Search results for: inflammation detection

Authors: M. Van 'T Hof, R. V. Pasma, J. T. Bailly, H. W. Hoek, W. A. Ester

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Background: The transition into primary school can be challenging for children with an autism spectrum disorder (ASD). Due to the new demands that are made to children in this period, their limitations in social functioning and school achievements may manifest and appear faster. Detection of possible ASD signals mainly takes place by parents, teachers and during obligatory municipal maternal and child health centre visits. Physicians of municipal maternal and child health centres have limited education and instruments to detect ASD. Further education on detecting ASD is needed to optimally equip these doctors for this task. Most research aims to increase the early detection of ASD in children aged 0-3 years and shows positive results. However, there is a lack of research on educational interventions to detect ASD in children aged 4-6 years by municipal maternal and child health physicians. Aim: The aim of this study is to explore the effect of the online educational intervention: Detection of ASD in children aged 4-6 years for municipal maternal and child health physicians. This educational intervention is developed within The Reach-Aut Academic Centre for Autism; Transitions in education, and will be available throughout The Netherlands. Methods: Ninety-two participants will follow the educational intervention: Detection of ASD in children aged 4-6 years for municipal maternal and child health centre physicians. The educational intervention consists of three, one and a half hour sessions, which are offered through an online interactive classroom. The focus and content of the course has been developed in collaboration with three groups of stakeholders; autism scientists, clinical practitioners (municipal maternal and child health doctors and ASD experts) and parents of children with ASD. The primary outcome measure is knowledge about ASD: signals, early detection, communication with parents and referrals. The secondary outcome measures are the number of ASD related referrals, the attitude towards the mentally ill (CAMI), perceived competency about ASD knowledge and detection skills, and satisfaction about the educational intervention. Results and Conclusion: The study started in January 2016 and data collection will end mid 2017.

Keywords: ASD, child, detection, educational intervention, physicians

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Authors: W. Ling, Mohamed Saufi Bin Awang

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Introduction: Mycobacterium tuberculosis post a major health problem worldwide. Central nervous system (CNS) infection by mycobacterium tuberculosis is one of the most devastating complications of tuberculosis. Although with advancement in medical fields, we are yet to understand the pathophysiology of how mycobacterium tuberculosis was able to cross the blood-brain barrier (BBB) and infect the CNS. CNS TB may present with nonspecific clinical symptoms which can mimic other diseases/conditions; this is what makes the diagnosis relatively difficult and challenging. Public health has to be informed and educated about the spread of TB, and early identification of TB is important as it is a curable disease. Case Report: A young 21-year-old Malay gentleman was initially presented to us with symptoms of ear discharge, tinnitus, and right-sided headache for the past one year. Further history reveals that the symptoms have been mismanaged and neglected over the period of 1 year. Initial investigation reveals features of inflammation of the ear. Further imaging showed the feature of chronic inflammation of the otitis media and atypical right cerebral abscess, which has the same characteristic features and consistency. He further underwent a biopsy, and results reveal positive Mycobacterium tuberculosis of the otitis media. With the results and the available imaging, we were certain that this is likely a case of disseminated tuberculosis causing CNS TB. Conclusion: We aim to highlight the challenge and difficult face in our health care system and public health in early identification and treatment.

Keywords: central nervous system tuberculosis, intracranial tuberculosis, tuberculous encephalopathy, tuberculous meningitis

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Authors: Elmongi Elbellili, Ben Lauwens, Daan Huybrechs

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The increasing complexity of modern engineering systems presents a challenge to the digital simulation of these systems which usually can be represented by differential equations. The Linearly Implicit Quantized State System (LIQSS) offers an alternative approach to traditional numerical integration techniques for solving Ordinary Differential Equations (ODEs). This method proved effective for handling discontinuous and large stiff systems. However, the inherent discrete nature of LIQSS may introduce oscillations that result in unnecessary computational steps. The current oscillation detection mechanism relies on a condition that checks the significance of the derivatives, but it could be further improved. This paper describes a different cycle detection mechanism and presents the outcomes using LIQSS order one in simulating the Advection Diffusion problem. The efficiency of this new cycle detection mechanism is verified by comparing the performance of the current solver against the new version as well as a reference solution using a Runge-Kutta method of order14.

Keywords: numerical integration, quantized state systems, ordinary differential equations, stiffness, cycle detection, simulation

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Authors: Kunal Das, Priya Sengupta, Abhishek K. Singh

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Pin assignment, scheduling, routing and error detection for arbitrary biochemical protocols in Digital Microfluidic Biochip have been reported in this paper. The research work is concentrating on pin assignment for 2 or 3 droplets routing in the arbitrary biochemical protocol, scheduling and routing in m × n biochip. The volumetric error arises due to droplet split in the biochip. The volumetric error detection is also addressed using biochip AND logic gate which is known as microfluidic AND or mAND gate. The algorithm for pin assignment for m × n biochip required m+n-1 numbers of pins. The basic principle of this algorithm is that no same pin will be allowed to be placed in the same column, same row and diagonal and adjacent cells. The same pin should be placed a distance apart such that interference becomes less. A case study also reported in this paper.

Keywords: digital microfludic biochip, cross-contamination, pin assignment, microfluidic AND gate

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Authors: Chun-Wei Huang, Jyh-Cherng Gu, Ming-Ta Yang

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Non-synchronous breakage or line failure in power systems with light or no loads can lead to core saturation in transformers or potential transformers. This can cause component and capacitance matching resulting in the formation of resonant circuits, which trigger ferroresonance. This study employed a wavelet transform for the detection of ferroresonance. Simulation results demonstrate the efficacy of the proposed method.

Keywords: ferroresonance, wavelet transform, intelligent electronic device, transformer

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Authors: Agampodi Promoda Perera, Yong Shin, Mi Kyoung Park

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The successful detection of pathogenic bacteria in blood provides important information for early detection, diagnosis and the prevention and treatment of infectious diseases. Silicon microring resonators are refractive-index-based optical biosensors that provide highly sensitive, label-free, real-time multiplexed detection of biomolecules. We demonstrate the technique of using GO (graphene oxide) to enhance the signal output of the silicon microring optical sensor. The activated carboxylic groups in GO molecules bind directly to single stranded DNA with an amino modified 5’ end. This conjugation amplifies the shift in resonant wavelength in a real-time manner. We designed a capture probe for strain Staphylococcus aureus of 21 bp and a longer complementary target sequence of 70 bp. The mismatched target sequence we used was of Streptococcus agalactiae of 70 bp. GO is added after the complementary binding of the probe and target. GO conjugates to the unbound single stranded segment of the target and increase the wavelength shift on the silicon microring resonator. Furthermore, our results show that GO could successfully differentiate between the mismatched DNA sequences from the complementary DNA sequence. Therefore, the proposed concept could effectively enhance sensitivity of pathogen detection sensors.

Keywords: label free biosensor, pathogenic bacteria, graphene oxide, diagnosis

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Authors: Hiranmoyee Das

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Aim. Due to late presentation and delayed diagnosis mortality rate of retinoblastoma is more than 50% in developing counties. So to facilitate the diagnosis, to decrease the disease and treatment burden and to increase the disease survival rate, an attempt was made for early diagnosis of Retinoblastoma by including fundus examination in routine immunization programs. Methods- A unique immunization card is followed in a tertiary health care center where examination of pupillary reflex is made mandatory in each visit of the child for routine immunization. In case of any abnormality, the child is referred to the ophthalmology department. Conclusion- Early detection is the key in the management of retinoblastoma. Every child is brought to the health care system at least five times before the age of 2 years for routine immunization. We should not miss this golden opportunity for early detection of retinoblastoma.

Keywords: retinoblastoma, immunization, unique, early

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Authors: Thanh Nga Thai

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A major issue in air transportation is in flight safety. Recent developments in control engineering have an attractive potential for resolving new issues related to guidance, navigation, and control of flying vehicles. Many future atmospheric missions will require increased on board autonomy including fault diagnosis and the subsequent control and guidance recovery actions. To improve designing system diagnostic, an efficient FDI- fault detection and identification- methodology is necessary to achieve. Contribute to characteristic of different faults in sensor and actuator in the view of mathematics brings a lot of profit in some condition changes in the system. This research finds some profit to reduce a trade-off to achieve between fault detection and performance of the closed loop system and cost and calculated in simulation.

Keywords: fault detection and identification, sensor faults, actuator faults, flight control system

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Authors: Zahow Muoftah

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Traditional manual visual grading of fruits has been one of the agricultural industry’s major challenges due to its laborious nature as well as inconsistency in the inspection and classification process. The main requirements for computer vision and visual processing are some effective techniques for identifying defects and estimating defect areas. Automated defect detection using computer vision and machine learning has emerged as a promising area of research with a high and direct impact on the visual inspection domain. Grading, sorting, and disease detection are important factors in determining the quality of fruits after harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have been conducted to identify diseases and pests that affect the fruits of agricultural crops. However, most previous studies concentrated solely on the diagnosis of a lesion or disease. This study focused on a comprehensive study to identify pests and diseases of apple and banana fruits using detection and classification defects on Banana and Apples by Computer Vision. As a result, the current article includes research from these domains as well. Finally, various pattern recognition techniques for detecting apple and banana defects are discussed.

Keywords: computer vision, banana, apple, detection, classification

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Authors: Agastya Pratap Singh

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This review paper examines the emerging applications of generative adversarial networks (GANs) in the fields of image recognition and anomaly detection. With the rapid growth of digital image data, the need for efficient and accurate methodologies to identify and classify images has become increasingly critical. GANs, known for their ability to generate realistic data, have gained significant attention for their potential to enhance traditional image recognition systems and improve anomaly detection performance. The paper systematically analyzes various GAN architectures and their modifications tailored for image recognition tasks, highlighting their strengths and limitations. Additionally, it delves into the effectiveness of GANs in detecting anomalies in diverse datasets, including medical imaging, industrial inspection, and surveillance. The review also discusses the challenges faced in training GANs, such as mode collapse and stability issues, and presents recent advancements aimed at overcoming these obstacles.

Keywords: generative adversarial networks, image recognition, anomaly detection, synthetic data generation, deep learning, computer vision, unsupervised learning, pattern recognition, model evaluation, machine learning applications

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: Sudkate Chaiyo, Weena Siangproh, Orawon Chailapakul, Kurt Kalcher

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In the present work, a simple and sensitive non-enzymatic electrochemical detection of glucose in disposable paper-based sensor was developed at ionic liquid/graphene/cobalt phthalocyanine composite (IL/G/CoPc) modified electrode. The morphology of the fabricated composite was characterized and confirmed by scanning electron microscopy and UV-Vis spectroscopy. The UV-Vis spectroscopy results confirmed that the G/CoPc composite formed via the strong π–π interaction between CoPc and G. Amperometric i-t technique was used for the determination of glucose. The response of glucose was linear over the concentration ranging from 10 µM to 1.5 mM. The response time of the sensor was found as 30 s with a limit of detection of 0.64 µM (S/N=3). The fabricated sensor also exhibited its good selectivity in the presence of common interfering species. In addition, the fabricated sensor exhibited its special advantages such as low working potential, good sensitivity along with good repeatability and reproducibility for the determination of glucose.

Keywords: glucose, paper-based sensor, ionic liquid/graphene/cobalt phthalocyanine composite, electrochemical detection

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Authors: S. Nasri, G. H. Amin, A. Azimi

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The use of herbs to treat disease is accompanied with the history of human life. This research is aimed to study the anti-inflammatory and antinociceptive effects of hydroalcoholic extract of aerial parts of "Tanacetum balsamita balsamita". In the experimental studies 144 male mice are used. In the inflammatory test, animals were divided into six groups: Control, positive control (receiving Dexamethason at dose of 15mg/kg), and four experimental groups receiving Tanacetum balsamita balsamita hydroalcoholic extract at doses of 25, 50, 100 and 200mg/kg. Xylene was used to induce inflammation. Formalin was used to study the nociceptive effects. Animals were divided into six groups: control group, positive control group (receiving morphine) and four experimental groups receiving Tanacetum balsamita balsamita (Tb.) hydroalcoholic extract at doses of 25, 50, 100 and 200mg/kg. I.p. injection of drugs or normal saline was performed 30 minutes before test. The data were analyzed by using one way Variance analysis and Tukey post-test. Aerial parts of Tanacetum balsamita balsamita hydroalcoholic extract decreased significantly inflammatory at dose of 200mg/kg (P<0/001) and caused a significant decrease and alleviated the nociception in both first and second phases at doses of 200mg/kg (p<0/001) and 100mg/kg (P<0/05). Tanacetum balsamita balsamita extract has the anti-inflammatory and anti-nociceptive effects which seems to be related with flavonoids especially Quercetin.

Keywords: inflammation, nociception, hydroalcoholic extract, aerial parts of Tanacetum balsamita balsamita L.

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Authors: Yu-Ling Tsai, Chih-Jung Chang, Chia-Chen Lu, Eric Wu, Chuan-Sheng Lin, Tzu-Lung Lin, Hsin-Chih Lai

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It is urgent that novel anti-obesity measures that are safe, effective and widely available are developed for counteracting the rapidly growing obesity epidemics. In the present study, we show that a probiotic bacterium Parabacteroides goldsteinii screened through culture under the high molecular weight polysaccharides prepared from two iconic medicinal fungi, the Ganoderma lucidum and the Hirsutella sinensis, reduced body weight by ca. 20% in high-fat diet (HFD)-fed mice. The bacterium also decreased intestinal permeability, metabolic endotoxemia, inflammation and insulin resistance. Notably, oral administration of live, but not high temperature-killed, P. goldsteinii to HFD fed mice considerably reduces weight gain and obesity-associated metabolic disorders. A three months feeding of the mice with P. goldsteinii did not show any aberrant side effects, indicating the safety of this bacterium. Transcriptome analysis indicated that P. goldsteinii enhances immunity in resting dendritic cells, but reduces inflammation in lipopolysaccharide (LPS)-induced dendritic cells. On top, Naïve T-cells were skewed towards regulatory T-cells after encountering with dendritic cells (DCs) pretreated with P. goldsteinii. These results indicated P. goldsteinii showed anti-inflammatory effects and can work as a potential probiotic ameliorating obesogenicity and related metabolic syndromes.

Keywords: Parabacteroides goldsteinii, gut microbiome, obesity, immune modulation

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Authors: Grishma D. Solanki, Karshan Kandoriya

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In modern era of information age, digitalization has revolutionized like never before. Powerful computers, advanced photo editing software packages and high resolution capturing devices have made manipulation of digital images incredibly easy. As per as image forensics concerns, one of the most actively researched area are detection of copy move forgeries. Higher computational complexity is one of the major component of existing techniques to detect such tampering. Moreover, copy move forgery is usually performed in three steps. First, copying of a region in an image then pasting the same one in the same respective image and finally doing some post-processing like rotation, scaling, shift, noise, etc. Consequently, pseudo Zernike moment is used as a features extraction method for matching image blocks and as a primary factor on which performance of detection algorithms depends.

Keywords: copy-move image forgery, digital forensics, image forensics, image forgery

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Authors: Shwu-Ling Peng, Chiung-Man Tsai, Chia-Jui Weng

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Chronic micro-inflammation is a hallmark of many aging-related neurodegenerative and metabolic syndrome-driven diseases. In high glucose (HG) environment, reactive oxygen species (ROS) is generated and the ROS induced inflammation, cytokines secretion, DNA damage, and cell cycle arrest to lead to cellular senescence. Water chestnut shell (WCS) is a plant hull which containing polyphenolic compounds and showed antioxidant and anticancer activities. Orchid, which containing a natural polysaccharide compound, possesses many physiological activities including anti-inflammatory and neuroprotective effects. These agricultural plants might be able to reduce oxidative stress and inflammation. This study was used HG-induced human normal dermal fibroblasts (HG-HNDFs) as an in vitro model to disclose the effects of water extract of Phalaenopsis orchid flower (WEPF) and ethanol extract of water chestnut shell (EEWCS) on the anti-aging and their underlying molecular mechanisms. The toxicity of extracts on human normal dermal fibroblasts (HNDFs) was determined by MTT method. The senescence of cells was assayed by β-galactosidase (SA-β-gal) kit. ROS and nitrate production was analyzed by Intracellular ROS contents and ELISA, respectively. Western blotting was used to detect the proteins in cells. The results showed that the exposure of HNDFs to HG (30 mM) for 72 h were caused cellular senescence and arrested cells at G0/G1 phase. Indeed, the treatment of HG-HNDFs with WEPF (200 μg/ml) and EEWCS (10 μg/ml) significantly released cell cycle arrest and promoted cell proliferation. The G1/S phase transition regulatory proteins such as protein retinoblastoma (pRb), p53, and p16ᴵᴺᴷ⁴ᵃ depressed by WEPF and EEWCS were also observed. Additionally, the treatment of WEPF and EEWCS increased the activity of HO-1 through upregulating Nrf2 as well as decreased the ROS and NO of HG-HNDFs. Therefore, the senescence marker protein-30 (SMP30) in cells was diminished. In conclusion, the WEPF and EEWCS might inhibit HG-induced aging of HNDFs by reducing oxidative stress and free radicals.

Keywords: agricultural plant extract, anti-aging, high glucose, Phalaenopsis orchid flower, water chestnut shell

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Authors: Ng Liang Shen, Hau Yuan Wen

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Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.

Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS

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Authors: Sadia Munir

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Preeclampsia is the contributor to the worldwide maternal mortality of approximately 100,000 deaths a year. It complicates about 10% of all pregnancies and is the first cause of maternal admission to intensive care units. Predicting preeclampsia is a major challenge in obstetrics. More importantly, no major progress has been achieved in the treatment of preeclampsia. As placenta is the main cause of the disease, the only way to treat the disease is to extract placental and deliver the baby. In developed countries, the cost of an average case of preeclampsia is estimated at £9000. Interestingly, preeclampsia may have an impact on the health of mother or infant, beyond the pregnancy. We performed a systematic search of PubMed including the combination of terms such as preeclampsia, biomarkers, treatment, hypoxia, inflammation, oxidative stress, vascular endothelial growth factor A, activin A, inhibin A, placental growth factor, transforming growth factor β-1, Nodal, placenta, trophoblast cells, microRNAs. In this review, we have summarized current knowledge on the identification of potential biomarkers for the diagnosis of preeclampsia. Although these studies show promising data in early diagnosis of preeclampsia, the current value of these factors as biomarkers, for the precise prediction of preeclampsia, has its limitation. Therefore, future studies need to be done to support some of the very promising and interesting data to develop affordable and widely available tests for early detection and treatment of preeclampsia.

Keywords: activin, biomarkers, growth factors, miroRNA

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Authors: Abbassi Daloii Asieh, Yazdani Hoda

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Background and Objective: evidence supports systemic inflammation in obesity and insulin resistance. Apelin that is secreted by adipose tissue plays an important role in the inflammation process and appear act as an anti-inflammatory cytokines. The aim of this study was the effect of eight weeks aerobic training and nitro-L-arginine-methyl ester (L-NAME) on plasma apelin in male’s rats. Materials and Methods: For this purpose, 24 male Wistar rats aged 20 months were randomly assigned into four groups: Control, training, training and L-NAME and L-NAME. Training intervention was eight weeks aerobic exercise (5 time/weekly) at 75-80 (%) of maximal oxygen consumption. All rats were killed 72 hours after lasted exercise session; blood samples collected and plasma were stored. Data was analyzed by one way ANOVA and Tucky Test. A p value less than 0.05 was considered statistically signigcant. Results: The results showed that after eight weeks of endurance training exercise Apelin plasma compared to the control group did not change significantly. Also, the results showed that there was significant difference in plasma Apelin between groups(P > 0/05). Also, the results showed no significant difference between the insulin levels and glucose of four groups (P > 0/05). Conclusion: It seems that aerobic exercise plasma Apelin levels in male rats is not affected. On the other hand, nitric oxide inhibitors can reduce levels of plasma Apelin.

Keywords: aerobic training, L-NAME, plasma Apelin, male’s rats

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Authors: Hatem Hajri, Mohamed-Cherif Rahal

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Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on obstacles velocities and less precise on their positions. Sensor fusion between Lidar and Radar aims at improving obstacle detection using advantages of the two sensors. The present paper proposes a real-time Lidar/Radar data fusion algorithm for obstacle detection and tracking based on the global nearest neighbour standard filter (GNN). This algorithm is implemented and embedded in an automative vehicle as a component generated by a real-time multisensor software. The benefits of data fusion comparing with the use of a single sensor are illustrated through several tracking scenarios (on a highway and on a bend) and using real-time kinematic sensors mounted on the ego and tracked vehicles as a ground truth.

Keywords: ground truth, Hungarian algorithm, lidar Radar data fusion, global nearest neighbor filter

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Authors: Chao Yu, Qing-Guo Wang, Dan Zhang

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The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low-rank, sparse matrices and further recast as a semidefinite programming (SDP) problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered “clean” data from the proposed method can give much better parameter estimation compared with that based on the raw data.

Keywords: outlier detection, system identification, matrix decomposition, low-rank matrix, sparsity, semidefinite programming, interior-point methods, denoising

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: ring recognition, edge detection, X-ray computed tomography, dendrochronology

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Authors: Benedict Ofori, Kwabena Sarpong, Stephen Antwi

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Background: Medicinal plants are utilized all around the world and are becoming increasingly important economically. The WHO notes that ‘inappropriate use of traditional medicines or practices can have negative or dangerous effects and that future research is needed to ascertain the efficacy and safety of such practices and medicinal plants used by traditional medicine systems. The poor around the world have limited access to palliative care or pain relief. Pharmacologists have been focused on developing safe and effective anti-inflammatory drugs. Most of the issues related to their use have been linked to the fact that numerous traditional and herbal treatments are classified in different nations as meals or dietary supplements. As a result, there is no need for evidence of the quality, efficacy, or safety of these herbal formulations before they are marketed. The fact that access to drugs meant for pain relief is limited in low-income countries means advanced studies should be done on home drugs meant for inflammation to close the gap. Methods: The ethanolic extracts of the plant were screened for the presence of 10 phytochemicals. The Pierce BCA Protein Assay Kit was used for the determination of the protein concentration of the egg white. The rats were randomly selected and put in 6 groups. The egg white was sub-plantar injected into the right-hand paws of the rats to induce inflammation. The animals were treated with the three plant extracts obtained from the root bark, stem, and leaves of the plant. The control groups were treated with normal saline, while the standard groups were treated with standard drugs indomethacin and celecoxib. Plethysmometer was used to measure the change in paw volume of the animals over the course of the experiment. Results: The results of the phytochemical screening revealed the presence of reducing sugars and saponins. Alkaloids were present in only R.L.S (1:1:1), and phytosterols were found in R.L(1:1) and R.L.S (1:1:1). The estimated protein concentration was found to be 103.75 mg/ml. The control group had an observable increase in paw volume, which indicated that inflammation was induced during the 5 hours. The increase in paw volume for the control group peaked at the 1st hour and decreased gradually throughout the experiment, with minimal changes in the paw volumes. The 2nd and 3rd groups were treated with 20 mg/kg of indomethacin and celecoxib. The anti-inflammatory activities of indomethacin and celecoxib were calculated to be 21.4% and 4.28%, respectively. The remaining 3 groups were treated with 2 dose levels of 200mg/kg plant extracts. R.L.S, R.L, and S.R.L had anti-inflammatory activities of 22.3%, 8.2%, and 12.07%, respectively. Conclusions: Egg albumin-induced paw model in rats can be used to evaluate the anti-inflammatory activity of herbs that might have potential anti-inflammatory activity. Herbal medications have potential anti-inflammatory activities and can be used to manage various inflammatory conditions if their efficacy and side effects are well studied. The three extracts all possessed anti-inflammatory activity, with R.L.S having the highest anti-inflammatory activity.

Keywords: inflammation, capparis erythrocarpos, anti-inflammatory activity, herbal medicine, paw volume, egg albumin

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Authors: Seyed Sadegh Naseralavi

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This paper presents a Kernel parallelization equation for damage identification in structures under unknown periodic excitations. Herein, the dynamic differential equation of the motion of structure is viewed as a mapping from displacements to external forces. Utilizing this viewpoint, a new method for damage detection in structures under periodic loads is presented. The developed method requires only two periods of load. The method detects the damages without finding the input loads. The method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering the concept, kernel parallelization equation (KPE) is derived for damage detection under unknown periodic loads. The method is verified for a case study under periodic loads.

Keywords: Kernel, unknown periodic load, damage detection, Kernel parallelization equation

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Authors: O. I. Papagianni, P. Potsaki, K. Almpounioti, D. Chatzicharalampous, A. Voutsa, O. Katira, A. Michalaki, H. C. Karantonis, A. E. Koutelidakis

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High intakes of carbohydrates and fats have been associated with an increased risk of chronic diseases due to the role of postprandial oxidative stress. This pilot nutritional intervention aimed to examine the acute effect of consuming two different types of breadsticks prepared from durum wheat flour mixtures differing in total phenolic content on postprandial inflammatory and oxidant responses in healthy volunteers. A cross-over, controlled, and single-blind clinical trial was designed, and two isocaloric high-fat and high-carbohydrate meals were tested. Serum total, HDL- and LDL-cholesterol, triglycerides, glucose, CRP, uric acid, plasma total antioxidant capacity, and antiplatelet activity were determined in fasting and 30, 60, and 120 min after consumption. The results showed a better postprandial HDL-cholesterol and total antioxidant activity response in the intervention group. The choice of durum wheat flours with higher phenolic content and antioxidant activity is presented as promising for human health, and clinical studies will expand to draw safer conclusions.

Keywords: breadsticks, durum wheat flours, postprandial inflammation, postprandial oxidative stress, ex vivo antiplatelet activity

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Authors: N. Nalini, Lokesh B. Bhajantri

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In Distributed Sensor Networks, the sensor nodes are prone to failure due to energy depletion and some other reasons. In this regard, fault tolerance of network is essential in distributed sensor environment. Energy efficiency, network or topology control and fault-tolerance are the most important issues in the development of next-generation Distributed Sensor Networks (DSNs). This paper proposes a node fault detection and recovery using Genetic Algorithm (GA) in DSN when some of the sensor nodes are faulty. The main objective of this work is to provide fault tolerance mechanism which is energy efficient and responsive to network using GA, which is used to detect the faulty nodes in the network based on the energy depletion of node and link failure between nodes. The proposed fault detection model is used to detect faults at node level and network level faults (link failure and packet error). Finally, the performance parameters for the proposed scheme are evaluated.

Keywords: distributed sensor networks, genetic algorithm, fault detection and recovery, information technology

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Authors: C. P. Providakis, G. M. Angeli, M. J. Favvata, N. A. Papadopoulos, C. E. Chalioris, C. G. Karayannis

Abstract:

An effort for the detection of damages in the reinforcement bars of reinforced concrete members using PZTs is presented. The damage can be the result of excessive elongation of the steel bar due to steel yielding or due to local steel corrosion. In both cases the damage is simulated by considering reduced diameter of the rebar along the damaged part of its length. An integration approach based on both electromechanical admittance methodology and guided wave propagation technique is used to evaluate the artificial damage on the examined longitudinal steel bar. Two actuator PZTs and a sensor PZT are considered to be bonded on the examined steel bar. The admittance of the Sensor PZT is calculated using COMSOL 3.4a. Fast Furrier Transformation for a better evaluation of the results is employed. An effort for the quantification of the damage detection using the root mean square deviation (RMSD) between the healthy condition and damage state of the sensor PZT is attempted. The numerical value of the RSMD yields a level for the difference between the healthy and the damaged admittance computation indicating this way the presence of damage in the structure. Experimental measurements are also presented.

Keywords: concrete reinforcement, damage detection, electromechanical admittance, experimental measurements, finite element method, guided waves, PZT

Procedia PDF Downloads 251

Authors: Deepak Mohan, Sushma Sharma, Mohammad Asif

Abstract:

Diclofenac sodium being one of the most common non-steroidal anti-inflammatory drugs is normally used as painkiller and to reduce inflammation. The drug is known to alter the enzymatic activities of acid and alkaline phosphatase, glutamate oxaloacetate transaminase and glutamate pyruvate transaminases. The drug also results in change in the concentration of proteins and lipids in the body. The present study is an attempt to study different biochemical changes electrophoretically due to administration of different doses of diclofenac (4mg/kg/body weight and 14mg/kg/body weight) on liver and testes of mice from 7-28 days of investigation. Homogenization of the tissue was done, supernatant separated was loaded in the gel and native polyacrylamide gel electrophoresis was conducted. Diclofenac administration resulted in alterations of all these biochemical parameters which were observed in native polyacrylamide gel electrophoretic studies. The severe degenerative changes as observed during later stages of the experiment showed correlation with increase or decrease in the activities of all the enzymes studied in the present investigation. Image analysis of gel in liver showed a decline of 7.4 and 5.3 % in low and high dose group after 7 days whereas a decline of 9.6 and 7.5% was registered after 28 days of investigation. Similar analysis for testis also showed an appreciable decline in the activity of alkaline phosphatase after 28 days. Gel analysis of serum was also performed to find a correlation in the enzymatic activities between the tissue and blood.

Keywords: diclofenac, inflammation, polyacrylamide, phosphatase

Procedia PDF Downloads 146

Authors: C. P. Providakis, G. M. Angeli, M. J. Favvata, N. A. Papadopoulos, C. E. Chalioris, C. G. Karayannis

Abstract:

An effort for the detection of damages in the reinforcement bars of reinforced concrete members using PZTs is presented. The damage can be the result of excessive elongation of the steel bar due to steel yielding or due to local steel corrosion. In both cases the damage is simulated by considering reduced diameter of the rebar along the damaged part of its length. An integration approach based on both electro-mechanical admittance methodology and guided wave propagation technique is used to evaluate the artificial damage on the examined longitudinal steel bar. Two actuator PZTs and a sensor PZT are considered to be bonded on the examined steel bar. The admittance of the Sensor PZT is calculated using COMSOL 3.4a. Fast Furrier Transformation for a better evaluation of the results is employed. An effort for the quantification of the damage detection using the root mean square deviation (RMSD) between the healthy condition and damage state of the sensor PZT is attempted. The numerical value of the RSMD yields a level for the difference between the healthy and the damaged admittance computation indicating this way the presence of damage in the structure. Experimental measurements are also presented.

Keywords: concrete reinforcement, damage detection, electromechanical admittance, experimental measurements, finite element method, guided waves, PZT

Procedia PDF Downloads 288

Authors: Chia-Yen Lee, Hao-Jen Wang, Jhih-Hao Lai

Abstract:

In recent years, infrared (IR) imaging has been considered as a potential tool to assess the efficacy of chemotherapy and early detection of breast cancer. Regions of tumor growth with high metabolic rate and angiogenesis phenomenon lead to the high temperatures. Observation of differences between the heat maps in long term is useful to help assess the growth of breast cancer cells and detect breast cancer earlier, wherein the multi-time infrared image alignment technology is a necessary step. Representative feature points detection and matching are essential steps toward the good performance of image registration and quantitative analysis. However, there is no clear boundary on the infrared images and the subject's posture are different for each shot. It cannot adhesive markers on a body surface for a very long period, and it is hard to find anatomic fiducial markers on a body surface. In other words, it’s difficult to detect and match features in an IR sequence images. In this study, automated feature detection and matching algorithms with two type of automatic feature points (i.e., vascular branch points and modified Harris corner) are developed respectively. The preliminary results show that the proposed method could identify the representative feature points on the IR breast images successfully of 98% accuracy and the matching results of 93% accuracy.

Keywords: Harris corner, infrared image, feature detection, registration, matching

Procedia PDF Downloads 299