Search results for: brain lymphatic system

Authors: Avyarthana Dey, Naren P. Rao, Arpitha Jacob, Chaitra V. Hiremath, Shivarama Varambally, Ganesan Venkatasubramanian, Rose Dawn Bharath, Bangalore N. Gangadhar

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Objective: Impaired facial emotion recognition is widely reported in schizophrenia. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. However, its effect on facial emotion recognition deficits seen in schizophrenia is not well explored. In this study, we examined the effect of intranasal OXT on processing facial emotions and its neural correlates in patients with schizophrenia. Method: 12 male patients (age= 31.08±7.61 years, education= 14.50±2.20 years) participated in this single-blind, counterbalanced functional magnetic resonance imaging (fMRI) study. All participants underwent three fMRI scans; one at baseline, one each after single dose 24IU intranasal OXT and intranasal placebo. The order of administration of OXT and placebo were counterbalanced and subject was blind to the drug administered. Participants performed a facial emotion recognition task presented in a block design with six alternating blocks of faces and shapes. The faces depicted happy, angry or fearful emotions. The images were preprocessed and analyzed using SPM 12. First level contrasts comparing recognition of emotions and shapes were modelled at individual subject level. A group level analysis was performed using the contrasts generated at the first level to compare the effects of intranasal OXT and placebo. The results were thresholded at uncorrected p < 0.001 with a cluster size of 6 voxels. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. Results: Compared to placebo, intranasal OXT attenuated activity in inferior temporal, fusiform and parahippocampal gyri (BA 20), premotor cortex (BA 6), middle frontal gyrus (BA 10) and anterior cingulate gyrus (BA 24) and enhanced activity in the middle occipital gyrus (BA 18), inferior occipital gyrus (BA 19), and superior temporal gyrus (BA 22). There were no significant differences between the conditions on the accuracy scores of emotion recognition between baseline (77.3±18.38), oxytocin (82.63 ± 10.92) or Placebo (76.62 ± 22.67). Conclusion: Our results provide further evidence to the modulatory effect of oxytocin in patients with schizophrenia. Single dose oxytocin resulted in significant changes in activity of brain regions involved in emotion processing. Future studies need to examine the effectiveness of long-term treatment with OXT for emotion recognition deficits in patients with schizophrenia.

Keywords: recognition, functional connectivity, oxytocin, schizophrenia, social cognition

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Authors: Saleh Mobasseri, Mohammad Mobasseri

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The article refers to the history of the rise of brake system and described it’s importance in passenger’s lives. The disc brake system performance and ABS are also compared with each other by the kinetic and kinematic analysis of the braking system,and evaluate the impact of each parameters is checked on the vehicle stopping distance. Anti−lock braking system (ABS) is one of the most important features that affect on vehicle safety and for this reason much efforts have been made to improve this system. The objectives of the anti−lock system (ABS) are as follows: Preventing the wheels from locking, achieving maximum technical momentum in terms of braking,stability,reducing stopping distances. In this paper,we study the comparative of ABS brake and disc brake.

Keywords: anti−lock braking System (ABS), stopping distances, booster, car stability, force exerted on the brake pedal

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Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

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Authors: Bassant M. M. Ibrahim, Doha H. Abou Baker, Ahmed Abd Elghafour

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Excessive exposure to heavy metals contributes to the occurrence of deleterious health problems that affect vital organs like the brain, liver, kidneys, and heart. The use of natural products that have antioxidant capabilities may contribute to the protection of these organs. In the present study, the essential oil of summer savory (Satureja hortensis) was used to evaluate its protective effects against lead acetate induced damaging effect on rats’ vital organs, due to its high contents of carvacrol, y-terpinene, and p-cymene. Forty female Wister Albino rats were classified into five equal groups, the 1st served as normal group, the 2nd served as positive control group was given lead acetate (60 mg/kg) intra-peritoneal (IP), the third to fifth groups were treated with calcium disodium (EDTA) as chelating agent and summer savory essential oil in doses of (50 and 100mg/kg) respectively. All treatments were given IP concomitant with lead acetate for ten successive days. At the end of the experiment duration electrocardiogram (ECG), an open field test for the evaluation of psychological state, rotarod test as for the evaluation of locomotor coordination ability as well as anti-inflammatory and oxidative stress biomarkers in serum and histopathology of vital organs were performed. The investigations in this study show that the protective effect of high dose of summer savory essential oil is more than the low dose and that the essential oil of summer savory is a promising agent that can contribute to the protection of vital organs against the hazardous damaging effects of lead acetate.

Keywords: brain, heart, kidneys, lead acetate, liver, protective, summer savory

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Authors: Ünal Kızıl, Levent Genç, Sefa Aksu, Ahmet Tapınç

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The Figaro AM-1 sensor module which employs TGS 2600 model gas sensor in air quality assessment was used. The system was coupled with a microprocessor that enables sensor module to create warning message via telephone. This low cot sensor system’s performance was compared with a Diagnose II commercial electronic nose system. Both air quality sensor and electronic nose system employ metal oxide chemical gas sensors. In the study experimental setup, data acquisition methods for electronic nose system, and performance of the low cost air quality system were evaluated and explained.

Keywords: air quality, electronic nose, environmental quality, gas sensor

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Authors: Alpesh Adeshara, Rajendrasinh Jadeja, Praghnesh Bhatt

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Implementation of advanced technologies requires sophisticated instruments that deal with the operation, control, restoration and protection of rapidly growing power system network under normal and abnormal conditions. Presently, the applications of Phasor Measurement Unit (PMU) are widely found in real time operation, monitoring, controlling and analysis of power system network as it eliminates the various limitations of Supervisory Control and Data Acquisition System (SCADA) conventionally used in power system. The use of PMU data is very rapidly increasing its importance for online and offline analysis. Wide Area Measurement System (WAMS) is developed as new technology by use of multiple PMUs in power system. The present paper proposes a model of MATLAB based PMU using Discrete Fourier Transform (DFT) algorithm and evaluation of its operation under different contingencies. In this paper, PMU based two bus system having WAMS network is presented as a case study.

Keywords: GPS global positioning system, PMU phasor measurement system, WAMS wide area monitoring system, DFT, PDC

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Authors: A. Harrouz, O. Harrouz, A. Benatiallah

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This paper is to review the essential definitions, roles, and characteristics of communication of metering system. We discuss measurement, data acquisition, and metrological control of a signal sensor from dynamic metering system. After that, we present control of instruments of metering system of fluid with more detailed discussions to the reference standards.

Keywords: data acquisition, dynamic metering system, reference standards, metrological control

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Authors: Gabriele Barrocas, Habon Issa

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The amygdala is one of various brain regions that tend to be pathological in individuals with autism spectrum disorder (ASD). ASD is a prevalent and heterogeneous developmental disorder affecting all ethnic and socioeconomic groups and consists of a broad range of severity, etiology, and behavioral symptoms. Common features of ASD include but are not limited to repetitive behaviors, obsessive interests, and anxiety. Neuroscientists view the amygdala as the core of the neural system that regulates behavioral responses to anxiogenic and threatening stimuli. Despite this consensus, many previous studies and literature reviews on the amygdala’s alterations in individuals with ASD have reported inconsistent findings. In this review, we will address these conflicts by highlighting recent studies which reveal that anatomical and related socio-emotional differences detected between individuals with and without ASD are highly age-dependent. We will specifically discuss studies using functional magnetic resonance imaging (fMRI), structural MRI, and diffusion tensor imaging (DTI) to provide insights into the neuroanatomical substrates of ASD across development, with a focus on amygdala volumes, cell densities, and connectivity.

Keywords: autism, amygdala, development, abnormalities

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Authors: Maria Del Carmen Millan-Linares, Ana Lemus Conejo, Rocio Toscano, Alvaro Villanueva, Francisco Millan, Justo Pedroche, Sergio Montserrat-De La Paz

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GPETAFLR (Glycine-Proline-Glutamine-Threonine-Alanine-Phenylalanine-Leucine-Arginine) is a peptide isolated from Lupinus angustifolius L. protein hydrolysate (LPH). Herein, the effect of this peptide was investigated in two different models of neuroinflammation: in the immortalized murine microglia cell line BV-2 and in a high-fat-diet-induced obesity mouse model. Methods and Results: Effects of GPETAFLR on neuroinflammation were evaluated by RT-qPCR, flow cytometry, and ELISA techniques. In BV-2 microglial cells, Lipopolysaccharides (LPS) enhanced the release of pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6) whereas GPETAFLR decreased pro-inflammatory cytokine levels and increased the release of the anti-inflammatory cytokine IL-10 in BV2 microglial cells. M1 (CCR7 and iNOS) and M2 (Arg-1 and Ym-1) polarization markers results showed how the GPETAFLR octapeptide was able to decrease M1 polarization marker expression and increase the M2 polarization marker expression compared to LPS. Animal model results indicate that GPETAFLR has an immunomodulatory capacity, both decreasing pro-inflammatory cytokine IL-6 and increasing the anti-inflammatory cytokine IL-10 in brain tissue. Polarization markers in the brain tissue were also modulated by GPETAFLR that decreased the pro-inflammatory expression (M1) and increased the anti-inflammatory expression (M2). Conclusion: Our results suggest that GPETAFLR isolated from LPH has significant potential for management of neuroinflammatory conditions and offer benefits derived from the consumption of Lupinus angustifolius L. in the prevention of neuroinflammatory-related diseases.

Keywords: GPETAFLR peptide, BV-2 cell line, neuroinflammation, cytokines, high-fat-diet

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Authors: Abdulqader Rasool Feqi Mohammed, Ergun Erçelebi̇

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A large number of hospitals from developed countries are adopting hospital information system to bring efficiency in hospital information system. The purpose of this project is to research on new network security techniques in order to enhance the current network security structure of save a hospital information system (HIS). This is very important because, it will avoid the system from suffering any attack. Security architecture was optimized but there are need to keep researching on best means to protect the network from future attacks. In this final project research, security techniques were uncovered to produce best network security results when implemented in an integrated framework.

Keywords: hospital information system, HIS, network security techniques, internet protocol, IP, network

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Authors: Haffaf Hafid

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Hypergraphs, after being used to model the structural organization of System of Sytems (SoS) at macroscopic level, has recent trends towards generalizing this powerful representation at different stages of complex system modelling. In this paper, we first describe different applications of hypergraph theory, and step by step, introduce multilevel modeling of SoS by means of integrating Constraint Programming Langages (CSP) dealing with engineering system reconfiguration strategy. As an application, we give an A.C.T Terminal controlled by a set of Intelligent Automated Vehicle.

Keywords: hypergraph model, structural analysis, bipartite graph, monitoring, system of systems, reconfiguration analysis, hypernetwork

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Authors: Uma Kanth, Amy Cook

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Conceptual Metaphor Theory (CMT) proposes that metaphor is fundamental to human thought. CMT utilizes embodied cognition, in that emotions are conceptualized as effects on the body because of a coupling of one’s bodily experiences and one’s somatosensory system. Time perception is a function of embodied cognition and conceptual metaphor in that one’s experience of time is inextricably dependent on one’s perception of the world around them. A hallmark of depressive disorders is the distortion in one’s perception of time, such as neurological dysfunction and psychomotor retardation, and yet, to the author’s best knowledge, previous studies have not before linked CMT, embodied cognition, and depressive disorders. Therefore, the focus of this paper is the investigation of how the applications of CMT and embodied cognition (especially regarding time perception) have promise in improving current techniques to treat depressive disorders. This paper aimed to extend, through a thorough review of literature, the theoretical basis required to further research into CMT and embodied cognition’s application in treating time distortion related symptoms of depressive disorders. Future research could include the development of brain training technologies that capitalize on the principles of CMT, with the aim of promoting cognitive remediation and cognitive activation to mitigate symptoms of depressive disorder.

Keywords: depression, conceptual metaphor theory, embodied cognition, time

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Authors: P. Javid, A. Aeenmehr, J. Taghavifar

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In this paper, supply air pressure of HVAC system has been modeled with second-order transfer function plus dead-time. In HVAC system, the desired input has step changes, and the output of proposed control system should be able to follow the input reference, so the idea of using model based predictive control is proceeded and designed in this paper. The closed loop control system is implemented in MATLAB software and the simulation results are provided. The simulation results show that the model based predictive control is able to control the plant properly.

Keywords: air conditioning system, GPC, dead time, air supply control

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Authors: Samara E., Kilintzis P., Katsoras E., Martinidis G.

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Regions play an important role in the global economy by driving research and innovation policies through a major tool, the Regional Innovation System (RIS). RIS is a social system that encompasses the systematic interaction of the various organizations that comprise it in order to improve local knowledge and innovation. This article describes the methodological framework for developing and validating a RIS model utilizing system dynamics. This model focuses on the functional structure of the RIS, separating it in six diverse, interacting sub-systems.

Keywords: innovations, regional development, systems thinking, social system

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Authors: John E. Muñoz, Jose F. Lopez, David S. Lopez

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Attention Deficit Hyperactivity Disorder (ADHD) is a disorder that affects 1 out of 5 Colombian children, converting into a real public health problem in the country. Conventional treatments such as medication and neuropsychological therapy have been proved to be insufficient in order to decrease high incidence levels of ADHD in the principal Colombian cities. This work demonstrates a design and development of a videogame that uses a brain computer interface not only to serve as an input device but also as a tool to monitor neurophysiologic signal. The video game named “The Harvest Challenge” puts a cultural scene of a Colombian coffee grower in its context, where a player can use his/her avatar in three mini games created in order to reinforce four fundamental aspects: i) waiting ability, ii) planning ability, iii) ability to follow instructions and iv) ability to achieve objectives. The details of this collaborative designing process of the multimedia tool according to the exact clinic necessities and the description of interaction proposals are presented through the mental stages of attention and relaxation. The final videogame is presented as a tool for sustained attention training in children with ADHD using as an action mechanism the neuromodulation of Beta and Theta waves through an electrode located in the central part of the front lobe of the brain. The processing of an electroencephalographic signal is produced automatically inside the videogame allowing to generate a report of the theta/beta ratio evolution - a biological marker, which has been demonstrated to be a sufficient measure to discriminate of children with deficit and without.

Keywords: BCI, neuromodulation, ADHD, videogame, neurofeedback, theta/beta ratio

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Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

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Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

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Authors: M. S. Sreejith, Steffy Joy, Abhishesh Pal, Beom-Sahng Ryuh, V. R. Sanal Kumar

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In this paper an attempt has been made for the design of a robotic library using an intelligent system. The robot works on the ARM microprocessor, motor driver circuit with 5 degrees of freedom with Wi-Fi and GPS based communication protocol. The authenticity of the library books is controlled by RFID. The proposed robotic library system is facilitated with embedded system and ARM. In this library issuance system the previous potential readers’ authentic review reports have been taken into consideration for recommending suitable books to the deserving new users and the issuance of books or periodicals is based on the users’ decision. We have conjectured that the Wi-Fi based robotic library management system would allow fast transaction of books issuance and it also produces quality readers.

Keywords: GPS bsed based Robotic library, library management system, robotic library, Wi-Fi library

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Authors: Ahmad Shah Irshad, Naqibullah Kargar, Wais Samadi

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Building an integrated photovoltaic (BIPV) system is a new and modern technique for solar energy production in Kandahar. Due to its location, Kandahar has abundant sources of solar energy. People use both monocrystalline and polycrystalline silicon solar PV modules for the grid-connected solar PV system, and they don’t know which technology performs better for the BIPV system. This paper analyses the parameters described by IEC61724, “Photovoltaic System Performance Monitoring Guidelines for Measurement, Data Exchange and Analysis,” to evaluate which technology shows better performance for the BIPV system. The monocrystalline silicon BIPV system has a 3.1% higher array yield than the polycrystalline silicon BIPV system. The final yield is 0.2%, somewhat higher for monocrystalline silicon than polycrystalline silicon. Monocrystalline silicon has 0.2% and 4.5% greater yearly yield factor and capacity factors than polycrystalline silicon, respectively. Monocrystalline silicon shows 0.3% better performance than polycrystalline silicon. With 1.7% reduction and 0.4% addition in collection losses and useful energy produced, respectively, monocrystalline silicon solar PV system shows good performance than polycrystalline silicon solar PV system. But system losses are the same for both technologies. The monocrystalline silicon BIPV system injects 0.2% more energy into the grid than the polycrystalline silicon BIPV system.

Keywords: photovoltaic technologies, performance analysis, solar energy, solar irradiance, performance ratio

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Authors: Mitchell Stanton

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Background: Endovascular management is well established as a mainstay treatment option for cerebral aneurysms. It is also well established that immediate post procedural imaging can be difficult to interpret due to the presence of contrast material. However, through the use of Dual-Energy computed tomography, it has become possible to differentiate contrast extravasation and intracranial haemorrhage. This case illustrates the importance of this technology following endovascular treatment of an unruptured cerebral aneurysm. Case Presentation: A 79-year-old female was found to have an unruptured large intracavernous ICA fusiform aneurysm on CT Brain Angiogram after presenting with acute ophthalmoplegia. This ophthalmoplegia was caused by mass effect from the aneurysm and subsequently the aneurysm was treated with an endovascular flow diverting stent. CT brain was performed post operatively due to a reduced level of consciousness and this showed diffuse subarachnoid hyperdensity of the left hemisphere. The use of Dual-Energy CT allowed accurate differentiation and illustrated diffuse contrast material extravasation, allowing patient to continue on dual-antiplatelets and therapeutic anticoagulation to reduce the risk of ischaemic injury post endovascular stent. Conclusion: Endovascular treatment options for management of intracranial aneurysms are constantly evolving. The use of Dual-Energy CT therefore has an integral role in accurately diagnosing any post-operative complications. Specifically, differentiating between subarachnoid haemorrhage and contrast extravasation is vital in these patients due to the significant consequences to their ongoing management in regards to continuation or cessation of antiplatelets or anticoagulation. With increasing access to this technology, its use should become standard practice in the post-operative investigation of these patients undergoing endovascular treatment.

Keywords: aneurysm, computed tomography, contrast extravasation, dual-energy CT, endovascular, subarachnoid haemorrhage

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Authors: Ahmed Gaber Abdel Raheem, Nashwa Ahmed Mohamed

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Introduction: Sensorineural hearing loss (SNHL) is largely caused by the degeneration of the cochlea. Therapeutic options for SNHL are limited to hearing aids and cochlear implants. The cell transplantation approach to the regeneration of hair cells has gained considerable attention because stem cells are believed to accumulate in the damaged sites and have the potential for the repair of damaged tissues. The aim of the work: was to assess the use of bone marrow transplantation in repair of damaged inner ear hair cells in rats after the damage had been inflicted by Amikacin injection. Material and Methods: Thirty albino rats were used in this study. They were divided into three groups. Each group ten rats. Group I: used as control. Group II: Were given Amikacin- intratympanic injection till complete loss of hearing function. This could be assessed by Distortion product Otoacoustic Emission (DPOAEs) and / or auditory brain stem evoked potential (ABR). GroupIII: were given intra-peritoneal injection of bone marrow stem cell after complete loss of hearing caused by Amikacin. Clinical assessment was done using DPOAEs and / or auditory brain stem evoked potential (ABR), before and after bone marrow injection. Histological assessment of the inner ear was done by light and electron microscope. Also, Detection of stem cells in the inner ear by immunohistochemistry. Results: Histological examination of the specimens showed promising improvement in the structure of cochlea that may be responsible for the improvement of hearing function in rats detected by DPOAEs and / or ABR. Conclusion: Bone marrow stem cells transplantation might be useful for the treatment of SNHL.

Keywords: amikacin, hair cells, sensorineural hearing loss, stem cells

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Authors: Noura Al-Ajmi, Mohammed A. Almulla

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With the increased utilization of technology devices around the world, healthcare and medical diagnosis are critical issues that people worry about these days. Doctors are doing their best to avoid any medical errors while diagnosing diseases and prescribing the wrong medication. Subsequently, artificial intelligence applications that can be installed on mobile devices such as rule-based expert systems facilitate the task of assisting doctors in several ways. Due to their many advantages, the usage of expert systems has increased recently in health sciences. This work presents a backward rule-based expert system that can be used for a headache diagnosis and medication recommendation system. The structure of the system consists of three main modules, namely the input unit, the processing unit, and the output unit.

Keywords: headache diagnosis system, prescription recommender system, expert system, backward rule-based system

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Authors: Ramanpreet Kaur, Upasana Sharma

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The purpose of this paper is to address the challenges facing the water supply for the Machine Learning Database (MLDB) system at the piston foundry plant. In the MLDB system, one main unit, i.e., robotic, is connected by two sub-units. The functioning of the system depends on the robotic and water supply. Lack of water supply causes system failure. The system operates at full capacity with the help of two sub-units. If one sub-unit fails, the system runs at a low capacity. Reliability modeling is performed using semi-Markov processes and regenerative point techniques. Several system effects such as mean time to system failure, availability at full capacity, availability at reduced capacity, busy period for repair and expected number of visits have been achieved. Benefits have been analyzed. The graphical study is designed for a specific case using programming in C++ and MS Excel.

Keywords: MLDB system, robotic, semi-Markov process, regenerative point technique

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Authors: Bo-Wei Song, Yun-Jung Lee

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This paper presents an intention interface and controller for a wire-driven heavy object lifting system that assists the operator with moving a heavy object. The handler is designed to allow a comfortable working posture for the operator. Plus, as a human assistive system, the operator is involved in the control loop, where a fuzzy control system is used to consider the human control characteristics. The effectiveness and performance of the proposed system are proved by experiments.

Keywords: fuzzy controller, handler design, heavy object lifting system, human-assistive device, human-in-the-loop system

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Authors: Burak Yildirim, Muhsin Tunay Gençoğlu

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A microgrid (MG) is a small power grid composed of localized medium or low level power generation, storage systems, and loads. In this paper, the effects of a MG on power systems voltage stability are shown. The MG model, designed to demonstrate the effects of the MG, was applied to the IEEE 14 bus power system which is widely used in power system stability studies. Eigenvalue and modal analysis methods were used in simulation studies. In the study results, it is seen that MGs affect system voltage stability positively by increasing system voltage instability limit value for buses of a power system in which MG are placed.

Keywords: eigenvalue analysis, microgrid, modal analysis, voltage stability

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Authors: Syed Auon Raza, Tahir Mahmood, Syed Basit Ali Bukhari

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In power system properly coordinated protection scheme is designed to make sure that only the faulty part of the system will be isolated when abnormal operating condition of the system will reach. The complexity of the system as well as the increased user demand and the deregulated environment enforce the utilities to improve system reliability by using a properly coordinated protection scheme. This paper presents overview of over current relay coordination techniques. Different techniques such as Deterministic Techniques, Meta Heuristic Optimization techniques, Hybrid Optimization Techniques, and Trial and Error Optimization Techniques have been reviewed in terms of method of their implementation, operation modes, nature of distribution system, and finally their advantages as well as the disadvantages.

Keywords: distribution system, relay coordination, optimization, Plug Setting Multiplier (PSM)

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Authors: Lanlan Xiao, Yang Liu, Shuo Chen, Bingmei Fu

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Most cancer-related deaths are due to metastasis. Metastasis is a complex, multistep processes including the detachment of cancer cells from the primary tumor and the migration to distant targeted organs through blood and/or lymphatic circulations. During hematogenous metastasis, the emigration of tumor cells from the blood stream through the vascular wall into the tissue involves arrest in the microvasculature, adhesion to the endothelial cells forming the microvessel wall and transmigration to the tissue through the endothelial barrier termed as extravasation. The narrow slit between endothelial cells that line the microvessel wall is the principal pathway for tumor cell extravasation to the surrounding tissue. To understand this crucial step for tumor hematogenous metastasis, we used Dissipative Particle Dynamics method to investigate an individual cell passing through a narrow slit numerically. The cell membrane was simulated by a spring-based network model which can separate the internal cytoplasm and surrounding fluid. The effects of the cell elasticity, cell shape and cell surface area increase, and slit size on the cell transmigration through the slit were investigated. Under a fixed driven force, the cell with higher elasticity can be elongated more and pass faster through the slit. When the slit width decreases to 2/3 of the cell diameter, the spherical cell becomes jammed despite reducing its elasticity modulus by 10 times. However, transforming the cell from a spherical to ellipsoidal shape and increasing the cell surface area only by 3% can enable the cell to pass the narrow slit. Therefore the cell shape and surface area increase play a more important role than the cell elasticity in cell passing through the narrow slit. In addition, the simulation results indicate that the cell migration velocity decreases during entry but increases during exit of the slit, which is qualitatively in agreement with the experimental observation.

Keywords: dissipative particle dynamics, deformability, surface area increase, cell migration

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Authors: Lawong Damian Bernsah

Abstract:

Neglected Tropical Diseases (NTDs) are most predominant among the poor and rural populations and are endemic in 149 countries. These diseases are the most prevalent and responsible for infecting 1.4 billion people worldwide. There are 17 neglected tropical diseases recognized by WHO that constitute the fourth largest disease health and economic burden of all communicable diseases. Five of these 17 diseases are considered for the cost analysis of this paper: lymphatic filariasis, onchocerciasis, trachoma, schistosomiasis, and soil transmitted helminth infections. WHO has proposed a roadmap for eradication and elimination by 2020 and treatments have been donated through the London Declaration by pharmaceutical manufacturers. The paper estimates the cost of NTD control programme and elimination for each NTD disease and total in Nigeria. This is necessary as it forms the bases upon which programme budget and expenditure could be based. Again, given the opportunity cost the resources for NTD face it is necessary to estimate the cost so as to provide bases for comparison. Cost of NTDs control and elimination programme is estimated using the population at risk for each NTD diseases and for the total. The population at risk is gotten from the national master plan for the 2015 - 2020, while the cost per person was gotten for similar studies conducted in similar settings and ranges from US$0.1 to US$0.5 for Mass Administration of Medicine (MAM) and between US$1 to US$1.5 for each NTD disease. The combined cost for all the NTDs was estimated to be US$634.88 million for the period 2015-2020 and US$1.9 billion for each NTD disease for the same period. For the purpose of sensitivity analysis and for robustness of the analysis the cost per person was varied and all were still high. Given that health expenditure for Nigeria (% of GDP) averages 3.5% for the period 1995-2014, it is very clear that efforts have to be made to improve allocation to the health sector in general which is hoped could trickle to NTDs control and elimination. Thus, the government and the donor partners would need to step-up budgetary allocation and also to be aware of the costs of NTD control and elimination programme since they have alternative uses. Key Words: Neglected Tropical Disease, Cost Analysis, NTD Programme Control and Elimination, Cost per Person

Keywords: Neglected Tropical Disease, Cost Analysis, Neglected Tropical Disease Programme Control and Elimination, Cost per Person

Procedia PDF Downloads 273

Authors: Oluwaponmile David Alao

Abstract:

Due to an increase in the death rate as a result of heart attack. There is need to develop a system that can be useful in the diagnosis of the disease at the medical centre. This system will help in preventing misdiagnosis that may occur from the medical practitioner or the physicians. In this research work, heart disease dataset obtained from UCI repository has been used to develop an intelligent prediction diagnosis system. The system is modeled on a feedforwad neural network and trained with back propagation neural network. A recognition rate of 86% is obtained from the testing of the network.

Keywords: heart disease, artificial neural network, diagnosis, prediction system

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Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

Abstract:

Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

Procedia PDF Downloads 394

Authors: Ayman M. Mansour

Abstract:

In this paper, we propose a multi-agent intelligent system that is used for monitoring the health conditions of elderly people. Monitoring the health condition of elderly people is a complex problem that involves different medical units and requires continuous monitoring. Such expert system is highly needed in rural areas because of inadequate number of available specialized physicians or nurses. Such monitoring must have autonomous interactions between these medical units in order to be effective. A multi-agent system is formed by a community of agents that exchange information and proactively help one another to achieve the goal of elderly monitoring. The agents in the developed system are equipped with intelligent decision maker that arms them with the rule-based reasoning capability that can assist the physicians in making decisions regarding the medical condition of elderly people.

Keywords: fuzzy logic, inference system, monitoring system, multi-agent system

Procedia PDF Downloads 607