Search results for: real time kernel preemption

Authors: Sara T. K. Li, Belinda H. J. Chung, Jeffery C. N. Yip, Janet H. Hsiao

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Music notation and text reading both involve statistical learning of music or linguistic structures. However, it remains unclear how music reading expertise influences text reading behavior. The present study examined this issue through an eye-tracking study. Chinese-English bilingual musicians and non-musicians read English sentences, Chinese sentences, musical phrases, and sentences in Tibetan, a language novel to the participants, with their eye movement recorded. Each set of stimuli consisted of two conditions in terms of structural regularity: syntactically correct and syntactically incorrect musical phrases/sentences. They then completed a sentence comprehension (for syntactically correct sentences) or a musical segment/word recognition task afterwards to test their comprehension/recognition abilities. The results showed that in reading musical phrases, as compared with non-musicians, musicians had a higher accuracy in the recognition task, and had shorter reading time, fewer fixations, and shorter fixation duration when reading syntactically correct (i.e., in diatonic key) than incorrect (i.e., in non-diatonic key/atonal) musical phrases. This result reflects their expertise in music reading. Interestingly, in reading Tibetan sentences, which was novel to both participant groups, while non-musicians did not show any behavior differences between reading syntactically correct or incorrect Tibetan sentences, musicians showed a shorter reading time and had marginally fewer fixations when reading syntactically correct sentences than syntactically incorrect ones. However, none of the musicians reported discovering any structural regularities in the Tibetan stimuli after the experiment when being asked explicitly, suggesting that they may have implicitly acquired the structural regularities in Tibetan sentences. This group difference was not observed when they read English or Chinese sentences. This result suggests that music reading expertise facilities reading texts in a novel language (i.e., Tibetan), but not in languages that the readers are already familiar with (i.e., English and Chinese). This phenomenon may be due to the similarities between reading music notations and reading texts in a novel language, as in both cases the stimuli follow particular statistical structures but do not involve semantic or lexical processing. Thus, musicians may transfer their statistical learning skills stemmed from music notation reading experience to implicitly discover structures of sentences in a novel language. This speculation is consistent with a recent finding showing that music reading expertise modulates the processing of English nonwords (i.e., words that do not follow morphological or orthographic rules) but not pseudo- or real words. These results suggest that the modulation of music reading expertise on language processing depends on the similarities in the cognitive processes involved. It also has important implications for the benefits of music education on language and cognitive development.

Keywords: eye movement behavior, eye-tracking, music reading expertise, sentence reading, structural regularity, visual processing

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Authors: Daria Druzhinenko- Silhan, Patrick Schmoll

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Childhood obesity is one of the important problem in domain of health care. During two recent decades we are observing a real epidemic of this noninfectious illness. Its consequences are hard: cardio-vascular disease; diabetes; arthrosis etc. (OMS, 2012) Keep Healthy Kids  » study aims to create a new system of accompanying of childhood obesity based on new technologies as mobile applications or serious video-games. We realize a support-study which aims to understand motivations, psychological dynamite and family's impact on weight-loss process in childhood. Sample: 65 children from 7 to 10 years old accompanied by special Care Center in France. Methodology: we proceed by an innovative approach that bases on quantitative and qualitative methods of data collection. We focus our proposal on data collected from medical files. We are also realizing individual assessment (still ongoing) that aims to understand psychological profiles of obese children and their family dynamic. Results: Only 16,9% of children asked for medical accompanying of obesity. We noted that the most important reason to come to the care Center was the fact of mates' scoffs (46,2%°), the second one was the appearance or look (40 %). We found out that the self-image of these children in self-evaluation questionnaire was described mostly as rather good (46,2) or good (28,2%); the most part of children evaluated their well-being as rather good (29,7%) or good (51,4%). In interviews children had tendency to not recall why they came to the Care Center. Discussion : These results permit us to make a hypothesis that children suffering of overweight or obesity are not clearly aware why they must loose weight. It was rather the peer environment that pointed out the problem of overweight for them. So the motivation to loose weight is mostly supported by environment. We suppose that it is a « weak-point » of their motivation and it can be over-come using serious video-games supporting physical activity that can make deviate the motivation from « to loose weight for be looked better by the others » into « have fun and feeling me better ».

Keywords: childhood obesity, motivation, weight-loss, serious video-game

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Authors: Bing Lu, Shuang Li, Hongyuan Zhou

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The steel–concrete hybrid structure has been extensively employed in high–rise buildings and super high–rise buildings. The light gauge steel–concrete hybrid structure, including light gauge steel structure and concrete hybrid structure, is a new–type steel–concrete hybrid structure, which possesses some advantages of light gauge steel structure and concrete hybrid structure. The seismic behavior and loss assessment of three high–rise buildings with three different concrete hybrid structures were investigated through finite element software, respectively. The three concrete hybrid structures are reinforced concrete column–steel beam (RC‒S) hybrid structure, concrete–filled steel tube column–steel beam (CFST‒S) hybrid structure, and tubed concrete column–steel beam (TC‒S) hybrid structure. The nonlinear time-history analysis of three high–rise buildings under 80 earthquakes was carried out. After simulation, it indicated that the seismic performances of three high–rise buildings were superior. Under extremely rare earthquakes, the maximum inter–storey drifts of three high–rise buildings are significantly lower than 1/50. The inter–storey drift and floor acceleration of high–rise building with CFST‒S hybrid structure were bigger than those of high–rise buildings with RC‒S hybrid structure, and smaller than those of high–rise building with TC‒S hybrid structure. Then, based on the time–history analysis results, the post-earthquake repair cost ratio and repair time of three high–rise buildings were predicted through an economic performance analysis method proposed in FEMA‒P58 report. Under frequent earthquakes, basic earthquakes and rare earthquakes, the repair cost ratio and repair time of three high-rise buildings were less than 5% and 15 days, respectively. Under extremely rare earthquakes, the repair cost ratio and repair time of high-rise buildings with TC‒S hybrid structure were the most among three high rise buildings. Due to the advantages of CFST-S hybrid structure, it could be extensively employed in high-rise buildings subjected to earthquake excitations.

Keywords: seismic behavior, loss assessment, light gauge steel–concrete hybrid structure, high–rise building, time–history analysis

Procedia PDF Downloads 162

Authors: Binod Shrestha, Sandrine Hoppe, Thierry Ghislain, Phillipe Marchal, Nicolas Brosse, Anthony Dufour

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The thermochemical conversion of lignin has received an increasing interest in the frame of different biorefinery concepts for the production of chemicals or energy. It is needed to better understand the physical and chemical conversion of lignin for feeder and reactor designs. In-situ rheology reveals the viscoelastic behaviour of lignin upon thermal conversion. The softening, re-solidification (char formation), swelling and shrinking behaviours are quantified during pyrolysis in real-time [1]. The in-situ rheology of an alkali lignin (Protobind 1000) was conducted in high torque controlled strain rheometer from 35°C to 400°C with a heating rate of 5°C.min-1. The swelling, through glass phase transition overlapped with depolymerization, and solidification (crosslinking and “char” formation) are two main phenomena observed during lignin pyrolysis. The onset of temperatures for softening and solidification for this lignin has been found to be 141°C and 248°C respectively. An ex-situ characterization of lignin/char residues obtained at different temperatures after quenching in the rheometer gives a clear understanding of the pathway of lignin degradation. The lignin residues were sampled from the mid-point temperatures of the softening range and solidification range to study the chemical transformations undergoing. Elemental analysis, FTIR and solid state NMR were conducted after quenching the solid residues (lignin/char). The quenched solid was also extracted by suitable solvent and followed by acetylation and GPC-UV analysis. The combination of 13C NMR and GPC-UV reveals the depolymerization followed by crosslinking of lignin/char. NMR and FTIR provide the evolution of functional moieties upon temperature. Physical and chemical mechanisms occurring during lignin pyrolysis are accounted in this study. Thanks to all these complementary methods.

Keywords: pyrolysis, bio-chemicals, valorization, mechanism, softening, solidification, cross linking, rheology, spectroscopic methods

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Authors: D. Calogine, O. Chau, S. Dotti, O. Ramiarinjanahary, P. Rasoavonjy, F. Tovondahiniriko

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Mafate is a natural circus in the north-western part of Reunion Island, without an electrical grid and road network. A micro-grid concept is being experimented in this area, composed of a photovoltaic production combined with electrochemical batteries, in order to meet the local population for self-consumption of electricity demands. This work develops a discrete model as well as a stochastic model in order to reach an optimal equilibrium between production and consumptions for a cluster of houses. The management of the energy power leads to a large linearized programming system, where the time interval of interest is 24 hours The experimental data are solar production, storage energy, and the parameters of the different electrical devices and batteries. The unknown variables to evaluate are the consumptions of the various electrical services, the energy drawn from and stored in the batteries, and the inhabitants’ planning wishes. The objective is to fit the solar production to the electrical consumption of the inhabitants, with an optimal use of the energies in the batteries by satisfying as widely as possible the users' planning requirements. In the discrete model, the different parameters and solutions of the linear programming system are deterministic scalars. Whereas in the stochastic approach, the data parameters and the linear programming solutions become random variables, then the distributions of which could be imposed or established by estimation from samples of real observations or from samples of optimal discrete equilibrium solutions.

Keywords: photovoltaic production, power consumption, battery storage resources, random variables, stochastic modeling, estimations of probability distributions, mixed integer linear programming, smart micro-grid, self-consumption of electricity.

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Authors: Hamed K. Esfahani, Bithin Datta

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Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

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Authors: Qiuying Li, Fan Chen

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It is a shared opinion that sustainable development requires continuously updated, meaning that apparent changes in the way we usually produce our buildings are strongly needed. In China’s construction field, the associated environmental, health problems are quite prominent.Especially low sustainable performance (as opposed to Green creation) flooding the real estate boom and high-speed urban and rural urbanization. Currently, we urgently need to improve the existing design basis,objectives,scope and procedures,optimization design portfolio.More new evaluation system designed to facilitate the building to enhance the overall level.

Keywords: design for sustainability, design and materials, ecomaterials, sustainable architecture and urban design

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Authors: Yaxin Bi

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Accurate prediction and understanding of the evolution mechanisms of earthquakes remain challenging in the fields of geology, geophysics, and seismology. This study leverages Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs), a generative model tailored to time-series data, for generating synthetic time series data based on Swarm satellite data, which will be used for detecting seismic anomalies. LSTMs demonstrated commendable predictive performance in generating synthetic data across multiple countries. In contrast, the GAN models struggled to generate synthetic data, often producing non-informative values, although they were able to capture the data distribution of the time series. These findings highlight both the promise and challenges associated with applying deep learning techniques to generate synthetic data, underscoring the potential of deep learning in generating synthetic electromagnetic satellite data.

Keywords: LSTM, GAN, earthquake, synthetic data, generative AI, seismic precursors

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Authors: Ben Haines, Li Bai

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Patch based reconstruction methods have been and still are one of the top performing approaches to 3D reconstruction to date. Their local approach to refining the position and orientation of a patch, free of global minimisation and independent of surface smoothness, make patch based methods extremely powerful in recovering fine grained detail of an objects surface. However, patch based approaches still fail to faithfully reconstruct textureless or highly occluded surface regions thus though performing well under lab conditions, deteriorate in industrial or real world situations. They are also computationally expensive. Current patch based methods generate point clouds with holes in texturesless or occluded regions that require expensive energy minimisation techniques to fill and interpolate a high fidelity reconstruction. Such shortcomings hinder the adaptation of the methods for industrial applications where object surfaces are often highly textureless and the speed of reconstruction is an important factor. This paper presents on-going work towards a multi-resolution approach to address the problems, utilizing particle swarm optimisation to reconstruct high fidelity geometry, and increasing robustness to textureless features through an adapted approach to the normalised cross correlation. The work also aims to speed up the reconstruction using advances in GPU technologies and remove the need for costly initialization and expansion. Through the combination of these enhancements, it is the intention of this work to create denser patch clouds even in textureless regions within a reasonable time. Initial results show the potential of such an approach to construct denser point clouds with a comparable accuracy to that of the current top-performing algorithms.

Keywords: 3D reconstruction, multiview stereo, particle swarm optimisation, photo consistency

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Authors: F. Fatoye, C. E. Mbada, T. Gebrye, A. O. Ogunsola, C. Fatoye, O. Oyewole

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Musculoskeletal disorders (MSDs) such as low back pain (LBP), cervical spondylosis (CSPD), sprain, osteoarthritis (OA), and post immobilization stiffness (PIS) have a major impact on individuals, health systems and society in terms of morbidity, long-term disability, and economics. This study estimated the direct and indirect costs of common MSDs in Osun State, Nigeria. A review of medical charts for adult patients attending Physiotherapy Outpatient Clinic at the Obafemi Awolowo University Teaching Hospitals Complex, Osun State, Nigeria between 2009 and 2018 was carried out. The occupational class of the patients was determined using the International Labour Classification (ILO). The direct and indirect costs were estimated using a cost-of-illness approach. Physiotherapy related health resource use, and costs of the common MSDs, including consultation fee, total fee charge per session, costs of consumables were estimated. Data were summarised using descriptive statistics mean and standard deviation (SD). Overall, 1582 (Male = 47.5%, Female = 52.5%) patients with MSDs population with a mean age of 47.8 ± 25.7 years participated in this study. The mean (SD) direct costs estimate for LBP, CSPD, PIS, sprain, OA, and other conditions were $18.35 ($17.33), $34.76 ($17.33), $32.13 ($28.37), $35.14 ($44.16), $37.19 ($41.68), and $15.74 ($13.96), respectively. The mean (SD) indirect costs estimate of LBP, CSPD, PIS, sprain, OA, and other MSD conditions were $73.42 ($43.54), $140.57 ($69.31), $128.52 ($113.46), sprain $140.57 ($69.31), $148.77 ($166.71), and $62.98 ($55.84), respectively. Musculoskeletal disorders contribute a substantial economic burden to individuals with the condition and society. The unacceptable economic loss of MSDs should be reduced using appropriate strategies. Further research is required to determine the clinical and cost effectiveness of strategies to improve health outcomes of patients with MSDs. The findings of the present study may assist health policy and decision makers to understand the economic burden of MSDs and facilitate efficient allocation of healthcare resources to alleviate the burden associated with these conditions in Nigeria.

Keywords: economic burden, low back pain, musculoskeletal disorders, real-world

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Authors: Janaina Camile Pasqual Lofhagen, David Savarese, Veronika Vazhnik

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The urgency of the climate crisis requires both innovation and practicality. The energy transition framework allows industry to deliver resilient cities, enhance adaptability to change, pursue energy objectives such as growth or efficiencies, and increase renewable energy. This paper investigates a real-world application perspective for the use of biogas in Brazil and the U.S.. It will examine interventions to provide a foundation of infrastructure, as well as the tangible benefits for policy-makers crafting law and providing incentives.

Keywords: resilience, vulnerability, risks, biogas, sustainability.

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Authors: Felicia K. Oluwalola

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This paper examines the relevance of technology on education. It identified the concept of technology on education, bringing real-world learning to the classroom situation, examples of where technology can be used. This study established the fact that technology facilitates students learning compared with traditional method of teaching. It was recommended that the teachers should use technology to supplement, not replace, other instructional modes. It should be used in conjunction with hands-on labs and activities that also address the concepts targeted by the technology. Also, technology should be students centered and not teachers centered.

Keywords: computer, simulation, classroom teaching, education

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Authors: Ekaterina A. Redkina

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The necessity and importance of teaching professionally oriented content in English needs no proof nowadays. Consequently, the ability to share personal ESP teaching experience seems of great importance. This paper is based on the 8-year ESP and EFL teaching experience at the Moscow State Linguistic University, Moscow, Russia, and presents theoretical analysis of specifics, possible problems, and perspectives of teaching Psychology in English to Russian psychology-students. The paper concerns different issues that are common for different ESP classrooms, and familiar to different teachers. Among them are: designing ESP curriculum (for psychologists in this case), finding the balance between content and language in the classroom, main teaching principles (the 4 C’s), the choice of assessment techniques and teaching material. The main objective of teaching psychology in English to Russian psychology students is developing knowledge and skills essential for professional psychologists. Belonging to international professional community presupposes high-level content-specific knowledge and skills, high level of linguistic skills and cross-cultural linguistic ability and finally high level of professional etiquette. Thus, teaching psychology in English pursues 3 main outcomes, such as content, language and professional skills. The paper provides explanation of each of the outcomes. Examples are also given. Particular attention is paid to the lesson structure, its objectives and the difference between a typical EFL and ESP lesson. There is also made an attempt to find commonalities between teaching ESP and CLIL. There is an approach that states that CLIL is more common for schools, while ESP is more common for higher education. The paper argues that CLIL methodology can be successfully used in ESP teaching and that many CLIL activities are also well adapted for professional purposes. The research paper provides insights into the process of teaching psychologists in Russia, real teaching experience and teaching techniques that have proved efficient over time.

Keywords: ESP, CLIL, content, language, psychology in English, Russian students

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Authors: Ibrahim Turfanda, Soniya Rai, Karan Vadher

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Objectives— The study aims to compare real-world adherence to and persistence with dulaglutide and liraglutide in patients with type 2 diabetes (T2D) initiating treatment in UAE. Methods— This was a retrospective, non-interventional study (observation period: 01 March 2017–31 August 2019) using the UAE Dubai e-Claims database. Included: adult patients initiating dulaglutide/liraglutide 01 September 2017–31 August 2018 (index period) with: ≥1 claim for T2D in the 6 months before index date (ID); ≥1 claim for dulaglutide/liraglutide during index period; and continuous medical enrolment for ≥6 months before and ≥12 months after ID. Key endpoints, assessed 3/6/12 months after ID: adherence to treatment (proportion of days covered [PDC; PDC ≥80% considered ‘adherent’], per-group mean±standard deviation [SD] PDC); and persistence (number of continuous therapy days from ID until discontinuation [i.e., >45 days gap] or end of observation period). Patients initiating dulaglutide/liraglutide were propensity score matched (1:1) based on baseline characteristics. Between-group comparison of adherence was analysed using the McNemar test (α=0.025). Persistence was analysed using Kaplan–Meier estimates with log-rank tests (α=0.025) for between-group comparisons. This study presents 12-month outcomes. Results— Following propensity score matching, 263 patients were included in each group. Mean±SD PDC for all patients at 12 months was significantly higher in the dulaglutide versus the liraglutide group (dulaglutide=0.48±0.30, liraglutide=0.39±0.28, p=0.0002). The proportion of adherent patients favored dulaglutide (dulaglutide=20.2%, liraglutide=12.9%, p=0.0302), as did the probability of being adherent to treatment (odds ratio [97.5% CI]: 1.70 [0.99, 2.91]; p=0.03). Proportion of persistent patients also favoured dulaglutide (dulaglutide=15.2%, liraglutide=9.1%, p=0.0528), as did the probability of discontinuing treatment 12 months after ID (p=0.027). Conclusions— Based on the UAE Dubai e-Claims database data, dulaglutide initiators exhibited significantly greater adherence in terms of mean PDC versus liraglutide initiators. The proportion of adherent patients and the probability of being adherent favored the dulaglutide group, as did treatment persistence.

Keywords: adherence, dulaglutide, effectiveness, liraglutide, persistence

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Authors: C. A. Barros, Ana P. Barroso

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Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: automotive Industry, industry 4.0, Internet of Things, IATF 16949:2016, measurement system analysis

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Authors: Ł. Morawiński, C. Jasiński, M. Jurkiewicz, S. Bou Habib, M. Bondyra

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With the development of optics, electronics, and computers, vision systems are increasingly used in various areas of life, science, and industry. Vision systems have a huge number of applications. They can be used in quality control, object detection, data reading, e.g., QR-code, etc. A large part of them is used for measurement purposes. Some of them make it possible to obtain a 3D reconstruction of the tested objects or measurement areas. 3D reconstruction algorithms are mostly based on creating depth maps from data that can be acquired from active or passive methods. Due to the specific appliance in airfield technology, only passive methods are applicable because of other existing systems working on the site, which can be blinded on most spectral levels. Furthermore, reconstruction is required to work long distances ranging from hundreds of meters to tens of kilometers with low loss of accuracy even with harsh conditions such as fog, rain, or snow. In response to those requirements, HRESS (Heliport REmote Safeguard System) was developed; which main part is a rotational head with a two-camera stereovision rig gathering images around the head in 360 degrees along with stereovision 3D reconstruction and point cloud combination. The sub-pixel analysis introduced in the HRESS system makes it possible to obtain an increased distance measurement resolution and accuracy of about 3% for distances over one kilometer. Ultimately, this leads to more accurate and reliable measurement data in the form of a point cloud. Moreover, the program algorithm introduces operations enabling the filtering of erroneously collected data in the point cloud. All activities from the programming, mechanical and optical side are aimed at obtaining the most accurate 3D reconstruction of the environment in the measurement area.

Keywords: airfield monitoring, artificial intelligence, stereovision, 3D reconstruction

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Authors: Athicha Cherdpunt, Patompong Satapornpong

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The medical cannabis is made up of components also known as cannabinoids, which consists of two ingredients which are Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD). Interestingly, the Cannabinoid can be used for many treatments such as chemotherapy, including nausea and vomiting, cachexia, anorexia nervosa, spinal cord injury and disease, epilepsy, pain, and many others. However, the adverse drug reactions (ADRs) of THC can cause sedation, anxiety, dizziness, appetite stimulation and impairments in driving and cognitive function. Furthermore, genetic polymorphisms of CYP2C9, CYP2C19 and CYP3A4 influenced the THC metabolism and might be a cause of ADRs. Particularly, CYP2C19*17 allele increases gene transcription and therefore results in ultra-rapid metabolizer phenotype (UM). The aim of this study, is to investigate the frequency of CYP2C19*17 alleles in Thai patients who have been treated with medical cannabis. We prospectively enrolled 60 Thai patients who were treated with medical cannabis and clinical data from College of Pharmacy, Rangsit University. DNA of each patient was isolated from EDTA blood, using the Genomic DNA Mini Kit. CYP2C19*17 genotyping was conducted using the real time-PCR ViiA7 (ABI, Foster City, CA, USA). 30 patients with medical cannabis-induced ADRs group, 20 (67%) were female, and 10 (33%) were male, with an age range of 30-69 years. On the other hand, 30 patients without medical cannabis-induced ADRs (control group) consist of 17 (57%) female and 13 (43%) male. The most ADRs for medical cannabis treatment in the case group were dry mouth and dry throat (77%), tachycardia (70%), nausea (30%) and arrhythmia(10%). Accordingly, the case group carried CYP2C19*1/*1 (normal metabolizer) approximately 93%, while 7% patients carrying CYP2C19*1/*17 (ultra rapid metabolizers) exhibited in this group. Meanwhile, we found 90% of CYP2C19*1/*1 and 10% of CYP2C19*1/*17 in control group. In this study, we identified the frequency of CYP2C19*17 allele in Thai population which will support the pharmacogenetics biomarkers for screening and avoid ADRs of medical cannabis treatment.

Keywords: CYP2C19, allele frequency, ultra rapid metabolizer, medical cannabis

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Authors: Faisal Saleem, Kui Zhang, Adam Harvey

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The role of N₂ carrier gas towards the conversion of tar analogue was studied in a non-thermal plasma dielectric barrier discharge (DBD) reactor. The important parameters such as power (5-40W), residence time (1.41-4.23 s), concentration (20-82 g/Nm³), and temperature (Ambient-400°C) were explored. The present study demonstrated that plasma power and residence time played a key role in the decomposition of toluene, and almost complete removal of toluene was observed at 40w and 4.23 s. H₂ is obtained as a major gaseous product with a maximum selectivity of 40% along with some lighter hydrocarbons (5.5%). The removal efficiency of toluene slightly decreases with increasing the concentration of toluene from 20 g/Nm³ to 82 g/Nm³. The solid residue formation takes place inside the plasma reactor. The selectivity of LHC (lower hydrocarbons) increased up to 15% by increasing the temperature to 400°C. Introducing H₂ to the gas at elevated temperature opens up new reaction routes to raise the selectivity to lower hydrocarbons. The selectivity to methane reaches to 42% using 35% H₂ at 400°C and total selectivity of LHC increases to 57%.

Keywords: biomass gasification tar, non-thermal plasma, dielectric barrier discharge, residence time

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Authors: V. N. Chebotkevich, E. E. Schetinkina, V. V. Burylev, E. I. Kaytandzhan, N. P. Stizhak

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Objective: Blood stream infections (BSI) are severe, life-threatening illness for immuno compromised patients with hematological malignancies. We report the trend in blood-stream infections in this group of patients in the period 1991-2013. Methods: A total of 4742 blood samples investigated. All blood cultures were incubated in a continuous monitoring system for 7 days before discarding negative. On signaled positive, organism was identified by conventional methods. The Real-time polymerase chain reaction (PCR) was used for the indication of human herpes virus 6 (HHV-6), Cytomegalovirus (CMV) and Epstein-Barr virus (EBV). Results: Between 1991 and 2001 the incidence of Gram-positive bacteria (Staphylococcus epidermidis, Staphylococcus aureus) being the most common germs isolated (70,9%) were as Gram-negative rods (Escherichia coli, Klebsiella spp., Pseudomonas spp.) – 29,1%. In next decade 2002-2012 the number of Gram-negative bacteria was increased up to 40.2%. It is shown that the incidence of bacteremia was significantly more frequent at the background of detectable Cytomegalovirus and Epstein-Barr virus-specific DNA in blood. Over recent years, an increased frequency of micro mycetes was registered in blood of the patients with hematological malignancies (Candida spp. was predominant). Conclusion: Accurate and timely detection of BSI is important in determining appropriate treatment of infectious complications in patients with hematological malignancies. The isolation of Staphylococcus epidermidis from blood cultures remains a clinical dilemma for physicians and microbiologists. But in many cases this agent is of the clinical significance in immunocompromised patients with hematological malignancies. The role of CMV and EBV in development of bacteremia was demonstrated.

Keywords: infectious complications, blood stream infections, bacteremia, hemoblastosis

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Authors: Bushra Zafar, Usman Qamar

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Large data sample size and dimensions render the effectiveness of conventional data mining methodologies. A data mining technique are important tools for collection of knowledgeable information from variety of databases and provides supervised learning in the form of classification to design models to describe vital data classes while structure of the classifier is based on class attribute. Classification efficiency and accuracy are often influenced to great extent by noisy and undesirable features in real application data sets. The inherent natures of data set greatly masks its quality analysis and leave us with quite few practical approaches to use. To our knowledge first time, we present a new approach for investigation of structure and quality of datasets by providing a targeted analysis of localization of noisy and irrelevant features of data sets. Machine learning is based primarily on feature selection as pre-processing step which offers us to select few features from number of features as a subset by reducing the space according to certain evaluation criterion. The primary objective of this study is to trim down the scope of the given data sample by searching a small set of important features which may results into good classification performance. For this purpose, a heuristic for wrapper-based feature selection using genetic algorithm and for discriminative feature selection an external classifier are used. Selection of feature based on its number of occurrence in the chosen chromosomes. Sample dataset has been used to demonstrate proposed idea effectively. A proposed method has improved average accuracy of different datasets is about 95%. Experimental results illustrate that proposed algorithm increases the accuracy of prediction of different diseases.

Keywords: data mining, generic algorithm, KNN algorithms, wrapper based feature selection

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Authors: Ben Mansour Mouin, Elloumi Abdelkarim

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We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).

Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics

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Authors: Regina Rekuviene, Vykintas Samaitis, Liudas Mažeika, Audrius Jankauskas, Virginija Jankauskaitė, Laura Gegeckienė, Abdolali Sadaghiani, Shaghayegh Saeidiharzand

Abstract:

Icing brings significant damage to aviation and renewable energy installations. Air-conditioning, refrigeration, wind turbine blades, airplane and helicopter blades often suffer from icing phenomena, which cause severe energy losses and impair aerodynamic performance. The icing process is a complex phenomenon with many different causes and types. Icing mechanisms, distributions, and patterns are still relevant to research topics. The adhesion strength between ice and surfaces differs in different icing environments. This makes the task of anti-icing very challenging. The techniques for various icing environments must satisfy different demands and requirements (e.g., efficient, lightweight, low power consumption, low maintenance and manufacturing costs, reliable operation). It is noticeable that most methods are oriented toward a particular sector and adapting them to or suggesting them for other areas is quite problematic. These methods often use various technologies and have different specifications, sometimes with no clear indication of their efficiency. There are two major groups of anti-icing methods: passive and active. Active techniques have high efficiency but, at the same time, quite high energy consumption and require intervention in the structure’s design. It’s noticeable that vast majority of these methods require specific knowledge and personnel skills. The main effect of passive methods (ice-phobic, superhydrophobic surfaces) is to delay ice formation and growth or reduce the adhesion strength between the ice and the surface. These methods are time-consuming and depend on forecasting. They can be applied on small surfaces only for specific targets, and most are non-biodegradable (except for anti-freezing proteins). There is some quite promising information on ultrasonic ice mitigation methods that employ UGW (Ultrasonic Guided Wave). These methods are have the characteristics of low energy consumption, low cost, lightweight, and easy replacement and maintenance. However, fundamental knowledge of ultrasonic de-icing methodology is still limited. The objective of this work was to identify the ice formation processes and its progress by employing ultrasonic guided wave technique. Throughout this research, the universal set-up for acoustic measurement of ice formation in a real condition (temperature range from +240 C to -230 C) was developed. Ultrasonic measurements were performed by using high frequency 5 MHz transducers in a pitch-catch configuration. The selection of wave modes suitable for detection of ice formation phenomenon on copper metal surface was performed. Interaction between the selected wave modes and ice formation processes was investigated. It was found that selected wave modes are sensitive to temperature changes. It was demonstrated that proposed ultrasonic technique could be successfully used for the detection of ice layer formation on a metal surface.

Keywords: ice formation processes, ultrasonic GW, detection of ice formation, ultrasonic testing

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Authors: Ayse Cagil Kandemir, Derya Erdem, Markus Niederberger, Ralph Spolenak

Abstract:

Dip Pen nanolithography (DPN), which is a tip based method, serves a novel approach to produce nano and micro-scaled patterns due to its high resolution and pattern flexibility. It is introduced as a new constructive scanning probe lithography (SPL) technique. DPN delivers materials in the form of an ink by using the tip of a cantilever as pen and substrate as paper in order to form surface architectures. First studies rely on delivery of small organic molecules on gold substrate in ambient conditions. As time passes different inks such as; polymers, colloidal particles, oligonucleotides, metallic salts were examined on a variety of surfaces. Discovery of DPN also enabled patterning with multiple inks by using multiple cantilevers for the first time in SPL history. Specifically, polymer inks, which constitute a flexible matrix for various materials, can have a potential in MEMS, NEMS and drug delivery applications. In our study, it is aimed to construct polymer patterns using DPN by studying wetting behavior of polymer on semiconductor, metal and polymer surfaces. The optimum viscosity range of polymer and effect of environmental conditions such as humidity and temperature are examined. It is observed that there is an inverse relation with ink viscosity and depletion time. This study also yields the optimal writing conditions to produce consistent patterns with DPN. It is shown that written dot sizes increase with dwell time, indicating that the examined writing conditions yield repeatable patterns.

Keywords: dip pen nanolithography, polymer, surface patterning, surface science

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Authors: Driouiche Ali, Karmal Ilham

Abstract:

The Agadir region is characterized by a dry climate, ranging from arid attenuated by oceanic influences to hyper-arid. The water mobilized in the agricultural sector of greater Agadir is 95% of underground origin and comes from the water table of Chtouka. The rest represents the surface waters of the Youssef Ben Tachfine dam. These waters are intended for the irrigation of 26880 hectares of modern agriculture. More than 120 boreholes and wells are currently exploited. Their depth varies between 10 m and 200 m and the unit flow rates of the boreholes are 5 to 50 l/s. A drop in the level of the water table of about 1.5 m/year, on average, has been observed during the last five years. Farmers are thus called upon to improve irrigation methods. Thus, localized or drip irrigation is adopted to allow rational use of water. The importance of this irrigation system is due to the fact that water is applied directly to the root zone and its compatibility with fertilization. However, this irrigation system faces a thorny problem which is the clogging of pipes and drippers. This leads to a lack of uniformity of irrigation over time. This so-called scaling phenomenon, the consequences of which are harmful (cleaning or replacement of pipes), leads to considerable unproductive expenditure. The objective set by this work is the search for green inhibitors likely to prevent this phenomenon of scaling. This study requires a better knowledge of these waters, their physico-chemical characteristics and their scaling power. Thus, using the "LCGE" controlled degassing technique, we initially evaluated, on pure calco-carbonic water at 30°F, the scaling-inhibiting power of some available plant extracts in our region of Souss-Massa. We then carried out a comparative study of the efficacy of these green inhibitors. The action of the most effective green inhibitor on real agricultural waters was then studied.

Keywords: green inhibitors, localized irrigation, plant extracts, scaling inhibition

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Authors: Zhuo Feng, Ying Gao

Abstract:

Public-private partnership (PPP), as an innovative way to provide infrastructures by the private sector, is being widely used throughout the world. Compared with the traditional mode, PPP emerges largely for merits of relieving public budget constraint and improving infrastructure supply efficiency by involving private funds. However, PPP projects are characterized by large scale, high investment, long payback period, and long concession period. These characteristics make PPP projects full of risks. One of the most important risks faced by the private sector is demand risk because many factors affect the real demand. If the real demand is far lower than the forecasting demand, the private sector will be got into big trouble because operating revenue is the main means for the private sector to recoup the investment and obtain profit. Therefore, it is important to study how the government compensates the private sector when the demand risk occurs in order to achieve Pareto-improvement. This research focuses on price compensation mechanism, an ex-post compensation mechanism, and analyzes, by mathematical modeling, the impact of price compensation mechanism on payoff of the private sector and consumer surplus for PPP toll road projects. This research first investigates whether or not price compensation mechanisms can obtain Pareto-improvement and, if so, then explores boundary conditions for this mechanism. The research results show that price compensation mechanism can realize Pareto-improvement under certain conditions. Especially, to make the price compensation mechanism accomplish Pareto-improvement, renegotiation costs of the government and the private sector should be lower than a certain threshold which is determined by marginal operating cost and distortionary cost of the tax. In addition, the compensation percentage should match with the price cut of the private investor when demand drops. This research aims to provide theoretical support for the government when determining compensation scope under the price compensation mechanism. Moreover, some policy implications can also be drawn from the analysis for better risk-sharing and sustainability of PPP projects.

Keywords: infrastructure, price compensation mechanism, public-private partnership, renegotiation

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Authors: Shaloom Mbambu Kabeya, Léonard Kabeya Mukeba

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Churches, cathedrals and castles beaten from antiquity to modern times were relevant from that time to the present day, and preserved as cultural heritage. Our predecessors as François 1er1, Michelangelo2, and Giotto3 left us traces. Gustave Eiffel4, Hector Guimard5 did not decrease their time to show modernization (evolution) in architecture. Plagiarism is a brake on architectural development, construction works of spirits is necessary architecture. This work explains the relationship between ancient and modern architecture. It also shows the power of mathematics in modern architecture.

Keywords: architectural modernization, heritage, mathematical architecture, materials

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Authors: Rafia Asghar, Abdul Hafeez

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The current research was related with natural dyes’ extraction from the powder of Neem (Azadirachta indica) bark and studied characterization of this dye under microwave radiation’s influence. Both cotton fabric and dyeing powder were exposed to microwave rays for different time intervals (2minutes, 4 minutes, 6 minutes, 8 minutes and 10 minutes) using conventional oven. Aqueous, 60% Methanol and Ethyl Acetate solubilized extracts obtained from Neem (Azadirachta indica) bark were also exposed to different time intervals (2minutes, 4 minutes, 6 minutes, 8 minutes and 10 minutes) of microwave rays exposure. Pre, meta and post mordanting with Alum (2%, 4%, 6%, 8%, and 10%) was done to improve color strength of the extracted dye. Exposure of Neem (Azadirachta indica) bark extract and cotton to microwave rays enhanced the extraction process and dyeing process by reducing extraction time, dyeing time and dyeing temperature. Microwave rays treatment had a very strong influence on color fastness and color strength properties of cotton that was dyes using Neem (Azadirachta indica) bark for 30 minutes and dyeing cotton with that Neem bark extract for 75 minutes at 30°C. Among pre, meta and post mordanting, results indicated that 5% concentration of Alum in meta mordanting exhibited maximum color strength.

Keywords: dyes, natural dyeing, ecofriendly dyes, microwave treatment

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Authors: Sagar R. Patil, Dinesh R. Gawade, Sudhir N. Divekar

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One of the medical devices we found when we visit a hospital care unit such device is ‘patient monitoring system’. This device (patient monitoring system) informs doctors and nurses about the patient’s physiological signals. However, this device (patient monitoring system) does not have a remote monitoring capability, which is necessitates constant onsite attendance by support personnel (doctors and nurses). Thus, we have developed a Remote Wireless Patient Monitoring System using some biomedical sensors and Android OS, which is a portable patient monitoring. This device(Remote Wireless Patient Monitoring System) monitors the biomedical signals of patients in real time and sends them to remote stations (doctors and nurse’s android Smartphone and web) for display and with alerts when necessary. Wireless Patient Monitoring System different from conventional device (Patient Monitoring system) in two aspects: First its wireless communication capability allows physiological signals to be monitored remotely and second, it is portable so patients can move while there biomedical signals are being monitor. Wireless Patient Monitoring is also notable because of its implementation. We are integrated four sensors such as pulse oximeter (SPO2), thermometer, respiration, blood pressure (BP), heart rate and electrocardiogram (ECG) in this device (Wireless Patient Monitoring System) and Monitoring and communication applications are implemented on the Android OS using threads, which facilitate the stable and timely manipulation of signals and the appropriate sharing of resources. The biomedical data will be display on android smart phone as well as on web Using web server and database system we can share these physiological signals with remote place medical personnel’s or with any where in the world medical personnel’s. We verified that the multitasking implementation used in the system was suitable for patient monitoring and for other Healthcare applications.

Keywords: patient monitoring, wireless patient monitoring, bio-medical signals, physiological signals, embedded system, Android OS, healthcare, pulse oximeter (SPO2), thermometer, respiration, blood pressure (BP), heart rate, electrocardiogram (ECG)

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Authors: Stephanie Ducrot, Marie Vernet, Eve Meiss, Yves Chaix

Abstract:

Learning to read is a key topic of debate today, both in terms of its implications on school failure and illiteracy and regarding what are the best teaching methods to develop. It is estimated today that four to six percent of school-age children suffer from specific developmental disorders that impair learning. The findings from people with dyslexia and typically developing readers suggest that the problems children experience in learning to read are related to the preliteracy skills that they bring with them from kindergarten. Most tools available to professionals are designed for the evaluation of child language problems. In comparison, there are very few tools for assessing the relations between visual skills and the process of learning to read. Recent literature reports that visual-motor skills and visual-spatial attention in preschoolers are important predictors of reading development — the main goal of this study aimed at improving screening for future reading difficulties in preschool children. We used a prospective, longitudinal approach where oculomotor processes (assessed with the DiagLECT test) were measured in pre-readers, and the impact of these skills on future reading development was explored. The dialect test specifically measures the online time taken to name numbers arranged irregularly in horizontal rows (horizontal time, HT), and the time taken to name numbers arranged in vertical columns (vertical time, VT). A total of 131 preschoolers took part in this study. At Time 0 (kindergarten), the mean VT, HT, errors were recorded. One year later, at Time 1, the reading level of the same children was evaluated. Firstly, this study allowed us to provide normative data for a standardized evaluation of the oculomotor skills in 5- and 6-year-old children. The data also revealed that 25% of our sample of preschoolers showed oculomotor impairments (without any clinical complaints). Finally, the results of this study assessed the validity of the DiagLECT test for predicting reading outcomes; the better a child's oculomotor skills are, the better his/her reading abilities will be.

Keywords: vision, attention, oculomotor processes, reading, preschoolers

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Authors: Engy S. El-Kayal, Mohamed M. S. Arafa

Abstract:

There are various causes of ankle pain including traumatic and non-traumatic causes. Various imaging techniques are available for assessment of AP. MRI is considered to be the imaging modality of choice for ankle joint evaluation with an advantage of its high spatial resolution, multiplanar capability, hence its ability to visualize small complex anatomical structures around the ankle. However, the high costs and the relatively limited availability of MRI systems, as well as the relatively long duration of the examination all are considered disadvantages of MRI examination. Therefore there is a need for a more rapid and less expensive examination modality with good diagnostic accuracy to fulfill this gap. HRU has become increasingly important in the assessment of ankle disorders, with advantages of being fast, reliable, of low cost and readily available. US can visualize detailed anatomical structures and assess tendinous and ligamentous integrity. The aim of this study was to compare the diagnostic accuracy of HRU with MRI in the assessment of patients with AP. We included forty patients complaining of AP. All patients were subjected to real-time HRU and MRI of the affected ankle. Results of both techniques were compared to surgical and arthroscopic findings. All patients were examined according to a defined protocol that includes imaging the tendon tears or tendinitis, muscle tears, masses, or fluid collection, ligament sprain or tears, inflammation or fluid effusion within the joint or bursa, bone and cartilage lesions, erosions and osteophytes. Analysis of the results showed that the mean age of patients was 38 years. The study comprised of 24 women (60%) and 16 men (40%). The accuracy of HRU in detecting causes of AP was 85%, while the accuracy of MRI in the detection of causes of AP was 87.5%. In conclusions: HRU and MRI are two complementary tools of investigation with the former will be used as a primary tool of investigation and the latter will be used to confirm the diagnosis and the extent of the lesion especially when surgical interference is planned.

Keywords: ankle pain (AP), high-resolution ultrasound (HRU), magnetic resonance imaging (MRI) ultrasonography (US)

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