Search results for: multi-abdominal organ segmentation

Authors: Molakala Mourya Vardhan Reddy, Kandimala Revanth, Koduru Sumanth, Beena B. M.

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Emergency response and recovery operations are severely hampered by natural catastrophes, especially floods. Understanding post-flood scenarios is essential to disaster management because it facilitates quick evaluation and decision-making. To this end, we introduce FloodNet, a brand-new high-resolution aerial picture collection created especially for comprehending post-flood scenes. A varied collection of excellent aerial photos taken during and after flood occurrences make up FloodNet, which offers comprehensive representations of flooded landscapes, damaged infrastructure, and changed topographies. The dataset provides a thorough resource for training and assessing computer vision models designed to handle the complexity of post-flood scenarios, including a variety of environmental conditions and geographic regions. Pixel-level semantic segmentation masks are used to label the pictures in FloodNet, allowing for a more detailed examination of flood-related characteristics, including debris, water bodies, and damaged structures. Furthermore, temporal and positional metadata improve the dataset's usefulness for longitudinal research and spatiotemporal analysis. For activities like flood extent mapping, damage assessment, and infrastructure recovery projection, we provide baseline standards and evaluation metrics to promote research and development in the field of post-flood scene comprehension. By integrating FloodNet into machine learning pipelines, it will be easier to create reliable algorithms that will help politicians, urban planners, and first responders make choices both before and after floods. The goal of the FloodNet dataset is to support advances in computer vision, remote sensing, and disaster response technologies by providing a useful resource for researchers. FloodNet helps to create creative solutions for boosting communities' resilience in the face of natural catastrophes by tackling the particular problems presented by post-flood situations.

Keywords: image classification, segmentation, computer vision, nature disaster, unmanned arial vehicle(UAV), machine learning.

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Authors: E. M. D. Akuoko, Eliana Vasquez Osorio, Marcel Van Herk, Marianne Aznar

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Radiotherapy is an integral part of treatment for many patients with breast cancer. However, side effects can occur, e.g., fibrosis or erythema. If patients at higher risks of radiation-induced side effects could be identified before treatment, they could be given more individual information about the risks and benefits of radiotherapy. We hypothesize that breast density is correlated with the risk of side effects and present a novel method for automatic evaluation based on radiotherapy planning CT scans. Methods: 799 supine CT scans of breast radiotherapy patients were available from the REQUITE dataset. The methodology was first established in a subset of 114 patients (cohort 1) before being applied to the whole dataset (cohort 2). All patients were scanned in the supine position, with arms up, and the treated breast (ipsilateral) was identified. Manual experts contour available in 96 patients for both the ipsilateral and contralateral breast in cohort 1. Breast tissue was segmented using atlas-based automatic contouring software, ADMIRE® v3.4 (Elekta AB, Sweden). Once validated, the automatic segmentation method was applied to cohort 2. Breast density was then investigated by thresholding voxels within the contours, using Otsu threshold and pixel intensity ranges based on Hounsfield units (-200 to -100 for fatty tissue, and -99 to +100 for fibro-glandular tissue). Volumetric breast density (VBD) was defined as the volume of fibro-glandular tissue / (volume of fibro-glandular tissue + volume of fatty tissue). A sensitivity analysis was performed to verify whether calculated VBD was affected by the choice of breast contour. In addition, we investigated the correlation between volumetric breast density (VBD) and patient age and breast size. VBD values were compared between ipsilateral and contralateral breast contours. Results: Estimated VBD values were 0.40 (range 0.17-0.91) in cohort 1, and 0.43 (0.096-0.99) in cohort 2. We observed ipsilateral breasts to be denser than contralateral breasts. Breast density was negatively associated with breast volume (Spearman: R=-0.5, p-value < 2.2e-16) and age (Spearman: R=-0.24, p-value = 4.6e-10). Conclusion: VBD estimates could be obtained automatically on a large CT dataset. Patients’ age or breast volume may not be the only variables that explain breast density. Future work will focus on assessing the usefulness of VBD as a predictive variable for radiation-induced side effects.

Keywords: breast cancer, automatic image segmentation, radiotherapy, big data, breast density, medical imaging

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Authors: Ojiegbe Ikenna Nathan

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Obesity is a medical condition in which excess body fat has accumulated to the extent that it leads to reduced life expectancy and or increased health problems. Obesity as a worldwide problem is seen clustered in the families and it moves from generation to generation. It causes some disabilities, mortality and morbidity if left unattended to. The predisposing factors to obesity are either genetic or environment in origin. Nevertheless, the main predisposing factor to obesity is the excessive consumption of food rich in low-density lipoprotein (LDL) such as organ meats, saturated fats etc. This low-density lipoprotein causes an increase in adipose tissue and complicates to obesity. There are varieties of obesity which one needs to take appropriate measures to avoid; such as android, gynoid and morbid obesity. Nonetheless, studies have shown that there is hope for the obese individuals, despite the cause, type and degree of their obesity. This is through the use of the different available treatment measures which increase in physical activities, caloric restrictions, drug therapy and surgical intervention.

Keywords: low-density, lipoprotein, culprit, obesity

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Authors: Anoop T. R., Otman Basir, Robert F. Hess, Eileen E. Birch, Brooke A. Koritala, Reed M. Jost, Becky Luu, David Stager, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. We developed a two-stage method for strabismus detection and classification based on photographs of the face. The first stage detects the presence or absence of strabismus, and the second stage classifies the type of strabismus. The first stage comprises face detection using Haar cascade, facial landmark estimation, face alignment, aligned face landmark detection, segmentation of the eye region, and detection of strabismus using VGG 16 convolution neural networks. Face alignment transforms the face to a canonical pose to ensure consistency in subsequent analysis. Using facial landmarks, the eye region is segmented from the aligned face and fed into a VGG 16 CNN model, which has been trained to classify strabismus. The CNN determines whether strabismus is present and classifies the type of strabismus (exotropia, esotropia, and vertical deviation). If stage 1 detects strabismus, the eye region image is fed into stage 2, which starts with the estimation of pupil center coordinates using mask R-CNN deep neural networks. Then, the distance between the pupil coordinates and eye landmarks is calculated along with the angle that the pupil coordinates make with the horizontal and vertical axis. The distance and angle information is used to characterize the degree and direction of the strabismic eye misalignment. This model was tested on 100 clinically labeled images of children with (n = 50) and without (n = 50) strabismus. The True Positive Rate (TPR) and False Positive Rate (FPR) of the first stage were 94% and 6% respectively. The classification stage has produced a TPR of 94.73%, 94.44%, and 100% for esotropia, exotropia, and vertical deviations, respectively. This method also had an FPR of 5.26%, 5.55%, and 0% for esotropia, exotropia, and vertical deviation, respectively. The addition of one more feature related to the location of corneal light reflections may reduce the FPR, which was primarily due to children with pseudo-strabismus (the appearance of strabismus due to a wide nasal bridge or skin folds on the nasal side of the eyes).

Keywords: strabismus, deep neural networks, face detection, facial landmarks, face alignment, segmentation, VGG 16, mask R-CNN, pupil coordinates, angle deviation, horizontal and vertical deviation

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Authors: Feng Guo

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Human brain organoids, 3D brain tissue cultures derived from human pluripotent stem cells, hold promising potential in modeling neuroinflammation for a variety of neurological diseases. However, challenges remain in generating standardized human brain organoids that can recapitulate key physiological features of a human brain. Here, this study presents a series of organoids-on-a-chip systems to generate better human brain organoids and model neuroinflammation. By employing 3D printing and microfluidic 3D cell culture technologies, the study’s systems enable the reliable, scalable, and reproducible generation of human brain organoids. Compared with conventional protocols, this study’s method increased neural progenitor proliferation and reduced heterogeneity of human brain organoids. As a proof-of-concept application, the study applied this method to model substance use disorders.

Keywords: human brain organoids, microfluidics, organ-on-a-chip, neuroinflammation

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Authors: Alona Faktor

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In this work, we present a NN-based computational model that can perform attention shifts according to high-level instruction. The instruction specifies the type of attentional shift using explicit geometrical relation. The instruction also can be of cognitive nature, specifying more complex human-human interaction or human-object interaction, or object-object interaction. Applying this approach sequentially allows obtaining a structural description of an image. A novel data-set of interacting humans and objects is constructed using a computer graphics engine. Using this data, we perform systematic research of relational segmentation shifts.

Keywords: cognitive science, attentin, deep learning, generalization

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Authors: Izabela Poprawa, Alina Chachulska-Zymelka, Lukasz Chajec, Grazyna Wilczek, Piotr Wilczek, Sebastian Student, Magdalena Rost-Roszkowska

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Heavy metals polluting the environment, especially soil, have a harmful effect on organisms, because they can damage the organ structure, disturb their function and cause developmental disorders. They can affect not only the somatic tissues but also the germinal tissues. In the natural environment, plants and animals are exposed to short- and long-term exposure to these stressors, which have a major influence on the functioning of these organisms. Numerous animals have been treated as the bioindicators of the environment. Therefore, studies on any alterations caused by, e.g., heavy metals are in the center of interests of not only environmental but also medical and biological science. Myriapods are invertebrates which are bioindicators of the environment. One of the species which lives in the upper layers of soil, particularly under stones and rocks is Lithobius forficatus (Chilopoda), commonly known as the brown centipede or stone centipede. It is a European species of the family Lithobiidae. This centipede living in the soil is exposed to, e.g., heavy metals such as cadmium, lead, arsenic. The main goal of our project was to analyze the impact of long-term exposure to cadmium on the structure of ovary with the emphasis on the course of oogenesis. As the material for analysis of cadmium exposure to ovaries, we chose the centipede species, L. forficatus. Animals were divided into two experimental groups: C – the control group, the animals cultured in laboratory conditions in a horticultural soil; Cd2 – the animals cultured in a horticultural soil supplemented with 80 mg/kg (dry weight) of CdCl2 for 45 days – long-term exposure. Animals were fed with Acheta and Chironomus larvae maintained in tap water. The analyzes were carried out using transmission electron microscopy (TEM), flow cytometry and laser scanning (confocal) microscopy. Here we present the results of long-term exposure to cadmium concentration in soil on the organ responsible for female germ cell formation. Analysis with the use of the transmission electron microscope showed changes in the ultrastructure of both somatic and germ cells in the ovary. Moreover, quantitative analysis revealed the decrease in the percentage of cells viability, the increase in the percentage of cells with depolarized mitochondria and increasing the number of early apoptotic cells. All these changes were statistically significant compared to the control. Additionally, an increase in the ADP/ATP index was recorded. However, changes were not statistically significant to the control. Acknowledgment: The study has been financed by the National Science Centre, Poland, grant no 2017/25/B/NZ4/00420.

Keywords: cadmium, centipede, ovary, ultrastructure

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Authors: Natalie A. Sterk, Bernard van Vuuren, Petrie Marais, Bongani Mthombeni

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Injuries to the internal structures of the thorax and abdomen remain a leading cause of death among soldiers. Body armour is a standard issue piece of military equipment designed to protect the vital organs against ballistic and stab threats. When configured for maximum protection, the excessive weight and size of the armour may limit soldier mobility and increase physical fatigue and discomfort. Providing soldiers with more armour than necessary may, therefore, hinder their ability to react rapidly in life-threatening situations. The capability to determine the optimal trade-off between the amount of essential anatomical coverage and hindrance on soldier performance may significantly enhance the design of armour systems. The current study aimed to develop and pilot a methodology for relating internal anatomical structures with actual armour plate coverage in real-time using low-dose diagnostic X-ray scanning. Several pilot scanning sessions were held at Lodox Systems (Pty) Ltd head-office in South Africa. Testing involved using the Lodox eXero-dr to scan dummy trunk rigs at various degrees and heights of measurement; as well as human participants, wearing correctly fitted body armour while positioned in supine, prone shooting, seated and kneeling shooting postures. The verification of sizing and metrics obtained from the Lodox eXero-dr were then confirmed through a verification board with known dimensions. Results indicated that the low-dose diagnostic X-ray has the capability to clearly identify the vital internal structures of the aortic arch, heart, and lungs in relation to the position of the external armour plates. Further testing is still required in order to fully and accurately identify the inferior liver boundary, inferior vena cava, and spleen. The scans produced in the supine, prone, and seated postures provided superior image quality over the kneeling posture. The X-ray-source and-detector distance from the object must be standardised to control for possible magnification changes and for comparison purposes. To account for this, specific scanning heights and angles were identified to allow for parallel scanning of relevant areas. The low-dose diagnostic X-ray provides a non-invasive, safe, and rapid technique for relating vital internal structures with external structures. This capability can be used for the re-evaluation of anatomical coverage required for essential protection while optimising armour design and fit for soldier performance.

Keywords: body armour, low-dose diagnostic X-ray, scanning, vital organ coverage

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Authors: B. Selma, S. Chouraqui

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The pancreas is an elongated organ that extends across the abdomen, below the stomach. In addition, it secretes certain enzymes that aid in food digestion. The pancreas also manufactures hormones responsible for regulating blood glucose levels. In the present paper, we propose a mathematical model to study the homeostasis of glucose and insulin in healthy human, and a simulation of this model, which depicts the physiological events after a meal, will be represented in ordinary humans. The aim of this paper is to design an algorithm which regulates the level of glucose in the blood. The algorithm applied the concept of expert system for performing an algorithm control in the form of an "active" used to prescribe the rate of insulin infusion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. The results showed a performance of the control system.

Keywords: modeling, algorithm, regulation, glucose-insulin, blood, control system

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Authors: Nikita Sankhe

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A Frenum is a band or fold of mucous membrane, which is usually with enclosed muscle fibers, that attaches the lip and cheek to the alveolar mucosa or the gingiva and the underlying periosteum. It curbs or limits the movements of an organ. A frenum becomes a problem if its attachment is too close to the marginal or papillary gingiva, namely localized gingival recession and a midline diastema or it may pull the gingival margin away from the tooth allowing plaque accumulation and inhibit toothbrushing. Frenectomy is the complete removal of the frenum including its attachment to the underlying bone. Miller suggested a technique where by a closure was done across the midline by laterally positioned gingiva. Healing by primary intention resulted in aesthetically acceptable attached gingiva across the midline. This paper aims at showing how a lateral pedicle graft technique combined with frenectomy proves to be more advantageous than any other technique.

Keywords: frenum , frenectomy , lateral pedicle graft , classical frenectomy

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Authors: Rongli Gai, Zhiyuan Chang

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At this stage, in view of various situations in the interpolation process, most researchers use self-adaptation to adjust the interpolation process, which is also one of the current and future research hotspots in the field of CNC machining. In the interpolation process, according to the overview of the spline curve interpolation algorithm, the adaptive analysis is carried out from the factors affecting the interpolation process. The adaptive operation is reflected in various aspects, such as speed, parameters, errors, nodes, feed rates, random Period, sensitive point, step size, curvature, adaptive segmentation, adaptive optimization, etc. This paper will analyze and summarize the research of adaptive imputation in the direction of the above factors affecting imputation.

Keywords: adaptive algorithm, CNC machining, interpolation constraints, spline curve interpolation

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Authors: Ramandeep Kaur, Gurjit Singh Bhathal

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Cancer diagnosis is very difficult task. Magnetic resonance imaging (MRI) scan is used to produce image of any part of the body and provides an efficient way for diagnosis of cancer or tumor. In existing method, fuzzy clustering mean (FCM) is used for the diagnosis of the tumor. In the proposed method FCM is used to diagnose the cancer of the foot. FCM finds the centroids of the clusters of the foot cancer obtained from MRI images. FCM thresholding result shows the extract region of the cancer. Morphological operations are applied to get extracted region of cancer.

Keywords: magnetic resonance imaging (MRI), fuzzy C mean clustering, segmentation, morphological operations

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Ferjani Hanen, El Arem Amira, Boussema Ayed Imen, Bacha Hassen

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Tacrolimus (TAC), a calcineurin inhibitor, is clinically used as an immunosuppressive agent in the transplant recipient, but its use associated-hepatotoxicity. Mycophenolate mofetil (MMF), an anti-metabolite, is a potent immunosuppressive drug. MMF is not hepatotoxic and is the most common adjunctive immunosuppressant for TAC. The effects of TAC and MMF combination in the liver is still not well understood. This work aimed to investigate their combined effect against in liver in rats Wistar after 24 h. The oral median lethal doses (LD50) of TAC and MMF alone were evaluated in rats are 240 mg/kg and 500 mg/kg respectively. Oral administration of the MMF at 50 mg/kg to male Wistar intoxicated with TAC at 60 mg/kg, demonstrated a significant protective effect by lowering the levels of hepatic markers enzymes (AST, ALT) in the serum rat. MMF attenuated oxidative stress by restoring the activities of SOD, CAT and by reducing the malondialdehyde (MDA) and protein carbonyl levels liver. This study provided evidence that MMF protects rat liver from TAC-induced injury and suggests a most combination use for organ transplantation.

Keywords: tacrolimus, mycophenolate mofetil, combination, liver, rat

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Authors: Mekdelawit Teferi Alamirew

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As a practical tool, the Geographical information system (GIS) was used for data integration, collection, management, analysis, and output presentation in pavement mangement systems . There are many GIS techniques to improve the maintenance activities like Dynamic segmentation and weighted overlay analysis which considers Multi Criteria Decision Making process. The results indicated that the developed MPI model works sufficiently and yields adequate output for providing accurate decisions. Hence considering multi criteria to prioritize the pavement sections for maintenance, as a result of the fact that GIS maps can express position, extent, and severity of pavement distress features more effectively than manual approaches, lastly the paper also offers digitized distress maps that can help agencies in their decision-making processes.

Keywords: pavement, flexible, maintenance, index

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Authors: A. Askerov, Y. Teterin, P. Yartcev, S. Novikov

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Introduction: Acute pancreatitis (AP) is a socially significant problem for public health and continues to be one of the most common causes of hospitalization of patients with pathology of the gastrointestinal tract. It is characterized by high mortality rates, which reaches 62-65% in infected pancreatic necrosis. Aims & Methods: The study group included 63 patients who underwent transluminal drainage (TLD) fluid collection (FC). All patients were performed transabdominal ultrasound, computer tomography of the abdominal cavity and retroperitoneal organs and endoscopic ultrasound (EUS) of the pancreatobiliary zone. The EUS was used as a final diagnostic method to determine the characteristics of FC. The indications for TLD were: the distance between the wall of the hollow organ and the FC was not more than 1 cm, the absence of large vessels on the puncture trajectory (more than 3 mm), and the size of the formation was more than 5 cm. When a homogeneous cavity with clear, even contours was detected, a plastic stent with rounded ends (“double pig tail”) was installed. The indication for the installation of a fully covered self-expanding stent was the detection of nonhomogeneous anechoic FC with hyperechoic inclusions and cloudy purulent contents. In patients with necrotic forms after drainage of the purulent cavity, a cystonasal drainage with a diameter of 7Fr was installed in its lumen under X-ray control to sanitize the cavity with a 0.05% aqueous solution of chlorhexidine. Endoscopic necrectomy was performed every 24-48 hours. The plastic stent was removed in 6 month, the fully covered self-expanding stent - in 1 month after the patient was discharged from the hospital. Results: Endoscopic TLD was performed in 63 patients. The FC corresponding to interstitial edematous pancreatitis was detected in 39 (62%) patients who underwent TLD with the installation of a plastic stent with rounded ends. In 24 (38%) patients with necrotic forms of FC, a fully covered self-expanding stent was placed. Communication with the ductal system of the pancreas was found in 5 (7.9%) patients. They underwent pancreaticoduodenal stenting. A complicated postoperative period was noted in 4 (6.3%) cases and was manifested by bleeding from the zone of pancreatogenic destruction. In 2 (3.1%) cases, this required angiography and endovascular embolization a. gastroduodenalis, in 1 (1.6%) case, endoscopic hemostasis was performed by filling the cavity with 4 ml of Hemoblock hemostatic solution. The combination of both methods was used in 1 (1.6%) patient. There was no evidence of recurrent bleeding in these patients. Lethal outcome occurred in 4 patients (6.3%). In 3 (4.7%) patients, the cause of death was multiple organ failure, in 1 (1.6%) - severe nosocomial pneumonia that developed on the 32nd day after drainage. Conclusions: 1. EUS is not only the most important method for diagnosing FC in AP, but also allows you to determine further tactics for their intraluminal drainage.2. Endoscopic intraluminal drainage of fluid zones in 45.8% of cases is the final minimally invasive method of surgical treatment of large-focal pancreatic necrosis. Disclosure: Nothing to disclose.

Keywords: acute pancreatitis, fluid collection, endoscopy surgery, necrectomy, transluminal drainage

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Authors: Gulten Yilmaz, A. Beril Tugrul, Mustafa Demir, Dogan Yasar, Bayram Demir, Bulent Buyuk

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A Positron Emission Tomography (PET) is a radioisotope imaging technique that illustrates the organs and the metabolisms of the human body. This technique is based on the simultaneous detection of 511 keV annihilation photons, annihilated as a result of electrons annihilating positrons that radiate from positron-emitting radioisotopes that enter biological active molecules in the body. This study was conducted on ten patients in an effort to conduct patient-related experimental studies. Dosage monitoring for the bladder, which was the organ that received the highest dose during PET applications, was conducted for 24 hours. Assessment based on measuring urination activities after injecting patients was also a part of this study. The MIRD method was used to conduct dosage calculations for results obtained from experimental studies. Results obtained experimentally and theoretically were assessed comparatively.

Keywords: PET/CT, TLD, MIRD, dose measurement, patient doses

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Authors: Parthasarathi Pramanik

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Paediatric blunt abdominal trauma associated with superficial bruise, hematoma, or laceration and internal organ damage secondary to bicycle handlebar is widely documented in the literature. In this article, we have presented a case of bicycle handlebar inflicted fatal neck laceration in a road accident. The deceased sustained a horizontally placed laceration injury over the front and both sides of the middle third of neck (13 cm x 5-8 cm x 2-3.5 cm).The margins of the wound were irregular and focally abraded. The right corner of the injury was pointed whereas the left one was ended with a skin flap. Multiple graze abrasions, contusions and lacerations were found on different parts of body. Autopsy findings and other circumstantial evidences revealed that the victim died due to exsanguination because of severance of carotid artery and jugular vein of both sides. Analysis of the wound suggests the decease sustained the wound by the revolving bicycle handle bar while he had lost the balance.

Keywords: bicycle handle bar, neck injury, lacerated injury, road acident

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Authors: Arthi Ganapathy, Arithra Banerjee, Saroj Kaler

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Abdominal aorta is the sole purveyor of all organs in the abdomen. Anomalies of its main trunk or its branches are to be meticulously observed as it effects the perfusion of an organ. Varying patterns of the testicular artery is one of them. The origin and course of testicular arteries have to be identified carefully during various surgical procedures like renal transplant, intra abdominal surgeries and even in orthopedic surgery like spine surgery. With the advent of new intra-abdominal therapeutic and diagnostic techniques, the anatomy of testicular arteries has assumed much more significance. Though the variations of the testicular vein are well documented, the variations of the testicular artery are not so frequent in incidence. We report a case of the bilateral aberrant origin of the testicular artery from polar renal arteries. We also discuss its developmental basis. Such anomalies if left unnoticed will lead to serious intraoperative complications during procedures on retroperitoneal organs. Any damage to testicular arteries will compromise the function of the gonads.

Keywords: cadaver, gonadal, renal, surgery

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Authors: Ismael Lins Patriota

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Arvo Pärt is an Estonian composer who started his musical career under the influence of twelve-tone music and dodecaphonism. From 1968 to 1976, he isolated himself to search for a new path as a composer. In this period, he converted to Russian orthodoxy and changed his composing to tintinnabuli, a musical technique combining triadic chords with simple melodies. The recent analysis of Pärt’s output demonstrates that mathematics remained an influence after the invention of tintinnabuli. The present discussion deals with the relationship between math and religion in his work Out of the Depths (1980), proposing a musical-text approach and examining the minimum elements of the piece, such as motives and sub-phrases, which is the main focus of this work, considering text patterns and the role of the organ, which also uses the tintinnabuli system. The analysis of these elements demonstrates that Pärt uses math as a formal element, and the composer combines musical parameters to execute a personal and innovative interpretation of the text.

Keywords: Arvo Pärt, Out of the Depths, math, religion, analysis

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Authors: Ashis Pradhan, Mohan P. Pradhan

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Pattern Matching is useful for recognizing character in a digital image. OCR is one such technique which reads character from a digital image and recognizes them. Line segmentation is initially used for identifying character in an image and later refined by morphological operations like binarization, erosion, thinning, etc. The work discusses a recognition technique that defines a set of morphological operators based on its orientation in a character. These operators are further categorized into groups having similar shape but different orientation for efficient utilization of memory. Finally the characters are recognized in accordance with the occurrence of frequency in hierarchy of significant pattern of those morphological operators and by comparing them with the existing database of each character.

Keywords: binary image, morphological patterns, frequency count, priority, reduction data set and recognition

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Authors: Yunusa Odiba

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Islam, from its root is a divine religion and it does not exercise anything except within the scope of its divinity-its culture, tradition morality, and the like. The damage done to the legacies, traditions, culture, morality, viability, continued existence and relevance of the Islamic religious way of life by the prevalent western secular education system in the Muslim world has become a thing of interest to many scholars especially, the Muslim scholars, hence, advocating the integration of Islamic education with the western circular educational system. The aim is to produce a new generation of dedicated Muslims whose education has prepared them for the challenges of contemporary materialistic circulation alongside real Islamic knowledge. This paper, however, examines the process of integrating Islamic schools with the contemporary western based schools that would under-take the unification which should function as basic organ of Muslim ideological revivalism, cultural retention, identity formation, socio-economic development, and scientific and ecological inventiveness.

Keywords: challenges, integrating, Islamic education, secular system, Igalaland

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Authors: Yousif M. Yousif Abdallah, Mohamed E. Gar-Elnabi, Abdoelrahman H. A. Bakary, Alaa M. H. Eltoum, Abdelazeem K. M. Ali

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The study was established to measure the amount of radiation outside the treatment field in external beam radiation therapy using day method of dose calculation, the data was collected from 89 patients of cervical carcinoma in order to determine if the dose outside side the irradiation treatment field for spleen, liver, both kidneys, small bowel, large colon, skin within the acceptable limit or not. The cervical field included mainly 4 organs which are bladder, rectum part of small bowel and hip joint these organ received mean dose of (4781.987±281.321), (4736.91±331.8), (4647.64±387.1) and (4745.91±321.11) respectively. The mean dose received by outfield organs was (77.69±15.24cGy) to large colon, (93.079±12.31cGy) to right kidney (80.688±12.644cGy) to skin, (155.86±17.69cGy) to small bowel. This was more significant value noted.

Keywords: radiation dose, cervical carcinoma, day’s methods, radiation medicine

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Authors: Diamant Irene, Shklarnik Batya

Abstract:

In on to its widespread effects on health and economic issues, Covid-19 shook the work and employment world. Among the prominent changes during the pandemic is the work-from-home trend, complete or partial, as part of social distancing. In fact, these changes accelerated an existing tendency of work flexibility already underway before the pandemic. Technology and means of advanced communications led to a re-assessment of “place of work” as a physical space in which work takes place. Today workers can remotely carry out meetings, manage projects, work in groups, and different research studies point to the fact that this type of work has no adverse effect on productivity. However, from the worker’s perspective, despite numerous advantages associated with work from home, such as convenience, flexibility, and autonomy, various drawbacks have been identified such as loneliness, reduction of commitment, home-work boundary erosion, all risk factors relating to the quality of life and burnout. Thus, a real need has arisen in exploring differences in work-from-home experiences and understanding the relationship between psychological characteristics and the prevalence of burnout. This understanding may be of significant value to organizations considering a future hybrid work model combining in-office and remote working. Based on Hobfoll’s Theory of Conservation of Resources, we hypothesized that burnout would mainly be found among workers whose physical remoteness from the workplace threatens or hinders their ability to retain significant individual resources. In the present study, we compared fully remote and partially remote workers (hybrid work), and we examined psychological characteristics and their connection to the formation of burnout. Based on the conceptualization of Place Attachment as the cognitive-emotional bond of an individual to a meaningful place and the need to maintain closeness to it, we assumed that individuals characterized with Place Attachment to the workplace would suffer more from burnout when working from home. We also assumed that extrovert individuals, characterized by the need of social interaction at the workplace and individuals with segmentationpreference – a need for separation between different life domains, would suffer more from burnout, especially among fully remote workers relative to partially remote workers. 194 workers, of which 111 worked from home in full and 83 worked partially from home, aged 19-53, from different sectors, were tested using an online questionnaire through social media. The results of the study supported our assumptions. The repercussions of these findings are discussed, relating to future occupational experience, with an emphasis on suitable occupational adjustment according to the psychological characteristics and needs of workers.

Keywords: working from home, burnout, place attachment, extraversion, segmentation preference, Covid-19

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Authors: Daniel C. S. Lim, W. Y. Tan

Abstract:

The world is facing a growing food crisis. The concerns of food nutritional value, food safety and food security are becoming increasingly real. There is also a direct relationship to the risk of diseases, particularly chronic diseases, to the food we consume. So, there are increasing concerns about the modern day food ecosystem creating foods that can provide the nutritional components for organ function sustenance, as well as, taking a serious view on diet-related diseases. This paper addresses some of the above concerns and gives an overview of the current global situation relating to food nutrition and safety. The paper reviews nutritional aspects of food today compared to those of the last century, compares whole foods found in supermarkets versus those organically grown, as well as population behaviour towards food choices. It provides scientific insights into the effects of some of the global trends such as climate change and other changes environmental changes, and presents what individuals and corporations are doing to use the latest nutritional technologies as strategic assets. Finally, it briefly highlights some of the innovative solutions that are being applied to address several of the above concerns.

Keywords: food crisis, food safety, global trends, nutritional aspects

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

Abstract:

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: Ali Ganoun, Wesam Algablawi, Wasim BenAnaif

Abstract:

Video based traffic surveillance based on License Plate Recognition (LPR) system is an essential part for any intelligent traffic management system. The LPR system utilizes computer vision and pattern recognition technologies to obtain traffic and road information by detecting and recognizing vehicles based on their license plates. Generally, the video based LPR system is a challenging area of research due to the variety of environmental conditions. The LPR systems used in a wide range of commercial applications such as collision warning systems, finding stolen cars, controlling access to car parks and automatic congestion charge systems. This paper presents an automatic LPR system of Libyan license plate. The performance of the proposed system is evaluated with three video sequences.

Keywords: license plate recognition, localization, segmentation, recognition

Procedia PDF Downloads 464

Authors: Iannello G., Coppa F., Pennisi S., Giuffrida G., Lo Faro R., Cartelli S., Ferruggia G., Brundo M. V.

Abstract:

Skin is the largest multifunctional human organ and possesses a complex, multilayered structure with the ability to regenerate and renew. The key role in skin regeneration is played by fibroblasts, which also occupy an important role in the wound healing process. Different methods, including dynamic light scattering, scanning electron microscopy, ELISA, and MTT assay, were employed to evaluate on fibroblasts the in vitro effects of plant-derived nanovesicles and cord blood stem cells‐derived exosomes. We compared the results with those of cells exposed to a technology called AMPLEX PLUS, containing a mixture of 20 different biologically active factors (GF20) and exosomes isolated and purified from bovine colostrum. AMPLEX PLUS was able to significantly enhance the cell proliferation status of cells at both 24 and 48 hours compared to untreated cells (control). The obtained results suggest how AMPLEX PLUS could be potentially effective in treating skin rejuvenation.

Keywords: AMPLEX PLUS, cell vitality, colostrum, nanovesicles

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Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

Abstract:

China launched satellite GF-2 in 2014. This study deals with comparing nearest neighbor object-based classification and neural network classification methods for classification of the fused GF-2 image. Firstly, rectification of GF-2 image was performed. Secondly, a comparison between nearest neighbor object-based classification and neural network classification for classification of fused GF-2 was performed. Thirdly, the overall accuracy of classification and kappa index were calculated. Results indicate that nearest neighbor object-based classification is better than neural network classification for urban mapping.

Keywords: GF-2 images, feature extraction-rectification, nearest neighbour object based classification, segmentation algorithms, neural network classification, multilayer perceptron

Procedia PDF Downloads 389