Search results for: robust diagnosis

Authors: Angelis P. Barlampas

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Theoretical background Disorders of fixation and rotation of the large intestine, result in the existence of its parts in ectopic anatomical positions. In case of symptomatology, the clinical picture is complicated by the possible symptomatology of the neighboring anatomical structures and a differential diagnostic problem arises. Target The purpose of this work is to demonstrate the difficulty of revealing the real cause of abdominal pain, in cases of anatomical variants and the decisive contribution of imaging and especially that of computed tomography. Methods A patient came to the emergency room, because of acute pain in the right hypochondrium. Clinical examination revealed tenderness in the gallbladder area and a positive Murphy's sign. An ultrasound exam depicted a normal gallbladder and the patient was referred for a CT scan. Results Flexible, unfixed ascending colon and cecum, located in the anatomical region of the right mesentery. Opacities of the surrounding peritoneal fat and a small linear concentration of fluid can be seen. There was an appendix of normal anteroposterior diameter with the presence of air in its lumen and without clear signs of inflammation. There was an impression of possible inflammatory swelling at the base of the appendix, (DD phenomenon of partial volume; e.t.c.). Linear opacities of the peritoneal fat in the region of the second loop of the duodenum. Multiple diverticula throughout the colon. Differential Diagnosis The differential diagnosis includes the following: Inflammation of the base of the appendix, diverticulitis of the cecum-ascending colon, a rare case of second duodenal loop ulcer, tuberculosis, terminal ileitis, pancreatitis, torsion of unfixed cecum-ascending colon, embolism or thrombosis of a vascular intestinal branch. Final Diagnosis There is an unfixed cecum-ascending colon, which is exhibiting diverticulitis.

Keywords: unfixed cecum-ascending colon, abdominal pain, malrotation, abdominal CT, congenital anomalies

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Authors: Jian Shi, Baoguo Yu, Haonan Jia, Meng Liu, Ping Huang

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Adapting to the flexibility of war, a large number of guided weapons launch from aircraft. Therefore, the inertial navigation system loaded in the weapon needs to undergo an alignment process in the air. This article proposes the following methods to the problem of inaccurate modeling of the system under large misalignment angles, the accuracy reduction of filtering caused by outliers, and the noise changes in GPS signals: first, considering the large misalignment errors of Strapdown Inertial Navigation System (SINS)/GPS, a more accurate model is made rather than to make a small-angle approximation, and the Unscented Kalman Filter (UKF) algorithms are used to estimate the state; then, taking into account the impact of GPS noise changes on the fine alignment algorithm, the innovation adaptive filtering algorithm is introduced to estimate the GPS’s noise in real-time; at the same time, in order to improve the anti-interference ability of the air fine alignment algorithm, a robust filtering algorithm based on outlier detection is combined with the air fine alignment algorithm to improve the robustness of the algorithm. The algorithm can improve the alignment accuracy and robustness under interference conditions, which is verified by simulation.

Keywords: air alignment, fine alignment, inertial navigation system, integrated navigation system, UKF

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Authors: Babina Aryal

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Background: The diagnosis of pancreatitis is generally based on clinical and laboratory findings; however, Computed Tomography (CT) is an imaging technique of choice specially Contrast Enhanced Computed Tomography (CECT) shows morphological characteristic findings that allow for establishing the diagnosis of pancreatitis and determining the extent of disease severity which is done along with the administration of appropriate contrast medium. The purpose of this study was to compare Computed Tomography Dose Index (CTDI), Dose Length Product (DLP) and Effective Dose (ED) among male and female patients from Contrast Enhanced Computed Tomography (CECT) Pancreatitis Protocol. Methods: This retrospective study involved data collection based on clinical/laboratory/ultrasonography diagnosis of Pancreatitis and has undergone CECT Abdomen pancreatitis protocol. data collection involved detailed information about a patient's Age and Gender, Clinical history, Individual Computed Tomography Dose Index and Dose Length Product and effective dose. Results: We have retrospectively collected dose data from 150 among which 127 were males and 23 were females. The values obtained from the display of the CT screen were measured, calculated and compared to determine whether the CTDI, DLP and ED values were similar or not. CTDI for females was more as compared to males. The differences in CTDI values for females and males were 32.2087 and 37.1609 respectively. DLP values and Effective dose for both the genders did not show significant differences. Conclusion: This study concluded that there were no more significant changes in the DLP and ED values among both the genders however we noticed that female patients had more CTDI than males.

Keywords: computed tomography, contrast enhanced computed tomography, computed tomography dose index, dose length product, effective dose

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Authors: T. S. Sowmya Bhaskaran, Shekhar Seshadri

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This study aims to study the clinical features of with a history of Child Sexual Abuse (CSA). A chart review of 40 children (<16 years) with history of CSA evaluated at the Department of Child and Adolescent Psychiatry of NIMHANS during a two year period was performed. Results:The most common form of abuse was contact penetrative abuse (65%) followed by non-contact penetrative abuse (32.5%). 75% (N=30) had a psychiatric diagnosis at baseline. 50% of these children had one or more psychiatric comorbidities. Anxiety disorder was the most common diagnosis (27.5%) which included PTSD (11%) followed by Depressive disorder (25.2%). Children abused by multiple perpetrators were found to be more likely to have depression, to having a comorbid psychiatric disorder and more prone to exhibit sexualized behaviour. Children who also experienced physical violence at home were more likely to develop psychiatric illness following child sexual abuse. Psychiatric morbidity is high in clinic population of children with history of CSA. It is important to increase the awareness regarding the consequences of CSA in order to increase help seeking.

Keywords: child sexual abuse, India, tertiary care centre, clinical characteristics

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Authors: Haoqi Gao, Koichi Ogawara

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Retinal vascular segmentation of color fundus is the basis of ophthalmic computer-aided diagnosis and large-scale disease screening systems. Early screening of fundus diseases has great value for clinical medical diagnosis. The traditional methods depend on the experience of the doctor, which is time-consuming, labor-intensive, and inefficient. Furthermore, medical images are scarce and fraught with legal concerns regarding patient privacy. In this paper, we propose a new Generative Adversarial Network based on CycleGAN for retinal fundus images. This method can generate not only synthetic fundus images but also generate corresponding segmentation masks, which has certain application value and challenge in computer vision and computer graphics. In the results, we evaluate our proposed method from both quantitative and qualitative. For generated segmented images, our method achieves dice coefficient of 0.81 and PR of 0.89 on DRIVE dataset. For generated synthetic fundus images, we use ”Toy Experiment” to verify the state-of-the-art performance of our method.

Keywords: retinal vascular segmentations, generative ad-versarial network, cyclegan, fundus images

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: M. Naeimi, H. Aghazadeh, E. Afjei, A. Siadatan

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In this paper, a novel view of air gap magnetic field analysis of synchronous reluctance motor and permanent magnet assisted synchronous reluctance motor under static eccentricity to provide the precise fault diagnosis based on three-dimensional finite element method is presented. Analytical nature of this method makes it possible to simulate reliable and precise model by considering the end effects and axial fringing effects. The results of the three-dimensional finite element analysis of synchronous reluctance motor and permanent magnet synchronous reluctance motor such as flux linkage, flux density, and compression both of SynRM and PM-SynRM for various eccentric motor conditions are obtained and analyzed. These results present useful information regarding to the detection of static eccentricity.

Keywords: synchronous reluctance motor (SynRM), permanent magnet assisted synchronous reluctance motor (PMaSynRM), finite element method, static eccentricity, fault analysis

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Authors: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee

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Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.

Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis

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Authors: Jasmine Latiolais

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Much of the disaster-related literature finds a positive relationship between the impact of a natural disaster and the growth of wages. Panel datasets are often used to explore these effects. However, natural disasters do not impact a single variable in the economy. Rather, natural disasters affect all facets of the economy, simultaneously, upon impact. It is difficult to control for all factors that would be influenced by the impact of a natural disaster, which can lead to lead to omitted variable bias in those studies employing panel datasets. To address this issue of omitted variable bias, an interrupted time series analysis is used to test the short-run relationship between the impact of Hurricanes Katrina and Rita on parish wage levels in Southern Louisiana, inherently controlling for economic conditions. This study provides evidence that natural disasters do increase wages in the very short term (one quarter following the impact of the hurricane) but that these results are not seen in the longer term and are not robust. In addition, the significance of the coefficients changes depending on the parish. Overall, this study finds that previous literature on this topic may not be robust when considered through a time-series lens.

Keywords: economic recovery, local economies, local wage growth, natural disasters

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Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: M. Bilal Ishfaq, Adnan N. Qureshi

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COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.

Keywords: COVID-19, feature engineering, artificial neural networks, radiology images

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Authors: S. Saju, G. Thirugnanam

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In this paper, a medical image watermarking algorithm based on contourlet is proposed. Medical image watermarking is a special subcategory of image watermarking in the sense that images have special requirements. Watermarked medical images should not differ perceptually from their original counterparts because clinical reading of images must not be affected. Watermarking techniques based on wavelet transform are reported in many literatures but robustness and security using contourlet are better when compared to wavelet transform. The main challenge in exploring geometry in images comes from the discrete nature of the data. In this paper, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image. To extract the watermark, Kernel ICA is used and it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that proposed scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with Discrete Wavelet Transform (DWT) to prove the robustness of the scheme. Simulations are carried out using Matlab Software.

Keywords: digital watermarking, independent component analysis, wavelet transform, contourlet

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Authors: T. Bensana, S. Mekhilef

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The methodology of vibration based condition monitoring technology has been developing at a rapid stage in the recent years suiting to the maintenance of sophisticated and complicated machines. The ability of wavelet analysis to efficiently detect non-stationary, non-periodic, transient features of the vibration signal makes it a demanding tool for condition monitoring. This paper presents a methodology for fault diagnosis of rolling element bearings based on wavelet envelope power spectrum technique is analysed in both the time and frequency domains. In the time domain the auto-correlation of the wavelet de-noised signal is applied to evaluate the period of the fault pulses. However, in the frequency domain the wavelet envelope power spectrum has been used to identify the fault frequencies with the single sided complex Laplace wavelet as the mother wavelet function. Results show the superiority of the proposed method and its effectiveness in extracting fault features from the raw vibration signal.

Keywords: preventive maintenance, fault diagnostics, rolling element bearings, wavelet de-noising

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Authors: Gabrielle Veloso, Melanie Porter, Kelsie Boulton, Adam Guastella

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The aim of the current systematic review was to examine child and parent factors and their associations with parent sensitivity towards children with Autism Spectrum Disorder (ASD). Eight bibliographic databases were used to identify peer-reviewed journal articles examining these associations via quantitative analyses, with parent sensitivity measured via validated and reliable observation coding systems. Thirty-one studies were finalized as having met full criteria for inclusion. The review found agreement across studies that parent sensitivity was positively associated with the child’s initiations and responsiveness toward their parent, with more frequent parent-directed behaviors providing greater opportunity for parents to act and react in sensitive manner. There was also substantial evidence that parent sensitivity predicted later growth in child language ability and child social skills. Other factors such as child attachment, parent insightfulness toward their child, and parent resolution of the diagnosis were also identified across a number of studies as being positively associated with parent sensitivity, however, interpretations of these findings were limited by the absence of covariates identified in the literature as explaining much of the variance in parent sensitivity. With respect to non-significant associations, the literature reliably found that parents showed sensitivity toward their child with ASD, regardless of child age, ASD symptomology, concurrent child social skills, and concurrent child cognitive abilities. The robust associations found in this review and their potential explanations can serve as a jump off point in identifying an understanding protective and risk factors for families of children with ASD. With regard to future directions in research, assessment of the studies’ methodological quality identified points for improvement with respect to the measurement of parent sensitivity, as well as the consideration of several important methodological confounds that may be controlled for in statistical analyses.

Keywords: ASD, autism, parenting, parent sensitivity

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Authors: Eda Jazexhiu-Postoli, Gladiola Hoxha, Ada Simeoni, Sonila Biba

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Background Neonatal hypotonia represents a commonly encountered issue in the Neonatal Intensive Care Unit and newborn nursery. The differential diagnosis is broad, encompassing chromosome abnormalities, primary muscular dystrophies, neuropathies and inborn errors of metabolism. Aim of study Our study describes some of the main clinical features of hypotonia in newborns and presents clinical cases of neonatal hypotonia we treated in our Neonatal unit in the last 3 years. Case reports Four neonates born in our hospital presented with hypotonia after birth, one preterm newborn 35-36 weeks of gestational age and three other term newborns (38-39 weeks of gestational age). Prenatal data revealed a decrease in fetal movements in both cases. Intrapartum meconium-stained amniotic fluid was found in 75% of our hypotonic newborns. Clinical features included inability to establish effective respiratory movements and need for resuscitation in the delivery room, respiratory distress syndrome, feeding difficulties and need for oro-gastric tube feeding, dysmorphic features, hoarse voice and moderate to severe muscular hypotonia. The genetic workup revealed the diagnosis of Autosomal Recessive Congenital Myasthenic Syndrome 1-B, Sotos Syndrome, Spinal Muscular Atrophy Type 1 and Transient Hypotonia of the Newborn. Two out of four hypotonic neonates were transferred to the Pediatric Intensive Care Unit and died at the age of three to five months old. Conclusion Hypotonia is a concerning finding in neonatal care and it is suggested by decreased intrauterine fetal movements, failure to establish first breaths, respiratory distress and feeding difficulties in the neonate. Prognosis is determined by its etiology and time of diagnosis and intervention.

Keywords: hypotonic neonate, respiratory distress, feeding difficulties, fetal movements

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Authors: Geir Kirkebøen

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Most patients with serious diagnoses want to know their prognosis, in particular their expected survival time. As part of the informed consent process, physicians are legally obligated to communicate such information to patients. However, there is no established (evidence based) ‘best practice’ for how to do this. The two questions explored in this study are: How do physicians communicate expected survival time to patients, and how should it be done? We explored the first, descriptive question in a study with Norwegian oncologists as participants. The study had a scenario and a survey part. In the scenario part, the doctors should imagine that a patient, recently diagnosed with a serious cancer diagnosis, has asked them: ‘How long can I expect to live with such a diagnosis? I want an honest answer from you!’ The doctors should assume that the diagnosis is certain, and that from an extensive recent study they had optimal statistical knowledge, described in detail as a right-skewed survival curve, about how long such patients with this kind of diagnosis could be expected to live. The main finding was that very few of the oncologists would explain to the patient the variation in survival time as described by the survival curve. The majority would not give the patient an answer at all. Of those who gave an answer, the typical answer was that survival time varies a lot, that it is hard to say in a specific case, that we will come back to it later etc. The survey part of the study clearly indicates that the main reason why the oncologists would not deliver the mortality prognosis was discomfort with its uncertainty. The scenario part of the study confirmed this finding. The majority of the oncologists explicitly used the uncertainty, the variation in survival time, as a reason to not give the patient an answer. Many studies show that patients want realistic information about their mortality prognosis, and that they should be given hope. The question then is how to communicate the uncertainty of the prognosis in a realistic and optimistic – hopeful – way. Based on psychological research, our hypothesis is that the best way to do this is by explicitly describing the variation in survival time, the (usually) right skewed survival curve of the prognosis, and emphasize to the patient the (small) possibility of being a ‘lucky outlier’. We tested this hypothesis in two scenario studies with lay people as participants. The data clearly show that people prefer to receive expected survival time as a median value together with explicit information about the survival curve’s right skewedness (e.g., concrete examples of ‘positive outliers’), and that communicating expected survival time this way not only provides people with hope, but also gives them a more realistic understanding compared with the typical way expected survival time is communicated. Our data indicate that it is not the existence of the uncertainty regarding the mortality prognosis that is the problem for patients, but how this uncertainty is, or is not, communicated and explained.

Keywords: cancer patients, decision psychology, doctor-patient communication, mortality prognosis

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Authors: Yassa Nacera, Badji Abderrezak, Saidoune Abdelmalek, Houassine Hamza

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Several kinds of faults can occur in a permanent magnet synchronous machine (PMSM) systems: bearing faults, electrically short/open faults, eccentricity faults, and demagnetization faults. Demagnetization fault means that the strengths of permanent magnets (PM) in PMSM decrease, and it causes low output torque, which is undesirable for EVs. The fault is caused by physical damage, high-temperature stress, inverse magnetic field, and aging. Motor current signature analysis (MCSA) is a conventional motor fault detection method based on the extraction of signal features from stator current. a simulation model of the PMSM under partial demagnetization and uniform demagnetization fault was established, and different degrees of demagnetization fault were simulated. The harmonic analyses using the Fast Fourier Transform (FFT) show that the fault diagnosis method based on the harmonic wave analysis is only suitable for partial demagnetization fault of the PMSM and does not apply to uniform demagnetization fault of the PMSM.

Keywords: permanent magnet, diagnosis, demagnetization, modelling

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Authors: Fahad Qureshi

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This paper provides detailed study on the diagnosis of intermittent high vibration spikes at exhaust bearing (Non-Drive End) of Mitsubishi H-25 gas turbine installed in a petrochemical plant in Pakistan. The diagnosis is followed by successful root cause analysis of the issue and recommendations for improving the reliability of machine. Engro Polymer and Chemicals (EPCL), a Chlor Vinyl complex, has a captive power plant consisting of one combined cycle power plant (CCPP), having two gas turbines each having 25 MW capacity (make: Hitachi) and one extraction condensing steam turbine having 15 MW capacity (make: HTC). Besides, one 6.75 MW SGT-200 1S gas turbine (make: Alstom) is also available. In 2018, the organization faced an issue of intermittent high vibration at exhaust bearing of one of H-25 units having tag GT-2101 A, which eventually led to tripping of machine at configured securities. Since the machine had surpassed 64,000 running hours and major inspection was also due, so bearings inspection was performed. Inspection revealed excessive coke deposition at labyrinth where evidence of rotor rub was also present. Bearing clearance was also at upper limit, and slight babbitt (soft metal) chip off was observed at one of its pads so it was preventively replaced. The unit was restated successfully and exhibited no abnormality until October 2020, when these spikes reoccurred, leading to machine trip. Recurrence of the issue within two years indicated that root cause was not properly addressed, so this paper furthers the discussion on in-depth analysis of findings and establishes successful root cause analysis, which captured significant learnings both in terms of machine design deficiencies and gaps in operation & maintenance (O & M) regime. Lastly, revised O& M regime along with set of recommendations are proposed to avoid recurrence.

Keywords: exhaust side bearing, Gas turbine, rubbing, vibration

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Authors: Houda Najeh, Stéphane Ploix, Mahendra Pratap Singh, Karim Chabir, Mohamed Naceur Abdelkrim

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Building systems are highly vulnerable to different kinds of faults and failures. In fact, various faults, failures and human behaviors could affect the building performance. This paper tackles the detection of unreliable sensors in buildings. Different literature surveys on diagnosis techniques for sensor grids in buildings have been published but all of them treat only bias and outliers. Occurences of data gaps have also not been given an adequate span of attention in the academia. The proposed methodology comprises the automatic thresholding for data gap detection for a set of heterogeneous sensors in instrumented buildings. Sensor measurements are considered to be regular time series. However, in reality, sensor values are not uniformly sampled. So, the issue to solve is from which delay each sensor become faulty? The use of time series is required for detection of abnormalities on the delays. The efficiency of the method is evaluated on measurements obtained from a real power plant: an office at Grenoble Institute of technology equipped by 30 sensors.

Keywords: building system, time series, diagnosis, outliers, delay, data gap

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Authors: Abbas Pourreza

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MicroRNAs (miRNAs) are small single-stranded non-coding RNAs. They are almost 18-25 nucleotides long and very conservative through evolution. They are involved in adjusting the expression of numerous genes due to the existence of a complementary region, generally in the 3' untranslated regions (UTR) of target genes, against particular mRNAs in the cell. Also, miRNAs have been proven to be involved in cell development, differentiation, proliferation, and apoptosis. More than 2000 miRNAs have been recognized in human cells, and these miRNAs adjust approximately one-third of all genes in human cells. Dysregulation of miRNA originated from abnormal DNA methylation patterns of the locus, cause to down-regulated or overexpression of miRNAs, and it may affect tumor formation or development of it. Breast cancer (BC) is the most commonly identified cancer, the most prevalent cancer (23%), and the second-leading (14%) mortality in all types of cancer in females. BC can be classified based on the status (+/−) of the hormone receptors, including estrogen receptor (ER), progesterone receptor (PR), and the Receptor tyrosine-protein kinase erbB-2 (ERBB2 or HER2). Currently, there are four main molecular subtypes of BC: luminal A, approximately 50–60 % of BCs; luminal B, 10–20 %; HER2 positive, 15–20 %, and 10–20 % considered Basal (triple-negative breast cancer (TNBC)) subtype. Aberrant expression of miR-145, miR-21, miR-10b, miR-125a, and miR-206 was detected by Stem-loop real-time RT-PCR in BC cases. Breast tumor formation and development may result from down-regulation of a tumor suppressor miRNA such as miR-145, miR-125a, and miR-206 and/or overexpression of an oncogenic miRNA such as miR-21 and miR-10b. MiR-125a, miR-206, miR-145, miR-21, and miR-10b are hugely predicted to be new tumor markers for the diagnosis and prognosis of BC. MiR-21 and miR-125a could play a part in the treatment of HER-2-positive breast cancer cells, while miR-145 and miR-206 could speed up the evolution of cure techniques for TNBC. To conclude, miRNAs will be presented as hopeful molecules to be used in the primary diagnosis, prognosis, and treatment of BC and battle as opposed to its developed drug resistance.

Keywords: breast cancer, HER2 positive, miRNA, TNBC

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Authors: Huang Bai-Cheng

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When deploying the Oriented Fast and Rotated Binary Robust Independent Elementary Feature (BRIEF) (ORB) extraction algorithm on field-programmable gate arrays (FPGA), the access of global storage for 31×31 pixel patches of the features has become the bottleneck of the system efficiency. Therefore, a feature zone strategy has been proposed. Zones are searched as features are detected. Pixels around the feature zones are extracted from global memory and distributed into patches corresponding to feature coordinates. The proposed FPGA structure is targeted on a Xilinx FPGA development board of Zynq UltraScale+ series, and multiple datasets are tested. Compared with the streaming pixel patch extraction method, the proposed architecture obtains at least two times acceleration consuming extra 3.82% Flip-Flops (FFs) and 7.78% Look-Up Tables (LUTs). Compared with the non-streaming one, the proposed architecture saves 22.3% LUT and 1.82% FF, causing a latency of only 0.2ms and a drop in frame rate for 1. Compared with the related works, the proposed strategy and hardware architecture have the superiority of keeping a balance between FPGA resources and performance.

Keywords: feature extraction, real-time, ORB, FPGA implementation

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Authors: Paula I. Buonfiglio, Carlos David Bruque, Lucia Salatino, Vanesa Lotersztein, Sebastián Menazzi, Paola Plazas, Ana Belén Elgoyhen, Viviana Dalamón

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Hearing loss (HL) is the most prevalent sensorineural disorder affecting about 10% of the global population, with more than half due to genetic causes. About 1 in 500-1000 newborns present congenital HL. Most of the patients are non-syndromic with an autosomal recessive mode of inheritance. To date, more than 100 genes are related to HL. Therefore, the Whole-exome sequencing (WES) technique has become a cost-effective alternative approach for molecular diagnosis. Nevertheless, new challenges arise from the detection of novel variants, in particular missense changes, which can lead to a spectrum of genotype-to-phenotype correlations, which is not always straightforward. In this work, we aimed to identify the genetic causes of HL in isolated and familial cases by designing a multistep approach to analyze target genes related to hearing impairment. Moreover, we performed in silico and in vivo analyses in order to further study the effect of some of the novel variants identified in the hair cell function using the zebrafish model. A total of 650 patients were studied by Sanger Sequencing and Gap-PCR in GJB2 and GJB6 genes, respectively, diagnosing 15.5% of sporadic cases and 36% of familial ones. Overall, 50 different sequence variants were detected. Fifty of the undiagnosed patients with moderate HL were tested for deletions in STRC gene by Multiplex ligation-dependent probe amplification technique (MLPA), leading to 6% of diagnosis. After this initial screening, 50 families were selected to be analyzed by WES, achieving diagnosis in 44% of them. Half of the identified variants were novel. A missense variant in MYO6 gene detected in a family with postlingual HL was selected to be further analyzed. A protein modeling with AlphaFold2 software was performed, proving its pathogenic effect. In order to functionally validate this novel variant, a knockdown phenotype rescue assay in zebrafish was carried out. Injection of wild-type MYO6 mRNA in embryos rescued the phenotype, whereas using the mutant MYO6 mRNA (carrying c.2782C>A variant) had no effect. These results strongly suggest the deleterious effect of this variant on the mobility of stereocilia in zebrafish neuromasts, and hence on the auditory system. In the present work, we demonstrated that our algorithm is suitable for the sequential multigenic approach to HL in our cohort. These results highlight the importance of a combined strategy in order to identify candidate variants as well as the in silico and in vivo studies to analyze and prove their pathogenicity and accomplish a better understanding of the mechanisms underlying the physiopathology of the hearing impairment.

Keywords: diagnosis, genetics, hearing loss, in silico analysis, in vivo analysis, WES, zebrafish

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Authors: Denise Ben-Porath, Tracy Masterson

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In the past, individuals who struggled with and sought treatment for mental health difficulties were stigmatized. However, the current generation holds more open attitudes around mental health issues. Indeed, public figures such as Demi Lovato, Naomi Osaka, and Simone Biles have taken to social media to break the silence around mental health, discussing their own struggles and the benefits of treatment. Thus, there is considerable reason to believe that this generation would hold fewer stigmatizing attitudes toward mental health difficulties and treatment compared to previous ones. In this study, we explored possible changes in stigma on mental health diagnosis and treatment seeking behavior between two generations: Gen Z, the current generation, and Gen X, those born between 1965-1980. It was hypothesized that Gen Z would hold less stigmatizing views on mental illness than Gen X. To examine possible changes in stigma attitudes between these two generations, we conducted a cross-generational cohort design by using the same methodology employed 20 years ago from the Ben-Porath (2002) study. Thus, participants were randomly assigned to read one of the following four case vignettes employed in the Ben-Porath (2002) study: (a) “Tom” who has received psychotherapy due to depression (b) “Tom” who has been depressed but received no psychological help, (c) “Tom” who has received medical treatment due to a back pain, or (d) “Tom” who had a back pain but did not receive medical attention. After reading the vignette, participants rated “Tom” on various personality dimensions using the IFQ Questionnaire and answered questions about their frequency of social media use and willingness to seek mental health treatment on a scale from 1-10. Identical to the results 20 years prior, a significant main effect was found for diagnosis with “Tom” being viewed in more negative terms when he was described as having depression vs. a medical condition (back pain) [F (1, 376) = 126.53, p < .001]. However, in the study conducted 20 years earlier, a significant interaction was found between diagnosis and help-seeking behavior [F (1, 376) = 8.28, p < .005]. Specifically, “Tom” was viewed in the most negative terms when described as depressed and seeking treatment. Alternatively, the current study failed to find a significant interaction between depression and help seeking behavior. These findings suggest that while individuals who hold a mental health diagnosis may still be stigmatized as they were 20 years prior, seeking treatment for mental health issues may be less so. Findings are discussed in the context of social media use and its impact on destigmatization.

Keywords: stigma, mental illness, help-seeking, social media

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Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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Authors: Eva Karaskova, Jana Volejnikova, Dusan Holub, Maria Velganova-Veghova, Michaela Spenerova, Dagmar Pospisilova

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Background: Hepcidin is the central regulator of iron metabolism. Its production is mainly affected by an iron deficiency and the presence of inflammatory activity in the body. The aim of this study was to compare serum hepcidin levels in paediatric patients with newly diagnosed inflammatory bowel disease and hepcidin levels during maintenance therapy, correlate changes of serum hepcidin levels with selected markers of iron metabolism and inflammation and type of provided treatment. Methods: Children with newly diagnosed Crohn's disease (CD) and ulcerative colitis (UC) were included in this prospective study. Blood and stool samples were collected before treatment (baseline). Serum hepcidin, hemoglobin levels, platelet counts, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), interleukin-6 (IL 6), ferritin, iron, soluble transferrin receptors, and fecal calprotectin were assessed. The same parameters were measured and compared with the baseline levels in the follow-up period, during maintenance therapy (average of 39 months after diagnosis). Results: Patients with CD (n=30) had higher serum hepcidin levels (expressed as a median and interquartile range) at diagnosis than subjects with UC (n=13). These levels significantly decreased during the follow-up (from 36.5 (11.5-79.6) ng/ml to 2.1 (0.9-6.7) ng/ml). Contrarily, no significant serum hepcidin level changes were observed in UC (from 5.4 (3.4-16.6) ng/ml to 4.8 (0.9-8.1) ng/ml). While in children with CD hepcidin level dynamics correlated with disease activity and inflammatory markers (ESR, CRP), an only correlation with serum iron levels was observed in patients with UC. Conclusion: Children with CD had higher serum hepcidin levels at diagnosis compared to subjects with UC. Decrease of serum hepcidin in the CD group during anti-inflammatory therapy has been observed, whereas low hepcidin levels in children with UC have remained unchanged. Acknowledgment: This study was supported by grant MH CZ–DRO (FNOl, 00098892).

Keywords: children, Crohn's disease, ulcerative colitis, anaemia, hepcidin

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Authors: Boukrida Rafiq

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Democracy is based on the notion that all citizens have the right to participate in the managing of political affairs and that every citizens input is of equal importance. This basic assumption clearly places emphasis on public participation in maintaining a stable democracy. The level of public participation, however is highly contested with many theorists arguing that too much public participation would overwhelm and ultimately cripple democratic systems. On the other hand, others who favor high levels of participation argue that more citizen involvement leads to greater representation. Regardless of these disagreements over the utopian level of participation, there is widespread agreement amongst scholars that, at the very least, some participation is necessary to maintain democratic systems. The ways in which citizens participate vary greatly and depending on the method used, influence political decision making at varying levels. The method of political participation is a key in controlling public influence over political affairs and therefore is also an integral part of maintaining democracy, whether it be "thin" (low levels of participation) or "Robust" (high levels of participation). High levels of participation or "robust" democracy are argued by some theorists to enhance democracy through providing the opportunity for more issues to be represented during decision making. The notion of widespread participation was first advanced by classical theorists.

Keywords: assumption clearly places emphasis, ultimately cripple, influence political decision making at varying, classical theorists

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Authors: Ben-Caleb Egbide, Omolehinwa O. Eddy, Adeyemi S. Keyinde, Eriabie Sylvester, Ojeka Stephen

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The national budget remains an integral part of the developmental plan of the economy of any country. The budget reflects the fundamental values underlying the government’s economic policies and objectives and whose execution is expected to realize national/public desires. In Nigeria, over three decades budget had failed to deliver the desired benefits, suggesting the existence of infractions, which are yet to be empirically ascertained. This paper attempts a diagnosis of the infractions peculiar to Nigeria budgetary system and their suggested panacea. Data were collected through the administration of questionnaire to a cross section of organizations/institutions representing government agencies and the general public. Mann-Whitney U test was employed to gauge the consistency in perception of the two groups. The result revealed that budget indiscipline, official corruption, allocative inefficiency and poor budget governance are the most influential infractions of budgeting in Nigeria. Consequently, it was suggested that budget transparency, target budgeting, zero tolerance on corruption and budget discipline are the most cogent therapies to the malfunctioning in Nigerian budgetary system.

Keywords: budgeting, budget maladies, budget therapies, Nigeria

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Authors: Ioannis Panagiotopoulos, Efstathios Kastritis, Anastasia Katinioti, Georgios Efthymiadis, Argyrios Doumas, Maria Koutelou

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Introduction: Transthyretin amyloidosis (ATTR) is a rare but serious infiltrative disease. Myocardial scintigraphy with DPD has emerged as the most effective, non-invasive, highly sensitive, and highly specific diagnostic method for cardiac ATTR amyloidosis. However, there are cases in which additional laboratory investigations reveal AL amyloidosis or other diseases despite a positive DPD scintigraphy. We describe the experience from the Onassis Cardiac Surgery Center and the monitoring center for infiltrative myocardial diseases of the cardiology clinic at AHEPA. Materials and Methods: All patients with clinical suspicion of cardiac or extracardiac amyloidosis undergo a myocardial scintigraphy scan with Tc-99m DPD. In this way, over 500 patients have been examined. Further diagnostic approach based on clinical and imaging findings includes laboratory investigation and invasive techniques (e.g., biopsy). Results: Out of 76 patients in total with positive myocardial scintigraphy Grade 2 or 3 according to the Perugini scale, 8 were proven to suffer from AL Amyloidosis during the investigation of paraproteinemia. Among these patients, 3 showed Grade 3 uptake, while the rest were graded as Grade 2, or 2 to 3. Additionally, one patient presented diffuse and unusual radiopharmaceutical uptake in soft tissues throughout the body without cardiac involvement. These findings raised suspicions, leading to the analysis of κ and λ light chains in the serum, as well as immunostaining of proteins in the serum and urine of these specific patients. The final diagnosis was AL amyloidosis. Conclusion: The value of DPD scintigraphy in the diagnosis of cardiac amyloidosis from transthyretin is undisputed. However, positive myocardial scintigraphy with DPD should not automatically lead to the diagnosis of ATTR amyloidosis. Laboratory differentiation between ATTR and AL amyloidosis is crucial, as both prognosis and therapeutic strategy are dramatically altered. Laboratory exclusion of paraproteinemia is a necessary and essential step in the diagnostic algorithm of ATTR amyloidosis for all positive myocardial scintigraphy with diphosphonate tracers since >20% of patients with Grade 3 and 2 uptake may conceal AL amyloidosis.

Keywords: AL amyloidosis, amyloidosis, ATTR, myocardial scintigraphy, Tc-99m DPD

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Authors: Seungwoo Kim, Yeongcheol Cho

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In this paper, a holonomic mobile robot is designed in omnidirectional wheels and an adaptive fuzzy controller is presented for its precise trajectories. A kind of adaptive controller based on fuzzy multi-layered algorithm is used to solve the big parametric uncertainty of motor-controlled dynamic system of 3-wheels omnidirectional mobile robot. The system parameters such as a tracking force are so time-varying due to the kinematic structure of omnidirectional wheels. The fuzzy adaptive control method is able to solve the problems of classical adaptive controller and conventional fuzzy adaptive controllers. The basic idea of new adaptive control scheme is that an adaptive controller can be constructed with parallel combination of robust controllers. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good performance of a holonomic mobile robot is confirmed through live tests of the tracking control task.

Keywords: fuzzy adaptive control, fuzzy multi-layered controller, holonomic mobile robot, omnidirectional wheels, robustness and stability.

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Authors: Giovanni Duran Polo

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Demonstrate the importance of the stages such as Information, Diagnosis, Management, and Intervention is fundamental to have a historical, live, and quality inhabited center. One of the major actions to take is to promote the concept of the management of a historic center with harmonious development. For that, concerned actors should strengthen the concept that said historic center may be the neighborhood of all and for all. The centers of historical cities, presented as any other urban area, social, environmental issues etc; yet they get added value that have no other city neighborhoods. The equity component, either by the urban plan, or environmental quality offered properties of architectural, landscape or some land uses are the differentiating element, while the tool that makes them attractive face pressure exerted by new housing developments or shopping centers. That's why through the experience of working in historical centers, they are declared the actions in heritage areas. This paper will show how the encounter with each of these places are trying to take the phases of information, to gather all the data needed to be closer to the territory with specific data, diagnosis; which allowed the actors to see what state they were, felt how the heart is related to the rest of the city, show what problems affected the situation and what potential it had to compete in a global market. Also, to discuss the importance of the organization, as it is legal and normative basis for it have an order and a concept, when you know what can and what cannot, in an area where the citizen has many myth or history, when he wanted to intervene in protected buildings. It is also appropriate to show how it could develop the intervention phase, where the shares on the tangible elements and intervention for the protection of the heritage property are executed. The management is the final phase which will carry out all that was raised on paper, it's time to orient, explain, persuade, promote, and encourage citizens to take care of the heritage. It is profitable and also an obligation and it is not an insurmountable burden. It has to be said this is the time to pull all the cards to make the historical center and heritage becoming more alive today. It is the moment to make it more inhabited and to transformer it into a quality place, so citizens will cherish and understand the importance of such a place. Inhabited historical centers, endowments and equipment required, with trade quality, with constant cultural offer, with well-preserved buildings and tidy, modern and safe public spaces are always attractive for tourism, but first of all, the place should be conceived for citizens, otherwise everything will be doomed to failure.

Keywords: development, diagnosis, heritage historic center, intervention, management, patrimony

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