Search results for: impedance function
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5391

Search results for: impedance function

4101 The Usefulness and Usability of a Linkedin Group for the Maintenance of a Community of Practice among Hand Surgeons Worldwide

Authors: Vaikunthan Rajaratnam

Abstract:

Maintaining continuous professional development among clinicians has been a challenge. Hand surgery is a unique speciality with the coming together of orthopaedics, plastics and trauma surgeons. The requirements for a team-based approach to care with the inclusion of other experts such as occupational, physiotherapist and orthotic and prosthetist provide the impetus for the creation of communities of practice. This study analysed the community of practice in hand surgery that was created through a social networking website for professionals. The main objectives were to discover the usefulness of this community of practice created in the platform of the group function of LinkedIn. The second objective was to determine the usability of this platform for the purposes of continuing professional development among members of this community of practice. The methodology used was one of mixed methods which included a quantitative analysis on the usefulness of the social network website as a community of practice, using the analytics provided by the LinkedIn platform. Further qualitative analysis was performed on the various postings that were generated by the community of practice within the social network website. This was augmented by a respondent driven survey conducted online to assess the usefulness of the platform for continuous professional development. A total of 31 respondents were involved in this study. This study has shown that it is possible to create an engaging and interactive community of practice among hand surgeons using the group function of this professional social networking website LinkedIn. Over three years the group has grown significantly with members from multiple regions and has produced engaging and interactive conversations online. From the results of the respondents’ survey, it can be concluded that there was satisfaction of the functionality and that it was an excellent platform for discussions and collaboration in the community of practice with a 69 % of satisfaction. Case-based discussions were the most useful functions of the community of practice. This platform usability was graded as excellent using the validated usability tool. This study has shown that the social networking site LinkedIn’s group function can be easily used as a community of practice effectively and provides convenience to professionals and has made an impact on their practice and better care for patients. It has also shown that this platform was easy to use and has a high level of usability for the average healthcare professional. This platform provided the improved connectivity among professionals involved in hand surgery care which allowed for the community to grow and with proper support and contribution of relevant material by members allowed for a safe environment for the exchange of knowledge and sharing of experience that is the foundation of a community practice.

Keywords: community of practice, online community, hand surgery, lifelong learning, LinkedIn, social media, continuing professional development

Procedia PDF Downloads 316
4100 A Study of Algebraic Structure Involving Banach Space through Q-Analogue

Authors: Abdul Hakim Khan

Abstract:

The aim of the present paper is to study the Banach Space and Combinatorial Algebraic Structure of R. It is further aimed to study algebraic structure of set of all q-extension of classical formula and function for 0 < q < 1.

Keywords: integral functions, q-extensions, q numbers of metric space, algebraic structure of r and banach space

Procedia PDF Downloads 579
4099 Inhouse Inhibitor for Mitigating Corrosion in the Algerian Oil and Gas Industry

Authors: Hadjer Didouh, Mohamed Hadj Meliani, Izzeddine Sameut Bouhaik

Abstract:

As global demand for natural gas intensifies, Algeria is increasing its production to meet this rising need, placing significant strain on the nation's extensive pipeline infrastructure. Sonatrach, Algeria's national oil and gas company, faces persistent challenges from metal corrosion, particularly microbiologically influenced corrosion (MIC), leading to substantial economic losses. This study investigates the corrosion-inhibiting properties of Calotropis procera extracts, known as karanka, as a sustainable alternative to conventional inhibitors, which often pose environmental risks. The Calotropis procera extracts were evaluated for their efficacy on carbon steel API 5L X52 through electrochemical techniques, including potentiodynamic polarization and electrochemical impedance spectroscopy (EIS), under simulated operational conditions at varying concentrations, particularly at 10%, and elevated temperatures up to 60°C. The results demonstrated remarkable inhibition efficiency, achieving 96.73% at 60°C, attributed to the formation of a stable protective film on the metal surface that suppressed anodic and cathodic corrosion reactions. Scanning electron microscopy (SEM) confirmed the stability and adherence of these protective films, while EIS analysis indicated a significant increase in charge transfer resistance, highlighting the extract's effectiveness in enhancing corrosion resistance. The abundant availability of Calotropis procera in Algeria and its low-cost extraction processes present a promising opportunity for sustainable biocorrosion management strategies in the oil and gas industry, reinforcing the potential of plant-based extracts as viable alternatives to synthetic inhibitors for environmentally friendly corrosion control.

Keywords: corrosion inhibition, calotropis procera, microbiologically influenced corrosion, eco-friendly inhibitor

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4098 [Keynote Talk]: Applying p-Balanced Energy Technique to Solve Liouville-Type Problems in Calculus

Authors: Lina Wu, Ye Li, Jia Liu

Abstract:

We are interested in solving Liouville-type problems to explore constancy properties for maps or differential forms on Riemannian manifolds. Geometric structures on manifolds, the existence of constancy properties for maps or differential forms, and energy growth for maps or differential forms are intertwined. In this article, we concentrate on discovery of solutions to Liouville-type problems where manifolds are Euclidean spaces (i.e. flat Riemannian manifolds) and maps become real-valued functions. Liouville-type results of vanishing properties for functions are obtained. The original work in our research findings is to extend the q-energy for a function from finite in Lq space to infinite in non-Lq space by applying p-balanced technique where q = p = 2. Calculation skills such as Hölder's Inequality and Tests for Series have been used to evaluate limits and integrations for function energy. Calculation ideas and computational techniques for solving Liouville-type problems shown in this article, which are utilized in Euclidean spaces, can be universalized as a successful algorithm, which works for both maps and differential forms on Riemannian manifolds. This innovative algorithm has a far-reaching impact on research work of solving Liouville-type problems in the general settings involved with infinite energy. The p-balanced technique in this algorithm provides a clue to success on the road of q-energy extension from finite to infinite.

Keywords: differential forms, holder inequality, Liouville-type problems, p-balanced growth, p-harmonic maps, q-energy growth, tests for series

Procedia PDF Downloads 235
4097 Efficient Implementation of Finite Volume Multi-Resolution Weno Scheme on Adaptive Cartesian Grids

Authors: Yuchen Yang, Zhenming Wang, Jun Zhu, Ning Zhao

Abstract:

An easy-to-implement and robust finite volume multi-resolution Weighted Essentially Non-Oscillatory (WENO) scheme is proposed on adaptive cartesian grids in this paper. Such a multi-resolution WENO scheme is combined with the ghost cell immersed boundary method (IBM) and wall-function technique to solve Navier-Stokes equations. Unlike the k-exact finite volume WENO schemes which involve large amounts of extra storage, repeatedly solving the matrix generated in a least-square method or the process of calculating optimal linear weights on adaptive cartesian grids, the present methodology only adds very small overhead and can be easily implemented in existing edge-based computational fluid dynamics (CFD) codes with minor modifications. Also, the linear weights of this adaptive finite volume multi-resolution WENO scheme can be any positive numbers on condition that their sum is one. It is a way of bypassing the calculation of the optimal linear weights and such a multi-resolution WENO scheme avoids dealing with the negative linear weights on adaptive cartesian grids. Some benchmark viscous problems are numerical solved to show the efficiency and good performance of this adaptive multi-resolution WENO scheme. Compared with a second-order edge-based method, the presented method can be implemented into an adaptive cartesian grid with slight modification for big Reynolds number problems.

Keywords: adaptive mesh refinement method, finite volume multi-resolution WENO scheme, immersed boundary method, wall-function technique.

Procedia PDF Downloads 149
4096 Performance Analysis of New Types of Reference Targets Based on Spaceborne and Airborne SAR Data

Authors: Y. S. Zhou, C. R. Li, L. L. Tang, C. X. Gao, D. J. Wang, Y. Y. Guo

Abstract:

Triangular trihedral corner reflector (CR) has been widely used as point target for synthetic aperture radar (SAR) calibration and image quality assessment. The additional “tip” of the triangular plate does not contribute to the reflector’s theoretical RCS and if it interacts with a perfectly reflecting ground plane, it will yield an increase of RCS at the radar bore-sight and decrease the accuracy of SAR calibration and image quality assessment. Regarding this problem, two types of CRs were manufactured. One was the hexagonal trihedral CR. It is a self-illuminating CR with relatively small plate edge length, while large edge length usually introduces unexpected edge diffraction error. The other was the triangular trihedral CR with extended bottom plate which considers the effect of ‘tip’ into the total RCS. In order to assess the performance of the two types of new CRs, flight campaign over the National Calibration and Validation Site for High Resolution Remote Sensors was carried out. Six hexagonal trihedral CRs and two bottom-extended trihedral CRs, as well as several traditional triangular trihedral CRs, were deployed. KOMPSAT-5 X-band SAR image was acquired for the performance analysis of the hexagonal trihedral CRs. C-band airborne SAR images were acquired for the performance analysis of the bottom-extended trihedral CRs. The analysis results showed that the impulse response function of both the hexagonal trihedral CRs and bottom-extended trihedral CRs were much closer to the ideal sinc-function than the traditional triangular trihedral CRs. The flight campaign results validated the advantages of new types of CRs and they might be useful in the future SAR calibration mission.

Keywords: synthetic aperture radar, calibration, corner reflector, KOMPSAT-5

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4095 Robotic Assisted vs Traditional Laparoscopic Partial Nephrectomy Peri-Operative Outcomes: A Comparative Single Surgeon Study

Authors: Gerard Bray, Derek Mao, Arya Bahadori, Sachinka Ranasinghe

Abstract:

The EAU currently recommends partial nephrectomy as the preferred management for localised cT1 renal tumours, irrespective of surgical approach. With the advent of robotic assisted partial nephrectomy, there is growing evidence that warm ischaemia time may be reduced compared to the traditional laparoscopic approach. There is still no clear differences between the two approaches with regards to other peri-operative and oncological outcomes. Current limitations in the field denote the lack of single surgeon series to compare the two approaches as other studies often include multiple operators of different experience levels. To the best of our knowledge, this study is the first single surgeon series comparing peri-operative outcomes of robotic assisted and laparoscopic PN. The current study aims to reduce intra-operator bias while maintaining an adequate sample size to assess the differences in outcomes between the two approaches. We retrospectively compared patient demographics, peri-operative outcomes, and renal function derangements of all partial nephrectomies undertaken by a single surgeon with experience in both laparoscopic and robotic surgery. Warm ischaemia time, length of stay, and acute renal function deterioration were all significantly reduced with robotic partial nephrectomy, compared to laparoscopic nephrectomy. This study highlights the benefits of robotic partial nephrectomy. Further prospective studies with larger sample sizes would be valuable additions to the current literature.

Keywords: partial nephrectomy, robotic assisted partial nephrectomy, warm ischaemia time, peri-operative outcomes

Procedia PDF Downloads 141
4094 Optimization Modeling of the Hybrid Antenna Array for the DoA Estimation

Authors: Somayeh Komeylian

Abstract:

The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

Procedia PDF Downloads 100
4093 Environmental Controls on the Distribution of Intertidal Foraminifers in Sabkha Al-Kharrar, Saudi Arabia: Implications for Sea-Level Changes

Authors: Talha A. Al-Dubai, Rashad A. Bantan, Ramadan H. Abu-Zied, Brian G. Jones, Aaid G. Al-Zubieri

Abstract:

Contemporary foraminiferal samples sediments were collected from the intertidal sabkha of Al-Kharrar Lagoon, Saudi Arabia, to study the vertical distribution of Foraminifera and, based on a modern training set, their potential to develop a predictor of former sea-level changes in the area. Based on hierarchical cluster analysis, the intertidal sabkha is divided into three vertical zones (A, B & C) represented by three foraminiferal assemblages, where agglutinated species occupied Zone A and calcareous species occupied the other two zones. In Zone A (high intertidal), Agglutinella compressa, Clavulina angularis and C. multicamerata are dominant species with a minor presence of Peneroplis planatus, Coscinospira hemprichii, Sorites orbiculus, Quinqueloculina lamarckiana, Q. seminula, Ammonia convexa and A. tepida. In contrast, in Zone B (middle intertidal) the most abundant species are P. planatus, C. hemprichii, S. orbiculus, Q. lamarckiana, Q. seminula and Q. laevigata, while Zone C (low intertidal) is characterised by C. hemprichii, Q. costata, S. orbiculus, P. planatus, A. convexa, A. tepida, Spiroloculina communis and S. costigera. A transfer function for sea-level reconstruction was developed using a modern dataset of 75 contemporary sediment samples and 99 species collected from several transects across the sabkha. The model provided an error of 0.12m, suggesting that intertidal foraminifers are able to predict the past sea-level changes with high precision in Al-Kharrar Lagoon, and thus the future prediction of those changes in the area.

Keywords: Lagoonal foraminifers, intertidal sabkha, vertical zonation, transfer function, sea level

Procedia PDF Downloads 169
4092 Life Prediction Method of Lithium-Ion Battery Based on Grey Support Vector Machines

Authors: Xiaogang Li, Jieqiong Miao

Abstract:

As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines.For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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4091 Cross-Cultural Adaptation and Validation of the Child Engagement in Daily Life in Greek

Authors: Rigas Dimakopoulos, Marianna Papadopoulou, Roser Pons

Abstract:

Background: Participation in family, recreational activities and self-care is an integral part of health. It is also the main outcome of rehabilitation services for children and adolescents with motor disabilities. There are currently no tools in Greek to assess participation in young children. Purpose: To culturally adapt and validate the Greek version of the Child Engagement in Daily Living (CEDL). Method: The CEDL was cross-culturally translated into Greek using forward-backward translation, review by the expert committee, pretest application and final review. Internal consistency was evaluated using the Cronbach alpha and test-retest reliability using the intra-class correlation coefficient (ICC). Parents of children aged 18 months to 5 years and with motor disabilities were recruited. Participants completed the CEDL and the children’s gross motor function was classified using the Gross Motor Function Classification System (GMFCS). Results: Eighty-three children were included, GMFCS I-V. Mean ± standard deviation of the CEDL domains “frequency of participation” “enjoyment of participation” and “self-care” were 58.4±14.0, 3.8±1.0 and 49.9±24, respectively. Internal consistency of all domains was high; Cronbach alpha for “frequency of participation” was 0.83, for “enjoyment of participation” was 0.76 and for “self-care” was 0.92. Test-retest reliability (ICC) was excellent for the “self-care” (0.95) and good for “frequency of participation” and “enjoyment of participation” domains (0.90 and 0.88, respectively). Conclusion: The Greek CEDL has good reliability. It can be used to evaluate participation in Greek young children with motor disabilities GMFCS levels I-V.

Keywords: participation, child, disabilities, child engagement in daily living

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4090 An Analytical Approach of Computational Complexity for the Method of Multifluid Modelling

Authors: A. K. Borah, A. K. Singh

Abstract:

In this paper we deal building blocks of the computer simulation of the multiphase flows. Whole simulation procedure can be viewed as two super procedures; The implementation of VOF method and the solution of Navier Stoke’s Equation. Moreover, a sequential code for a Navier Stoke’s solver has been studied.

Keywords: Bi-conjugate gradient stabilized (Bi-CGSTAB), ILUT function, krylov subspace, multifluid flows preconditioner, simple algorithm

Procedia PDF Downloads 528
4089 Clouds Influence on Atmospheric Ozone from GOME-2 Satellite Measurements

Authors: S. M. Samkeyat Shohan

Abstract:

This study is mainly focused on the determination and analysis of the photolysis rate of atmospheric, specifically tropospheric, ozone as function of cloud properties through-out the year 2007. The observational basis for ozone concentrations and cloud properties are the measurement data set of the Global Ozone Monitoring Experiment-2 (GOME-2) sensor on board the polar orbiting Metop-A satellite. Two different spectral ranges are used; ozone total column are calculated from the wavelength window 325 – 335 nm, while cloud properties, such as cloud top height (CTH) and cloud optical thick-ness (COT) are derived from the absorption band of molecular oxygen centered at 761 nm. Cloud fraction (CF) is derived from measurements in the ultraviolet, visible and near-infrared range of GOME-2. First, ozone concentrations above clouds are derived from ozone total columns, subtracting the contribution of stratospheric ozone and filtering those satellite measurements which have thin and low clouds. Then, the values of ozone photolysis derived from observations are compared with theoretical modeled results, in the latitudinal belt 5˚N-5˚S and 20˚N - 20˚S, as function of CF and COT. In general, good agreement is found between the data and the model, proving both the quality of the space-borne ozone and cloud properties as well as the modeling theory of ozone photolysis rate. The found discrepancies can, however, amount to approximately 15%. Latitudinal seasonal changes of photolysis rate of ozone are found to be negatively correlated to changes in upper-tropospheric ozone concentrations only in the autumn and summer months within the northern and southern tropical belts, respectively. This fact points to the entangled roles of temperature and nitrogen oxides in the ozone production, which are superimposed on its sole photolysis induced by thick and high clouds in the tropics.

Keywords: cloud properties, photolysis rate, stratospheric ozone, tropospheric ozone

Procedia PDF Downloads 211
4088 Effects of Turkish Classical Music on Cognitive Function, Depression and Quality of Life in Elderly

Authors: Rukiye Pinar Boluktas

Abstract:

According to 2015 statistics, in Turkey, 46% of older people live alone in their homes, 55% have poor health perceptions, 18% face poverty, and 43% are unhappy. Prevalence of depression is between 14% and 20%. In 2013, rate of suicide was 6.5. However, the most of older people prefer to live in their community although they are lonely, they face poverty, and face limitations as a result of chronic diseases and disabilities. Community based care for older people is also encouraged by Ministry of Health as it is more cost-effective. Music therapy is a simple, effective, safe, and nonpharmacologic intervention that may be used to decrease depression and to improve cognition, and health related quality of life (HRQOL). In Turkish culture, music is typically described as ‘food for soul’. This study aimed to investigate the effect of Turkish classical music songs in 32 community dwelling older people. Participants were received interventions two or three times per week, 50-60 min per session, for 8 weeks at a day health center. Each intervention session started listening music for 15-20 min to get remember songs, then followed singing songs as a group. Participants were assessed at baseline (week 0), and two follow-up at month 1 and month 2. Compared to baseline, at two follow-up, we observed that cognition improved, depression decreased, and SF-36 scores, including 8 domains and two summary scores increased. We conclude that an intervention comprising listening and singing Turkish classical music improve cognition, depression and HRQOL in older people.

Keywords: cognitive function, depression, elderly, quality of life, Turkish classical music

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4087 A Relative Entropy Regularization Approach for Fuzzy C-Means Clustering Problem

Authors: Ouafa Amira, Jiangshe Zhang

Abstract:

Clustering is an unsupervised machine learning technique; its aim is to extract the data structures, in which similar data objects are grouped in the same cluster, whereas dissimilar objects are grouped in different clusters. Clustering methods are widely utilized in different fields, such as: image processing, computer vision , and pattern recognition, etc. Fuzzy c-means clustering (fcm) is one of the most well known fuzzy clustering methods. It is based on solving an optimization problem, in which a minimization of a given cost function has been studied. This minimization aims to decrease the dissimilarity inside clusters, where the dissimilarity here is measured by the distances between data objects and cluster centers. The degree of belonging of a data point in a cluster is measured by a membership function which is included in the interval [0, 1]. In fcm clustering, the membership degree is constrained with the condition that the sum of a data object’s memberships in all clusters must be equal to one. This constraint can cause several problems, specially when our data objects are included in a noisy space. Regularization approach took a part in fuzzy c-means clustering technique. This process introduces an additional information in order to solve an ill-posed optimization problem. In this study, we focus on regularization by relative entropy approach, where in our optimization problem we aim to minimize the dissimilarity inside clusters. Finding an appropriate membership degree to each data object is our objective, because an appropriate membership degree leads to an accurate clustering result. Our clustering results in synthetic data sets, gaussian based data sets, and real world data sets show that our proposed model achieves a good accuracy.

Keywords: clustering, fuzzy c-means, regularization, relative entropy

Procedia PDF Downloads 259
4086 Bio-Inspired Design Approach Analysis: A Case Study of Antoni Gaudi and Santiago Calatrava

Authors: Marzieh Imani

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Antoni Gaudi and Santiago Calatrava have reputation for designing bio-inspired creative and technical buildings. Even though they have followed different independent approaches towards design, the source of bio-inspiration seems to be common. Taking a closer look at their projects reveals that Calatrava has been influenced by Gaudi in terms of interpreting nature and applying natural principles into the design process. This research firstly discusses the dialogue between Biomimicry and architecture. This review also explores human/nature discourse during the history by focusing on how nature revealed itself to the fine arts. This is explained by introducing naturalism and romantic style in architecture as the outcome of designers’ inclination towards nature. Reviewing the literature, theoretical background and practical illustration of nature have been included. The most dominant practical aspects of imitating nature are form and function. Nature has been reflected in architectural science resulted in shaping different architectural styles such as organic, green, sustainable, bionic, and biomorphic. By defining a set of common aspects of Gaudi and Calatrava‘s design approach and by considering biomimetic design categories (organism, ecosystem, and behaviour as the main division and form, function, process, material, and construction as subdivisions), Gaudi’s and Calatrava’s project have been analysed. This analysis explores if their design approaches are equivalent or different. Based on this analysis, Gaudi’s architecture can be recognised as biomorphic while Calatrava’s projects are literally biomimetic. Referring to these architects, this review suggests a new set of principles by which a bio-inspired project can be determined either biomorphic or biomimetic.

Keywords: biomimicry, Calatrava, Gaudi, nature

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4085 Physics-Informed Convolutional Neural Networks for Reservoir Simulation

Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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4084 Certain Results of a New Class of Meromorphic Multivalent Functions Involving Ruscheweyh Derivative

Authors: Kassim A. Jassim

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In the present paper, we introduce and discuss a new class Kp(λ,α) of meromorphic multivalent functions in the punctured unit disk U*={z∈¢:0<|z|<1} defined by Ruscheweyh derivative. We obtain some sufficient conditions for the functions belonging to the class Kp(λ,α).

Keywords: meromorphic multivalent function, Ruscheweyh derivative, hadamard product

Procedia PDF Downloads 336
4083 Single Ion Conductors for Lithium-Ion Battery Application

Authors: Seyda Tugba Gunday Anil, Ayhan Bozkurt

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Next generation lithium batteries are taking more attention and single-ion polymer electrolytes are expected to play a significant role in the development of these kinds of energy storage systems. In the present work we used a different strategy to design of novel solid single-ion conducting inorganic polymer electrolytes based on lithium polyvinyl alcohol oxalate borate (Li(PVAOB), lithium polyacrylic acid oxalate borate (LiPAAOB) and poly (ethylene glycol) methacrylate (PEGMA). Free radical polymerization was used to convert PEGMA into PPEGMA and LiPAAOB is prepared from poly (acrylic acid), oxalic acid and boric acid. Blend polymer electrolytes were produced by mixing of LiPAAOB or Li (PVAOB with PPEGMA at different stoichiometric ratios to enhance the single ion conductivity of the systems. To exploit the flexible chemistry and increase the segmental mobility of the blend electrolyte, the composition was changed up to 80% with respect to the guest polymer, PPEGMA. FT-IR and differential scanning calorimeter techniques confirmed the interaction between the host and guest polymers. TGA verified that the thermal stability of the blends increased up to approximately 200 C. Scanning electron microscopy images confirm the homogeneity of the blend electrolytes. CV studies showed that electrochemical stability electrochemical stability window is approximately 5 V versus Li/Li⁺. The effect of PPEGMA on to the Lithium-ion conductivity was investigated using dielectric impedance analyzer. The maximum single ion conductivity was measured as 1.3 × 10⁻⁴ S/cm at 100 C for the sample LiPAAOB-80PPEGMA. Clearly, the results confirmed the positive effect to the increment in ionic conductivity of the blend electrolytes with the addition of PPEGMA.

Keywords: single-ion conductor, inorganic polymer, blends, polymer electrolyte

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4082 DUSP16 Inhibition Rescues Neurogenic and Cognitive Deficits in Alzheimer's Disease Mice Models

Authors: Huimin Zhao, Xiaoquan Liu, Haochen Liu

Abstract:

The major challenge facing Alzheimer's Disease (AD) drug development is how to effectively improve cognitive function in clinical practice. Growing evidence indicates that stimulating hippocampal neurogenesis is a strategy for restoring cognition in animal models of AD. The mitogen-activated protein kinase (MAPK) pathway is a crucial factor in neurogenesis, which is negatively regulated by Dual-specificity phosphatase 16 (DUSP16). Transcriptome analysis of post-mortem brain tissue revealed up-regulation of DUSP16 expression in AD patients. Additionally, DUSP16 was involved in regulating the proliferation and neural differentiation of neural progenitor cells (NPCs). Nevertheless, whether the effect of DUSP16 on ameliorating cognitive disorders by influencing NPCs differentiation in AD mice remains unclear. Our study demonstrates an association between DUSP16 SNPs and clinical progression in individuals with mild cognitive impairment (MCI). Besides, we found that increased DUSP16 expression in both 3×Tg and SAMP8 models of AD led to NPC differentiation impairments. By silencing DUSP16, cognitive benefits, the induction of AHN and synaptic plasticity, were observed in AD mice. Furthermore, we found that DUSP16 is involved in the process of NPC differentiation by regulating c-Jun N-terminal kinase (JNK) phosphorylation. Moreover, the increased DUSP16 may be regulated by the ETS transcription factor (ELK1), which binds to the promoter region of DUSP16. Loss of ELK1 resulted in decreased DUSP16 mRNA and protein levels. Our data uncover a potential regulatory role for DUSP16 in adult hippocampal neurogenesis and provide a possibility to find the target of AD intervention.

Keywords: alzheimer's disease, cognitive function, DUSP16, hippocampal neurogenesis

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4081 Psychological Nano-Therapy: A New Method in Family Therapy

Authors: Siamak Samani, Nadereh Sohrabi

Abstract:

Psychological nano-therapy is a new method based on systems theory. According to the theory, systems with severe dysfunctions are resistant to changes. Psychological nano-therapy helps the therapists to break this ice. Two key concepts in psychological nano-therapy are nano-functions and nano-behaviors. The most important step in psychological nano-therapy in family therapy is selecting the most effective nano-function and nano-behavior. The aim of this study was to check the effectiveness of psychological nano-therapy for family therapy. One group pre-test-post-test design (quasi-experimental Design) was applied for research. The sample consisted of ten families with severe marital conflict. The important character of these families was resistance for participating in family therapy. In this study, sending respectful (nano-function) text massages (nano-behavior) with cell phone were applied as a treatment. Cohesion/respect sub scale from self-report family processes scale and family readiness for therapy scale were used to assess all family members in pre-test and post-test. In this study, one of family members was asked to send a respectful text massage to other family members every day for a week. The content of the text massages were selected and checked by therapist. To compare the scores of families in pre-test and post-test paired sample t-test was used. The results of the test showed significant differences in both cohesion/respect score and family readiness for therapy between per-test and post-test. The results revealed that these families have found a better atmosphere for participation in a complete family therapy program. Indeed, this study showed that psychological nano-therapy is an effective method to make family readiness for therapy.

Keywords: family therapy, family conflicts, nano-therapy, family readiness

Procedia PDF Downloads 659
4080 Evaluation of Ensemble Classifiers for Intrusion Detection

Authors: M. Govindarajan

Abstract:

One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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4079 Design of Two-Channel Quadrature Mirror Filter Banks Using a Transformation Approach

Authors: Ju-Hong Lee, Yi-Lin Shieh

Abstract:

Two-dimensional (2-D) quadrature mirror filter (QMF) banks have been widely considered for high-quality coding of image and video data at low bit rates. Without implementing subband coding, a 2-D QMF bank is required to have an exactly linear-phase response without magnitude distortion, i.e., the perfect reconstruction (PR) characteristics. The design problem of 2-D QMF banks with the PR characteristics has been considered in the literature for many years. This paper presents a transformation approach for designing 2-D two-channel QMF banks. Under a suitable one-dimensional (1-D) to two-dimensional (2-D) transformation with a specified decimation/interpolation matrix, the analysis and synthesis filters of the QMF bank are composed of 1-D causal and stable digital allpass filters (DAFs) and possess the 2-D doubly complementary half-band (DC-HB) property. This facilitates the design problem of the two-channel QMF banks by finding the real coefficients of the 1-D recursive DAFs. The design problem is formulated based on the minimax phase approximation for the 1-D DAFs. A novel objective function is then derived to obtain an optimization for 1-D minimax phase approximation. As a result, the problem of minimizing the objective function can be simply solved by using the well-known weighted least-squares (WLS) algorithm in the minimax (L∞) optimal sense. The novelty of the proposed design method is that the design procedure is very simple and the designed 2-D QMF bank achieves perfect magnitude response and possesses satisfactory phase response. Simulation results show that the proposed design method provides much better design performance and much less design complexity as compared with the existing techniques.

Keywords: Quincunx QMF bank, doubly complementary filter, digital allpass filter, WLS algorithm

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4078 Analyzing the Impact of Bariatric Surgery in Obesity Associated Chronic Kidney Disease: A 2-Year Observational Study

Authors: Daniela Magalhaes, Jorge Pedro, Pedro Souteiro, Joao S. Neves, Sofia Castro-Oliveira, Vanessa Guerreiro, Rita Bettencourt- Silva, Maria M. Costa, Ana Varela, Joana Queiros, Paula Freitas, Davide Carvalho

Abstract:

Introduction: Obesity is an independent risk factor for renal dysfunction. Our aims were: (1) evaluate the impact of bariatric surgery (BS) on renal function; (2) clarify the factors determining the postoperative evolution of the glomerular filtration rate (GFR); (3) access the occurrence of oxalate-mediated renal complications. Methods: We investigated a cohort of 1448 obese patients who underwent bariatric surgery. Those with basal GFR (GFR0) < 30mL/min or without information about the GFR 2-year post-surgery (GFR2) were excluded. Results: We included 725 patients, of whom 647 (89.2%) women, with 41 (IQR 34-51) years, a median weight of 112.4 (IQR 103.0-125.0) kg and a median BMI of 43.4 (IQR 40.6-46.9) kg/m2. Of these, 459 (63.3%) performed gastric bypass (RYGB), 144 (19.9%) placed an adjustable gastric band (AGB) and 122 (16.8%) underwent vertical gastrectomy (VG). At 2-year post-surgery, excess weight loss (EWL) was 60.1 (IQR 43.7-72.4) %. There was a significant improve of metabolic and inflammatory status, as well as a significant decrease in the proportion of patients with diabetes, arterial hypertension and dyslipidemia (p < 0.0001). At baseline, 38 (5.2%) of subjects had hyperfiltration with a GFR0 ≥ 125mL/min/1.73m2, 492 (67.9%) had a GFR0 90-124 mL/min/1.73m2, 178 (24.6%) had a GFR0 60-89 mL/min/1.73m2, and 17 (2.3%) had a GFR0 < 60 mL/min/1.73m2. GFR decreased in 63.2% of patients with hyperfiltration (ΔGFR=-2.5±7.6), and increased in 96.6% (ΔGFR=22.2±12.0) and 82.4% (ΔGFR=24.3±30.0) of the subjects with GFR0 60-89 and < 60 mL/min/1.73m2, respectively ( p < 0.0001). This trend was maintained when adjustment was made for the type of surgery performed. Of 321 patients, 10 (3.3%) had a urinary albumin excretion (UAE) > 300 mg/dL (A3), 44 (14.6%) had a UAE 30-300 mg/dL (A2) and 247 (82.1%) has a UAE < 30 mg/dL (A1). Albuminuria decreased after surgery and at 2-year follow-up only 1 (0.3%) patient had A3, 17 (5.6%) had A2 and 283 (94%) had A1 (p < 0,0001). In multivariate analysis, the variables independently associated with ΔGFR were BMI (positively) and fasting plasma glucose (negatively). During the 2-year follow-up, only 57 of the 725 patients had transient urinary excretion of calcium oxalate crystals. None has records of oxalate-mediated renal complications at our center. Conclusions: The evolution of GFR after BS seems to depend on the initial renal function, as it decreases in subjects with hyperfiltration, but tends to increase in those with renal dysfunction. Our results suggest that BS is associated with improvement of renal outcomes, without significant increase of renal complications. So, apart the clear benefits in metabolic and inflammatory status, maybe obese adults with nondialysis-dependent CKD should be referred for bariatric surgery evaluation.

Keywords: albuminuria, bariatric surgery, glomerular filtration rate, renal function

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4077 Forest Soil Greenhouse Gas Real-Time Analysis Using Quadrupole Mass Spectrometry

Authors: Timothy L. Porter, T. Randy Dillingham

Abstract:

Vegetation growth and decomposition, along with soil microbial activity play a complex role in the production of greenhouse gases originating in forest soils. The absorption or emission (respiration) of these gases is a function of many factors relating to the soils themselves, the plants, and the environment in which the plants are growing. For this study, we have constructed a battery-powered, portable field mass spectrometer for use in analyzing gases in the soils surrounding trees, plants, and other areas. We have used the instrument to sample in real-time the greenhouse gases carbon dioxide and methane in soils where plant life may be contributing to the production of gases such as methane. Gases such as isoprene, which may help correlate gas respiration to microbial activity have also been measured. The instrument is composed of a quadrupole mass spectrometer with part per billion or better sensitivity, coupled to battery-powered turbo and diaphragm pumps. A unique ambient air pressure differentially pumped intake apparatus allows for the real-time sampling of gases in the soils from the surface to several inches below the surface. Results show that this instrument is capable of instant, part-per-billion sensitivity measurement of carbon dioxide and methane in the near surface region of various forest soils. We have measured differences in soil respiration resulting from forest thinning, forest burning, and forest logging as compared to pristine, untouched forests. Further studies will include measurements of greenhouse gas respiration as a function of temperature, microbial activity as measured by isoprene production, and forest restoration after fire.

Keywords: forest, soil, greenhouse, quadrupole

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4076 Vibration Absorption Strategy for Multi-Frequency Excitation

Authors: Der Chyan Lin

Abstract:

Since the early introduction by Ormondroyd and Den Hartog, vibration absorber (VA) has become one of the most commonly used vibration mitigation strategies. The strategy is most effective for a primary plant subjected to a single frequency excitation. For continuous systems, notable advances in vibration absorption in the multi-frequency system were made. However, the efficacy of the VA strategy for systems under multi-frequency excitation is not well understood. For example, for an N degrees-of-freedom (DOF) primary-absorber system, there are N 'peak' frequencies of large amplitude vibration per every new excitation frequency. In general, the usable range for vibration absorption can be greatly reduced as a result. Frequency modulated harmonic excitation is a commonly seen multi-frequency excitation example: f(t) = cos(ϖ(t)t) where ϖ(t)=ω(1+α sin⁡(δt)). It is known that f(t) has a series expansion given by the Bessel function of the first kind, which implies an infinity of forcing frequencies in the frequency modulated harmonic excitation. For an SDOF system of natural frequency ωₙ subjected to f(t), it can be shown that amplitude peaks emerge at ω₍ₚ,ₖ₎=(ωₙ ± 2kδ)/(α ∓ 1),k∈Z; i.e., there is an infinity of resonant frequencies ω₍ₚ,ₖ₎, k∈Z, making the use of VA strategy ineffective. In this work, we propose an absorber frequency placement strategy for SDOF vibration systems subjected to frequency-modulated excitation. An SDOF linear mass-spring system coupled to lateral absorber systems is used to demonstrate the ideas. Although the mechanical components are linear, the governing equations for the coupled system are nonlinear. We show using N identical absorbers, for N ≫ 1, that (a) there is a cluster of N+1 natural frequencies around every natural absorber frequency, and (b) the absorber frequencies can be moved away from the plant's resonance frequency (ω₀) as N increases. Moreover, we also show the bandwidth of the VA performance increases with N. The derivations of the clustering and bandwidth widening effect will be given, and the superiority of the proposed strategy will be demonstrated via numerical experiments.

Keywords: Bessel function, bandwidth, frequency modulated excitation, vibration absorber

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4075 Endothelial Dysfunction in Non-Alcoholic Fatty Liver Disease: An Updated Meta-Analysis

Authors: Anit S. Malhotra, Ajay Duseja, Neelam Chadha

Abstract:

Endothelial dysfunction is a precursor to atherosclerosis, and flow-mediated dilatation (FMD) in the brachial artery is the commonest method to evaluate endothelial function in humans. Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver disorders encountered in clinical practice. An earlier meta-analysis had quantitatively assessed the degree of endothelial dysfunction using FMD. However, the largest study investigating the relation of FMD with NAFLD was published after that meta-analysis. In addition, that meta-analysis did not include some studies, including one from our centre. Therefore, an updating the previous meta-analysis was considered important. We searched PubMed, Cochrane Library, Embase, Scopus, SCI, Google Scholar, conference proceedings, and references of included studies till June 2017 to identify observational studies evaluating endothelial function using FMD in patients with non-alcoholic fatty liver disease. Data was analyzed using MedCalc. Fourteen studies were found eligible for inclusion in the meta-analysis. Patients with NAFLD had lower brachial artery FMD as compared to controls, standardized mean difference (random effects model) being –1.279%; 95% confidence interval (CI), –1.478 to –0.914. The effect size became smaller after addition of the recent study with the largest sample size was included compared with the earlier meta-analysis. In conclusion, patients with NAFLD had low FMD values indicating that they are at a higher risk of cardiovascular disease although our results suggest the effect size is not as large as reported previously.

Keywords: endothelial dysfunction, flow-mediated dilatation, meta-analysis, non-alcoholic fatty liver disease

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4074 Function Study of IrMYB55 in Regulating Synthesis of Terpenoids in Isodon Rubescens

Authors: Qingfang Guo

Abstract:

Isodon rubescens is rich in a variety of terpenes such as oridonin. It has important medicinal value. MYB transcription factors are involved in the regulation of plant secondary metabolic pathways. The combined transcriptomics and metabolomics analysis revealed that IrMYB55 might be involved in the regulation of the synthesis of terpenes. The function of IrMYB55 was further verified by establishing of a genetic transformation system by CRISPR/Cas9. Obtaining a virus-mediated Isodon rubescens gene silencing material. The main research results are as follows: (1) Screening IrMYB which can regulate the synthesis of terpenes. Metabolomics and transcriptomics analyses of materials with high (TJ)-and low (FL)-content populations which revealed significant differences in terpene content and IrMYB55 expression. Correlation analysis showed that the expression level of IrMYB55 had a significant correlation with the content of terpenes. (2) Establishment of a genetic transformation system of Isodon rubescens. The IrPDS gene could be knocked out by injection of Isodon rubescens cotyledon, and the transformed material showed obvious albino phenotype. Subsequently, IrMYB55 conversion material was obtained by this method. (3) The IrMYB55 silencing material was obtained. Subcellular localization indicated that IrMYB55 was located in the nucleus, indicating that it might regulate the synthesis of terpenoids through transcription. In summary, IrMYB55 that may regulate the synthesis of oridonin was dug out from the transcriptome and metabolome data. In this study, a genetic transformation system of Isodon rubescens was successfully established. Further studies showed that IrMYB55 regulated the transcription level of genes related to the synthesis of terpenoids, thereby promoting the accumulation of oridonin.

Keywords: isodon rubescens, MYB, oridonin, CRISPR/Cas9

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4073 Artificial Intelligence Based Predictive Models for Short Term Global Horizontal Irradiation Prediction

Authors: Kudzanayi Chiteka, Wellington Makondo

Abstract:

The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.

Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models

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4072 Assessing the Blood-Brain Barrier (BBB) Permeability in PEA-15 Mutant Cat Brain using Magnetization Transfer (MT) Effect at 7T

Authors: Sultan Z. Mahmud, Emily C. Graff, Adil Bashir

Abstract:

Phosphoprotein enriched in astrocytes 15 kDa (PEA-15) is a multifunctional adapter protein which is associated with the regulation of apoptotic cell death. Recently it has been discovered that PEA-15 is crucial in normal neurodevelopment of domestic cats, a gyrencephalic animal model, although the exact function of PEA-15 in neurodevelopment is unknown. This study investigates how PEA-15 affects the blood-brain barrier (BBB) permeability in cat brain, which can cause abnormalities in tissue metabolite and energy supplies. Severe polymicrogyria and microcephaly have been observed in cats with a loss of function PEA-15 mutation, affecting the normal neurodevelopment of the cat. This suggests that the vital role of PEA-15 in neurodevelopment is associated with gyrification. Neurodevelopment is a highly energy demanding process. The mammalian brain depends on glucose as its main energy source. PEA-15 plays a very important role in glucose uptake and utilization by interacting with phospholipase D1 (PLD1). Mitochondria also plays a critical role in bioenergetics and essential to supply adequate energy needed for neurodevelopment. Cerebral blood flow regulates adequate metabolite supply and recent findings also showed that blood plasma contains mitochondria as well. So the BBB can play a very important role in regulating metabolite and energy supply in the brain. In this study the blood-brain permeability in cat brain was measured using MRI magnetization transfer (MT) effect on the perfusion signal. Perfusion is the tissue mass normalized supply of blood to the capillary bed. Perfusion also accommodates the supply of oxygen and other metabolites to the tissue. A fraction of the arterial blood can diffuse to the tissue, which depends on the BBB permeability. This fraction is known as water extraction fraction (EF). MT is a process of saturating the macromolecules, which has an effect on the blood that has been diffused into the tissue while having minimal effect on intravascular blood water that has not been exchanged with the tissue. Measurement of perfusion signal with and without MT enables to estimate the microvascular blood flow, EF and permeability surface area product (PS) in the brain. All the experiments were performed with Siemens 7T Magnetom with 32 channel head coil. Three control cats and three PEA-15 mutant cats were used for the study. Average EF in white and gray matter was 0.9±0.1 and 0.86±0.15 respectively, perfusion in white and gray matter was 85±15 mL/100g/min and 97±20 mL/100g/min respectively, PS in white and gray matter was 201±25 mL/100g/min and 225±35 mL/100g/min respectively for control cats. For PEA-15 mutant cats, average EF in white and gray matter was 0.81±0.15 and 0.77±0.2 respectively, perfusion in white and gray matter was 140±25 mL/100g/min and 165±18 mL/100g/min respectively, PS in white and gray matter was 240±30 mL/100g/min and 259±21 mL/100g/min respectively. This results show that BBB is compromised in PEA-15 mutant cat brain, where EF is decreased and perfusion as well as PS are increased in the mutant cats compared to the control cats. This findings might further explain the function of PEA-15 in neurodevelopment.

Keywords: BBB, cat brain, magnetization transfer, PEA-15

Procedia PDF Downloads 143