Segmentation and counting of blood cells are considered as an important step that helps to extract features to diagnose some specific diseases like malaria or leukemia. The manual counting of white blood cells (WBCs) and red blood cells (RBCs) in microscopic images is an extremely tedious, time consuming, and inaccurate process. Automatic analysis will allow hematologist experts to perform faster and more accurately. The proposed method uses an iterative structured circle detection algorithm for the segmentation and counting of WBCs and RBCs. The separation of WBCs from RBCs was achieved by thresholding, and specific preprocessing steps were developed for each cell type. Counting was performed for each image using the proposed method based on modified circle detection, which automatically counted the cells. Several modifications were made to the basic (RCD) algorithm to solve the initialization problem, detecting irregular circles (cells), selecting the optimal circle from the candidate circles, determining the number of iterations in a fully dynamic way to enhance algorithm detection, and running time. The validation method used to determine segmentation accuracy was a quantitative analysis that included Precision, Recall, and F-measurement tests. The average accuracy of the proposed method was 95.3% for RBCs and 98.4% for WBCs.
DFT and G4 results reveal that cations display the following trends in imparting its positive charge to acrylonitrile; H⁺ > Li⁺ > Na⁺ > K⁺ for group I and Be²⁺ > Mg²⁺ > Ca²⁺ for group II. Solvation by water molecules and interaction with cation make the cyano bond more polarized and exhibits ketene-imine character. Bond order in nitrile-cation complexes has been predicted based on the s character of the covalent bond orbitals. Mulliken, CHELPG, and NPA charges are in good agreement in predicting positive charge buildup and GIAO nuclear deshileding on C1. G4 enthalpies show that Mg²⁺ is more strongly bound to acrylonitrile than to acetonitrile by 3 kcal mol⁻¹, and the proton affinity of the former is higher by 0.8 kcal mol⁻¹. G4 enthalpies of reductions support prior experimental observation that metalated conjugated nitriles show enhanced reactivity toward weak nucleophiles to afford Michael addition products.
Molecular dynamics simulation and biophysical analysis were employed to reveal the characteristics and the influence of ionic liquids (ILs) on the structural properties of DNA. Both computational and experimental evidence indicate that DNA retains its native B-conformation in ILs. Simulation data show that the hydration shells around the DNA phosphate group were the main criteria for DNA stabilization in this ionic media. Stronger hydration shells reduce the binding ability of ILs' cations to the DNA phosphate group, thus destabilizing the DNA. The simulation results also indicated that the DNA structure maintains its duplex conformation when solvated by ILs at different temperatures up to 373.15 K. The result further suggests that the thermal stability of DNA at high temperatures is related to the solvent thermodynamics, especially entropy and enthalpy of water. All the molecular simulation results were consistent with the experimental findings. The understanding of the properties of IL-DNA could be used as a basis for future development of specific ILs for nucleic acid technology.
This paper presents a study on gene knockout strategies to identify candidate genes to be knocked out for improving the production of succinic acid in Escherichia coli. Succinic acid is widely used as a precursor for many chemicals, for example production of antibiotics, therapeutic proteins and food. However, the chemical syntheses of succinic acid using the traditional methods usually result in the production that is far below their theoretical maximums. In silico gene knockout strategies are commonly implemented to delete the gene in E. coli to overcome this problem. In this paper, a hybrid of Ant Colony Optimization (ACO) and Minimization of Metabolic Adjustment (MoMA) is proposed to identify gene knockout strategies to improve the production of succinic acid in E. coli. As a result, the hybrid algorithm generated a list of knockout genes, succinic acid production rate and growth rate for E. coli after gene knockout. The results of the hybrid algorithm were compared with the previous methods, OptKnock and MOMAKnock. It was found that the hybrid algorithm performed better than OptKnock and MOMAKnock in terms of the production rate. The information from the results produced from the hybrid algorithm can be used in wet laboratory experiments to increase the production of succinic acid in E. coli.
One of the uses of ultrasound in dentistry is in the field of endodontics (i.e. root canal treatment) in order to enhance cleaning efficiency during the treatment. The acoustic pressures generated by the oscillation of files in narrow channels has been calculated using the COMSOL simulation package. Acoustic pressures in excess of the cavitation threshold can be generated and higher values were found in narrower channels. This parallels experimental observations of sonochemiluminescence. The effect of varying the channel width and length and the dimensions and shape of the file are reported. As well as explaining experimental observations, the work provides a basis for the further development and optimisation of the design of endosonic files.
This study uncovered inhibiting factors to cost performance in large construction projects of Malaysia. Questionnaire survey was conducted among clients and consultants involved in large construction projects. In the questionnaire, a total of 35 inhibiting factors grouped in 7 categories were presented to the respondents for rating significant level of each factor. A total of 300 questionnaire forms were distributed. Only 144 completed sets were received and analysed using advanced multivariate statistical software of Structural Equation Modelling (SmartPLS v2). The analysis involved three iteration processes where several of the factors were deleted in order to make the model acceptable. The result of the analysis found that R(2) value of the model is 0.422 which indicates that the developed model has a substantial impact on cost performance. Based on the final form of the model, contractor's site management category is the most prominent in exhibiting effect on cost performance of large construction projects. This finding is validated using advanced techniques of power analysis. This vigorous multivariate analysis has explicitly found the significant category which consists of several causative factors to poor cost performance in large construction projects. This will benefit all parties involved in construction projects for controlling cost overrun.
This study evaluated the use of alginate-immobilized bentonite to remove Cu(II) as an alternative to mitigate clogging problems. The adsorption efficacy (under the influence of time, pH and initial Cu(II) concentration) and reusability of immobilized-bentonite (1% w/v bentonite) was tested against plain alginate beads. Results revealed that immobilized bentonite demonstrated significantly higher sorption efficacy compared to plain alginate beads with 114.70 and 94.04 mg Cu(II) adsorbed g(-1) adsorbent, respectively. Both sorbents were comparable in other aspects where sorption equilibrium was achieved within 6 h, with optimum pH between pH 4 and 5 for adsorption, displayed maximum adsorption capacity at initial Cu(II) concentrations of 400 mg l(-1), and demonstrated excellent reusability potential with desorption greater than 90% throughout three consecutive adsorption-desorption cycles. Both sorbents also conformed to Langmuir isotherm and pseudo-second order kinetic model. Immobilized bentonite is therefore recommended for use in water treatments to remove Cu(II) without clogging the system.
Functional assessment of a coronary artery stenosis severity is generally assessed by fractional flow reserve (FFR), which is calculated from pressure measurements across the stenosis. The purpose of this study is to investigate the effect of porous media of the stenosed arterial wall on this diagnostic parameter. To understand the role of porous media on the diagnostic parameter FFR, a 3D computational simulations of the blood flow in rigid and porous stenotic artery wall models are carried out under steady state and transient conditions for three different percentage area stenoses (AS) corresponding to 70% (moderate), 80% (intermediate), and 90% (severe). Blood was modeled as a non Newtonian fluid. The variations of pressure drop across the stenosis and diagnostic parameter were studied in both models. The FFR decreased in proportion to the increase in the severity of the stenosis. The relationship between the percentage AS and the FFR was non linear and inversely related in both the models. The cut-off value of 0.75 for FFR was observed at 81.89% AS for the rigid artery model whereas 83.61% AS for the porous artery wall model. This study demonstrates that the porous media consideration on the stenotic arterial wall plays a substantial role in defining the cut-off value of FFR. We conclude that the effect of porous media on FFR, could lead to misinterpretation of the functional severity of the stenosis in the region of 81.89 %-83.61% AS.
The accuracy of the numerical result is closely related to mesh density as well as its distribution. Mesh plays a very significant role in the outcome of numerical simulation. Many nasal airflow studies have employed unstructured mesh and more recently hybrid mesh scheme has been utilized considering the complexity of anatomical architecture. The objective of this study is to compare the results of hybrid mesh with unstructured mesh and study its effect on the flow parameters inside the nasal cavity. A three-dimensional nasal cavity model is reconstructed based on computed tomographic images of a healthy Malaysian adult nose. Navier-Stokes equation for steady airflow is solved numerically to examine inspiratory nasal flow. The pressure drop obtained using the unstructured computational grid is about 22.6 Pa for a flow rate of 20 L/min, whereas the hybrid mesh resulted in 17.8 Pa for the same flow rate. The maximum velocity obtained at the nasal valve using unstructured grid is 4.18 m/s and that with hybrid mesh is around 4.76 m/s. Hybrid mesh reported lower grid convergence index (GCI) than the unstructured mesh. Significant differences between unstructured mesh and hybrid mesh are determined highlighting the usefulness of hybrid mesh for nasal airflow studies.
Theoretically, Ultrasound method is an economical and environmentally friendly or "green" technology, which has been of interest for more than six decades for the purpose of enhancement of oil/heavy-oil production. However, in spite of many studies, questions about the effective mechanisms causing increase in oil recovery still existed. In addition, the majority of the mechanisms mentioned in the previous studies are theoretical or speculative. One of the changes that could be recognized in the fluid properties is viscosity reduction due to radiation of ultrasound waves. In this study, a technique was developed to investigate directly the effect of ultrasonic waves (different frequencies of 25, 40, 68 kHz and powers of 100, 250, 500 W) on viscosity changes of three types of oil (Paraffin oil, Synthetic oil, and Kerosene) and a Brine sample. The viscosity calculations in the smooth capillary tube were based on the mathematical models developed from the Poiseuille's equation. The experiments were carried out for uncontrolled and controlled temperature conditions. It was observed that the viscosity of all the liquids was decreased under ultrasound in all the experiments. This reduction was more significant for uncontrolled temperature condition cases. However, the reduction in viscosity under ultrasound was higher for lighter liquids compare to heavier ones. Pressure difference was diminished by decreasing in the fluid viscosity in all the cases which increases fluid flow ability, which in turn aids to higher oil recovery in enhanced oil recovery (EOR) operations. Higher ultrasound power showed higher liquid viscosity reduction in all the cases. Higher ultrasound frequency revealed higher and lower viscosity reduction for uncontrolled and controlled temperature condition experiments, respectively. In other words, the reduction in viscosity was inversely proportional to increasing the frequency in temperature controlled experiments. It was concluded that cavitation, heat generation, and viscosity reduction are three of the promising mechanisms causing increase in oil recovery under ultrasound.
We describe the work on infusion of emotion into a limited-task autonomous spoken conversational agent situated in the domestic environment, using a need-inspired task-independent emotion model (NEMO). In order to demonstrate the generation of affect through the use of the model, we describe the work of integrating it with a natural-language mixed-initiative HiFi-control spoken conversational agent (SCA). NEMO and the host system communicate externally, removing the need for the Dialog Manager to be modified, as is done in most existing dialog systems, in order to be adaptive. The first part of the paper concerns the integration between NEMO and the host agent. The second part summarizes the work on automatic affect prediction, namely, frustration and contentment, from dialog features, a non-conventional source, in the attempt of moving towards a more user-centric approach. The final part reports the evaluation results obtained from a user study, in which both versions of the agent (non-adaptive and emotionally-adaptive) were compared. The results provide substantial evidences with respect to the benefits of adding emotion in a spoken conversational agent, especially in mitigating users' frustrations and, ultimately, improving their satisfaction.
The study was conducted based on two objectives as framework. The first objective is to determine the point of microwave signal reflection while penetrating into the simulation models and, the second objective is to analyze the reflection pattern when the signal penetrate into the layers with different relative permittivity, εr. Thus, several microwave models were developed to make a close proximity of the in vivo human brain. The study proposed two different layers on two different characteristics models. The radii on the second layer and the corresponding antenna positions are the factors for both models. The radii for model 1 is 60 mm with an antenna position of 10 mm away, in contrast, model 2 is 10 mm larger in size with a closely adapted antenna without any gap. The layers of the models were developed with different combination of materials such as Oil, Sandy Soil, Brain, Glycerin and Water. Results show the combination of Glycerin + Brain and Brain + Sandy Soil are the best proximity of the in vivo human brain grey and white matter. The results could benefit subsequent studies for further enhancement and development of the models.
Combined computational and experimental strategies for the systematic design of chemical sensor arrays using carbonitrile neutral receptors are presented. Binding energies of acetonitrile, n-pentylcarbonitrile and malononitrile with Ca(II), Mg(II), Be(II) and H⁺ have been investigated with the B3LYP, G3, CBS-QB3, G4 and MQZVP methods, showing a general trend H⁺ > Be(II) > Mg(II) > Ca(II). Hydrogen bonding, donor-acceptor and cation-lone pair electron simple models were employed in evaluating the performance of computational methods. Mg(II) is bound to acetonitrile in water by 12.5 kcal/mol, and in the gas phase the receptor is more strongly bound by 33.3 kcal/mol to Mg(II) compared to Ca(II). Interaction of bound cations with carbonitrile reduces the energies of the MOs involved in the proposed σ-p conjugated network. The planar malononitrile-Be(II) complex possibly involves a π-network with a cationic methylene carbon. Fabricated potentiometric chemical sensors show distinct signal patterns that can be exploited in sensor array applications.
We present a new theoretical model for the broadband reflection spectra of etched FBGs which includes the effects of axial contraction and stress-induced index change. The reflection spectra of the etched FBGs with several different taper profiles are simulated based on the proposed model. In our observation, decaying exponential profile produces a broadband reflection spectrum with good uniformity over the range of 1540-1560 nm. An etched FBG with similar taper profile is fabricated and the experimental result shows good agreement with the theoretical model.
Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.
Cytochromes P450 (CYPs) play a central role in the Phase I metabolism of drugs and other xenobiotics. It is estimated that CYPs can metabolize up to two-thirds of drugs present in humans. Over the past two decades, there have been numerous advances in in vitro methodologies to characterize drug metabolism and interaction involving CYPs.
This study aimed to develop a three-dimensional finite element model of a functionally graded femoral prosthesis. The model consisted of a femoral prosthesis created from functionally graded materials (FGMs), cement, and femur. The hip prosthesis was composed of FGMs made of titanium alloy, chrome-cobalt, and hydroxyapatite at volume fraction gradient exponents of 0, 1, and 5, respectively. The stress was measured on the femoral prosthesis, cement, and femur. Stress on the neck of the femoral prosthesis was not sensitive to the properties of the constituent material. However, stress on the stem and cement decreased proportionally as the volume fraction gradient exponent of the FGM increased. Meanwhile, stress became uniform on the cement mantle layer. In addition, stress on the femur in the proximal part increased and a high surface area of the femoral part was involved in absorbing the stress. As such, the stress-shielding area decreased. The results obtained in this study are significant in the design and longevity of new prosthetic devices because FGMs offer the potential to achieve stress distribution that more closely resembles that of the natural bone in the femur.
A kinetic model incorporating adsorption, desorption and biodegradation processes was developed to describe the bioregeneration of granular activated carbon (GAC) loaded with 4-chlorophenol (4-CP) and 2,4-dichlorophenol (2,4-DCP), respectively, in simultaneous adsorption and biodegradation processes. The model was numerically solved and the results showed that the kinetic model was well-fitted (R(2)>0.83) to the experimental data at different GAC dosages and at various initial 4-CP and 2,4-DCP concentrations. The rate of bioregeneration in simultaneous adsorption and biodegradation processes was influenced by the ratio of initial chlorophenol concentration to GAC dosage. Enhancement in the rate of bioregeneration was achieved by using the lowest ratio under either one of the following experimental conditions: (1) increasing initial chlorophenol concentration at constant GAC dosage and (2) increasing GAC dosage at constant initial chlorophenol concentration. It was found that the rate enhancement was more pronounced under the second experimental condition.
The effect of the recently developed graphene nanoflakes (GNFs) on the polymerase chain reaction (PCR) has been investigated in this paper. The rationale behind the use of GNFs is their unique physical and thermal properties. Experiments show that GNFs can enhance the thermal conductivity of base fluids and results also revealed that GNFs are a potential enhancer of PCR efficiency; moreover, the PCR enhancements are strongly dependent on GNF concentration. It was found that GNFs yield DNA product equivalent to positive control with up to 65% reduction in the PCR cycles. It was also observed that the PCR yield is dependent on the GNF size, wherein the surface area increases and augments thermal conductivity. Computational fluid dynamics (CFD) simulations were performed to analyze the heat transfer through the PCR tube model in the presence and absence of GNFs. The results suggest that the superior thermal conductivity effect of GNFs may be the main cause of the PCR enhancement.
The wrist is the most complex joint for virtual three-dimensional simulations, and the complexity is even more pronounced when dealing with skeletal disorders of the joint such, as rheumatoid arthritis (RA). In order to analyse the biomechanical difference between healthy and diseased joints, three-dimensional models of these two wrist conditions were developed from computed tomography images. These images consist of eight carpal bones, five metacarpal bones, the distal radius and ulna. The cartilages were developed based on the shape of the available articulations and ligaments were simulated via mechanical links. The RA model was developed accurately by simulating all ten common criteria of the disease related to the wrist. Results from the finite element (FE) analyses showed that the RA model produced three times higher contact pressure at the articulations compared to the healthy model. Normal physiological load transfer also changed from predominantly through the radial side to an increased load transfer approximately 5% towards the ulnar. Based on an extensive literature search, this is the first ever reported work that simulates the pathological conditions of the rheumatoid arthritis of the wrist joint.