Search results for: segmentation genes

Authors: Andre Peres Ramos, Franklin Cesar Flores

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Colorization is the process of add colors to a monochromatic image or video. Usually, the process involves to segment the image in regions of interest and then apply colors to each one, for videos, this process is repeated for each frame, which makes it a tedious and time-consuming job. We propose a new assisted method for video colorization; the user only has to colorize one frame, and then the colors are propagated to following frames. The user can intervene at any time to correct eventual errors in color assignment. The method consists of to extract intensity and texture descriptors from the frames and then perform a feature matching to determine the best color for each segment. To reduce computation time and give a better spatial coherence we narrow the area of search and give weights for each feature to emphasize texture descriptors. To give a more natural result, we use an optimization algorithm to make the color propagation. Experimental results in several image sequences, compared to others existing methods, demonstrates that the proposed method perform a better colorization with less time and user interference.

Keywords: colorization, feature matching, texture descriptors, video segmentation

Procedia PDF Downloads 146

Authors: Razieh Karimi Aghcheh, Christian Kubicek, Joseph Strauss, Gerhard Braus

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Filamentous fungi are of considerable economic and social significance for human health, nutrition and in white biotechnology. These organisms are dominant producers of a range of primary metabolites such as citric acid, microbial lipids (biodiesel) and higher unsaturated fatty acids (HUFAs). In particular, they produce also important but structurally complex secondary metabolites with enormous therapeutic applications in pharmaceutical industry, for example: cephalosporin, penicillin, taxol, zeranol and ergot alkaloids. Several fungal secondary metabolites, which are significantly relevant to human health do not only include antibiotics, but also e.g. lovastatin, a well-known antihypercholesterolemic agent produced by Aspergillus. terreus, or aflatoxin, a carcinogen produced by A. flavus. In addition to their roles for human health and agriculture, some fungi are industrially and commercially important: Species of the ascomycete genus Hypocrea spp. (teleomorph of Trichoderma) have been demonstrated as efficient producer of highly active cellulolytic enzymes. This trait makes them effective in disrupting and depolymerization of lignocellulosic materials and thus applicable tools in number of biotechnological areas as diverse as clothes-washing detergent, animal feed, and pulp and fuel productions. Fungal LaeA/LAE1 (Loss of aflR Expression A) homologs their gene products act at the interphase between secondary metabolisms, cellulase production and development. Lack of the corresponding genes results in significant physiological changes including loss of secondary metabolite and lignocellulose degrading enzymes production. At the molecular level, the encoded proteins are presumably methyltransferases or demethylases which act directly or indirectly at heterochromatin and interact with velvet domain proteins. Velvet proteins bind to DNA and affect expression of secondary metabolites (SMs) genes and cellulases. The dynamic interplay between LaeA/LAE1, velvet proteins and additional interaction partners is the key for an understanding of the coordination of metabolic and morphological functions of fungi and is required for a biotechnological control of the formation of desired bioactive products. Aspergilli and Trichoderma represent different biotechnologically significant species with significant differences in the LaeA/LAE1-Velvet protein machinery and their target proteins. We, therefore, performed a comparative study of the interaction partners of this machinery and the dynamics of the various protein-protein interactions using our robust proteomic and mass spectrometry techniques. This enhances our knowledge about the fungal coordination of secondary metabolism, cellulase production and development and thereby will certainly improve recombinant fungal strain construction for the production of industrial secondary metabolite or lignocellulose hydrolytic enzymes.

Keywords: cellulases, LaeA/1, proteomics, secondary metabolites

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Authors: Saumya Srivastava, Rina Maiti

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In order to achieve a better performance of vehicle detection in a complex environment, we present an efficient approach for a multi-vehicle detection system using an adaptive sliding window technique. For a given frame, image segmentation is carried out to establish the region of interest. Gradient computation followed by thresholding, denoising, and morphological operations is performed to extract the binary search image. Near-region field and far-region field are defined to generate hypotheses using the adaptive sliding window technique on the resultant binary search image. For each vehicle candidate, features are extracted using a histogram of oriented gradients, and a pre-trained support vector machine is applied for hypothesis verification. Later, the Kalman filter is used for tracking the vanishing point. The experimental results show that the method is robust and effective on various roads and driving scenarios. The algorithm was tested on highways and urban roads in India.

Keywords: gradient, vehicle detection, histograms of oriented gradients, support vector machine

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Authors: Yousif Mohamed Y. Abdallah, Razan Manofely, Rajab M. Ben Yousef

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X-Ray images are very popular as a first tool for diagnosis. Automating the process of analysis of such images is important in order to help physician procedures. In this practice, teeth segmentation from the radiographic images and feature extraction are essential steps. The main objective of this study was to study correction preprocessing of x-rays images using local adaptive filters in order to evaluate contrast enhancement pattern in different x-rays images such as grey color and to evaluate the usage of new nonlinear approach for contrast enhancement of soft tissues in x-rays images. The data analyzed by using MatLab program to enhance the contrast within the soft tissues, the gray levels in both enhanced and unenhanced images and noise variance. The main techniques of enhancement used in this study were contrast enhancement filtering and deblurring images using the blind deconvolution algorithm. In this paper, prominent constraints are firstly preservation of image's overall look; secondly, preservation of the diagnostic content in the image and thirdly detection of small low contrast details in diagnostic content of the image.

Keywords: enhancement, x-rays, pixel intensity values, MatLab

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Authors: Eszter Repasi, Akos Koller

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Our genetic information determines our look, physiology, sports performance and all our features. Maximizing the performances of athletes have adopted a science-based approach to the nutritional support. Nowadays genetics studies have blended with nutritional sciences, and a dynamically evolving, new research field have appeared. Nutritional genomics is needed to be used by nutritional experts. This is a recent field of nutritional science, which can provide a solution to reach the best sport performance using correlations between the athlete’s genome, nutritions, molecules, included human microbiome (links between food, microbiome and epigenetics), nutrigenomics and nutrigenetics. Nutritional genomics has a tremendous potential to change the future of dietary guidelines and personal recommendations. Experts need to use new technology to get information about the athletes, like nutritional genomics profile (included the determination of the oral and gut microbiome and DNA coded reaction for food components), which can modify the preparation term and sports performance. The influence of nutrients on the genes expression is called Nutrigenomics. The heterogeneous response of gene variants to nutrients, dietary components is called Nutrigenetics. The human microbiome plays a critical role in the state of health and well-being, and there are more links between food or nutrition and the human microbiome composition, which can develop diseases and epigenetic changes as well. A nutritional genomics-based profile of athletes can be the best technic for a dietitian to make a unique sports nutrition diet plan. Using functional food and the right food components can be effected on health state, thus sports performance. Scientists need to determine the best response, due to the effect of nutrients on health, through altering genome promote metabolites and result changes in physiology. Nutritional biochemistry explains why polymorphisms in genes for the absorption, circulation, or metabolism of essential nutrients (such as n-3 polyunsaturated fatty acids or epigallocatechin-3-gallate), would affect the efficacy of that nutrient. Controlled nutritional deficiencies and failures, prevented the change of health state or a newly discovered food intolerance are observed by a proper medical team, can support better sports performance. It is important that the dietetics profession informed on gene-diet interactions, that may be leading to optimal health, reduced risk of injury or disease. A special medical application for documentation and monitoring of data of health state and risk factors can uphold and warn the medical team for an early action and help to be able to do a proper health service in time. This model can set up a personalized nutrition advice from the status control, through the recovery, to the monitoring. But more studies are needed to understand the mechanisms and to be able to change the composition of the microbiome, environmental and genetic risk factors in cases of athletes.

Keywords: gene-diet interaction, multidisciplinary team, microbiome, diet plan

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Authors: Sibo Lu, Zhongkai Qian, Haotian Zhang

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This article examines the phenomenon of micro-sovereignty in the context of property management and its implications for biopolitics and urban governance in mainland China. It explores the transformation of urban spaces into privatized communities managed by property companies, leading to the reterritorialization of urban areas and the segmentation of urban populations. Drawing on legal frameworks, we analyze how commercial real estate development and property management have reshaped the urban landscape, placing nearly all urban residents within service areas of property management firms, thus establishing micro-sovereign entities that exercise control over residential spaces. Through a critique of property management's sovereign effects on social organization and the exploration of autonomous, democratic alternatives in community governance, this article contributes to the broader discourse on sovereignty, governance, and resistance within the urban milieu of contemporary China. It underscores the urgent need for more democratic forms of community management that can transcend the capitalist logic of property management companies and foster genuine participatory governance at the grassroots level.

Keywords: biopolitic, critical theory, political sociology, political philosophy

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Authors: Md. M. Hossain, Regan Roat, Jenica Christopherson, Colette Free, Zhiguang Guo

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Long noncoding RNA (lncRNA) mediated post-transcriptional gene regulation, and their epigenetic landscapes have been shown to be involved in many human diseases. However, their regulation in diabetes through governing islet’s β-cell function and survival needs to be elucidated. Due to the technical and ethical constraints, it is difficult to study their role in β-cell function and survival in human under in vivo condition. In this study, humanized mice have been developed through transplanting human pancreatic islet under the kidney capsule of NOD.SCID mice and induced β-cell death leading to diabetes condition to study lncRNA mediated regulation. For this, human islets from 3 donors (3000 IEQ, purity > 80%) were transplanted under the kidney capsule of STZ induced diabetic NOD.scid mice. After at least 2 weeks of normoglycecemia, lymphocytes from diabetic NOD mice were adoptively transferred and islet grafts were collected once blood glucose reached > 200 mg/dl. RNA from human donor islets, islet grafts from humanized mice with either adoptive lymphocyte transfer (ALT) or PBS control (CTL) were ribodepleted; barcoded fragment libraries were constructed and sequenced on the Ion Proton sequencer. lncRNA expression in isolated human islets, islet grafts from humanized mice with and without induced β-cell death and their regulation in human islets function in vitro under glucose challenge, cytokine mediated inflammation and induced apoptotic condition were investigated. Out of 3155 detected lncRNAs, 299 that highly expressed in islets were found to be significantly downregulated and 224 upregulated in ALT compared to CTL. Most of these are found to be collocated within 5 kb upstream and 1 kb downstream of 788 up- and 624 down-regulated mRNAs. Genomic Regions Enrichment of Annotations Analysis revealed deregulated and collocated genes are related to pancreas endocrine development; insulin synthesis, processing, and secretion; pancreatitis and diabetes. Many of them, that found to be located within enhancer domains for islet specific gene activity, are associated to the deregulation of known islet/βcell specific transcription factors and genes that are important for β-cell differentiation, identity, and function. RNA sequencing analysis revealed aberrant lncRNA expression which is associated to the deregulated mRNAs in β-cell function as well as in molecular pathways related to diabetes. A distinct set of candidate lncRNA isoforms were identified as highly enriched and specific to human islets, which are deregulated in human islets from donors with different BMIs and with type 2 diabetes. These RNAs show an interesting regulation in cultured human islets under glucose stimulation and with induced β-cell death by cytokines. Aberrant expression of these lncRNAs was detected in the exosomes from the media of islets cultured with cytokines. Results of this study suggest that the islet specific lncRNAs are deregulated in human islet with β-cell death, hence important in diabetes. These lncRNAs might be important for human β-cell function and survival thus could be used as biomarkers and novel therapeutic targets for diabetes.

Keywords: β-cell, humanized mouse, pancreatic islet, LncRNAs

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Authors: D. P. Houhoula, J. Papaparaskevas, S. Konteles, A. Dargenta, A. Farka, C. Spyrou, M. Ziaka, S. Koussisis, E. Charvalos

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Objectives: Nanotechnology is providing revolutionary opportunities for the rapid and simple diagnosis of many infectious diseases. Staphylococcus aureus, Listeria monocytogenes and Salmonella enteritis are important human pathogens. Diagnostic assays for bacterial culture and identification are time consuming and laborious. There is an urgent need to develop rapid, sensitive, and inexpensive diagnostic tests. In this study, a gold nanoprobe strategy developed and relies on the colorimetric differentiation of specific DNA sequences based approach on differential aggregation profiles in the presence or absence of specific target hybridization. Method: Gold nanoparticles (AuNPs) were purchased from Nanopartz. They were conjugated with thiolated oligonucleotides specific for the femA gene for the identification of members of Staphylococcus aureus, the mecA gene for the differentiation of Staphylococcus aureus and MRSA Staphylococcus aureus, hly gene encoding the pore-forming cytolysin listeriolysin for the identification of Listeria monocytogenes and the invA sequence for the identification of Salmonella enteritis. DNA isolation from Staphylococcus aureus Listeria monocytogenes and Salmonella enteritis cultures was performed using the commercial kit Nucleospin Tissue (Macherey Nagel). Specifically 20μl of DNA was diluted in 10mMPBS (pH5). After the denaturation of 10min, 20μl of AuNPs was added followed by the annealing step at 58oC. The presence of a complementary target prevents aggregation with the addition of acid and the solution remains pink, whereas in the opposite event it turns to purple. The color could be detected visually and it was confirmed with an absorption spectrum. Results: Specifically, 0.123 μg/μl DNA of St. aureus, L.monocytogenes and Salmonella enteritis was serially diluted from 1:10 to 1:100. Blanks containing PBS buffer instead of DNA were used. The application of the proposed method on isolated bacteria produced positive results with all the species of St. aureus and L. monocytogenes and Salmonella enteritis using the femA, mecA, hly and invA genes respectively. The minimum detection limit of the assay was defined at 0.2 ng/μL of DNA. Below of 0.2 ng/μL of bacterial DNA the solution turned purple after addition of HCl, defining the minimum detection limit of the assay. None of the blank samples was positive. The specificity was 100%. The application of the proposed method produced exactly the same results every time (n = 4) the evaluation was repeated (100% repeatability) using the femA, hly and invA genes. Using the gene mecA for the differentiation of Staphylococcus aureus and MRSA Staphylococcus aureus the method had a repeatability 50%. Conclusion: The proposed method could be used as a highly specific and sensitive screening tool for the detection and differentiation of Staphylococcus aureus Listeria monocytogenes and Salmonella enteritis. The use AuNPs for the colorimetric detection of DNA targets represents an inexpensive and easy-to-perform alternative to common molecular assays. The technology described here, may develop into a platform that could accommodate detection of many bacterial species.

Keywords: gold nanoparticles, pathogens, nanotechnology, bacteria

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Authors: Ksenia Meshkova

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With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, Rebecca K. Rossi, Yanmin Yuan, Xianpei Li

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The fiscal growth of any country hinges on the prudent administration of water resources. The river Yamuna and Ganga are measured as the life line of India as it affords the needs for life to endure. Earth observation over remote sensing images permits the precise description and identification of ingredients on the superficial from space and airborne platforms. Multiple and heterogeneous image sources are accessible for the same geographical section; multispectral, hyperspectral, radar, multitemporal, and multiangular images. In this paper, a taxonomical learning of the fluvial geomorphological features of river Yamuna and Ganga over doon valley using color fusion of multispectral remote sensing images was performed. Experimental results exhibited that the segmentation based colorization technique stranded on pattern recognition, and color mapping fashioned more colorful and truthful colorized images for geomorphological feature extraction.

Keywords: color fusion, geomorphology, fluvial processes, multispectral images, pattern recognition

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Authors: Hasan Basri Jumin

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Protoplasts isolated from embryogenic callus of Citrus sinensis were electrically used with mesophyll protoplasts isolated from seedless Citrus relatives. Hybrid of somatic embryos plantlets was obtained after 7 months of culture. Somatic hybrid plants were regenerated into normal seedlings and successfully transferred to soil after strictly acclimatization in the glass pot. The somatic hybrid plants were obtained by screening on the basis of chromosomes count. The number of chromosome of root tip counting revealed plantlets tetraploids (2n = 4x = 36) and the other were diploids (2n = 2x = 18) morphologically resembling the mesophyll parent. This somatic hybrid will be utilized as a possible pollen parent for improving the Citrus sinensis. A complete protoplast-to-plant system of somatic hybrid was developed for Citrus sinensis and Citrus relatives which could facilitate the transfer of nuclear and cytoplasmic genes from this species into cultivated Citrus through protoplast fusion.

Keywords: chromosome, Murraya paniculata, protoplast fusion, somatic hybrid, tetrapoliod

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Authors: Rugang Tian

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In this study, we generated whole-genome sequence (WGS) data from110 native cattle. Together with whole-genome sequences from world-wide cattle populations, we estimated the genetic diversity and population genetic structure of different cattle populations. Our findings revealed clustering of cattle groups in line with their geographic locations. We identified noticeable genetic diversity between indigenous cattle breeds and commercial populations. Among all studied cattle groups, lower genetic diversity measures were found in commercial populations, however, high genetic diversity were detected in some local cattle, particularly in Rashoki and Mongolian breeds. Our search for potential genomic regions under selection in native cattle revealed several candidate genes related with immune response and cold shock protein on multiple chromosomes such as TRPM8, NMUR1, PRKAA2, SMTNL2 and OXR1 that are involved in energy metabolism and metabolic homeostasis.

Keywords: cattle, whole-genome, population structure, adaptation

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Authors: Stephy Saavedra, Annsy C. Arredondo, Gisele Monteiro, Adalberto Pessoa Jr, Carol N. Flores-Fernandez, Amparo I. Zavaleta

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L-asparaginase from bacterial sources is used in leukemic treatment and food industry. This enzyme is classified based on its affinity towards L-asparagine and L-glutamine. Likewise, ansZ genes express L-asparaginase with higher affinity to L-asparagine. The aim of this work was to clone and express of ansZ gene from Bacillus sp. CH11 isolated from Chilca salterns in Peru. The gene encoding L-asparaginase was cloned into pET15b vector and transformed in Escherichia coli BL21 (DE3) pLysS. The expression was carried out in a batch culture using LB broth and 0.5 mM IPTG. The recombinant L-asparaginase showed a molecular weight of ~ 39 kDa by SDS PAGE and a specific activity of 3.19 IU/mg of protein. The cloning and expression of ansZ gene from this halotolerant Bacillus sp. CH11 allowed having a biological input to improve a future scaling-up.

Keywords: ansZ gene, Bacillus sp, Chilca salterns, recombinant L-asparaginase

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Sourour Khouaja, Hejer Jlassi, Nadia Feddaoui, Kamel Hamrouni

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Most medical images, and especially mammographies, are now stored in large databases. Retrieving a desired image is considered of great importance in order to find previous similar cases diagnosis. Our method is implemented to assist radiologists in retrieving mammographic images containing breast with similar density aspect as seen on the mammogram. This is becoming a challenge seeing the importance of density criteria in cancer provision and its effect on segmentation issues. We used the BEMD (Bidimensional Empirical Mode Decomposition) to characterize the content of images and Euclidean distance measure similarity between images. Through the experiments on the MIAS mammography image database, we confirm that the results are promising. The performance was evaluated using precision and recall curves comparing query and retrieved images. Computing recall-precision proved the effectiveness of applying the CBIR in the large mammographic image databases. We found a precision of 91.2% for mammography with a recall of 86.8%.

Keywords: BEMD, breast density, contend-based, image retrieval, mammography

Procedia PDF Downloads 215

Authors: Qianwei Cheng, A. K. M. Mahbubur Rahman, Anis Sarker, Abu Bakar Siddik Nayem, Ovi Paul, Amin Ahsan Ali, M. Ashraful Amin, Ryosuke Shibasaki, Moinul Zaber

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Thomas Friedman, in his famous book, argued that the world in this 21st century is flat and will continue to be flatter. This is attributed to rapid globalization and the interdependence of humanity that engendered tremendous in-flow of human migration towards the urban spaces. In order to keep the urban environment sustainable, policy makers need to plan based on extensive analysis of the urban environment. With the advent of high definition satellite images, high resolution data, computational methods such as deep neural network analysis, and hardware capable of high-speed analysis; urban planning is seeing a paradigm shift. Legacy data on urban environments are now being complemented with high-volume, high-frequency data. However, the first step of understanding urban space lies in useful categorization of the space that is usable for data collection, analysis, and visualization. In this paper, we propose a pragmatic categorization method that is readily usable for machine analysis and show applicability of the methodology on a developing world setting. Categorization to plan sustainable urban spaces should encompass the buildings and their surroundings. However, the state-of-the-art is mostly dominated by classification of building structures, building types, etc. and largely represents the developed world. Hence, these methods and models are not sufficient for developing countries such as Bangladesh, where the surrounding environment is crucial for the categorization. Moreover, these categorizations propose small-scale classifications, which give limited information, have poor scalability and are slow to compute in real time. Our proposed method is divided into two steps-categorization and automation. We categorize the urban area in terms of informal and formal spaces and take the surrounding environment into account. 50 km × 50 km Google Earth image of Dhaka, Bangladesh was visually annotated and categorized by an expert and consequently a map was drawn. The categorization is based broadly on two dimensions-the state of urbanization and the architectural form of urban environment. Consequently, the urban space is divided into four categories: 1) highly informal area; 2) moderately informal area; 3) moderately formal area; and 4) highly formal area. In total, sixteen sub-categories were identified. For semantic segmentation and automatic categorization, Google’s DeeplabV3+ model was used. The model uses Atrous convolution operation to analyze different layers of texture and shape. This allows us to enlarge the field of view of the filters to incorporate larger context. Image encompassing 70% of the urban space was used to train the model, and the remaining 30% was used for testing and validation. The model is able to segment with 75% accuracy and 60% Mean Intersection over Union (mIoU). In this paper, we propose a pragmatic categorization method that is readily applicable for automatic use in both developing and developed world context. The method can be augmented for real-time socio-economic comparative analysis among cities. It can be an essential tool for the policy makers to plan future sustainable urban spaces.

Keywords: semantic segmentation, urban environment, deep learning, urban building, classification

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Authors: Ramkumar Gunasekaran, John Cater, Vinod Suresh, Haribalan Kumar

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The main objective of this project is to develop a statistical shape model using principal component analysis that could be used for analyzing the shape of the human airway. The ultimate goal of this project is to identify geometric risk factors for diagnosis and management of Obstructive Sleep Apnoea (OSA). Anonymous CBCT scans of 25 individuals were obtained from the Otago Radiology Group. The airways were segmented between the hard-palate and the aryepiglottic fold using snake active contour segmentation. The point data cloud of the segmented images was then fitted with a bi-cubic mesh, and pseudo landmarks were placed to perform PCA on the segmented airway to analyze the shape of the airway and to find the relationship between the shape and OSA risk factors. From the PCA results, the first four modes of variation were found to be significant. Mode 1 was interpreted to be the overall length of the airway, Mode 2 was related to the anterior-posterior width of the retroglossal region, Mode 3 was related to the lateral dimension of the oropharyngeal region and Mode 4 was related to the anterior-posterior width of the oropharyngeal region. All these regions are subjected to the risk factors of OSA.

Keywords: medical imaging, image processing, FEM/BEM, statistical modelling

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Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

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In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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Authors: Nahid H. Hajrah, Jamal S. M. Sabir, Neil Hall

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The jasmonic pathway is ubiquitous in plants and is crucial to plant development. It Is involved in fertility, ripening, and sex determination as well as in response to environmental stresses such as herbivory, pathogen drought or temperature shock. Essentially the jasmonic pathway acts to shut down growth in order to induce defence pathways. These pathways include the production of secondary metabolites which have evolved to defend against herbivores and pathogens but are of increasing interest due to their roll in medicine and biotechnology. Here we describe the transcriptional response of Rhazia stricta (a poisonous shrub widely used in traditional medicine) to jasmonic acid, in order to better characterize the genes involved in secondary metabolite production and its response to stress. We observe coordinated upregulation of flavonoid biosynthesis pathway leading to flavonols, flavones and anthocyanins but no similar coordination of the monoterpene indole alkaloid pathway.

Keywords: medicinal plants, Rhazia stricta, jasmonic acid, transcriptional analysis

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Authors: Ali Asghar Saki, Sayed Ali Hosseini Siyar, Abbass Ashoori

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This study was conducted to evaluate the effect of Echinacea purpurea on the expression of cyclooxygenase-2 (COX-2), interleukin-17F (IL-17F) in seven-day-old broiler chickens. Four groups were fed with concentration of 0 g/kg, 5 g/kg, 10 g/kg and 20 g/kg from the root of E. purpurea in the basal diet and two other groups were only fed with the basal diet for 21 days. At the 28^th day, lipopolysaccharide (LPS, 2 mg/kg diet) was injected in four groups and the basal diet group was injected by saline as control. The chickens’ spleen RNA expression was measured for the COX-2 and IL-17F genes by Real-Time PCR. The results have shown that chickens which were fed E. purpurea had a lower COX-2 and IL-17F mRNA expression. The chickens who have received LPS only, lymphocyte was lower than other treatments. Vital organ weights were not significantly different, but body weight loss was recovered by dietary herbs inclusion. The results of this study have shown the positive effect of an anti-inflammatory herb to prevent the undesirable effect of inflammation.

Keywords: broiler chickens, Echinacea purporea, gene expression, lipopolysaccharide

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Authors: Moohyun Lee, Soojung Hur, Yongwan Park

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In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR.

Keywords: obstacle, classification, database, LIDAR, segmentation, intensity

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Authors: Mehdi Soula, Yosra Mani, Estelle Saras, Antoine Drapeau, Raoudha Grami, Mahjoub Aouni, Jean-Yves Madec, Marisa Haenni, Wejdene Mansour

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Multi-resistance to antibiotics in gram-negative bacilli and particularly in enterobacteriaceae, has become frequent in hospitals in Tunisia. However, data on antibiotic resistant bacteria in aquatic products are scarce. The aims of this study are to estimate the proportion of ESBL- and carbapenemase-producing Enterobacterales in seafood (clams and fish) in Tunisia and to molecularly characterize the collected isolates. Two types of seafood were sampled in unrelated markets in four different regions in Tunisia (641 pieces of farmed fish and 1075 mediterranean clams divided into 215 pools, and each pool contained 5 pieces). Once purchased, all samples were incubated in tubes containing peptone salt broth for 24 to 48h at 37°C. After incubation, overnight cultures were isolated on selective MacConkey agar plates supplemented with either imipenem or cefotaxime, identified using API20E test strips (bioMérieux, Marcy-l’Étoile, France) and confirmed by Maldi-TOF MS. Antimicrobial susceptibility was determined by the disk diffusion method on Mueller-Hinton agar plates and results were interpreted according to CA-SFM 2021. ESBL-producing Enterobacterales were detected using the Double Disc Synergy Test (DDST). Carbapenem-resistance was detected using an ertapenem disk and was respectively confirmed using the ROSCO KPC/MBL and OXA-48 Confirm Kit (ROSCO Diagnostica, Taastrup, Denmark). DNA was extracted using a NucleoSpin Microbial DNA extraction kit (Macherey-Nagel, Hoerdt, France), according to the manufacturer’s instructions. Resistance genes were determined using the CGE online tools. The replicon content and plasmid formula were identified from the WGS data using PlasmidFinder 2.0.1 and pMLST 2.0. From farmed fishes, nine ESBL-producing strains (9/641, 1.4%) were isolated, which were identified as E. coli (n=6) and K. pneumoniae (n=3). Among the 215 pools of 5 clams analyzed, 18 ESBL-producing isolates were identified, including 14 E. coli and 4 K. pneumoniae. A low isolation rate of ESBL-producing Enterobacterales was detected 1.6% (18/1075) in clam pools. In fish, the ESBL phenotype was due to the presence of the blaCTX-M-15 gene in all nine isolates, but no carbapenemase gene was identified. In clams, the predominant ESBL phenotype was blaCTX-M-1 (n=6/18). blaCPE (NDM1, OXA48) was detected only in 3 isolates ‘K. pneumoniae isolates’. Replicon typing on the strains carring the ESBL and carbapenemase gene revelead that the major type plasmid carried ESBL were IncF (42.3%) [n=11/26]. In all, our results suggest that seafood can be a reservoir of multi-drug resistant bacteria, most probably of human origin but also by the selection pressure of antibiotic. Our findings raise concerns that seafood bought for consumption may serve as potential reservoirs of AMR genes and pose serious threat to public health.

Keywords: BLSE, carbapenemase, enterobacterales, tunisian seafood

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Authors: Jaqueline Maria Ribeiro Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). Previously we developed and proposed a novel strategy capable of detecting patterns at borehole images that may point to regions that have tension and breakout characteristics, based on segmented images. In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge data set configurations.

Keywords: image segmentation, oil well visualization, classifiers, data-mining, visual computer

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Authors: Aslı Şalcıoğlu, Grigorous Krey, Raşit Bilgin

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In this study, the effect of the Turkish Straits System (TSS), comprising a biogeographical boundary that forms the connection between the Mediterranean and the Black Sea, on the evolutionary history, phylogeography and intraspecific gene flow of the whiting (Merlangius merlangus) a demersal fish species, was investigated. For these purposes, the mitochondrial DNA (CO1, cyt-b) genes were used. In addition, genetic comparisons samples from other regions (Greece, France, Atlantic) obtained from GenBank and Barcode of Life Database were made to better understand the phylogeographic history of the species at a larger geographic scale. Within this study, high level of genetic differentiation was observed along the Turkish coastal waters based on cyt-b gene, suggesting that TSS is a barrier to dispersal. Two different sub-species were also observed based on mitochondrial DNA, one found in Turkish coastal waters and Greece (M.m euxinus) and other (M.m. merlangus) in Atlantic, France.

Keywords: genetic, phylogeography, TSS, whiting

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Authors: Lidia Sanchis-Marco, Antonio Rubia, Pedro Serrano

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This paper studies the informational content of pricing errors in the term structure of sovereign CDS spreads. The residuals from a non-arbitrage model are employed to construct a Price discrepancy estimate, or noise measure. The noise estimate is understood as an indicator of market distress and reflects frictions such as illiquidity. Empirically, the noise measure is computed for an extensive panel of CDS spreads. Our results reveal an important fraction of systematic risk is not priced in default swap contracts. When projecting the noise measure onto a set of financial variables, the panel-data estimates show that greater price discrepancies are systematically related to a higher level of offsetting transactions of CDS contracts. This evidence suggests that arbitrage capital flows exit the marketplace during time of distress, and this consistent with a market segmentation among investors and arbitrageurs where professional arbitrageurs are particularly ineffective at bringing prices to their fundamental values during turbulent periods. Our empirical findings are robust for the most common CDS pricing models employed in the industry.

Keywords: credit default swaps, noise measure, illiquidity, capital arbitrage

Procedia PDF Downloads 558

Authors: Aysun Sezer

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Magnetic Resonance Imaging (MRI) is one of the advanced diagnostic tools for evaluating shoulder pathologies. Proton Density (PD)-weighted MRI sequences prove highly effective in detecting edema. However, they are deficient in the anatomical identification of bones due to a trauma-induced decrease in signal-to-noise ratio and blur in the traumatized cortices. Computer-based diagnostic systems require precise segmentation, identification, and localization of anatomical regions in medical imagery. Deep learning-based object detection algorithms exhibit remarkable proficiency in real-time object identification and localization. In this study, the YOLOv8 model was employed to detect humeral head and scapular regions in 665 axial PD-weighted MR images. The YOLOv8 configuration achieved an overall success rate of 99.60% and 89.90% for detecting the humeral head and scapula, respectively, with an intersection over union (IoU) of 0.5. Our findings indicate a significant promise of employing YOLOv8-based detection for the humerus and scapula regions, particularly in the context of PD-weighted images affected by both noise and intensity inhomogeneity.

Keywords: YOLOv8, object detection, humerus, scapula, IRM

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Authors: S. Najafi, E. Bertini, M. Pezzotti, G.B. Tornielli, S. Zenoni

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Grapevine is an important agricultural fruit crop plant consumed worldwide and with a key role in the global economy. Grapevine is strongly affected by both biotic and abiotic stresses, which impact grape growth at different stages, such as during plant and berry development and pre- and post-harvest, consequently causing significant economic losses. Recently global warming has propelled the anticipation of the onset of berry ripening, determining the reduction of a grape color and increased volatilization of aroma compounds. Climate change could negatively alter the physiological characteristics of the grape and affect the berry and wine quality. Modern plant breeding can provide tools such as genome editing for improving grape resilience traits while maintaining intact the viticultural and oenological quality characteristics of the genotype. This study aims at developing a platform for genome editing application in grapevine plants with the final goal to improve berry quality, biotic, and abiotic resilience traits. We chose to directly deliver ribonucleoproteins (RNP, preassembled Cas protein and guide RNA) into plant protoplasts, and, from these cell structures, regenerate grapevine plants edited in specific selected genes controlling traits of interest. Edited plants regenerated by somatic embryogenesis from protoplasts will then be sequenced and molecularly characterized. Embryogenic calli of Sultana and Shiraz cultivars were initiated from unopened leaves of in-vitro shoot tip cultures and from stamens, respectively. Leaves were placed on NB2 medium while stamens on callus initiation medium (PIV) medium and incubated in the dark at 28 °C for three months. Viable protoplasts, tested by FDA staining, isolated from embryogenic calli were cultured by disc method at 1*105 protoplasts/ml. Mature well-shaped somatic embryos developed directly in the protoplast culture medium two months later and were transferred in the light into to shooting medium for further growth. Regenerated plants were then transferred to the greenhouse; no phenotypic alterations were observed when compared to non in-vitro cultured plants. The performed experiments allowed to established an efficient protocol of embryogenic calli production, protoplast isolation, and regeneration of the whole plant through somatic embryogenesis in both Sultana and Shiraz. Regenerated plants, through direct somatic embryogenesis deriving from a single cell, avoid the risk of chimerism during the regeneration process, therefore improving the genome editing process. As pre-requisite of genome editing, an efficient method for transfection of protoplast by yellow fluorescent protein (YFP) marker genes was also established and experiments of direct delivery of CRISPR–Cas9 ribonucleoproteins (RNPs) in protoplasts to achieve efficient DNA-free targeted mutations are in progress.

Keywords: CRISPR-cas9, plant regeneration, protoplast isolation, Vitis vinifera

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Authors: Srijata Mitra, Mobina Parveen, Pranab Roy, Narayan Chandra Chattopadhyay

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Chlorinated hydrocarbon can be a major pollution problem in groundwater as well as soil. Many people interact with these chemicals on daily accidentally or by professionally in the laboratory. One of the most common sources for Chlorinated hydrocarbon contamination of soil and groundwater are industrial effluents. The wide use and discharge of Trichloroethylene (TCE), a volatile chlorohydrocarbon from chemical industry, led to major water pollution in rural areas. TCE is an mainly used as an industrial metal degreaser in industries. Biotransformation of TCE to the potent carcinogen vinyl chloride (VC) by consortia of anaerobic bacteria might have role for the above purpose. For these reasons, the aim of current study was to isolate and characterized the genes involved in TCE metabolism and also to investigate the in silico study of those genes. To our knowledge, only one aromatic dioxygenase system, the toluene dioxygenase in Pseudomonas putida F1 has been shown to be involved in TCE degradation. This is first instance where Bacillus cereus group being used in biodegradation of trichloroethylene. A novel bacterial strain 2479 was isolated from oil depot site at Rajbandh, Durgapur (West Bengal, India) by enrichment culture technique. It was identified based on polyphasic approach and ribotyping. The bacterium was gram positive, rod shaped, endospore forming and capable of degrading trichloroethylene as the sole carbon source. On the basis of phylogenetic data and Fatty Acid Methyl Ester Analysis, strain 2479 should be placed within the genus Bacillus and species cereus. However, the present isolate (strain 2479) is unique and sharply different from the usual Bacillus strains in its biodegrading nature. Fujiwara test was done to estimate that the strain 2479 could degrade TCE efficiently. The gene for TCE biodegradation was PCR amplified from genomic DNA of Bacillus cereus 2479 by using todC1 gene specific primers. The 600bp amplicon was cloned into expression vector pUC I8 in the E. coli host XL1-Blue and expressed under the control of lac promoter and nucleotide sequence was determined. The gene sequence was deposited at NCBI under the Accession no. GU183105. In Silico approach involved predicting the physico-chemical properties of deduced Tce1 protein by using ProtParam tool. The tce1 gene contained 342 bp long ORF encoding 114 amino acids with a predicted molecular weight 12.6 kDa and the theoretical pI value of the polypeptide was 5.17, molecular formula: C559H886N152O165S8, total number of atoms: 1770, aliphatic index: 101.93, instability index: 28.60, Grand Average of Hydropathicity (GRAVY): 0.152. Three differentially expressed proteins (97.1, 40 and 30 kDa) were directly involved in TCE biodegradation, found to react immunologically to the antibodies raised against TCE inducible proteins in Western blot analysis. The present study suggested that cloned gene product (TCE1) was capable of degrading TCE as verified chemically.

Keywords: cloning, Bacillus cereus, in silico analysis, TCE

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Authors: M. Khallaf, R. Khalil, H. Ghetas

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In the present study, V. harveyi and V. alginolyticus were isolated from cultured seabass and seabream at Damietta Governorate, Egypt, during summer season. Isolates were biochemically and molecularly identified using primers for Vhh and Collagenase genes. The most prominent clinical observations of diseased fish were exophthalmia, abdominal distension, and multifocal cutaneous hemorrhagic ulceration on the dorsal musculature and caudal peduncle. Physicochemical characteristics of water samples indicated that the unionized ammonia, nitrate, and hydrogen sulphate concentrations were higher than the acceptable limits. Heavy metals concentrations in water samples exhibited higher concentrations than the permissible levels for fish culture, which was considered as chemical stressors that increase the prevalence of these bacterial diseases. Immune parameters were lower in diseased seabass and seabream than apparently healthy fish. Lesions of different fish organs were identified histopathologically.

Keywords: seabass, seabream, Vibrio alginolyticus, Vibrio harveyi

Procedia PDF Downloads 103

Authors: D. R. Apoorva

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Ichthyosis follicularis, alopecia, and photophobia (IFAP) syndrome is a rare oculocutaneous disorder of genetic origin. This disorder results from mutations in the membrane-bound transcription factor protease site, two genes that impair cholesterol homeostasis, and the ability to cope with endoplasmic reticulum stress. We report a rare case of IFAP syndrome with an atypical presentation, and it was interesting to note that the child had patchy non-scarring alopecia over the scalp along with unilateral madarosis. To our best knowledge, this unique presentation has not been described earlier. The child presented with photophobia and unilateral ptosis. The child also had short stature and intellectual disability. Skin histopathology was nonspecific and consisted of dilated hair follicles with keratin plugs extending above the skin surface. This rare oculocutaneous disorder requires proper documentation so that identification of its variants may be possible in the future. Early recognition of atypical presentations can help in preventing cardiovascular complications, which remain the major cause of death.

Keywords: alopecia, photophobia, ichthyosis follicularis, IFAP syndrome

Procedia PDF Downloads 56