Numerical modeling and experimental optimization of Taylor dispersion analysis with and without an electric field.

Numerical modeling of Taylor dispersion analysis (TDA) was performed using COMSOL Multiphysics to facilitate better and faster optimization of the experimental conditions. Parameters, such as pressure, electric field, diameter, and length of capillary on the TDA conditions, were examined for particles with hydrodynamic radius (Rh) of 2.5-250 Å. The simulations were conducted using 25, 50, and 100 cm length tubes with diameters of 25, 50, and 100 µm. It was shown that particles with larger diffusion coefficients gave more accurate results at higher velocities, and in longer and wider columns; particles with smaller diffusion coefficients gave more accurate results at smaller velocities, and in shorter and thinner columns. Moreover, the effect of electric field on the validity and the applicability of TDA was studied using TDA in conjunction with capillary electrophoresis. Diffusion coefficients were obtained using a pressure and the TDA equation and compared with those obtained with a pressure in combination of an electric field for fluorescein, FD4, FD20, FD70, and FD500. We found that TDA can be used with the presence of moderate electrophoretic migration and electroosmotic flow, when appropriate conditions were met.

Temperature controls the relation between soil organic carbon and microbial carbon use efficiency.

Microbial carbon use efficiency (CUE) is an important variable mediating microbial effects on soil organic carbon (SOC) since it summarizes how much carbon is used for microbial growth or is respired. Yet, the role of CUE in regulating SOC storage remains debated, with evidence for both positive and negative SOC-CUE relations. Here, we use a combination of measured data around the world and numerical simulations to explore SOC-CUE relations accounting for temperature (T) effects on CUE. Results reveal that the sign of the CUE-T relation controls the direction of the SOC-CUE relations. A negative CUE-T relation leads to a positive SOC-CUE relation and vice versa, highlighting that CUE-T patterns significantly affect how organic carbon is used by microbes and hence SOC-CUE relations. Numerical results also confirm the observed negative SOC-T relation, regardless of the CUE-T patterns, implying that temperature plays a more dominant role than CUE in controlling SOC storage. The SOC-CUE relation is usually negative when temperature effects are isolated, even though it can become positive when nonlinear microbial turnover is considered. These results indicate a dominant role of CUE-T patterns in controlling the SOC-CUE relation. Our findings help to better understand SOC and microbial responses to a warming climate.

Invariances in relations between aging, exposure to external hazards, and mortality reflected in life table aging rate (LAR) patterns examined through the lens of generalized Gompertz-Makeham law.

According to the Gompertz law, the age-dependent change in the logarithm of mortality (life-table aging rate, LAR) is equal to the population-averaged age-independent biological aging rate (γ), and LAR would be constant if aging were the only cause of mortality increase. However, LAR is influenced by population exposures to the external hazards. If they were constant, according to the Gompertz-Makeham law (GML), LAR would be below γ at lower ages and asymptotically and monotonically approach γ with increasing age. Actually, LAR trajectories derived from data on mortality in different countries and historical periods feature systematic undulations. In the present investigation, mortality-vs.-age trajectories were modeled based on a generalized GML (gGML). Unlike the canonical GML terms, which are population-specific constants, the respective terms of the gGML are represented with some population-specific functions of age. Invariant in gGML are the modes of translation of these functions into the dependency of mortality on age: linear for population exposure to the irresistible external hazards or exponential for population-averaged ability to withstand the resistible external and internal hazards. Modeling suggests that, at earlier ages, LAR undulations are attributable to changes in population exposures to the former hazards. However, only their unrealistically high levels can produce the transient increase in LAR at about 65 to 90 years. This pervasive undulation of LAR-vs.-age trajectory is rather caused by an increment in γ. Reasons to regard gGML as a genuine natural law, which defines relations between mortality, aging and environment, are discussed.

Improvement in Active Cell Proliferation Area at Higher Permeability With Novel TPMS Lattice Structure.

The utilization of lattice-based scaffolds emerging as an advance technique over conventional bio-implants in Bone Tissue Engineering. In this study, totally six lattice structures are considered for permeability and wall shear stress (WSS) investigation. Namely triply periodic minimal surfaces (TPMS)-based Gyroid, Schwarz-P, Schwarz-D, and two beam-based structure-Cubic and Fluorite are compared with the proposed new lattice structure at porosity level of 80%, 75%, and 70%. The proposed new lattice has combine characteristic of Gyroid and Schwarz-D TPMS lattice. The permeability is determined through Darcy's law, where the pressure drop across the lattice structure is calculated using a computational fluid dynamics (CFD) tool at flowrate between 0.2 and 10 ml/min. The Cubic and Schwarz-P lattice structures exhibited the highest permeability but at the cost of a lower active surface area for WSS, measuring below 155 mm2, means least cell proliferation occurs while the permeability value in New Lattice structure is in the ideal range with the enhanced active surface area for WSS (514 mm2). The complex internal curvatures of New Lattice promote the cell proliferation while the through-pore holes allow the efficient cell seeding.

Evaluating the effect of glycerol on increasing the safety and efficiency of hyperthermic laser lipolysis.

This study aimed to investigate the effect of glycerol as an Optical Clearing Agent on the temperature profile of the skin during HyperThermic Laser Lipolysis using computer simulation. In this study, a three-layer model of the skin was used to simulate HyperThermic Laser Lipolysis. The Monte Carlo MCML code was used to investigate the propagation of laser photons inside skin tissue. The energy absorbed from photons is used as a heat source to determine the increase in temperature and assess thermal damage in the layers of the skin. The finite element method in COMSOL software was used for calculation. The simulation of single-pulse radiation exposure with and without applying glycerol to the skin model was investigated to assess the impact of glycerol. Glycerol decreases the temperature and thermal damage to the epidermis layer while increasing the temperature of the fat layer. Moreover, the presence of glycerol increases the depth of fat cell destruction. Glycerol, as a supplement, significantly improves the efficacy of HyperThermic Laser Lipolysis.

Using monitoring and mechanistic modeling to improve understanding of eutrophication in a shallow New England estuary.

Anthropogenic nutrient loading has resulted in eutrophication and habitat degradation within estuaries. Study of eutrophication in estuaries has often focused on larger systems, while there has been increasing interest in understanding the governing processes in smaller systems. In this study, we incorporate both monitoring data and mechanistic modeling to improve our understanding of eutrophication in a small, shallow New England estuary. High-frequency continuous and discrete water quality samples were collected from 2018 to 2020 along a salinity gradient and at varying depth to provide temporal and spatial resolution of the system. Conditions of this estuary were simulated using the Hydrological Simulation Program - FORTRAN (HSPF) and the Water Quality Analysis Simulation Program (WASP) to develop a mechanistic, numerical fate and transport model. Our findings suggest complex hydrodynamics with three distinct salinity gradients and variability in salinity concentration upstream. Simulated and observed nutrient trends demonstrated decreasing total nitrogen concentration moving downstream and low total phosphorus concentration throughout the system. Simulated nutrient depletion and shading via macroalgae suggest their importance in similar modeling initiatives. Dynamic spatiotemporal variability in dissolved oxygen concentrations ([DO]) resulted from hydrodynamic and ecological processes such as large, rapid swings in phytoplankton. Carbonaceous biological oxygen demand was suggested to be the driver of hypoxia in surface waters, while sediment oxygen demand may drive low [DO] in the stratified, benthic waters. These findings suggest that the coordination of monitoring and modeling was important to understanding the governing mechanisms of eutrophication and hypoxia. Insights from this study could be used to support regional management strategies to increase [DO], improve water clarity, and recover indigenous seagrass beds. This work has the potential to inform future study and management of small, complex estuaries.

Numerical Modeling of Anisotropic Particle Diffusion through a Cylindrical Channel.

The transport of molecules and particles through single pores is the basis of biological processes, including DNA and protein sequencing. As individual objects pass through a pore, they cause a transient change in the current that can be correlated with the object size, surface charge, and even chemical properties. The majority of experiments and modeling have been performed with spherical objects, while much less is known about the transport characteristics of aspherical particles, which would act as a model system, for example, for proteins and bacteria. The transport kinetics of aspherical objects is an especially important, yet understudied, problem in nanopore analytics. Here, using the Wiener process, we present a simplified model of the diffusion of rod-shaped particles through a cylindrical pore, and apply it to understand the translation and rotation of the particles as they pass through the pore. Specifically, we analyze the influence of the particles' geometrical characteristics on the effective diffusion type, the first passage time distribution, and the particles' orientation in the pore. Our model shows that thicker particles pass through the channel slower than thinner ones, while their lengths do not affect the passage time. We also demonstrate that both spherical and rod-shaped particles undergo normal diffusion, and the first passage time distribution follows an exponential asymptotics. The model provides guidance on how the shape of the particle can be modified to achieve an optimal passage time.

Pre-Failure Strain Localization in Siliclastic Rocks: A Comparative Study of Laboratory and Numerical Approaches.

We combined novel laboratory techniques and numerical modeling to investigate (a)seismic preparatory processes associated with deformation localization during a triaxial failure test on a dry sample of Berea sandstone. Laboratory observations were quantified by measuring strain localization on the sample surface with a distributed strain sensing (DSS) array, utilizing optical fibers, in conjunction with both passive and active acoustic emission (AE) techniques. A physics-based computational model was subsequently employed to understand the underlying physics of these observations and to establish a spatio-temporal correlation between the laboratory and modeling results. These simulations revealed three distinct stages of preparatory processes: (i) highly dissipative fronts propagated towards the middle of the sample correlating with the observed acoustic emission locations; (ii) dissipative regions were individuated in the middle of the sample and could be linked to a discernible decrease of the P-wave velocities; (iii) a system of conjugate bands formed, coalesced into a single band that grew from the center towards the sample surface and was interpreted to be representative for the preparation of a weak plane. Dilatative lobes at the process zones of the weak plane extended outwards and grew to the surface, causing strain localization and an acceleration of the simulated deformation prior to failure. This was also observed during the experiment with the strain rate measurements and spatio-temporally correlated with an increase of the seismicity rate in a similar rock volume. The combined approach of such laboratory and numerical techniques provides an enriched view of (a)seismic preparatory processes preceding the mainshock.

A Eulerian Numerical Model to Predict the Enhancement Effect of the Gravity-Driven Motion Melting Process for Latent Thermal Energy Storage.

Latent thermal energy storage (LTES) devices can efficiently store renewable energy in thermal form and guarantee a stable-temperature thermal energy supply. The gravity-driven motion melting (GDMM) process improves the overall melting rate for packaged phase-change material (PCM) by constructing an enhanced flow field in the liquid phase. However, due to the complex mechanisms involved in fluid-solid coupling and liquid-solid phase transition, numerical simulation studies that demonstrate physical details are necessary. In this study, a simplified numerical model based on the Eulerian method is proposed. We aimed to introduce a fluid deformation yield stress equation to the "solid phase" based on the Bingham fluid assumption. As a result, fluid-solid coupling and liquid-solid phase transition processes become continuously solvable. The proposed model is validated by the referenced experimental measurements. The enhanced performance of liquid-phase convection and the macroscopic settling of the "solid phase" are numerically analyzed. The results indicate that the enhanced liquid-phase fluidity allows for a stronger heat transfer process than natural convection for the pure liquid phase. The gravity-driven pressure difference is directly proportional to the vertical melting rate, which indicates the feasibility of controlling the pressure difference to improve the melting rate.

Centurial Persistence of Forever Chemicals at Military Fire Training Sites.

Drinking water contamination by per- and polyfluoroalkyl substances (PFAS) is widespread near more than 300 United States (U.S.) military bases that used aqueous film-forming foams (AFFF) for fire training and firefighting activities. Much of the PFAS at these sites consist of precursors that can transform into terminal compounds of known health concern but are omitted from standard analytical methods. Here, we estimate the expected duration and contribution of precursor biotransformation to groundwater PFAS contamination at an AFFF-contaminated military base on Cape Cod, Massachusetts, United States, by optimizing a geochemical box model using measured PFAS concentrations from a multidecadal time series of groundwater and a soil survey in the source zone. A toolbox of analytical techniques used to reconstruct the mass budget of PFAS showed that precursors accounted for 46 ± 8% of the extractable organofluorine (a proxy for total PFAS) across years. Terminal PFAS still exceed regulatory limits by 2000-fold decades after AFFF use ceased. Measurements and numerical modeling show that sulfonamido precursors are retained in the vadose zone and their slow biotransformation into perfluoroalkyl sulfonates (half-life > 66 yr) sustains groundwater concentrations of perfluorobutane sulfonate (PFBS) and perfluorohexane sulfonate (PFHxS). The estimated PFAS reservoir in the vadose zone and modeled flux into groundwater suggest PFAS contamination above regulatory guidelines will persist for centuries without remediation.

3D modeling of in vivo MRI-guided nano-photothermal therapy mediated by magneto-plasmonic nanohybrids.

BACKGROUND: Nano-photothermal therapy (NPTT) has gained wide attention in cancer treatment due to its high efficiency and selective treatment strategy. The biggest challenges in the clinical application are the lack of (i) a reliable platform for mapping the thermal dose and (ii) efficient photothermal agents (PTAs). This study developed a 3D treatment planning for NPTT to reduce the uncertainty of treatment procedures, based on our synthesized nanohybrid. METHODS: This study aimed to develop a three-dimensional finite element method (FEM) model for in vivo NPTT in mice using magneto-plasmonic nanohybrids, which are complex assemblies of superparamagnetic iron oxide nanoparticles and gold nanorods. The model was based on Pennes' bio-heat equation and utilized a geometrically correct mice whole-body. CT26 colon tumor-bearing BALB/c mice were injected with nanohybrids and imaged using MRI (3 Tesla) before and after injection. MR images were segmented, and STereoLithography (STL) files of mice bodies and nanohybrid distribution in the tumor were established to create a realistic geometry for the model. The accuracy of the temperature predictions was validated by using an infrared (IR) camera. RESULTS: The photothermal conversion efficiency of the nanohybrids was experimentally determined to be approximately 30%. The intratumoral (IT) injection group showed the highest temperature increase, with a maximum of 17 °C observed at the hottest point on the surface of the tumor-bearing mice for 300 s of laser exposure at a power density of 1.4 W/cm2. Furthermore, the highest level of tissue damage, with a maximum value of Ω = 0.4, was observed in the IT injection group, as determined through a simulation study. CONCLUSIONS: Our synthesized nanohybrid shows potential as an effective agent for MRI-guided NPTT. The developed model accurately predicted temperature distributions and tissue damage in the tumor. However, the current temperature validation method, which relies on limited 2D measurements, may be too lenient. Further refinement is necessary to improve validation. Nevertheless, the presented FEM model holds great promise for clinical NPTT treatment planning.

Total ice content and lipid saturation determine adipose tissue cryolipolysis by injection of ice-slurry.

OBJECTIVES: Cryolipolysis uses tissue cooling to solidify lipids, preferentially damaging lipid-rich cells. Topical cooling is popular for the reduction of local subcutaneous fat. Injection of biocompatible ice-slurry is a recently introduced alternative. We developed and verified a quantitative model that simulates the heat exchange and phase changes involved, offering insights into ice-slurry injection for treating subcutaneous fat. METHODS: Finite element method was used to model the spatial and temporal progression of heat transfer between adipose tissue and injected ice-slurry, estimating dose-response relationships between properties of the slurry and size of tissue affected by cryolipolysis. Phase changes of both slurry and adipose tissue lipids were considered. An in vivo swine model was used to validate the numerical solutions. Oils with different lipid compositions were exposed to ice-slurry in vitro to evaluate the effects of lipid freezing temperature. Microscopy and nuclear magnetic resonance (NMR) were performed to detect lipid phase changes. RESULTS: A ball of granular ice was deposited at the injection site in subcutaneous fat. Total injected ice content determines both the effective cooling region of tissue, and the duration of tissue cooling. Water's high latent heat of fusion enables tissue cooling long after slurry injection. Slurry temperature affects the rate of tissue cooling. In swine, when 30 ml slurry injection at -3.5°C was compared to 15 ml slurry injection at -4.8°C (both with the same total ice content), the latter led to almost twice faster tissue cooling. NMR showed a large decrease in diffusion upon lipid crystallization; saturated lipids with higher freezing temperatures were more susceptible to solidification after ice-slurry injection. CONCLUSIONS: Total injected ice content determines both the volume of tissue treated by cryolipolysis and the cooling duration after slurry injection, while slurry temperature affects the cooling rate. Lipid saturation, which varies with diet and anatomic location, also has an important influence.

Design of the Bimodal Grating Sensor with a Built-In Mode Demultiplexer.

This new sensor design provides good volume sensitivity (around 1600 nm/RIU) via collinear diffraction by the asymmetric grating placed in the waveguide vicinity. It provides the mode transformation between the fundamental TE0 and the first TE1 modes of the silicon wire (0.22 µm by a 0.580 µm cross-section) in the water environment. In order to provide the wavelength interrogation with a better extinction ratio for the measuring signal, the grating design is incorporated with the mode filter/demultiplexer. It selects, by the compact directional coupler (maximum 4 µm wide and 14 µm long), only the first guided mode (close to the cutoff) and transmits it with small excess loss (about -0.5 dB) to the fundamental TE0 mode of the neighboring single mode silicon wire, having variable curvature and width ranging from 0.26 µm to 0.45 µm. At the same time, the parasitic crosstalk of the input TE0 mode is below -42 dB, and that provides the option of simple and accurate wavelength sensor interrogation. The environment index is measured by the spectral peak position of the transmitted TE0 mode power in the output single mode silicon wire waveguide of the directional coupler. This type of optical sensor is of high sensitivity (iLOD~ 2.1 × 10-4 RIU for taking into account the water absorption at 1550 nm) and could be manufactured by modern technology and a single-step etching process.

Wave Equation Modeling via Physics-Informed Neural Networks: Models of Soft and Hard Constraints for Initial and Boundary Conditions.

Therapeutic ultrasound waves are the main instruments used in many noninvasive clinical procedures. They are continuously transforming medical treatments through mechanical and thermal effects. To allow for effective and safe delivery of ultrasound waves, numerical modeling methods such as the Finite Difference Method (FDM) and the Finite Element Method (FEM) are used. However, modeling the acoustic wave equation can result in several computational complications. In this work, we study the accuracy of using Physics-Informed Neural Networks (PINNs) to solve the wave equation when applying different combinations of initial and boundary conditions (ICs and BCs) constraints. By exploiting the mesh-free nature of PINNs and their prediction speed, we specifically model the wave equation with a continuous time-dependent point source function. Four main models are designed and studied to monitor the effects of soft or hard constraints on the prediction accuracy and performance. The predicted solutions in all the models were compared to an FDM solution for prediction error estimation. The trials of this work reveal that the wave equation modeled by a PINN with soft IC and BC (soft-soft) constraints reflects the lowest prediction error among the four combinations of constraints.

Transmission of droplet aerosols in an elevator cabin: Effect of the ventilation mode.

The recent outbreak of COVID-19 has threatened public health. Owing to the relatively sealed environment and poor ventilation in elevator cabins, passengers are at risk of respiratory tract infection. However, the distribution and dispersion of droplet aerosols in elevator cabins remain unclear. This study investigated the transmission of droplet aerosols exhaled by a source patient under three ventilation modes. Droplet aerosols produced by nose breathing and mouth coughing were resolved using computational fluid dynamics (CFD) simulations. We adopted the verified renormalization group (RNG) k-ε turbulence model to simulate the flow field and the Lagrangian method to track the droplet aerosols. In addition, the influence of the ventilation mode on droplet transmission was evaluated. The results showed that droplet aerosols gathered in the elevator cabin and were difficult to discharge under the mixed and displacement ventilation modes with specific initial conditions. The inhalation proportion of droplet aerosols for air curtain was 0.016%, which was significantly lower than that for mixed ventilation (0.049%) and displacement ventilation (0.071%). The air curtain confined the transmission of droplet aerosols with the minimum ratios of inhalation, deposition, and suspension and is thus recommended to reduce the exposure risk.

Modeling the Virus Infection at the Population Level.

As pointed out by many researchers in the last few decades, differential equations with fractional (non-integer) order differential operators, in comparison with classical integer order ones, have apparent advantages in modeling. A Caputo fractional order system of ordinary differential equations is introduced to model the virus infection at the population level in this chapter. As well known, there are two main methods to study the dynamics of a model: qualitative analysis and numerical modeling. Here the qualitative analysis, including uniqueness, invariant set, and stability, is first presented with intuitive derivation. Then the famous genetic algorithm is introduced to numerically model the dynamics of virus infection, i.e. to adjust the parameters of the Caputo fractional model such that its solution can properly fit real data and predict future.

Groundwater arsenic content in quaternary aquifers of the Red River delta, Vietnam, controlled by the hydrogeological processes.

The relation between arsenic groundwater concentrations and hydrogeological processes was investigated in the proximal part of the Red River delta, Vietnam, west of the depression cone formed by the exploitation of groundwater in Hanoi. Flow paths in the Quaternary aquifers were modeled based on previously interpreted geological structure and hydrogeological data gathered during field work in 2014-2017. Sedimentary structures and simulated flow patterns were compared with the spatial distribution of the groundwater arsenic concentration. The regression of the sea in the area started 4 ka BP in the Holocene. The low tectonic subsidence rate of the Red River delta led to intensive erosion and replacement of fine grained sediments of the sea level high stand by sandy channel belts, resulting in hydraulic connections between the Pleistocene and Holocene aquifers. The Pleistocene aquifer is recharged by both regional flow paths and naturally occurring vertical recharge through Holocene sand and clay layers. Young groundwater (<40 a) in the shallow Holocene aquifer generally discharges to surface water bodies. The shallow flow system is also seasonally recharged with surface water, as indicated by δ18O enrichment of groundwater and oscillating groundwater ages in wells in the vicinity of water channels. The deeper flow system discharges into the Red River and Day River or flows parallel to the rivers, toward the sea. The overall pattern of arsenic groundwater concentrations (decreasing with increasing sediment age) is modified by groundwater flow. The arsenic contamination of the Pleistocene aquifer of the Red River delta is not only caused by the intensive groundwater abstraction in Hanoi, as reported previously, but also by the natural flow of high arsenic groundwater from Holocene to Pleistocene aquifers in areas located outside of the depression cone. Groundwater with < 50 µg L-1 arsenic is found in the Pleistocene aquifer close to the recharge zone in the mountains bordering the Red River delta and in the Holocene and Pleistocene aquifers where clay deposits were eroded. Close to the recent Red River channel, recharge of older Holocene and Pleistocene sediments occurs partially by arsenic-contaminated groundwater from the youngest Holocene aquifers, and here arsenic concentrations exceed 50 µg L-1. A high arsenic concentration is also present in the early Holocene-Pleistocene aquifer, beneath thick clay layers, indicating a limited extent of flushing and the inflow of fresh organic matter.

Train-Track-Bridge Dynamic Interaction on a Bowstring-Arch Railway Bridge: Advanced Modeling and Experimental Validation.

This article describes the validation of a 3D dynamic interaction model of the train-track-bridge system on a bowstring-arch railway bridge based on experimental tests. The train, track, and bridge subsystems were modeled on the basis of large-scale and highly complex finite elements models previously calibrated on the basis of experimental modal parameters. The train-bridge dynamic interaction problem, in the vertical direction, was efficiently solved using a dedicated computational application (TBI software). This software resorts to an uncoupled methodology that considers the two subsystems, bridge and train, as two independent structures and uses an iterative procedure to guarantee the compatibility of the forces and displacements at the contact points at each timestep. The bridge subsystem is solved by the mode superposition method, while the train subsystem is solved by a direct integration method. The track irregularities were included in the dynamic problem based on real measurements performed by a track inspection vehicle. A dynamic test under traffic actions allowed measuring the responses in the bridge, track, and vehicles, which were synchronized by GPS systems. The test results demonstrated the occurrence of upward displacements on the deck, which is a characteristic of structures with an arch structural behavior, as well as an alternation of tensile/compressive stresses between the rail and deck due to the deck-track composite effect. Furthermore, the acceleration response of the bridge proved to be significantly influenced by the train operating speed. The validation procedure involved comparing the dynamic responses obtained from the train-bridge interaction model, including track irregularities, and the responses obtained experimentally, through the test under traffic actions. A very good correlation was obtained between numerical and experimental results in terms of accelerations, displacements, and strains. The contributions derived from the parametric excitation of the train, the global/local dynamic behavior of the bridge, and the excitation derived from the track irregularities were decisive to accurately reproduce the complex behavior of the train-track-bridge system.

Isolation Improvement in Reflectarray Antenna-Based FMCW Radar Systems.

This paper presents an optimization of reflectarray-based RF sensors for detecting UAV and human presence. Our previous human detection radar system adapted a center-fed reflectarray antenna to a commercially available radar system, successfully increasing the gains of the transmit (TX) and receive (RX) antennas by 21.18 dB and the range for detecting human targets 3.4 times. However, because the TX and RX antennas were placed in the focal point of the reflectarray, the TX signal reflected by the reflectarray was directly propagated into the RX antenna, causing desensitization or damage to the receiving circuit if high powers were used. To reduce this direct reflection, we propose a novel radar antenna configuration in which the TX and RX antennas are placed back-to-back with each other. In this configuration, the RX antenna does not directly face the reflectarray, thus direct path between the TX to RX through the reflectarray is removed. The results demonstrate that this approach achieves the optimum isolation level of 51.3 dB. With the reflectarray, the TX antenna gain increases to 30.6 dBi, but the RX antenna gain remains at 16 dBi since the RX antenna does not utilize the reflectarray. The TX and RX gain difference (14.6 dB) is a trade-off for good isolation and may be reduced by utilizing a high-gain receiver amplifier.

Patient Specific Numerical Modeling for Renal Blood Monitoring Using Electrical Bio-Impedance.

Knowledge of renal blood circulation is considered as an important physiological value, particularly for fast detection of acute allograft rejection as well as the management of critically ill patients with acute renal failure. The electrical impedance signal obtained from kidney with an appropriate electrode system and optimal electrode system position regarding to the kidney projection on skin surface reflects the nature of renal blood circulation and tone of renal blood vessels. This paper proposes a specific numerical modelling based on prior information from MRI-data. The numerical modelling was conducted for electrical impedance change estimation due to renal blood distribution. The proposed model takes into the account the geometrical and electrophysiological parameters of tissues around the kidney as well as the actual blood distribution within the kidney. The numerical modelling had shown that it is possible to register the electrical impedance signal caused by renal blood circulation with an electrode system commensurate with the size of kidney, which makes it possible to reduce the influence of surrounding tissues and organs. Experimental studies were obtained to prove the numerical modelling and the effectiveness of developed electrode systems based on the obtained simulation results. The obtained electrical impedance signal with the appropriate electrode system shows very good agreement with the renal blood change estimated using Doppler ultrasound. For the measured electrical impedance signal, it is possible to obtain the amplitude-time parameters, which reflect the hemodynamic characteristics of the kidneys and used in diagnostics, which is the subject of further research.