A Novel Composite Material-based Computational Model for Left Ventricle Biomechanics Simulation

To model cardiac mechanics effectively, various mechanical characteristics of cardiac muscle tissue including anisotropy, hyperelasticity, and tissue active contraction characteristics must be considered. Some of these features cannot be implemented using commercial finite element (FE) solvers unless additional custom-developed computer codes/subroutines are appended. Such codes/subroutines are unavailable for the research community. Accordingly, the overarching objective of this research is to develop a novel LV mechanics model which is implementable in commercial FE solvers and can be used effectively within inverse FE frameworks towards cardiac disease diagnosis and therapy. This was broken down into a number of objectives. The first objective is to develop a novel cardiac tissue mechanical model. This model was constructed of microstructural cardiac tissue constituents while their associated volume contributions and mechanical properties were incorporated into the model. These constituents were organized in small FE tissue specimen models consistent with the normal/pathological cardiac tissue microstructure. In silico biaxial/uniaxial mechanical tests were conducted on the specimen models and corresponding stress-strain data were validated by comparing them with cardiac tissue data reported in the literature. Another objective of this research is developing a novel FE-based mechanical model of the LV which is fully implementable using commercial FE solvers without requiring further coding, potentially leading to a computationally efficient model which is easily adaptable to diverse pathological conditions. This was achieved through considering a novel composite material model of the cardiac tissue while all aspects of the cardiac mechanics including hyperelasticity, anisotropy, and active tissue responses were preserved. The model was applied to an in silico geometry of a canine LV under both normal and pathological conditions and systolic/diastolic responses of the model were compared with corresponding data of other LV mechanical models and LV contraction measurements. To test the suitability of the proposed cardiac model for FE inversion-based algorithms, the model was utilized for LV diastolic mechanical simulation to estimate the tissue stiffness and blood pressure using an ad-hoc optimization scheme. This led to reasonable tissue stiffness and blood pressure values falling within the range of LV measurements of healthy subjects, confirming the efficacy of this model for inversion-based diagnosis applications

Is there an Economic Case for Energy-Efficient Dwellings in the UK Private Rental Market?

The rented sector of the housing market is a key concern for policies trying to improve dwelling-level energy efficiency levels. Currently, stepping up energy efficiency levels in the residential sector is hindered by a number of uncertainties. For rental properties, this is complicated by the split incentive problem (i.e. landlords do not benefit directly from the savings arising from these investments). Instead, the benefits are enjoyed by the tenants of these upgraded properties via lower energy bills and/or enhanced thermal comfort. Hence, the only way to recoup the investments is typically for landlords to obtain higher rents. This study confirms that energy efficiency features, as measured by the Energy Performance Certificate rating, are positively associated with a small but significant influence on transaction prices and quoted rental prices. Conversely, there appears to be a price discount for dwellings in the lowest energy performance category. A model of time-on-market yields inconclusive results but there is some, albeit weak, evidence of a negative relationship between time-on-market and energy efficiency ratings as more energy efficient dwellings tend to lease up more quickly.EU H2020 and BEI

The effect of preload and surface roughness quality on linear joint model parameters

The physical parameters of the contact interfaces, such as preload and surface roughness quality, significantly affect the stiffness of joints. Knowledge of the relationship between these interface parameters and the equivalent stiffness allows joints to be considered in the design stages of complex structures. Hence, this paper considers the effect of contact interface parameters on the identified equivalent stiffness parameters of joint models. First, a new generic joint model is proposed to model the contact interfaces. Then, the ability of three different joint models, including the new model proposed in this paper, to capture the linear effects of contact interfaces under different preloads and surface roughness qualities is investigated. Finally, it is concluded that the preload and surface roughness quality control the normal and shearing stiffness of the joint models respectively. Experimental investigations also reveal that a complex mechanism governs the energy dissipation in the contact interface

Stochastic modelling and updating of a joint contact interface

Dynamic properties of the contact interfaces in joints and mechanical connections have a great influence on the overall dynamic properties of assembled structures. Uncertainty and nonlinearity are two major effects of contact interfaces which introduce challenges in accurate modeling. Randomness in surface roughness quality, surface finish and contact preload are the main sources of variability in the contact interfaces. On the other side, slip and slap are two mechanisms responsible for nonlinear behavior of joints. Stochastic linear/nonlinear models need to be developed for such uncertain structures to be used in dynamic response analysis or system parameter identification. In this paper, variability in linear behavior of an assembled structure containing a bolted lap-joint is investigated by using experimental results. A stochastic model is then constructed for the structure by employing a stochastic generic joint model and the uncertainty in the joint model parameters is identified by using a Bayesian identification approach

An Optimization-Based Framework for Nonlinear Model Selection and Identification

This paper proposes an optimization-based framework to determine the type of nonlinear model present and identify its parameters. The objective in this optimization problem is to identify the parameters of a nonlinear model by minimizing the differences between the experimental and analytical responses at the measured coordinates of the nonlinear structure. The application of the method is demonstrated on a clamped beam subjected to a nonlinear electromagnetic force. In the proposed method, the assumption is that the form of nonlinear force is not known. For this reason, one may assume that any nonlinear force can be described using a Taylor series expansion. In this paper, four different possible nonlinear forms are assumed to model the electromagnetic force. The parameters of these four nonlinear models are identified from experimental data obtained from a series of stepped-sine vibration tests with constant acceleration base excitation. It is found that a nonlinear model consisting of linear damping and linear, quadratic, cubic, and fifth order stiffness provides excellent agreement between the predicted responses and the corresponding measured responses. It is also shown that adding a quadratic nonlinear damping does not lead to a significant improvement in the results

Methodology for Analyzing Factors that Effect Maintenance Costs in Public Hospitals

Maintenance costs of public hospitals in Syria is noticed to be highly expensive, beside hindering hospital jobs technically and humanly. It is noticed that most of public hospitals in Syria need, after a short time relatively from its operating start, comprehensive maintenance or rehabilitation with high expenses. This problem needs studying and analyzing reasons and factors to which they lead. The goal of This research is reducing high maintenance cost in hospitals, by determining factors affecting that cost, and observing them in future to reach the requested goal. To perform the above mentioned, the states of many public hospitals in Latakia and Tartus were studied, accordingly, factors that affect maintenance costs in hospitals were determined in addition to specifying the importance and effect degree for these factors. Furthermore, the software FuzzyTECH was utilized in analyzing factors and offering the ability of forecasting variations in maintenance cost on the basis of the evaluation and behavior of each factor affect it.

Homology modeling in the time of collective and artificial intelligence

Homology modeling is a method for building protein 3D structures using protein primary sequence and utilizing prior knowledge gained from structural similarities with other proteins. The homology modeling process is done in sequential steps where sequence/structure alignment is optimized, then a backbone is built and later, side-chains are added. Once the low-homology loops are modeled, the whole 3D structure is optimized and validated. In the past three decades, a few collective and collaborative initiatives allowed for continuous progress in both homology and ab initio modeling. Critical Assessment of protein Structure Prediction (CASP) is a worldwide community experiment that has historically recorded the progress in this field. Folding@Home and Rosetta@Home are examples of crowd-sourcing initiatives where the community is sharing computational resources, whereas RosettaCommons is an example of an initiative where a community is sharing a codebase for the development of computational algorithms. Foldit is another initiative where participants compete with each other in a protein folding video game to predict 3D structure. In the past few years, contact maps deep machine learning was introduced to the 3D structure prediction process, adding more information and increasing the accuracy of models significantly. In this review, we will take the reader in a journey of exploration from the beginnings to the most recent turnabouts, which have revolutionized the field of homology modeling. Moreover, we discuss the new trends emerging in this rapidly growing field.O

Acoustic Echo Cancellation using Adaptive Filter for Quranic Accent Signals

Quranic recordings and echoed portions of the emphasis are susceptible to signal reverberation, particularly when being listened to in a conference room. Tajweed and Quranic verse rule identification are susceptible to additive noise, which could lower classification accuracy. In order to reflect the most correct rate following pattern categorization, this study suggested the appropriate use of three adaptive algorithms: Affine Projection (AP), Least Mean Square (LMS), and Recursive Least Squares (RLS). For feature extraction, Mel Frequency Cepstral Coefficient is used together with Probabilities Principal Component Analysis (PPCA), K-Neural Network (KNN) and Gaussian Mixture Model (GMM). AP indicates 93.9% for all of the classification algorithm in used, while for LMS and RLS the results are differed varies on different pattern classification algorithm stated whereby with LMS and PPCA classification, 96.9 % for accuracy and 84.8% accuracy for LMS and KNN. While for RLS and GMM, 96.9% was achieved and the results were reduced for both KNN and PPCA. The analysis has  resulted for both on accuracies within different filtering algirithm and classification for accuracy and ERLE(dB).Towards this research it is hope will embark more understanding towards echo cancellation and quality of sound recordings that may affected even to the Quranic recordings

Highly efficient eco-friendly corrosion inhibitor for mild steel in 5 M HCl at elevated temperatures: experimental & molecular dynamics study

Laurhydrazide N?-propan-3-one was used as an eco-friendly inhibitor for the corrosion of mild steel in 5 M HCl at elevated temperatures. Various electrochemical techniques and surface characterization methods were utilized in this study. In addition, the kinetics and thermodynamic parameters were calculated and discussed. Furthermore, a geometry optimization of LHP was performed and the time-dependent density functional theory was utilized to calculate the electronic absorption spectra. Finally, frequency calculations were, also, performed on the optimized geometry. - 2019, The Author(s).This publication was supported by Qatar University Internal Grant No. GCC-2017-012. The findings achieved herein are solely the responsibility of the authors. Additionally, the authors thank the Center for Advanced Materials at Qatar University for their support.Scopu