Transfer factors for natural radioactivity into olive mill pomace.

The transfer factor (TF) of naturally occurring radioactivity between soil and olive mill pomace (OMP) was calculated in this study. Nine samples were collected from three locations in north Jordan. The study focused on calculating the 226Ra, 232Th, 40K, and 137Cs activity concentrations in both soil and OMP samples using high-purity germanium (HPGe) gamma-ray spectrometry. The average activity levels in the soil samples were determined to be 24.0±10.1, 31.3±9.1, 323.7±68.4, and 1.0±0.4 (Bqkg-1), respectively. In the OMP samples, the average activity levels of 226Ra, 232Th, and 40K were 6.7±1.8, 3.2±1.2, and 185.5±56.6 (Bqkg-1), respectively, while no trace of 137Cs was detected. The activity concentrations of 226Ra, 232Th, and 40K in the soils and OMP samples are within the average worldwide ranges. The calculated values of the TF geometric mean (geometric standard deviation) for 226Ra, 232Th, and 40K were determined to be 0.35 (0.2), 0.11 (0.05), and 0.59 (0.19), respectively. This research offers valuable information about the behavior and movement of radionuclides in the environment.

Magnetocaloric effect and critical behavior of the La0.75Ca0.1Na0.15MnO3 compound.

In this paper, we have studied the critical behavior and the magnetocaloric effect (MCE) simulation for the La0.75Ca0.1Na0.15MnO3 (LCNMO) compound at the second order ferromagnetic-paramagnetic phase transition. The optimized critical exponents, based on the Kouvel-Fisher method, were found to be: ß = 0.48 and γ = 1. These obtained values supposed that the Mean Field Model (MFM) is the proper model to analyze adequately the MCE in the LCNMO sample. The isothermal magnetization M(H, T) and the magnetic entropy change -ΔSM(H, T) curves were successfully simulated using three models, namely the Arrott-Noakes equation (ANE) of state, Landau theory, and MFM. The framework of the MFM allows us to estimate magnetic entropy variation in a wide temperature range within the thermodynamics of the model and without using the usual numerical integration of Maxwell relation.

Numerical optimization of microfluidic biosensor detection time for the SARS-CoV-2 using the Taguchi method.

The performance of microfluidic biosensor of the SARS-Cov-2 was numerically analyzed through finite element method. The calculation results have been validated with comparison with experimental data reported in the literature. The novelty of this study is the use of the Taguchi method in the optimization analysis, and an L8(25) orthogonal table of five critical parameters-Reynolds number (Re), Damköhler number (Da), relative adsorption capacity (σ), equilibrium dissociation constant (KD), and Schmidt number (Sc), with two levels was designed. ANOVA methods are used to obtain the significance of key parameters. The optimal combination of the key parameters is Re = 10-2, Da = 1000, σ = 0.2, KD = 5, and Sc 104 to achieve the minimum response time (0.15). Among the selected key parameters, the relative adsorption capacity (σ) has the highest contribution (42.17%) to the reduction of the response time, while the Schmidt number (Sc) has the lowest contribution (5.19%). The presented simulation results are useful in designing microfluidic biosensors in order to reduce their response time.

Taguchi method: artificial neural network approach for the optimization of high-efficiency microfluidic biosensor for COVID-19.

COVID-19 is a pandemic disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This virus is mainly spread by droplets, respiratory secretions, and direct contact. Caused by the huge spread of the COVID-19 epidemic, research is focused on the study of biosensors as it presents a rapid solution for reducing incidents and fatality rates. In this paper, a microchip flow confinement method for the rapid transport of small sample volumes to sensor surfaces is optimized in terms of the confinement coefficient ß, the position of the confinement flow X, and its inclination α relative to the main channel. A numerical simulation based on two-dimensional Navier-Stokes equations has been used. Taguchi's L9(33) orthogonal array was adopted to design the numerical assays taking into account the confining flow parameters (α, ß, and X) on the response time of microfluidic biosensors. Analyzing the signal-to-noise ratio allowed us to determine the most effective combinations of control parameters for reducing the response time. The contribution of the control factors to the detection time was determined via analysis of variance (ANOVA). Numerical predictive models using multiple linear regression (MLR) and an artificial neural network (ANN) were developed to accurately predict microfluidic biosensor response time. This study concludes that the best combination of control factors is α 3 ß 3 X 2 that corresponds to α = 90 ∘ , ß = 25 and X = 40 µm. Analysis of variance (ANOVA) shows that the position of the confinement channel (62% contribution) is the factor most responsible for the reduction in response time. Based on the correlation coefficient (R 2), and value adjustment factor (VAF), the ANN model performed better than the MLR model in terms of prediction accuracy.

Taguchi optimization of integrated flow microfluidic biosensor for COVID-19 detection.

In this research, Taguchi's method was employed to optimize the performance of a microfluidic biosensor with an integrated flow confinement for rapid detection of the SARS-CoV-2. The finite element method was used to solve the physical model which has been first validated by comparison with experimental results. The novelty of this study is the use of the Taguchi approach in the optimization analysis. An L 8 2 7 orthogonal array of seven critical parameters-Reynolds number (Re), Damköhler number (Da), relative adsorption capacity ( σ ), equilibrium dissociation constant (KD), Schmidt number (Sc), confinement coefficient (α) and dimensionless confinement position (X), with two levels was designed. Analysis of variance (ANOVA) methods are also used to calculate the contribution of each parameter. The optimal combination of these key parameters was Re = 10-2, Da = 1000, σ = 0.5, K D = 5, Sc = 105, α = 2 and X = 2 to achieve the lowest dimensionless response time (0.11). Among the all-optimization factors, the relative adsorption capacity ( σ ) has the highest contribution (37%) to the reduction of the response time, while the Schmidt number (Sc) has the lowest contribution (7%).

Sensitive Detection of SARS-CoV-2 Using a Novel Plasmonic Fiber Optic Biosensor Design.

The coronavirus (COVID-19) pandemic has put the entire world at risk and caused an economic downturn in most countries. This work provided theoretical insight into a novel fiber optic-based plasmonic biosensor that can be used for sensitive detection of SARS-CoV-2. The aim was always to achieve reliable, sensitive, and reproducible detection. The proposed configuration is based on Ag-Au alloy nanoparticle films covered with a layer of graphene which promotes the molecular adsorption and a thiol-tethered DNA layer as a ligand. Here, the combination of two recent approaches in a single configuration is very promising and can only lead to considerable improvement. We have theoretically analyzed the sensor performance in terms of sensitivity and resolution. To highlight the importance of the new configuration, a comparison was made with two other sensors. One is based on gold nanoparticles incorporated into a host medium; the other is composed of a bimetallic Ag-Au layer in the massive state. The numerical results obtained have been validated and show that the proposed configuration offers better sensitivity (7100 nm\RIU) and good resolution (figure of merit; FOM = 38.88 RIU - 1 and signal-to-noise ratio; SNR = 0.388). In addition, a parametric study was performed such as the graphene layers' number and the size of the nanoparticles.

Design parameters optimization of an electrothermal flow biosensor for the SARS-CoV-2 S protein immunoassay.

To combat the coronavirus disease 2019 (COVID-19), great efforts have been made by scientists around the world to improve the performance of detection devices so that they can efficiently and quickly detect the virus responsible for this disease. In this context we performed 2D finite element simulation on the kinetics of SARS-CoV-2 S protein binding reaction of a biosensor using the alternating current electrothermal (ACET) effect. The ACET flow can produce vortex patterns, thereby improving the transportation of the target analyte to the binding surface and thus enhancing the performance of the biosensor. Optimization of some design parameters concerning the microchannel height and the reaction surface, such as its length as well as its position on the top wall of the microchannel, in order to improve the biosensor efficiency, was studied. The results revealed that the detection time can be improved by 55% with an applied voltage of 10 V rms and an operating frequency of 150 kHz and that the decrease in the height of the microchannel and in the length of the binding surface can lead to an increase in the rate of the binding reaction and therefore decrease the biosensor response time. Also, moving the sensitive surface from an optimal position, located in front of the electrodes, decreases the performance of the device.

3D simulation of microfluidic biosensor for SARS-CoV-2 S protein binding kinetics using new reaction surface design.

In this study, we performed 3D finite element simulations on the binding reaction kinetics of SARS-CoV-2 S protein (target analyte) and its corresponding immobilized antibody (ligand) in a heterogeneous microfluidic immunoassay. Two types of biosensors with two different shapes and geometries of the reaction surface and electrodes were studied. Alternating current electrothermal (ACET) force was applied to improve the binding efficiency of the biomolecular pairs by accelerating the transport of analytes to the binding surface. The ACET force stirs the flow field, thereby reducing the thickness of the diffusion boundary layer, often developed on the reaction surface due to the slow flow velocity, low analyte diffusion coefficient, and surface reaction high rate. The results showed that the detection time of one of the biosensors can be improved by 69% under an applied voltage of 10 Vrms and an operating frequency of 100 kHz. Certain control factors such as the thermal boundary conditions as well as the electrical conductivity of the buffer solution were analyzed in order to find the appropriate values to improve the efficiency of the biosensor.

Enhancement of COVID-19 detection time by means of electrothermal force.

The rapid spread and quick transmission of the new ongoing pandemic coronavirus disease 2019 (COVID-19) has urged the scientific community to looking for strong technology to understand its pathogenicity, transmission, and infectivity, which helps in the development of effective vaccines and therapies. Furthermore, there was a great effort to improve the performance of biosensors so that they can detect the pathogenic virus quickly, in reliable and precise way. In this context, we propose a numerical simulation to highlight the important role of the design parameters that can significantly improve the performance of the biosensor, in particular the sensitivity as well as the detection limit. Applied alternating current electrothermal (ACET) force can generate swirling patterns in the fluid within the microfluidic channel, which improve the transport of target molecule toward the reaction surface and, thus, enhance the response time of the biosensor. In this work, the ACET effect on the SARS-CoV-2 S protein binding reaction kinetics and on the detection time of the biosensor was analyzed. Appropriate choice of electrodes location on the walls of the microchannel and suitable values of the dissociation and association rates of the binding reaction, while maintaining the same affinity, with and without ACET effect, are also, discussed to enhance the total performance of the biosensor and reduce its response time. The two-dimensional equations system is solved by the finite element approach. The best performance of the biosensor is obtained in the case where the response time decreased by 61% with AC applying voltage.

ECG compression with Douglas-Peucker algorithm and fractal interpolation.

In this paper, we propose a new ECG compression method using the fractal technique. The proposed approaches utilize the fact that ECG signals are a fractal curve. This algorithm consists of three steps: First, the original ECG signals are processed and they are converted into a 2-D array. Second, the Douglas-Peucker algorithm (DP) is used to detect critical points (compression phase). Finally, we used the fractal interpolation and the Iterated Function System (IFS) to generate missing points (decompression phase). The proposed (suggested) methodology is tested for different records selected from PhysioNet Database. The obtained results showed that the proposed method has various compression ratios and converges to a high value. The average compression ratios are between 3.19 and 27.58, and also, with a relatively low percentage error (PRD), if we compare it to other methods. Results depict also that the ECG signal can adequately retain its detailed structure when the PSNR exceeds 40 dB.

Analysis of Temperature-Jump Boundary Conditions on Heat Transfer for Heterogeneous Microfluidic Immunosensors.

The objective of the current study is to analyze numerically the effect of the temperature-jump boundary condition on heterogeneous microfluidic immunosensors under electrothermal force. A three-dimensional simulation using the finite element method on the binding reaction kinetics of C-reactive protein (CRP) was performed. The kinetic reaction rate was calculated with coupled Laplace, Navier-Stokes, energy, and mass diffusion equations. Two types of reaction surfaces were studied: one in the form of a disc surrounded by two electrodes and the other in the form of a circular ring, one electrode is located inside the ring and the other outside. The numerical results reveal that the performance of a microfluidic biosensor is enhanced by using the second design of the sensing area (circular ring) coupled with the electrothermal force. The improvement factor under the applied ac field 15 Vrms was about 1.2 for the first geometry and 3.6 for the second geometry. Furthermore, the effect of temperature jump on heat transfer rise and response time was studied. The effect of two crucial parameters, viz. Knudsen number (Kn) and thermal accommodation coefficient (σT) with and without electrothermal effect, were analyzed for the two configurations.

Structural and morphological studies, and temperature/frequency dependence of electrical conductivity of Ba0.97La0.02Ti1-x Nb4x/5O3 perovskite ceramics.

Conductivity measurements of our polycrystalline perovskite ceramic systems with a composition of Ba0.97La0.02Ti1-x Nb4x/5O3 (x = 5, 7 and 10, in mol%) were performed, in order to investigate frequency and temperature dependence. Our ferroelectric ceramics were fabricated by the molten-salt method (chemical reaction followed by an evaporation and filtration reaction); X-ray diffraction patterns indicated that a single phase was formed for pure BaLT1-x Nb4x/5 ceramics. The electrical behavior of the ceramics was studied by impedance spectroscopy in the 500-610 K temperature range. The conductivity was investigated which can be described by the Jonscher law. Both AC and DC electrical conductivities are completely studied as a function of frequency and temperature. The conductivity exhibits a notable increase with increasing Nb-rates. The low-frequency conductivity results from long-range ordering (close to frequency-independent) and the high-frequency conductivity is attributable to the localized orientation hopping process. Impedance analysis was performed revealing conductivity data which fitted the modified power, σ AC(ω) = Aω n . The frequency dependence of the conductivity plot has been found to obey the universal Jonscher power law. Both AC and DC electrical conductivities are thoroughly studied as a function of frequency as well as temperature. The AC conductivity reveals that correlated barrier hopping (CBH) and non-overlapping small polaron tunneling (NSPT) models are suitable theoretical models to elucidate the conduction mechanisms existing in our compounds. Significantly, by increasing the temperature, the DC conductivity was increased, which verifies the semiconducting nature of the materials.

Simulation of the Slip Velocity Effect in an AC Electrothermal Micropump.

The principal aim of this study was to analyze the effect of slip velocity at the microchannel wall on an alternating current electrothermal (ACET) flow micropump fitted with several pairs of electrodes. Using the finite element method (FEM), the coupled momentum, energy, and Poisson equations with and without slip boundary conditions have been solved to compute the velocity, temperature, and electrical field in the microchannel. The effects of the frequency and the voltage, and the electrical and thermal conductivities, respectively, of the electrolyte solution and the substrate material, have been minutely analyzed in the presence and absence of slip velocity. The slip velocity was simulated along the microchannel walls at different values of slip length. The results revealed that the slip velocity at the wall channel has a significant impact on the flow field. The existence of slip velocity at the wall increases the shear stress and therefore enhances the pumping efficiency. It was observed that higher average pumping velocity was achieved for larger slip length. When a glass substrate was used, the effect of the presence of the slip velocity was more manifest. This study shows also that the effect of slip velocity on the flow field is very important and must be taken into consideration in an ACET micropump.

AC Electroosmosis Effect on Microfluidic Heterogeneous Immunoassay Efficiency.

A heterogeneous immunoassay is an efficient biomedical test. It aims to detect the presence of an analyte or to measure its concentration. It has many applications, such as manipulating particles and separating cancer cells from blood. The enhanced performance of immunosensors comes down to capturing more antigens with greater efficiency by antibodies in a short time. In this work, we report an efficient investigation of the effects of alternating current (AC) electrokinetic forces such as AC electroosmosis (ACEO), which arise when the fluid absorbs energy from an applied electric field, on the kinetics of the antigen-antibody binding in a flow system. The force can produce swirling structures in the fluid and, thus, improve the transport of the analyte toward the reaction surface of the immunosensor device. A numerical simulation is adequate for this purpose and may provide valuable information. The convection-diffusion phenomenon is coupled with the first-order Langmuir model. The governing equations are solved using the finite element method (FEM). The impact of AC electroosmosis on the binding reaction kinetics, the fluid flow stream modification, the analyte concentration diffusion, and the detection time of the biosensor under AC electroosmosis are analyzed.

A microscopic and macroscopic investigation of the adsorption of N719 dye on ZnO nanopowders (ZNP) and ZnO nanorods (ZNR) for dye sensitized solar cells using statistical physics treatment and DFT simulation.

In this paper, three adsorption isotherms of N719 dye on two different adsorbents, ZnO nanopowder and ZnO nanorods, at three different thicknesses have been fitted using a monolayer model with three types of receptor sites treated by statistical physics. The model involved parameters are: three coefficients (n 1, n 2 and n 3) indicating the numbers of adsorbed dye molecules per site, three parameters (N m1, N m2 and N m3) indicating the receptor site densities and three adsorption energies ((-ε 1), (-ε 2) and (-ε 3)). The evolution of these parameters in relation with thickness of ZnO was discussed. The pore size distribution (PSD) of ZnO nanopowder and ZnO nanorods as a function of the thickness has been studied using the chosen adequate model. The molecular electrostatic potential (MEP) has been investigated to optimize the different adsorbed geometries of the complex N719 dye@ZnO. The intermolecular interactions between the N719 dye and the ZnO surface have been studied by using the quantum theory of atoms in molecules (AIM) and reduced density gradient RDG. The results of the MEP, topological AIM and RDG are in agreement with the results of statistical physics.

Numerical Modeling of the Electronic and Electrical Characteristics of InGaN/GaN-MQW Solar Cells.

In this paper, a numerical model allows to analyze the photovoltaic parameters according to the electronic properties of InxGa1-xN/GaN MQW solar cells under the effect of temperature, the number of quantum wells and indium composition. The numerical investigation starts from the evaluation through the finite difference (FDM) simulation of the self-consistent method coupled with the photovoltaic parameters taking into account the effects of the spontaneous and piezoelectric polarization. The results found were consistent with the literature. As expected, the temperature had a negative impact on the performance of InGaN/GaN MQW solar cells. However, increasing the number of quantum wells improves cell performance. This positive impact further improves with the increase in the indium rate. The obtained results were 28 mA/cm2 for the short-circuit current density, 1.43 V for the open-circuit voltage, and the obtained conversion efficiency was 31% for a model structure based on 50-period InGaN/GaN-MQW-SC under 1-sun AM1.5G.

Optimization of microfluidic biosensor efficiency by means of fluid flow engineering.

Binding reaction kinetics of analyte-ligand at the level of a sensitive membrane into a microchannel of a biosensor has been limited by the formation of the boundary diffusion layer. Therefore, the response time increases and affects the overall performance of a biosensor. In the present work, we develop an approach to engineer fluid streams into a complex configuration in order to improve the binding efficiency. We investigate numerically the flow deformations around a parallelepiped with square cross-section inside the microfluidic channel and exploit these deformations to simulate the analyte transport to the sensitive membrane and enhance both association and dissociation processes. The effect of several parameters on the binding reaction is provided such as: the obstacle location from the inlet of the microchannel, the average flow velocity, and the inlet analyte concentration. The optimal position of the obstacle is determined. An appropriate choice of the inlet flow velocity and inlet analyte concentration may reduce significantly the response time.

Novel Computerized Method for Measurement of Retinal Vessel Diameters.

Several clinical studies reveal the relationship between alterations in the topologies of the human retinal blood vessel, the outcrop and the disease evolution, such as diabetic retinopathy, hypertensive retinopathy, and macular degeneration. Indeed, the detection of these vascular changes always has gaps. In addition, the manual steps are slow, which may be subjected to a bias of the perceiver. However, we can overcome these troubles using computer algorithms that are quicker and more accurate. This paper presents and investigates a novel method for measuring the blood vessel diameter in the retinal image. The proposed method is based on a thresholding segmentation and thinning step, followed by the characteristic point determination step by the Douglas-Peucker algorithm. Thereafter, it uses the active contours to detect vessel contour. Finally, Heron's Formula is applied to assure the calculation of vessel diameter. The obtained results for six sample images showed that the proposed method generated less errors compared to other techniques, which confirms the high performance of the proposed method.

Numerical Study of the Electrothermal Effect on the Kinetic Reaction of Immunoassays for a Microfluidic Biosensor.

In this work, we simulate the binding reaction of C-reactive protein in a microchannel of a biosensor. A problem that arises in this device concerns the transport of the analyte toward the reaction surface of the biosensor, which is of a very small dimension. The limitation of mass transport causes the formation of a diffusion boundary layer and restrains the whole kinetic reaction. To enhance the performance of the biosensor by improving the transport, an applied AC electric field and flow confinement are used to stir the flow field. The numerical simulation of these mechanisms on the binding reaction is performed using the finite element method. Swirling patterns are generated in the fluid. They enhance the transport of the analyte and confine it near the reaction surface. The location of the electrode pair on the walls of the microchannel for the design of the biosensor has been studied to find out the effects of varying geometric configurations on the binding efficiency. The best performances of the biosensor are obtained when the electrodes are placed on the same wall of the microchannel as the reaction surface. For the best case, under the effect of the applied electric field alone, the enhancement factors raise up to 2.46 and 2.10 for the association and dissociation phases, respectively. By contrast, under the effect of the electric field with flow confinement, the enhancement factors for the association and the dissociation phases jump to 3.43 and 2.97, respectively, for 30:1 flow confinement (ratio of confining to sample flow).

Automatic extraction of blood vessels in the retinal vascular tree using multiscale medialness.

We propose an algorithm for vessel extraction in retinal images. The first step consists of applying anisotropic diffusion filtering in the initial vessel network in order to restore disconnected vessel lines and eliminate noisy lines. In the second step, a multiscale line-tracking procedure allows detecting all vessels having similar dimensions at a chosen scale. Computing the individual image maps requires different steps. First, a number of points are preselected using the eigenvalues of the Hessian matrix. These points are expected to be near to a vessel axis. Then, for each preselected point, the response map is computed from gradient information of the image at the current scale. Finally, the multiscale image map is derived after combining the individual image maps at different scales (sizes). Two publicly available datasets have been used to test the performance of the suggested method. The main dataset is the STARE project's dataset and the second one is the DRIVE dataset. The experimental results, applied on the STARE dataset, show a maximum accuracy average of around 94.02%. Also, when performed on the DRIVE database, the maximum accuracy average reaches 91.55%.