: digital image, image processing, edge detection, grayscale, castella beams

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Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

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Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

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Authors: Trenten Theis, Trevor Daubert, Kennedy Kluthe, Austin Nuxoll

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Staphylococcus aureus is a gram-positive bacterium responsible for an estimated 23,000 deaths in the United States and 25,000 deaths in the European Union annually. Recurring S. aureus bacteremia is associated with biofilm-mediated infections and can occur in 5 - 20% of cases, even with the use of antibiotics. Despite these infections being caused by drug-susceptible pathogens, they are surprisingly difficult to eradicate. One potential explanation for this is the presence of persister cells—a dormant type of cell that shows a high tolerance to antibiotic treatment. Recent studies have shown a connection between low intracellular ATP and persister cell formation. Specifically, this decrease in ATP, and therefore increase in persister cell formation, is due to an interrupted tricarboxylic acid (TCA) cycle. However, S. aureus persister cells’ role in pathogenesis remains unclear. Initial studies have shown that a fumC (TCA cycle gene) knockout survives challenge from aspects of the innate immune system better than wild-type S. aureus. Specifically, challenges from two antimicrobial peptides--LL-37 and hBD-3—show a log increase in survival of the fumC::N∑ strain compared to wild type S. aureus after 18 hours. Furthermore, preliminary studies show that the fumC knockout has a log more survival within a macrophage. These data lead us to hypothesize that the fumC knockout is better suited to other aspects of the innate immune system compared to wild-type S. aureus. To further investigate the mechanism for increased survival of fumC::N∑ within a macrophage, we tested bacterial growth in the presence of reactive oxygen species (ROS), reactive nitrogen species (RNS), and a low pH. Preliminary results suggest that the fumC knockout has increased growth compared to wild-type S. aureus in the presence of all three antimicrobial factors; however, no difference was observed in any single factor alone. To investigate survival within a host, a nine-day biofilm-associated catheter infection was performed on 6–8-week-old male and female C57Bl/6 mice. Although both sexes struggled to clear the infection, female mice were trending toward more frequently clearing the HG003 wild-type infection compared to the fumC::N∑ infection. One possible reason for the inability to reduce the bacterial burden is that biofilms are largely composed of persister cells. To test this hypothesis further, flow cytometry in conjunction with a persister cell marker was used to measure persister cells within a biofilm. Cap5A (a known persister cell marker) expression was found to be increased in a maturing biofilm, with the lowest levels of expression seen in immature biofilms and the highest expression exhibited by the 48-hour biofilm. Additionally, bacterial cells in a biofilm state closely resemble persister cells and exhibit reduced membrane potential compared to cells in planktonic culture, further suggesting biofilms are largely made up of persister cells. These data may provide an explanation as to why infections caused by antibiotic-susceptible strains remain difficult to treat.

Keywords: antibiotic tolerance, Staphylococcus aureus, host-pathogen interactions, microbial pathogenesis

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Authors: Natasa Ilic, Alisa Gruden-Movsesijan, Maja Kosanovic, Sofija Glamoclija, Marina Bekic, Ljiljana Sofronic-Milosavljevic, Sergej Tomic

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As a very promising candidate for modulation of immune response in the sense of biasing the inflammatory towards an anti-inflammatory type of response, Trichinella spiralis infection was shown to successfully alleviate the severity of experimental autoimmune encephalomyelitis, the animal model of human disease multiple sclerosis. This effect is achieved via its excretory-secretory muscle larvae (ES L1) products which affect the maturation status and function of dendritic cells (DCs) by inducing the tolerogenic status of DCs, which leads to the mitigation of the Th1 type of response and the activation of a regulatory type of immune response both in vitro and in vivo. ES L1 alone or via treated DCs successfully mitigated EAE in the same manner as the infection itself. On the other hand, it has been shown that T. spiralis infection slows down the tumour growth and significantly reduces the tumour size in the model of mouse melanoma, while ES L1 possesses a pro-apoptotic and anti-survival effect on melanoma cells in vitro. Hence, although the mechanisms still need to be revealed, T. spiralis infection and its ES L1 products have a bit of controversial potential to modulate both inflammatory diseases and malignancies. The recent discovery of T. spiralis extracellular vesicles (TsEVs) suggested that the induction of complex regulation of the immune response requires simultaneous delivery of different signals in nano-sized packages. This study aimed to explore whether TsEVs bare the similar potential as ES L1 to influence the status of DCs in initiation, progression and regulation of immune response, but also to investigate the effect of both ES L1 and TsEVs on myeloid derived suppressor cells (MDSC) which present the regular tumour tissue environment. TsEVs were enriched from the conditioned medium of T. spiralis muscle larvae by differential centrifugation and used for the treatment of human monocyte-derived DCs and MDSC. On DCs, TsEVs induced low expression of HLA DR and CD40, moderate CD83 and CD86, and increased expression of ILT3 and CCR7 on treated DCs, i.e., they induced tolerogenic DCs. Such DCs possess the capacity to polarize T cell immune response towards regulatory type, with an increased proportion of IL-10 and TGF-β producing cells, similarly to ES L1. These findings indicated that the ability of TsEVs to induce tolerogenic DCs favoring anti-inflammatory responses may be helpful in coping with diseases that involve Th1/Th17-, but also Th2-mediated inflammation. In MDSC in vitro model, although both ES L1 and TsEVs had the same impact on MDSC phenotype i.e., they acted suppressive, ES L1 treated MDSC, unlike TsEVs treated ones, induced T cell response characterized by the increased RoRγT and IFN-γ, while the proportion of regulatory cells was decreased followed by the decrease in IL-10 and TGF-β positive cells proportion within this population. These findings indicate the interesting ability of ES L1 to modulate T cells response via MDSC towards pro-inflamatory type, suggesting that, unlike TsEVs which consistently demonstrate the suppresive effect on inflammatory response, it could be used also for the development of new approaches aimed for the treatment of malignant diseases. Acknowledgment: This work was funded by the Promis project – Nano-MDCS-Thera, Science Fund, Republic of Serbia.

Keywords: dendritic cells, myeloid derived suppressor cells, immunomodulation, Trichinella spiralis

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Authors: Ying Shen, Weihua Zhu

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Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: magnetic resonance image (MRI), c-means model, image segmentation, information entropy

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Authors: Prabhavathi Sundaram, Heidi Abrahamse

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In recent years, nanotechnology coupled with photodynamic therapy (PDT) has received considerable attention in terms of improving the effectiveness of drug delivery in cancer therapeutics. The development of functionalized single-walled carbon nanotubes (SWCNTs) has become revolutionary in targeted photosensitizers delivery since it improves the therapeutic index of drugs. The objective of this study was to prepare, characterize and evaluate the potential of functionalized SWCNTs using hyaluronic acid and loading it with photosensitizer and to effectively target colon cancer cells. The single-walled carbon nanotubes were covalently functionalized with hyaluronic acid and the loaded photosensitizer by non-covalent interaction. The photodynamic effect of SWCNTs is detected under laser irradiation in vitro. The hyaluronic acid-functionalized nanocomposites had a good affinity with CD44 receptors, and it avidly binds on to the surface of CACO-2 cells. The cellular uptake of nanocomposites was studied using fluorescence microscopy using lyso tracker. The anticancer activity of nanocomposites was analyzed in CACO-2 cells using different studies such as cell morphology, cell apoptosis, and nuclear morphology. The combined effect of nanocomposites and PDT improved the therapeutic effect of cancer treatment. The study suggested that the nanocomposites and PDT have great potential in the treatment of colon cancer.

Keywords: colon cancer, hyaluronic acid, single walled carbon nanotubes, photosensitizers, photodynamic therapy

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Authors: Magno Enrique Mendoza Meza

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This paper deals with the comparison of three control techniques: the hysteresis on-off control (HyOOC), the hybrid on-off control (HOOC) and the simple Structured Treatment Interruptions (sSTI). These techniques are applied to the mathematical model developed by Kirschner and Webb. To compare these techniques we use a cost functional that minimize the wild-type virus population and the mutant virus population, but the main objective is to minimize the systemic cost of treatment and maximize levels of healthy CD4+ T cells. HyOOC, HOOC, and sSTI are applied to the drug therapies using a reverse transcriptase and protease inhibitors; simulations show that these controls maintain the uninfected cells in a small, bounded neighborhood of a pre-specified level. The controller HyOOC and HOOC are designed by appropriate choice of virtual equilibrium points.

Keywords: virus dynamics, on-off control, hysteresis, multi-drug therapies

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Authors: Samar Rabah

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Background: Incense woods are special kind of trees called Agarwood, which characterized by good smelling odors and many medical benefits. Incense smoke is heavily used in Saudi Arabia although comprehensive studies of its effects on health are limited. The present study demonstrated lung ultrastructure changes of mice after exposure and cessation to Incense smoke. Eighty mice are divided equally into four groups, three groups are exposed to different concentrations of Incense smoke (2, 4 and 6 gm) for three months, while the fourth group is control one. At the end of each month, lungs of five animals from each group are gathered, while the last five animals from each group are kept for another 60 days without exposure to the Incense smoke to allow for recovery. Results: Transmission electron microscope investigations of all exposed groups showed hypertrophy and hyperplasia in Clara Cells and some an enlargement of the macrophage to the point that it fills a large part of the alveolar lumen. Scanning electron microscope marks presence of mucus materials attached to the epithelial bronchioles. After prevention of exposure to the Incense smoke for 60 days, necrosis and degeneration in some cells of epithelial bronchioles, fibrosis of peribronchial, thickening in alveolar walls and aggregation of lymphoid cells were demonstrated. Conclusion: Based on the above findings and other related studies (not published), we conclude that exposure to Incense smoke causes harmful effects due to sever changes in pulmonary ultrastructure, such effects do not disappear even when Incense smoke inhalation was stopped. Therefore, we recommend that Incense smoke should use only in open places to reduce its harms.

Keywords: Incense smoke, lungs, ultrastructure of lungs, Agarwood

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Authors: Min-Ah Woo, Min-Cheol Lim, Hyun-Joo Chang, Sung-Wook Choi

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We developed a paper-based colorimetric sensor utilizing magnetic nanoparticles conjugated with aptamers (MNP-Apts) against E. coli O157:H7. The MNP-Apts were applied to a test sample solution containing the target cells, and the solution was simply dropped onto PVDF (polyvinylidene difluoride) membrane. The membrane moves the sample radially to form the sample spots of different compounds as concentric rings, thus the MNP-Apts on the membrane enabled specific recognition of the target cells through a color ring generation by MNP-promoted colorimetric reaction of TMB (3,3',5,5'-tetramethylbenzidine) and H₂O₂. This method could be applied to rapidly and visually detect various bacterial pathogens in less than 1 h without cell culturing.

Keywords: aptamer, colorimetric sensor, E. coli O157:H7, magnetic nanoparticle, polyvinylidene difluoride

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Authors: Ashit Syngle, Nidhi Garg, Pawan Krishan

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Background: Endothelial Progenitor Cells (EPCs) are depleted and contribute to increased cardiovascular (CV) risk in rheumatoid arthritis (RA). Statins exert a protective effect in CAD partly by promoting EPC mobilization. This vasculoprotective effect of statin has not yet been investigated in RA. We aimed to investigate the effect of rosuvastatin on EPCs in RA. Methods: 50 RA patients were randomized to receive 6 months of treatment with rosuvastatin (10 mg/day, n=25) and placebo (n=25) as an adjunct to existing stable antirheumatic drugs. EPCs (CD34+/CD133+) were quantified by Flow Cytometry. Inflammatory measures included DAS28, CRP and ESR were measured at baseline and after treatment. Lipids and pro-inflammatory cytokines (TNF-α, IL-6, and IL-1) were estimated at baseline and after treatment. Results: At baseline, inflammatory measures and pro-inflammatory cytokines were elevated and EPCs depleted among both groups. At baseline, EPCs inversely correlated with DAS28 and TNF-α in both groups. EPCs increased significantly (p < 0.01) after treatment with rosuvastatin but did not show significant change with placebo. Rosuvastatin exerted positive effect on lipid spectrum: lowering total cholesterol, LDL, non HDL and elevation of HDL as compared with placebo. At 6 months, DAS28, ESR, CRP, TNF-α and IL-6 improved significantly in rosuvastatin group. Significant negative correlation was observed between EPCs and DAS28, CRP, TNF-α, and IL-6 after treatment with rosuvastatin. Conclusion: First study to show that rosuvastatin improves inflammation and EPC biology in RA possibly through its anti-inflammatory and lipid lowering effect. This beneficial effect of rosuvastatin may provide a novel strategy to prevent cardiovascular events in RA.

Keywords: RA, Endothelial Progenitor Cells, rosuvastatin, cytokines

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Authors: Syed Sadique Anwer Askari, Mukul Kumar Das

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Zinc Oxide (ZnO) solar cells have drawn great attention due to the enhanced efficiency and low-cost fabrication process. In this study, ZnO thin film is used as the active layer, hole blocking layer, antireflection coating (ARC) as well as transparent conductive oxide. To improve the conductivity of ZnO, top layer of ZnO is doped with aluminum, for top contact. Intrinsic carrier concentration of silicon substrate plays an important role in enhancing the power conversion efficiency (PCE) of ZnO/Si solar cell. With the increase of intrinsic carrier concentration PCE decreased due to increase in dark current in solar cell. At 80nm ZnO and 160µm Silicon substrate thickness, power conversion efficiency of 26.45% and 21.64% is achieved with intrinsic carrier concentration of 1x109/cm3, 1.4x1010/cm3 respectively.

Keywords: hetero-junction solar cell, solar cell, substrate intrinsic carrier concentration, ZnO/Si

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Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

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Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

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Authors: Sophia Shi

Abstract:

Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

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Authors: Rachid Dehini, Brahim Berbaoui

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The main objectives of shunt active power filter (SAPF) is to preserve the power system from unwanted harmonic currents produced by nonlinear loads, as well as to compensate the reactive power. The aim of this paper is to present a (PAPF) supplied by the Photovoltaic cells ,in such a way that the (PAPF) feeds the linear and nonlinear loads by harmonics currents and the excess of the energy is injected into the power system. In order to improve the performances of conventional (PAPF) This paper also proposes artificial neural networks (ANN) for harmonics identification and DC link voltage control. The simulation study results of the new (SAPF) identification technique are found quite satisfactory by assuring good filtering characteristics and high system stability.

Keywords: SAPF, harmonics current, photovoltaic cells, MPPT, artificial neural networks (ANN)

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Authors: Eun Jung Sohn, Hwan Tae Park

Abstract:

Autophagy is a cellular response to stress or environment on cell survival. Here, we investigated the role of ectopic expression of miR 200c-3p in autophagy. Ectopic expression of miR 200c-3p increased the expression of IRE1alpha, ATF6 and CHOP by western blot and RT-qPCR. Furthermore, the level of microRNA 200c-3p was enhanced by treatment of TG or overexpression of GRP 78. Also, ectopic expression of miR200c-3p increased the LC3 II expression by western blot and RT-qPCR. Also, we found that western blot assay showed that miR200c-3p inhibitor was blocked the starvation–induced LC3II levels. Furthermore, starvation stress increased the level of miR200c-3p in different kinetics. Ectopic expression of miR200c-3p attenuated LC3II expression in IRE1 siRNA transfected PC3 cells. Here, we first demonstrate that miR200c-3p regulates autophagy via ER stress pathway.

Keywords: Autophagy, ER stress, LC3II, miR200c-3p

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Authors: Maxime Moreau, Silvère Baron, Jean-Marc Lobaccaro, Karine Charlet, Sébastien Menecier, Frédéric Perisse

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Cold Atmospheric Plasma (CAP) is an ionized gas generated at atmospheric pressure with the temperature of heavy particles (molecules, ions, atoms) close to the room temperature. Recent studies have shown that both in-vitro and in-vivo plasma exposition to many cancer cell lines are efficient to induce the apoptotic way of cell death. In some other works, normal cell lines seem to be less impacted by plasma than cancer cell lines. This is called selectivity of plasma. It is highly likely that the generated RNOS (Reactive Nitrogen Oxygen Species) in the plasma jet, but also in the medium, play a key-role in this selectivity. In this study, two CAP devices will be compared to electrical power, chemical species composition and their efficiency to kill cancer cells. A particular focus on the action of hydrogen peroxide will be made. The experiments will take place as described next for both devices: electrical and spectroscopic characterization for different voltages, plasma treatment of normal and cancer cells to compare the CAP efficiency between cell lines and to show that death is induced by an oxidative stress. To enlighten the importance of hydrogen peroxide, an inhibitor of H2O2 will be added in cell culture medium before treatment and a comparison will be made between the results of cell viability in this case and those from a simple plasma exposition. Besides, H2O2 production will be measured by only treating medium with plasma. Cell lines will also be exposed to different concentrations of hydrogen peroxide in order to characterize the cytotoxic threshold for cells and to make a comparison with the quantity of H2O2 produced by CAP devices. Finally, the activity of catalase for different cell lines will be quantified. This enzyme is an important antioxidant agent against hydrogen peroxide. A correlation between cells response to plasma exposition and this activity could be a strong argument in favor of the predominant role of H2O2 to explain the selectivity of plasma cancer treatment by cold atmospheric plasma.

Keywords: cold atmospheric plasma, hydrogen peroxide, prostate cancer, selectivity

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Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

Abstract:

Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

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