Abstract: In this study, hyaluronic acid (HA) microgels were developed for the goal of protein delivery. First, a hyaluronic acid-tyramine conjugate (HA-TA) was synthesized with a degree of substitution of 13 TA moieties per 100 disaccharide units. Then, HA-TA microdroplets were produced using a water in oil emulsion method and crosslinked in the presence of horseradish peroxidase (HRP) and hydrogen peroxide (H2O2). Loading capacity and the release kinetics of lysozyme and BSA, as model proteins, were investigated. It was shown that lysozyme, a cationic protein, can be incorporated efficiently in the HA microgels, while the loading efficiency for BSA, as a negatively charged protein, is low. The release profile of lysozyme showed a sustained release over a period of one month. The results demonstrated that the HA-TA microgels are a good carrier for spatial delivery of cationic proteins for biomedical applications.
Abstract: One dimensional pseudo-homogenous modeling has been performed for methanol steam reforming reactor. The results show that the models can well predict the industrial data. The reactor had minimum temperature along axial because of endothermic reaction. Hydrogen productions and temperature profiles along axial were investigated regarding operation conditions such as inlet mass flow rate and mass fraction of methanol, inlet temperature of external thermal oil. Low inlet mass flow rate of methanol, low inlet temperature, and high mass fraction of methanol decreased minimum temperature along axial. Low inlet mass flow rate of methanol, high mass fraction of methanol, and high inlet temperature of thermal oil made cold point forward. Low mass fraction, high mass flow rate, and high inlet temperature of thermal oil increased hydrogen production. One dimensional models can be a guide for industrial operation.
Abstract: The bearing capacity of closely spaced shallow footings alters with their spacing and the shape of footing. In this study, the bearing capacity and settlement of two adjacent footings constructed on a sand layer are investigated. The effect of different footing shapes including square, circular, ring and strip on sandy soil is captured in the calculations. The investigations are carried out numerically using PLAXIS-3D software and analytically employing conventional settlement equations. For this purpose, foundations are modelled in the program with practical dimensions and various spacing ratios ranging from 1 to 5. The spacing ratio is defined as the centre-to-centre distance to the width of foundations (S/B). Overall, 24 models are analyzed; and the results are compared and discussed in detail. It can be concluded that the presence of adjacent foundation leads to the reduction in bearing capacity for round shape footings while it can increase the bearing capacity of rectangular footings in some specific distances.
Abstract: The Earth system generates different phenomena that are observable at the surface of the Earth such as mass deformations and displacements leading to plate tectonics, earthquakes, and volcanism. The dynamic processes associated with the interior, surface, and atmosphere of the Earth affect the three pillars of geodesy: shape of the Earth, its gravity field, and its rotation. Geodesy establishes a characteristic structure in order to define, monitor, and predict of the whole Earth system. The traditional and new instruments, observables, and techniques in geodesy are related to the gravity field. Therefore, the geodesy monitors the gravity field and its temporal variability in order to transform the geodetic observations made on the physical surface of the Earth into the geometrical surface in which positions are mathematically defined. In this paper, the main components of the gravity field modeling, (Free-air and Bouguer) gravity anomalies are calculated via recent global models (EGM2008, EIGEN6C4, and GECO) over a selected study area. The model-based gravity anomalies are compared with the corresponding terrestrial gravity data in terms of standard deviation (SD) and root mean square error (RMSE) for determining the best fit global model in the study area at a regional scale in Turkey. The least SD (13.63 mGal) and RMSE (15.71 mGal) were obtained by EGM2008 for the Free-air gravity anomaly residuals. For the Bouguer gravity anomaly residuals, EIGEN6C4 provides the least SD (8.05 mGal) and RMSE (8.12 mGal). The results indicated that EIGEN6C4 can be a useful tool for modeling the gravity field of the Earth over the study area.
Abstract: Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.
Abstract: Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.
Abstract: In electrical discharge machining (EDM), a complete and clear theory has not yet been established. The developed theory (physical models) yields results far from reality due to the complexity of the physics. It is difficult to select proper parameter settings in order to achieve better EDM performance. However, modelling can solve this critical problem concerning the parameter settings. Therefore, the purpose of the present work is to develop mathematical model to predict performance characteristics of EDM on Ti-5Al-2.5Sn titanium alloy. Response surface method (RSM) and artificial neural network (ANN) are employed to develop the mathematical models. The developed models are verified through analysis of variance (ANOVA). The ANN models are trained, tested, and validated utilizing a set of data. It is found that the developed ANN and mathematical model can predict performance of EDM effectively. Thus, the model has found a precise tool that turns EDM process cost-effective and more efficient.
Abstract: The paper presents an approach to improve the reliability and reduce line losses of practical distribution system applying network reconfiguration. The change of the topology redirects the power flow within the distribution network to obtain better performance of the system. Practical distribution network (Pyigyitagon Industrial Zone (I)) is used as the case study network. The detailed calculations of the reliability indices are done by using analytical method and power flow calculation is performed by Newton-Rephason solver. The comparison of various network reconfiguration techniques are described with respect to power loss and reliability index levels. Finally, the optimal reconfigured network is selected among difference cases based on the two factors: the most reliable network and the least loss minimization.
Abstract: In recent years, waste tyre problem is considered as one of the most crucial environmental pollution problems facing the world. Thus, reusing waste rubber crumb from recycled tyres to develop highly damping concrete is technically feasible and a viable alternative to landfill or incineration. The utilization of waste rubber in concrete generally enhances the ductility, toughness, thermal insulation, and impact resistance. However, the mechanical properties decrease with the amount of rubber used in concrete. The aim of this paper is to develop artificial neural network (ANN) models to predict the compressive strength of rubberised concrete (RuC). A trained and tested ANN was developed using a comprehensive database collected from different sources in the literature. The ANN model developed used 5 input parameters that include: coarse aggregate (CA), fine aggregate (FA), w/c ratio, fine rubber (Fr), and coarse rubber (Cr), whereas the ANN outputs were the corresponding compressive strengths. A parametric study was also conducted to study the trend of various RuC constituents on the compressive strength of RuC.
Abstract: 21st century brought waves of business and industry eTransformations. The impact of change is also being seen in education. To identify the extent of this, scenario analysis methodology was utilised with the aim to assess business transformations across industry sectors ranging from craftsmanship, medicine, finance and manufacture to innovations and adoptions of new technologies and business models. Firstly, scenarios were drafted based on the current eTransformation models and its dimensions. Following this, eTransformation framework was utilised with the aim to derive the key eTransformation parameters, the essential characteristics that have enabled eTransformations across the sectors. Following this, identified key parameters were mapped to the transforming domain-education. The mapping assisted in deriving a cognitive eTransformation framework for education sector. The framework highlights the importance of context and the notion that education today needs not only to deliver content to students but it also needs to be able to meet the dynamically changing demands of specific student and industry groups. Furthermore, it pinpoints that for such processes to be supported, specific technology is required, so that instant, on demand and periodic feedback as well as flexible, dynamically expanding study content can be sought and received via multiple education mediums.
Abstract: This article presents a 3-D modified non-linear elastic model in the strain space. The Helmholtz free energy function is introduced with the existence of a dissipation potential surface in the space of thermodynamic conjugate forces. The constitutive equation and the damage evolution were derived as well. The modified damage has been examined to model the nonlinear behavior of reinforced concrete (RC) slabs with an opening. A parametric study with RC was carried out to investigate the impact of different factors on the behavior of RC slabs. These factors are the opening area, the opening shape, the place of opening, and the thickness of the slabs. And the numerical results have been compared with the experimental data from literature. Finally, the model showed its ability to be applied to the structural analysis of RC slabs.
Abstract: The present research is a paper on the characterization of aluminum alloy-6063 hybrid metal matrix composites using three different reinforcement materials (SiC, red mud, and fly ash) through stir casting method. The red mud was used in solid form, and particle size range varies between 103-150 µm. During this investigation, fly ash is received from Guru Nanak Dev Thermal Plant (GNDTP), Bathinda. The study has been done by using Taguchi’s L9 orthogonal array by taking fraction wt.% (SiC 5%, 7.5%, and 10% and Red Mud and Fly Ash 2%, 4%, and 6%) as input parameters with their respective levels. The study of the mechanical properties (tensile strength, impact strength, and microhardness) has been done by using Analysis of Variance (ANOVA) with the help of MINITAB 17 software. It is revealed that silicon carbide is the most significant parameter followed by red mud and fly ash affecting the mechanical properties, respectively. The fractured surface morphology of the composites using Field Emission Scanning Electron Microscope (FESEM) shows that there is a good mixing of reinforcement particles in the matrix. Energy-dispersive X-ray spectroscopy (EDS) was performed to know the presence of the phases of the reinforced material.
Abstract: Worldwide, improving tourism competitiveness has been on the agendas of many stakeholders of the hotel sector, and they seem to have agreed that one of the best ways to compete is via the implementation of electronic customer relationship management (e-CRM). In so doing, the organizations enjoy strategic positioning on the competitive market by managing better not only the customers but, other business components including knowledge and employee management. Over the recent years, the tourism industry in Mauritius has witnessed a drastic economic boom at international and national levels; providing a new outlook to boost business performance through existing and potential customers. E-CRM has been one of the management tools used to achieving this position. Thus, this insightful context- Mauritius- was opted for the study. The aim was to assess the effectiveness of e-CRM as a strategic tool in the hotel sector in Mauritius through the implementation of business strategy to create competitive advantage and impact on the business performance. To achieve the objectives of the study, a quantitative research methodology was adopted and the research revealed that e-CRM is indeed an effective strategic tool in the hotel industry in Mauritius that can provide a competitive advantage and impact positively on the organization’s performance.
Abstract: Studies estimate that there will be 266,120 new cases
of invasive breast cancer and 40,920 breast cancer induced deaths
in the year of 2018 alone. Despite the pervasiveness of this
affliction, the current process to obtain an accurate breast cancer
prognosis is tedious and time consuming. It usually requires a
trained pathologist to manually examine histopathological images and
identify the features that characterize various cancer severity levels.
We propose MITOS-RCNN: a region based convolutional neural
network (RCNN) geared for small object detection to accurately
grade one of the three factors that characterize tumor belligerence
described by the Nottingham Grading System: mitotic count. Other
computational approaches to mitotic figure counting and detection
do not demonstrate ample recall or precision to be clinically viable.
Our models outperformed all previous participants in the ICPR 2012
challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14
challenge along with recently published works. Our model achieved
an F- measure score of 0.955, a 6.11% improvement in accuracy from
the most accurate of the previously proposed models.
Abstract: The deployable descent technology is a lightweight entry method using an inflatable heat shield. The heatshield consists of a pressurized core which is covered by different layers of thermal insulation and flexible ablative materials in order to protect against the thermal loads. In this paper, both aluminum and silicon-aluminum aerogels were prepared by freeze-drying method. The latter material has bigger specific surface area and nano-scale pores. Mullite fibers are used as the reinforcing fibers to prepare the aerogel matrix to improve composite flexibility. The flexible composite materials were performed as an insulation layer to an underlying aramid fabric by a thermal shock test at a heat flux density of 120 kW/m2 and uniaxial tensile test. These results show that the aramid fabric with untreated mullite fibers as the thermal protective layer is completely carbonized at the heat of about 60 s. The aramid fabric as a thermal resistance layer of the composite material still has good mechanical properties at the same heat condition.
Abstract: Modern day electric vehicles require compact high torque/power density motors for electric propulsion. This necessitates proper thermal management of the electric motors. The main focus of this paper is to compare the steady state thermal analysis of a conventional 20 kW 8/6 Switched Reluctance Motor (SRM) with that of an Induction Motor and Inset Permanent Magnet (IPM) motor of the same rating. The goal is to develop a proper thermal model of the three types of models for Finite Element Thermal Analysis. JMAG software is used for the development and simulation of the thermal models. The results show that the induction motor is subjected to more heating when used for electric vehicle application constantly, compared to the SRM and IPM.
Abstract: Cellular complexity stems from the interactions
among thousands of different molecular species. Thanks to the
emerging fields of systems and synthetic biology, scientists are
beginning to unravel these regulatory, signaling, and metabolic
interactions and to understand their coordinated action. Reverse
engineering of biological networks has has several benefits but a
poor quality of data combined with the difficulty in reproducing
it limits the applicability of these methods. A few years back,
many of the commonly used predictive algorithms were tested
on a network constructed in the yeast Saccharomyces cerevisiae
(S. cerevisiae) to resolve this issue. The network was a synthetic
network of five genes regulating each other for the so-called in
vivo reverse-engineering and modeling assessment (IRMA). The
network was constructed in S. cereviase since it is a simple and well
characterized organism. The synthetic network included a variety
of regulatory interactions, thus capturing the behaviour of larger
eukaryotic gene networks on a smaller scale. We derive a new set of
algorithms by solving a nonlinear optimization problem and show
how these algorithms outperform other algorithms on these datasets.
Abstract: Opinion formation in complex social networks may exhibit complex system dynamics even when based on some simplest system evolution models. An interesting and important issue is the effects of the initial state on the final steady-state opinion distribution. By carrying out extensive simulations and providing necessary discussions, we show that, while different initial opinion distributions certainly make differences to opinion evolution in social systems without noises, in systems with noises, given enough time, different initial states basically do not contribute to making any significant differences in the final steady state. Instead, it is the basal distribution of the preferred opinions that contributes to deciding the final state of the systems. We briefly explain the reasons leading to the observed conclusions. Such an observation contradicts with a long-term belief on the roles of system initial state in opinion formation, demonstrating the dominating role that opinion mutation can play in opinion formation given enough time. The observation may help to better understand certain observations of opinion evolution dynamics in real-life social networks.
Abstract: Image registration is an important topic for many imaging systems and computer vision applications. The standard image registration techniques such as Mutual information/ Normalized mutual information -based methods have a limited performance because they do not consider the spatial information or the relationships between the neighbouring pixels or voxels. In addition, the amount of image noise may significantly affect the registration accuracy. Therefore, this paper proposes an efficient method that explicitly considers the relationships between the adjacent pixels, where the gradient information of the reference and scene images is extracted first, and then the cosine similarity of the extracted gradient information is computed and used to improve the accuracy of the standard normalized mutual information measure. Our experimental results on different data types (i.e. CT, MRI and thermal images) show that the proposed method outperforms a number of image registration techniques in terms of the accuracy.
Abstract: Next generation bio-alcohols produced from non-food based sources like cellulosic biomass are promising renewable energy sources. The present study investigates engine performance, combustion characteristics, and emissions of a small single cylinder direct injection diesel engine fueled by four kinds of next generation bio-alcohol isomer and diesel fuel blends with a constant blending ratio of 3:7 (mass). The tested bio-alcohol isomers here are n-butanol and iso-butanol (C4 alcohol), and n-pentanol and iso-pentanol (C5 alcohol). To obtain simultaneous reductions in NOx and smoke emissions, the experiments employed supercharging combined with EGR (Exhaust Gas Recirculation). The boost pressures were fixed at two conditions, 100 kPa (naturally aspirated operation) and 120 kPa (supercharged operation) provided with a roots blower type supercharger. The EGR rates were varied from 0 to 25% using a cooled EGR technique. The results showed that both with and without supercharging, all the bio-alcohol blended diesel fuels improved the trade-off relation between NOx and smoke emissions at all EGR rates while maintaining good engine performance, when compared with diesel fuel operation. It was also found that regardless of boost pressure and EGR rate, the ignition delays of the tested bio-alcohol isomer blends are in the order of iso-butanol > n-butanol > iso-pentanol > n-pentanol. Overall, it was concluded that, except for the changes in the ignition delays the influence of bio-alcohol isomer blends on the engine performance, combustion characteristics, and emissions are relatively small.