Search results for: objective function
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10965

Search results for: objective function

10575 Value Engineering and Its Impact on Drainage Design Optimization for Penang International Airport Expansion

Authors: R.M. Asyraf, A. Norazah, S.M. Khairuddin, B. Noraziah

Abstract:

Designing a system at present requires a vital, challenging task; to ensure the design philosophy is maintained in economical ways. This paper perceived the value engineering (VE) approach applied in infrastructure works, namely stormwater drainage. This method is adopted in line as consultants have completed the detailed design. Function Analysis System Technique (FAST) diagram and VE job plan, information, function analysis, creative judgement, development, and recommendation phase are used to scrutinize the initial design of stormwater drainage. An estimated cost reduction using the VE approach of 2% over the initial proposal was obtained. This cost reduction is obtained from the design optimization of the drainage foundation and structural system, where the pile design and drainage base structure are optimized. Likewise, the design of the on-site detention tank (OSD) pump was revised and contribute to the cost reduction obtained. This case study shows that the VE approach can be an important tool in optimizing the design to reduce costs.

Keywords: value engineering, function analysis system technique, stormwater drainage, cost reduction

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10574 RBF Neural Network Based Adaptive Robust Control for Bounded Position/Force Control of Bilateral Teleoperation Arms

Authors: Henni Mansour Abdelwaheb

Abstract:

This study discusses the design of a bounded position/force feedback controller developed to ensure position and force tracking for bilateral teleoperation arms operating with variable delay, and actuator saturation. Also, an adaptive robust Radial Basis Function (RBF) neural network is used to estimate the environment torque. The parameters of the environment torque are then sent from the slave site to the master site as a non-power signal to avoid passivity problems. Moreover, a nonlinear function is applied to each controller term as a smooth saturation function, providing a bounded control signal and preserving the system’s actuators. Lastly, the Lyapunov approach demonstrates the global stability of the controlled system, and numerical experiment results further confirm the validity of the presented strategy.

Keywords: teleoperation manipulators system, time-varying delay, actuator saturation, adaptive robust rbf neural network approximation, uncertainties

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10573 Transfer Learning for Protein Structure Classification at Low Resolution

Authors: Alexander Hudson, Shaogang Gong

Abstract:

Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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10572 Reduction of the Number of Traffic Accidents by Function of Driver's Anger Detection

Authors: Masahiro Miyaji

Abstract:

When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).

Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety

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10571 A High-Level Co-Evolutionary Hybrid Algorithm for the Multi-Objective Job Shop Scheduling Problem

Authors: Aydin Teymourifar, Gurkan Ozturk

Abstract:

In this paper, a hybrid distributed algorithm has been suggested for the multi-objective job shop scheduling problem. Many new approaches are used at design steps of the distributed algorithm. Co-evolutionary structure of the algorithm and competition between different communicated hybrid algorithms, which are executed simultaneously, causes to efficient search. Using several machines for distributing the algorithms, at the iteration and solution levels, increases computational speed. The proposed algorithm is able to find the Pareto solutions of the big problems in shorter time than other algorithm in the literature. Apache Spark and Hadoop platforms have been used for the distribution of the algorithm. The suggested algorithm and implementations have been compared with results of the successful algorithms in the literature. Results prove the efficiency and high speed of the algorithm.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, multi-objective optimization

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10570 Comparative Analysis of Sigmoidal Feedforward Artificial Neural Networks and Radial Basis Function Networks Approach for Localization in Wireless Sensor Networks

Authors: Ashish Payal, C. S. Rai, B. V. R. Reddy

Abstract:

With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to explore them in more effective and efficient manner. An important area which can bring efficiency to WSNs is the localization process, which refers to the estimation of the position of wireless sensor nodes in an ad hoc network setting, in reference to a coordinate system that may be internal or external to the network. In this paper, we have done comparison and analysed Sigmoidal Feedforward Artificial Neural Networks (SFFANNs) and Radial Basis Function (RBF) networks for developing localization framework in WSNs. The presented work utilizes the Received Signal Strength Indicator (RSSI), measured by static node on 100 x 100 m2 grid from three anchor nodes. The comprehensive evaluation of these approaches is done using MATLAB software. The simulation results effectively demonstrate that FFANNs based sensor motes will show better localization accuracy as compared to RBF.

Keywords: localization, wireless sensor networks, artificial neural network, radial basis function, multi-layer perceptron, backpropagation, RSSI, GPS

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10569 Overall Function and Symptom Impact of Self-Applied Myofascial Release in Adult Patients With Fibromyalgia. A Seven-Week Pilot Study

Authors: Domenica Tambasco, Riina Bray, Sophia Jaworski, Gillian Grant, Celeste Corkery

Abstract:

Fibromyalgia is a chronic condition characterized by widespread musculoskeletal pain, fatigue, and reduced function. Management of symptoms include medications, physical treatments and mindfulness therapies. Myofascial Release is a modality that has been successfully applied in var-ious musculoskeletal conditions. However, to the author’s best knowledge, it is not yet recog-nized as a self-management therapy option in Fibromyalgia. In this study, we investigated whether Self-applied Myofascial Release (SMR) is associated with overall improved function and symptoms in Fibromyalgia. Methods: Eligible adult patients with a confirmed diagnosis of Fibromyalgia at Women’s College Hospital were recruited to SMR. Sessions ran for 1 hour once a week for 7 weeks, led by the same two Physiotherapists knowledgeable in this physical treat-ment modality. The main outcome measure was an overall impact score for function and symp-toms based on the validated assessment tool for Fibromyalgia, the Revised Fibromyalgia Impact Questionnaire (FIQR), measured pre and post-intervention. Both descriptive and analytical methods were applied and reported. Results: We analyzed results using a paired t-test to deter-mine if there was a statistically significant difference in mean FIQR scores between initial (pre-intervention) and final (post-intervention) scores. A clinically significant difference in FIQR was defined as a reduction in score by 10 or more points. Conclusions: Our pilot study showed that SMR appeared to be a safe and effective intervention for our Fibromyalgia participants and the overall impact on function and symptoms occurred in only 7 weeks. Further studies with larger sample sizes comparing SMR to other physical treatment modalities (such as stretching) in an RCT are recommended.

Keywords: fibromyalgia, myofascial release, physical therapy, FIQR

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10568 A New Distribution and Application on the Lifetime Data

Authors: Gamze Ozel, Selen Cakmakyapan

Abstract:

We introduce a new model called the Marshall-Olkin Rayleigh distribution which extends the Rayleigh distribution using Marshall-Olkin transformation and has increasing and decreasing shapes for the hazard rate function. Various structural properties of the new distribution are derived including explicit expressions for the moments, generating and quantile function, some entropy measures, and order statistics are presented. The model parameters are estimated by the method of maximum likelihood and the observed information matrix is determined. The potentiality of the new model is illustrated by means of real life data set.

Keywords: Marshall-Olkin distribution, Rayleigh distribution, estimation, maximum likelihood

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10567 A Brouwer-Tarski Fixed-Point Theorem

Authors: Philippe Bich, Yu Lu

Abstract:

We provide n-dimensional fixed-point theorems for possibly discontinuous functions which extend Brouwer’s fixed-point theorem and encompass interesting cases of Tarski’s fixed-point theorem. The main idea is to require that at any discontinuity point where the graph of the function “crosses the diagonal”, the function satisfies a specific assumption (similar to upward jumps). For this purpose, we classify some types of discontinuities, and use them to prove our new fixed-point theorems, with some applications in game theory.

Keywords: fixed-point, Brouwer's fixed-point theorem, Tarski's fixed-point theorem, discontinuity, Nash equilibrium, supermodular game

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10566 Loss Function Optimization for CNN-Based Fingerprint Anti-Spoofing

Authors: Yehjune Heo

Abstract:

As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

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10565 Theoretical Analysis of the Optical and Solid State Properties of Thin Film

Authors: E. I. Ugwu

Abstract:

Theoretical analysis of the optical and Solid State properties of ZnS thin film using beam propagation technique in which a scalar wave is propagated through the material thin film deposited on a substrate with the assumption that the dielectric medium is section into a homogenous reference dielectric constant term, and a perturbed dielectric term, representing the deposited thin film medium is presented in this work. These two terms, constitute arbitrary complex dielectric function that describes dielectric perturbation imposed by the medium of for the system. This is substituted into a defined scalar wave equation in which the appropriate Green’s Function was defined on it and solved using series technique. The green’s value obtained from Green’s Function was used in Dyson’s and Lippmann Schwinger equations in conjunction with Born approximation method in computing the propagated field for different input regions of field wavelength during which the influence of the dielectric constants and mesh size of the thin film on the propagating field were depicted. The results obtained from the computed field were used in turn to generate the data that were used to compute the band gaps, solid state and optical properties of the thin film such as reflectance, Transmittance and reflectance with which the band gap obtained was found to be in close approximate to that of experimental value.

Keywords: scalar wave, optical and solid state properties, thin film, dielectric medium, perturbation, Lippmann Schwinger equations, Green’s Function, propagation

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10564 Burn/Traumatic Scar Maturation Using Autologous Fat Grafts + SVF

Authors: Ashok K. Gupta

Abstract:

Over the past few decades, since the bio-engineering revolution, autologous cell therapy (ACT) has become a rapidly evolving field. Currently, this form of therapy has broad applications in modern medicine and plastic surgery, ranging from the treatment/improvement of wound healing to life-saving operations. A study was conducted on 50 patients having to disfigure, and deform post burn scars and was treated by injection of extracted, refined adipose tissue grafts with their unique stem cell properties. To compare the outcome, a control of 20 such patients was treated with conventional skin or soft-tissue flaps or skin grafting, and a control of 10 was treated with more advanced microsurgical techniques such as Pre-fabricated flaps/pre laminated flaps / free flaps. Assessment of fat volume and survival post- follow up period was done by radiological aid, using MRI and clinically (Survival of the autograft and objective parameters for scar elasticity were evaluated skin elasticity parameters 3 to 9 months postoperatively). Recently, an enzyme that is involved in collagen crosslinking in fibrotic tissue, lysyl hydroxylase (LH2), was identified. This enzyme is normally active in bone and cartilage but hardly in the skin. It has been found that this enzyme is highly expressed in scar tissue and subcutaneous fat; this is in contrast to the dermis, where the enzyme is hardly expressed. Adipose tissue-derived stem cell injections are an effective method in the treatment of various extensive post-burn scar deformities that makes it possible to re-create the lost sub-dermal tissue for improvement in the function of involved joint movements.

Keywords: adipose tissue-derived stem cell injections, treatment of various extensive post-burn scar deformities, re-create the lost sub-dermal tissue, improvement in function of involved joint movements

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10563 Optimization of the Measure of Compromise as a Version of Sorites Paradox

Authors: Aleksandar Hatzivelkos

Abstract:

The term ”compromise” is mostly used casually within the social choice theory. It is usually used as a mere result of the social choice function, and this omits its deeper meaning and ramifications. This paper is based on a mathematical model for the description of a compromise as a version of the Sorites paradox. It introduces a formal definition of d-measure of divergence from a compromise and models a notion of compromise that is often used only colloquially. Such a model for vagueness phenomenon, which lies at the core of the notion of compromise enables the introduction of new mathematical structures. In order to maximize compromise, different methods can be used. In this paper, we explore properties of a social welfare function TdM (from Total d-Measure), which is defined as a function which minimizes the total sum of d-measures of divergence over all possible linear orderings. We prove that TdM satisfy strict Pareto principle and behaves well asymptotically. Furthermore, we show that for certain domain restrictions, TdM satisfy positive responsiveness and IIIA (intense independence of irrelevant alternatives) thus being equivalent to Borda count on such domain restriction. This result gives new opportunities in social choice, especially when there is an emphasis on compromise in the decision-making process.

Keywords: borda count, compromise, measure of divergence, minimization

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10562 A System Functions Set-Up through Near Field Communication of a Smartphone

Authors: Jaemyoung Lee

Abstract:

We present a method to set up system functions through a near filed communication (NFC) of a smartphone. The short communication distance of the NFC which is usually less than 4 cm could prevent any interferences from other devices and establish a secure communication channel between a system and the smartphone. The proposed set-up method for system function values is demonstrated for a blacbox system in a car. In demonstration, system functions of a blackbox which is manipulated through NFC of a smartphone are controls of image quality, sound level, shock sensing level to store images, etc. The proposed set-up method for system function values can be used for any devices with NFC.

Keywords: system set-up, near field communication, smartphone, android

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10561 Welfare Estimation in a General Equilibrium Model with Cities

Authors: Oded Hochman

Abstract:

We first show that current measures of welfare changes in the whole economy do not apply to an economy with cities. In addition, since such measures are defined over a partial equilibrium, they capture only partially the effect of a welfare change. We then define a unique and additive measure that we term the modified economic surplus (mES) which fully captures the welfare effects caused by a change in the price of a nationally traded good. We show that the price change causes, on the one hand a change of land rents in the economy and, on the other hand, an equal change of mES that can be estimated by measuring areas in the price-quantity national demand and supply plane. We construct for each city a cost function from which we derive a city’s and, after aggregation, an economy-wide demand and supply functions of nationwide prices and of either the unearned incomes (Marshalian functions) or the utility levels (compensated functions).

Keywords: city cost function, welfare measures, modified compensated variation, modified economic surplus, unearned income function, differential land rents, city size

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10560 From Self-Regulation to Self-Efficacy: Student Empowerment in Translator Training

Authors: Paulina Pietrzak

Abstract:

The understanding of the role of the contemporary translator is fraught with contradictions and idealistic visions of individuals who, by definition, should be fully competent and versatile. In spite of the fact that lots of translation researchers have probed into the identification and exploration of the concept of translator competence, little study has been devoted to its metacognitive aspects. Due to the dynamic nature of the translator’s occupation, it is difficult to predict what specific skills will prove useful for novice translators in their professional career. Thus, it is crucial that the translator is self-regulated enough to adapt to changing job demands and effectively function in the contemporary, highly dynamic, translation market. The objective of the presentation is to investigate the role and nature of the translator’s self-regulation. It will also demonstrate the results of a pilot study into translation trainees’ self-regulatory skills and explore implications of these findings for translator training in relation to theories of student empowerment.

Keywords: cognitive translation research, translator competence, self-regulatory skills, translator training

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10559 Design and Analysis of Universal Multifunctional Leaf Spring Main Landing Gear for Light Aircraft

Authors: Meiyuan Zheng, Jingwu He, Yuexi Xiong

Abstract:

A universal multi-function leaf spring main landing gear was designed for light aircraft. The main landing gear combined with the leaf spring, skidding, and wheels enables it to have a good takeoff and landing performance on various grounds such as the hard, snow, grass and sand grounds. Firstly, the characteristics of different landing sites were studied in this paper in order to analyze the load of the main landing gear on different types of grounds. Based on this analysis, the structural design optimization along with the strength and stiffness characteristics of the main landing gear has been done, which enables it to have good takeoff and landing performance on different types of grounds given the relevant regulations and standards. Additionally, the impact of the skidding on the aircraft during the flight was also taken into consideration. Finally, a universal multi-function leaf spring type of the main landing gear suitable for light aircraft has been developed.

Keywords: landing gear, multi-function, leaf spring, skidding

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10558 Algorithm Development of Individual Lumped Parameter Modelling for Blood Circulatory System: An Optimization Study

Authors: Bao Li, Aike Qiao, Gaoyang Li, Youjun Liu

Abstract:

Background: Lumped parameter model (LPM) is a common numerical model for hemodynamic calculation. LPM uses circuit elements to simulate the human blood circulatory system. Physiological indicators and characteristics can be acquired through the model. However, due to the different physiological indicators of each individual, parameters in LPM should be personalized in order for convincing calculated results, which can reflect the individual physiological information. This study aimed to develop an automatic and effective optimization method to personalize the parameters in LPM of the blood circulatory system, which is of great significance to the numerical simulation of individual hemodynamics. Methods: A closed-loop LPM of the human blood circulatory system that is applicable for most persons were established based on the anatomical structures and physiological parameters. The patient-specific physiological data of 5 volunteers were non-invasively collected as personalized objectives of individual LPM. In this study, the blood pressure and flow rate of heart, brain, and limbs were the main concerns. The collected systolic blood pressure, diastolic blood pressure, cardiac output, and heart rate were set as objective data, and the waveforms of carotid artery flow and ankle pressure were set as objective waveforms. Aiming at the collected data and waveforms, sensitivity analysis of each parameter in LPM was conducted to determine the sensitive parameters that have an obvious influence on the objectives. Simulated annealing was adopted to iteratively optimize the sensitive parameters, and the objective function during optimization was the root mean square error between the collected waveforms and data and simulated waveforms and data. Each parameter in LPM was optimized 500 times. Results: In this study, the sensitive parameters in LPM were optimized according to the collected data of 5 individuals. Results show a slight error between collected and simulated data. The average relative root mean square error of all optimization objectives of 5 samples were 2.21%, 3.59%, 4.75%, 4.24%, and 3.56%, respectively. Conclusions: Slight error demonstrated good effects of optimization. The individual modeling algorithm developed in this study can effectively achieve the individualization of LPM for the blood circulatory system. LPM with individual parameters can output the individual physiological indicators after optimization, which are applicable for the numerical simulation of patient-specific hemodynamics.

Keywords: blood circulatory system, individual physiological indicators, lumped parameter model, optimization algorithm

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10557 Impact of Safety and Quality Considerations of Housing Clients on the Construction Firms’ Intention to Adopt Quality Function Deployment: A Case of Construction Sector

Authors: Saif Ul Haq

Abstract:

The current study intends to examine the safety and quality considerations of clients of housing projects and their impact on the adoption of Quality Function Deployment (QFD) by the construction firm. Mixed method research technique has been used to collect and analyze the data wherein a survey was conducted to collect the data from 220 clients of housing projects in Saudi Arabia. Then, the telephonic and Skype interviews were conducted to collect data of 15 professionals working in the top ten real estate companies of Saudi Arabia. Data were analyzed by using partial least square (PLS) and thematic analysis techniques. Findings reveal that today’s customer prioritizes the safety and quality requirements of their houses and as a result, construction firms adopt QFD to address the needs of customers. The findings are of great importance for the clients of housing projects as well as for the construction firms as they could apply QFD in housing projects to address the safety and quality concerns of their clients.

Keywords: construction industry, quality considerations, quality function deployment, safety considerations

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10556 Role of Long Noncoding RNA HULC on Colorectal Carcinoma Progression through Epigenetically Repressing NKD2 Expression

Authors: Shu-Jun Li, Cheng-Cao Sun, De-Jia Li

Abstract:

Recently, long noncoding RNAs (lncRNAs) have been emerged as crucial regulators of human diseases and prognostic markers in numerous of cancers, including colorectal carcinoma (CRC). Here, we identified an oncogenetic lncRNA HULC, which may promote colorectal tumorigenesis. HULC has been found to be up-regulated and acts as oncogene in gastric cancer and hepatocellular carcinoma, but its expression pattern, biological function and underlying mechanism in CRC is still undetermined. Here, we reported that HULC expression is also over-expressed in CRC, and its increased level is associated with poor prognosis and shorter survival. Knockdown of HULC impaired CRC cells proliferation, migration and invasion, facilitated cell apoptosis in vitro, and inhibited tumorigenicity of CRC cells in vivo. Mechanistically, RNA immunoprecipitation (RIP) and RNA pull-down experiment demonstrated that HULC could simultaneously interact with EZH2 to repress underlying targets NKD2 transcription. In addition, rescue experiments determined that HULC oncogenic function is partly dependent on repressing NKD2. Taken together, our findings expound how HULC over-expression endows an oncogenic function in CRC.

Keywords: long noncoding RNA, HULC, NKD2, colorectal carcinoma, proliferation, apoptosis

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10555 Novel Inference Algorithm for Gaussian Process Classification Model with Multiclass and Its Application to Human Action Classification

Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

Abstract:

In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

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10554 Examining the Relationship between Concussion and Neurodegenerative Disorders: A Review on Amyotrophic Lateral Sclerosis and Alzheimer’s Disease

Authors: Edward Poluyi, Eghosa Morgan, Charles Poluyi, Chibuikem Ikwuegbuenyi, Grace Imaguezegie

Abstract:

Background: Current epidemiological studies have examined the associations between moderate and severe traumatic brain injury (TBI) and their risks of developing neurodegenerative diseases. Concussion, also known as mild TBI (mTBI), is however quite distinct from moderate or severe TBIs. Only few studies in this burgeoning area have examined concussion—especially repetitive episodes—and neurodegenerative diseases. Thus, no definite relationship has been established between them. Objectives : This review will discuss the available literature linking concussion and amyotrophic lateral sclerosis (ALS) and Alzheimer’s disease (AD). Materials and Methods: Given the complexity of this subject, a realistic review methodology was selected which includes clarifying the scope and developing a theoretical framework, developing a search strategy, selection and appraisal, data extraction, and synthesis. A detailed literature matrix was set out in order to get relevant and recent findings on this topic. Results: Presently, there is no objective clinical test for the diagnosis of concussion because the features are less obvious on physical examination. Absence of an objective test in diagnosing concussion sometimes leads to skepticism when confirming the presence or absence of concussion. Intriguingly, several possible explanations have been proposed in the pathological mechanisms that lead to the development of some neurodegenerative disorders (such as ALS and AD) and concussion but the two major events are deposition of tau proteins (abnormal microtubule proteins) and neuroinflammation, which ranges from glutamate excitotoxicity pathways and inflammatory pathways (which leads to a rise in the metabolic demands of microglia cells and neurons), to mitochondrial function via the oxidative pathways.

Keywords: amyotrophic lateral sclerosis, Alzheimer's disease, mild traumatic brain injury, neurodegeneration

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10553 Parameterized Lyapunov Function Based Robust Diagonal Dominance Pre-Compensator Design for Linear Parameter Varying Model

Authors: Xiaobao Han, Huacong Li, Jia Li

Abstract:

For dynamic decoupling of linear parameter varying system, a robust dominance pre-compensator design method is given. The parameterized pre-compensator design problem is converted into optimal problem constrained with parameterized linear matrix inequalities (PLMI); To solve this problem, firstly, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameterized Lyapunov function (PLF) and pre-compensator. Then the problem was reduced to a normal convex optimization problem with normal linear matrix inequalities (LMI) constraints on a newly constructed convex polyhedron. Moreover, a parameter scheduling pre-compensator was achieved, which satisfies robust performance and decoupling performances. Finally, the feasibility and validity of the robust diagonal dominance pre-compensator design method are verified by the numerical simulation of a turbofan engine PLPV model.

Keywords: linear parameter varying (LPV), parameterized Lyapunov function (PLF), linear matrix inequalities (LMI), diagonal dominance pre-compensator

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10552 Tip60’s Novel RNA-Binding Function Modulates Alternative Splicing of Pre-mRNA Targets Implicated in Alzheimer’s Disease

Authors: Felice Elefant, Akanksha Bhatnaghar, Keegan Krick, Elizabeth Heller

Abstract:

Context: The severity of Alzheimer’s Disease (AD) progression involves an interplay of genetics, age, and environmental factors orchestrated by histone acetyltransferase (HAT) mediated neuroepigenetic mechanisms. While disruption of Tip60 HAT action in neural gene control is implicated in AD, alternative mechanisms underlying Tip60 function remain unexplored. Altered RNA splicing has recently been highlighted as a widespread hallmark in the AD transcriptome that is implicated in the disease. Research Aim: The aim of this study was to identify a novel RNA binding/splicing function for Tip60 in human hippocampus and impaired in brains from AD fly models and AD patients. Methodology/Analysis: The authors used RNA immunoprecipitation using RNA isolated from 200 pooled wild type Drosophila brains for each of the 3 biological replicates. To identify Tip60’s RNA targets, they performed genome sequencing (DNB-SequencingTM technology, BGI genomics) on 3 replicates for Input RNA and RNA IPs by Tip60. Findings: The authors' transcriptomic analysis of RNA bound to Tip60 by Tip60-RNA immunoprecipitation (RIP) revealed Tip60 RNA targets enriched for critical neuronal processes implicated in AD. Remarkably, 79% of Tip60’s RNA targets overlap with its chromatin gene targets, supporting a model by which Tip60 orchestrates bi-level transcriptional regulation at both the chromatin and RNA level, a function unprecedented for any HAT to date. Since RNA splicing occurs co-transcriptionally and splicing defects are implicated in AD, the authors investigated whether Tip60-RNA targeting modulates splicing decisions and if this function is altered in AD. Replicate multivariate analysis of transcript splicing (rMATS) analysis of RNA-Seq data sets from wild-type and AD fly brains revealed a multitude of mammalian-like AS defects. Strikingly, over half of these altered RNAs were bonafide Tip60-RNA targets enriched for in the AD-gene curated database, with some AS alterations prevented against by increasing Tip60 in fly brain. Importantly, human orthologs of several Tip60-modulated spliced genes in Drosophila are well characterized aberrantly spliced genes in human AD brains, implicating disruption of Tip60’s splicing function in AD pathogenesis. Theoretical Importance: The authors' findings support a novel RNA interaction and splicing regulatory function for Tip60 that may underlie AS impairments that hallmark AD etiology. Data Collection: The authors collected data from RNA immunoprecipitation experiments using RNA isolated from 200 pooled wild type Drosophila brains for each of the 3 biological replicates. They also performed genome sequencing (DNBSequencingTM technology, BGI genomics) on 3 replicates for Input RNA and RNA IPs by Tip60. Questions: The question addressed by this study was whether Tip60 has a novel RNA binding/splicing function in human hippocampus and whether this function is impaired in brains from AD fly models and AD patients. Conclusions: The authors' findings support a novel RNA interaction and splicing regulatory function for Tip60 that may underlie AS impairments that hallmark AD etiology.

Keywords: Alzheimer's disease, cognition, aging, neuroepigenetics

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10551 Artificial Neural Networks Application on Nusselt Number and Pressure Drop Prediction in Triangular Corrugated Plate Heat Exchanger

Authors: Hany Elsaid Fawaz Abdallah

Abstract:

This study presents a new artificial neural network(ANN) model to predict the Nusselt Number and pressure drop for the turbulent flow in a triangular corrugated plate heat exchanger for forced air and turbulent water flow. An experimental investigation was performed to create a new dataset for the Nusselt Number and pressure drop values in the following range of dimensionless parameters: The plate corrugation angles (from 0° to 60°), the Reynolds number (from 10000 to 40000), pitch to height ratio (from 1 to 4), and Prandtl number (from 0.7 to 200). Based on the ANN performance graph, the three-layer structure with {12-8-6} hidden neurons has been chosen. The training procedure includes back-propagation with the biases and weight adjustment, the evaluation of the loss function for the training and validation dataset and feed-forward propagation of the input parameters. The linear function was used at the output layer as the activation function, while for the hidden layers, the rectified linear unit activation function was utilized. In order to accelerate the ANN training, the loss function minimization may be achieved by the adaptive moment estimation algorithm (ADAM). The ‘‘MinMax’’ normalization approach was utilized to avoid the increase in the training time due to drastic differences in the loss function gradients with respect to the values of weights. Since the test dataset is not being used for the ANN training, a cross-validation technique is applied to the ANN network using the new data. Such procedure was repeated until loss function convergence was achieved or for 4000 epochs with a batch size of 200 points. The program code was written in Python 3.0 using open-source ANN libraries such as Scikit learn, TensorFlow and Keras libraries. The mean average percent error values of 9.4% for the Nusselt number and 8.2% for pressure drop for the ANN model have been achieved. Therefore, higher accuracy compared to the generalized correlations was achieved. The performance validation of the obtained model was based on a comparison of predicted data with the experimental results yielding excellent accuracy.

Keywords: artificial neural networks, corrugated channel, heat transfer enhancement, Nusselt number, pressure drop, generalized correlations

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10550 Oxidantantioxidant Status in Calves Supplemented with Green Tea Extract

Authors: Ibrahim I. Elshahawy

Abstract:

The objective of the present study was to investigate the effect of green tea extract on serum oxidant and antioxidant profile, liver and kidney function. 40 Friesian calves are included in this study and allocated into two groups: Group I (n=20) clinically healthy calves showing no clinical abnormalities, not receiving any treatment and served as control; group II (n=20) received green tea extract (GTE) for 30 days. Non-significant changes in blood urea nitrogen (BUN) were detected between groups, on contrary, serum creatinine and activities of liver enzymes aspartate transaminase (AST) and alanine transaminase (ALT) were significantly different between two groups. There were significant increases in the mean values of serum antioxidative parameters (total antioxidant capacity, catalase, superoxide dismutase, reduced glutathione and glutathione peroxidase) in group II. Whereas, the activity of lipid peroxidase significantly decreased in GTE treated calves when compared to control.

Keywords: green tea extract, antioxidants, oxidants, calves

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10549 Physical Function and Physical Activity Preferences of Elderly Individuals Admitted for Elective Abdominal Surgery: A Pilot Study.

Authors: Rozelle Labuschagne, Ronel Roos

Abstract:

Individuals often experience a reduction in physical function, quality of life and basic activities of daily living after surgery. This is exponentially true for high-risk patients, especially the elderly and frail individuals. Not much is known about the physical function, physical activity preferences and factors associated with the six-minute walk test of elderly individuals who would undergo elective abdominal surgery in South Africa. Such information is important to design effective prehabilitation physiotherapy programs prior to elective surgery. The purpose of the study was to describe the demographic profile and physical function of elderly patients who would undergo elective surgery and to determine factors associated with their six-minute walk test distance findings. A cross-sectional descriptive study in elderly patients older than 60 years of age who would undergo elective abdominal surgery were consecutively sampled at a private hospital in Pretoria, South Africa. Participants’ demographics were collected and physical function assessed with the Functional Comorbidity Index (FCI), DeMorton Mobility Index (DEMMI), Lawton-Brody Instrumental Activities of Daily Living Scale (IADL) and six-minute walk test (6MWT). Descriptive and inferential statistics were used for data analysis with IBM SPSS 25. A p-value ≤ 0.05 were deemed statistically significant. The pilot study consisted of 12 participants (female (n=11, 91.7%), male (n=1, 8.3%) with a mean age of 65.8 (±4.5) years, body mass index of 28 (±4.2) kg.m2 with one (8.3%) participant being a current smoker and four (33.3%) participants having a smoking history. Nine (75%) participants lived independently at home and three (25%) had caregivers. Participants reported walking (n=6, 50%), stretching exercises (n=1, 8.3%), household chores & gardening (n=2, 16.7%), biking/swimming/running (n=1, 8.3%) as physical activity preferences. Physical function findings of the sample were: mean FCI score 3 (±1.1), DEMMI score 81.1 (±14.9), IADL 95 (±17.3), 6MWT 435.50 (IQR 364.75-458.50) with percentage 6MWT distance achieved 81.8% (IQR 64.4%-87.5%). A strong negative correlation was observed between 6MWT distance walked and FCI (r = -0.729, p=0.007). The majority of study participants reported incorporating some form of physical activity into their daily life as form of exercise. Most participants did not achieve their predicted 6MWT distance indicating less than optimal levels of physical function capacity. The number of comorbidities as determined by the FCI was associated with the distance that participants could walk with the 6MWT. The results of this pilot study could be used to indicate which elderly individuals would benefit most from a pre-surgical rehabilitation program. The main goal of such a program would be to improve physical function capacity as measured by the 6MWT. Surgeons could refer patients based on age and number of comorbidities, as determined by the FCI, to potentially improve surgical outcomes.

Keywords: abdominal surgery, elderly, physical function, six-minute walk test

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10548 Financial Liberalization, Exchange Rates and Demand for Money in Developing Economies: The Case of Nigeria, Ghana and Gambia

Authors: John Adebayo Oloyhede

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This paper examines effect of financial liberalization on the stability of the demand for money function and its implication for exchange rate behaviour of three African countries. As the demand for money function is regarded as one of the two main building blocks of most exchange rate determination models, the other being purchasing power parity, its stability is required for the monetary models of exchange rate determination to hold. To what extent has the liberalisation policy of these countries, for instance liberalised interest rate, affected the demand for money function and what has been the consequence on the validity and relevance of floating exchange rate models? The study adopts the Autoregressive Instrumental Package (AIV) of multiple regression technique and followed the Almon Polynomial procedure with zero-end constraint. Data for the period 1986 to 2011 were drawn from three developing countries of Africa, namely: Gambia, Ghana and Nigeria, which did not only start the liberalization and floating system almost at the same period but share similar and diverse economic and financial structures. Its findings show that the demand for money was a stable function of income and interest rate at home and abroad. Other factors such as exchange rate and foreign interest rate exerted some significant effect on domestic money demand. The short-run and long-run elasticity with respect to income, interest rates, expected inflation rate and exchange rate expectation are not greater than zero. This evidence conforms to some extent to the expected behaviour of the domestic money function and underscores its ability to serve as good building block or assumption of the monetary model of exchange rate determination. This will, therefore, assist appropriate monetary authorities in the design and implementation of further financial liberalization policy packages in developing countries.

Keywords: financial liberalisation, exchange rates, demand for money, developing economies

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10547 Effect of Annealing Temperature on the Photoelectric Work Function of Silver-Zinc Oxide Contact Materials

Authors: Bouchou Aïssa, Mohamed Akbi

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Contact materials used for electrical breakers are often made with silver alloys. Mechanical and thermo dynamical properties as well as electron emission of such complicated alloys present a lack of reliable and accurate experimental data. This paper deals mainly with electron work function (EWF) measurements about silver-metal oxide (Ag-MeO) electrical contacts (Ag-ZnO (92/8), before and after surface heat treatments at 296 K  813 K, under UHV conditions (residual gas pressure of 1.4 x 10-7 mbar). The electron work function (EWF) of silver zinc oxide materials was measured photoelectrically, using both Fowler’s method of isothermal curves and linearized Fowler plots. In this paper, we present the development of a method for measuring photoelectric work function of contact materials. Also reported in this manuscript are the results of experimental work whose purpose has been the buildup of a reliable photoelectric system and associated monochromatic ultra-violet radiations source, and the photoelectric measurement of the electron work functions (EWF) of contact materials. In order to study the influence of annealing temperature on the EWF, a vacuum furnace was used for heating the metallic samples up to 800 K. The EWF of the silver – zinc oxide materials were investigated to study the influence of annealing temperature on the EWF. In the present study, the photoelectric measurements about Ag-ZnO(92/8) contacts have shown a linear decrease of the EWF with increasing temperature, i.e. the temperature coefficient is constant and negative: for the first annealing # 1, in the temperature range [299 K  823 K]. On the contrary, a linear increase was observed with increasing temperature (i.e. , being constant and positive), for the next annealing # 2, in the temperature range [296 K  813 K]. The EWFs obtained for silver-zinc oxide Ag-ZnO(92/8) show an obvious dependence on the annealing temperature which is strongly associated with the evolution of the arrangement on ZnO nano particles on the Ag-ZnO contact surface as well as surface charge distribution.

Keywords: Photoemission, Electron work function, Fowler methods, Ag-ZnO contact materials, Vacuum heat treatment

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10546 Influence of Temperature on Properties of MOSFETs

Authors: Azizi Cherifa, O. Benzaoui

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The thermal aspects in the design of power circuits often deserve as much attention as pure electric components aspects as the operating temperature has a direct influence on their static and dynamic characteristics. MOSFET is fundamental in the circuits, it is the most widely used device in the current production of semiconductor components using their honorable performance. The aim of this contribution is devoted to the effect of the temperature on the properties of MOSFETs. The study enables us to calculate the drain current as function of bias in both linear and saturated modes. The effect of temperature is evaluated using a numerical simulation, using the laws of mobility and saturation velocity of carriers as a function of temperature.

Keywords: temperature, MOSFET, mobility, transistor

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