Accurate Nonstandard Path Integral Models for Arbitrary Dielectric Boundaries in 2-D NS-FDTD Domains.

An efficient path integral (PI) model for the accurate analysis of curved dielectric structures on coarse grids via the two-dimensional nonstandard finite-difference time-domain (NS-FDTD) technique is introduced in this paper. In contrast to previous PI implementations of the perfectly electric conductor case, which accommodates orthogonal cells in the vicinity of curved surfaces, the novel PI model employs the occupation ratio of dielectrics in the necessary cells, providing thus a straightforward and instructive means to treat an assortment of practical applications. For its verification, the reflection from a flat plate and the scattering from a cylinder using the PI model are investigated. Results indicate that the featured methodology can enable the reliable and precise modeling of arbitrarily shaped dielectrics in the NS-FDTD algorithm on coarse grids.

A non-invasive method to monitor respiratory muscle effort during mechanical ventilation.

PURPOSE: This study introduces a method to non-invasively and automatically quantify respiratory muscle effort (Pmus) during mechanical ventilation (MV). The methodology hinges on numerically solving the respiratory system's equation of motion, utilizing measurements of airway pressure (Paw) and airflow (Faw). To evaluate the technique's effectiveness, Pmus was correlated with expected physiological responses. In volume-control (VC) mode, where tidal volume (VT) is pre-determined, Pmus is expected to be linked to Paw fluctuations. In contrast, during pressure-control (PC) mode, where Paw is held constant, Pmus should correlate with VT variations. METHODS: The study utilized data from 250 patients on invasive MV. The data included detailed recordings of Paw and Faw, sampled at 31.25 Hz and saved in 131.1-second epochs, each covering 34 to 41 breaths. The algorithm identified 51,268 epochs containing breaths on either VC or PC mode exclusively. In these epochs, Pmus and its pressure-time product (PmusPTP) were computed and correlated with Paw's pressure-time product (PawPTP) and VT, respectively. RESULTS: There was a strong correlation of PmusPTP with PawPTP in VC mode (R² = 0.91 [0.76, 0.96]; n = 17,648 epochs) and with VT in PC mode (R² = 0.88 [0.74, 0.94]; n = 33,620 epochs), confirming the hypothesis. As expected, negligible correlations were observed between PmusPTP and VT in VC mode (R² = 0.03) and between PmusPTP and PawPTP in PC mode (R² = 0.06). CONCLUSION: The study supports the feasibility of assessing respiratory effort during MV non-invasively through airway signal analysis. Further research is warranted to validate this method and investigate its clinical applications.

Electrical Contacts With 2D Materials: Current Developments and Future Prospects.

Current electrical contact models are occasionally insufficient at the nanoscale owing to the wide variations in outcomes between 2D mono and multi-layered and bulk materials that result from their distinctive electrostatics and geometries. Contrarily, devices based on 2D semiconductors present a significant challenge due to the requirement for electrical contact with resistances close to the quantum limit. The next generation of low-power devices is already hindered by the lack of high-quality and low-contact-resistance contacts on 2D materials. The physics and materials science of electrical contact resistance in 2D materials-based nanoelectronics, interface configurations, charge injection mechanisms, and numerical modeling of electrical contacts, as well as the most pressing issues that need to be resolved in the field of research and development, will all be covered in this review.

Dosimetric assessment in the brain for downlink EMF exposure in Korean mobile communication networks.

Because the position and direction of the human body is not fixed in an actual environment, the incidence direction of the electromagnetic field (EMF) from mobile communication base stations, WiFi access points, broadcasting towers, and other far-field sources is arbitrary. To analyze the overall health effects of radio frequency EMF exposure, the dosimetric assessment for such environmental exposures created from an unspecified number of sources in daily life, along with exposures from specific EMF sources, must be quantified. This study is aimed at numerically evaluating the time-averaged specific absorption rate (SAR) of the human brain for environmental EMF exposure in the frequency range of 50-5800 MHz. Whole-body exposure to EMFs that are evenly incident spatially is considered. By comparing the results of several incidence directions and the number of polarizations, an optimal calculation condition has been derived. Finally, based on the results measured in Seoul at the end of 2021, the SAR and daily specific energy absorption (SA) in the brains of both a child and an adult for downlink exposures from 3G to 5G base stations are reported. Comparison results of the daily brain SA for exposure to DL EMF in all 3G to 5G mobile networks and exposure to a 10-min voice call (uplink EMF) using a mobile phone connected to a 4G network show that the SA from the downlinks is much higher than that from the uplinks.

Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data.

We propose a machine learning framework for the data-driven discovery of macroscopic chemotactic Partial Differential Equations (PDEs)-and the closures that lead to them- from high-fidelity, individual-based stochastic simulations of Escherichia coli bacterial motility. The fine scale, chemomechanical, hybrid (continuum-Monte Carlo) simulation model embodies the underlying biophysics, and its parameters are informed from experimental observations of individual cells. Using a parsimonious set of collective observables, we learn effective, coarse-grained "Keller-Segel class" chemotactic PDEs using machine learning regressors: (a) (shallow) feedforward neural networks and (b) Gaussian Processes. The learned laws can be black-box (when no prior knowledge about the PDE law structure is assumed) or gray-box when parts of the equation (e.g. the pure diffusion part) is known and "hardwired" in the regression process. More importantly, we discuss data-driven corrections (both additive and functional), to analytically known, approximate closures.

Palynomorphological Observations on the Genus Sabulina Rchb. (Caryophyllaceae) from Turkey Using Light Microscopy and Scanning Electron Microscopy.

Pollen morphology of 28 taxa belonging to the genus Sabulina Rchb. (Caryophyllaceae) from Turkey was examined and compared using light microscopy and scanning electron microscopy. The current study aimed to describe the palynological characteristics of the Sabulina taxa and to assess the diagnostic value of these features for taxonomic implications. The pollen grains of Sabulina are radially symmetrical, apolar, rarely isopolar, and pantopolyporate with 8-28 pores. Their shape is prolate-spheroidal with the A axes (long axes) 19.5 µm and the B axes (short axes) 19-39.5 µm. Exine sculpturing is microechinate-punctate in all taxa. Principal component analysis was used to evaluate the significant pollen morphological characters for distinguishing the taxa, with three components accounting for 95.112% of the total variance. Numerical analysis revealed that pollen sizes, pore diameters, pore numbers, distance between pores, spinule density, and punctum numbers are particularly the most useful variables for separating the Sabulina taxa. The results also display a partial relationship between the Sabulina taxa clusters based on pollen morphology and the systematics of these taxa based on general macromorphology.

Thermo-Electro-Chemo-Mechanical Coupled Modeling of Solid Oxide Fuel Cell with LSCF-GDC Composite Cathode.

Intricate relationships between transport phenomena, reaction mechanisms, and mechanical aspects likely affect the durability of solid oxide fuel cell (SOFC) stack. This study presents a modeling framework that combines thermo-electro-chemo models (including the methanol conversion process and the electrochemical reactions of the carbon monoxide as well as the hydrogen) and a contact thermo-mechanical model that considers the effective mechanical properties of composite electrode material. Detailed parametric studies are performed focusing on the inlet fuel species (hydrogen, methanol syngas) and flow arrangements (co-flow, counter-flow) under typical operating conditions (operating voltage 0.7 V), and performance indicators of the cell, such as the high-temperature zone, current density, and maximum thermal stress were discussed for parameter optimization. The simulated results show that the high temperature zone of the hydrogen-fueled SOFC is located at the central part of units 5, 6, and 7, and the maximum value is about 40 K higher than that of methanol syngas-fueled SOFC. The charge transfer reactions can occur throughout the cathode layer. The counter-flow improves the trend of the current density distribution of hydrogen-fueled SOFC, while the effect on the current density distribution of methanol syngas-fueled SOFC is small. The distribution characteristics of the stress field within SOFC are extremely complex, and the inhomogeneity of the stress field distribution can be effectively improved by feeding methanol syngas. The counter-flow improves the stress distribution state of the electrolyte layer of methanol syngas-fueled SOFC, and the maximum tensile stress value is reduced by about 37.7%.

Protein adsorption on a nanoparticle with a nanostructured surface.

In the present study, the adsorption of a protein on a nanoparticle with a nanostructured surface, which is created using successively patterned Gaussian pillars (GPs), is simulated by considering the charge regulation within the electrical double layer of a silica nanoparticle (NP). Namely, the mathematical models for the adsorption mechanism, such as classical Langmuir model, extended Langmuir model, and two-state model, are coupled with charge regulation model. By this means, size and pH variables are able to included to the calculations. Moreover, free space, surface curvature, and conformational changes are also taken into account. For systematic investigation, the solution's pH, surface charge density, initial protein concentration, electrostatic charge of the protein, and the diameter of the spherical NP are varied. As a result, the vital properties of a nanoparticle, such as protonation/deprotonation, polarization, topography, and morphology, are considered in the current simulations. The surface charge density and surface chemistry change with NP and GP sizes. The present results reveal that the protein adsorption on an NP with a smooth surface reaches a faster complete surface coverage than an NP with a nanostructured surface. Both states of conformational changes are also affected by the presence of the GP.

On the accuracy of short-term COVID-19 fatality forecasts.

BACKGROUND: Forecasting new cases, hospitalizations, and disease-induced deaths is an important part of infectious disease surveillance and helps guide health officials in implementing effective countermeasures. For disease surveillance in the US, the Centers for Disease Control and Prevention (CDC) combine more than 65 individual forecasts of these numbers in an ensemble forecast at national and state levels. A similar initiative has been launched by the European CDC (ECDC) in the second half of 2021. METHODS: We collected data on CDC and ECDC ensemble forecasts of COVID-19 fatalities, and we compare them with easily interpretable "Euler" forecasts serving as a model-free benchmark that is only based on the local rate of change of the incidence curve. The term "Euler method" is motivated by the eponymous numerical integration scheme that calculates the value of a function at a future time step based on the current rate of change. RESULTS: Our results show that simple and easily interpretable "Euler" forecasts can compete favorably with both CDC and ECDC ensemble forecasts on short-term forecasting horizons of 1 week. However, ensemble forecasts better perform on longer forecasting horizons. CONCLUSIONS: Using the current rate of change in incidences as estimates of future incidence changes is useful for epidemic forecasting on short time horizons. An advantage of the proposed method over other forecasting approaches is that it can be implemented with a very limited amount of work and without relying on additional data (e.g., data on human mobility and contact patterns) and high-performance computing systems.

Numerical analysis and animal study of noninvasive handheld electroporation delivery device for skin superficial lesion treatment.

INTRODUCTION: This study aims to investigate the feasibility of a noninvasive handheld electroporation pulses delivery device (EPDD) for electroporation-based treatment (EBT) of skin superficial lesions through numerical analysis and animal study. METHODS: Finite element analysis was performed to investigate the performance of the EPDD. The electric field, temperature, EI and TI were calculated under pulse voltages of 600, 800, and 1000 V. A mouse subcutaneous tumor model was established to evaluate the performance of the EPDD through histopathology and survival analyses. RESULTS: The electrical field strength increased from 151 (600 V) to 252 V/cm (1000 V) in the skin and from 1302 (600 V) to 2171 V/cm (1000 V) in the tumor. The volume of EI grew and reached a plateau at the 165th pulse, whereas the maximum volume of EI increased with higher voltage. The growth tendency of TI differed between groups, and it was higher in the high-voltage group (HVG) than in the low-voltage group. Histopathological analysis showed that the depth and range of the ablation area could be controlled by adjusting pulse voltage. Survival analysis showed that the survival of the HVG was better than that of the low-voltage and the control group (p < 0.01). CONCLUSIONS: The results demonstrate that the EPDD is feasible, safe, and effective for skin EBT. The volume of EP tissue injury can be controlled by adjusting the pulse voltage, pulse number, and other parameters. The proposed noninvasive handheld EPDD can be a potential therapeutic tool for EBT of superficial skin lesions in the future.

Numerical analysis evaluation of artificial joints.

Artificial joints are exposed to loads on a daily basis. Loads on the bone through the artificial joint and the joint's sliding surface shear force may cause implant fixation failure, fatigue fractures, wear of the bearing and foreign body reactions. Artificial joints can experience sudden internal damage, which can be fatal if it occurs during activities performed at high altitudes or in water. The standard design hip prosthesis has a metal femoral stem. Most stem fractures are caused at the proximal one third of the stem by fatigue due to repetitive loading. Femoral stem neck fractures can also occur. To eliminate in vivo prosthesis failures, safety performance preclinical studies evaluate stem body and neck breakage. However, the development of new femoral stems via prototyping and fatigue test verification would require excessive time and money. Therefore, evaluation methods based on numerical analyses, such as finite element analysis (FEA), have been introduced to simulate tests on actual machines. Fatigue strength design verification using FEA can efficiently identify a design that can pass International Organization for Standardization fatigue tests. FEA may also aid with composite implant development by enabling efficient preclinical testing to prove safety using minimal actual fatigue testing. Once a biological safety study of a composite material is performed, a clinical trial can prove its clinical efficacy and safety and device regulatory approval can be requested. This review was created based on a translation of the Japanese review written in the Japanese Journal of Artificial Organs in 2020 (Vol. 49, No. 3, pp. 195-198), with adding some additional contents and references.

Design, Fabrication, and Characterisation of a Label-Free Nanosensor for Bioapplications.

In this paper, we present a hybrid semiconductor structure for biosensing applications that features the co-integration of nanoelectromechanical systems with the well-known metal oxide semiconductor technology. The proposed structure features an MOSFET as a readout element, and a doubly clamped beam that is isolated from the substrate by a thin air gap, as well as by a tunnel oxide layer. The beam structure is functionalised by a thin layer of biotargets, and the main aim is to detect a particular set of biomolecules, such as enzymes, bacteria, viruses, and DNA/RNA chains, among others. In here, a three-dimensional finite element analysis is performed in order to study the behaviour of the functionalised, doubly clamped beam. Preliminary results for the fabrication and characterisation processes show good agreement between the simulated and measured characteristics.

Cyclic Behavior of Masonry Shear Walls Retrofitted with Engineered Cementitious Composite and Pseudoelastic Shape Memory Alloy.

The behavior of masonry shear walls reinforced with pseudoelastic Ni-Ti shape memory alloy (SMA) strips and engineered cementitious composite (ECC) sheets is the main focus of this paper. The walls were subjected to quasi-static cyclic in-plane loads and evaluated by using Abaqus. Eight cases of strengthening of masonry walls were investigated. Three masonry walls were strengthened with different thicknesses of ECC sheets using epoxy as adhesion, three walls were reinforced with different thicknesses of Ni-Ti strips in a cross form bonded to both the surfaces of the wall, and one was utilized as a reference wall without any reinforcing element. The final concept was a hybrid of strengthening methods in which the Ni-Ti strips were embedded in ECC sheets. The effect of mesh density on analytical outcomes is also discussed. A parameterized analysis was conducted to examine the influence of various variables such as the thickness of the Ni-Ti strips and that of ECC sheets. The results show that using the ECC sheet in combination with pseudoelastic Ni-Ti SMA strips enhances the energy absorption capacity and stiffness of masonry walls, demonstrating its efficacy as a reinforcing method.

Numerical Study on Death of Squamous Cell Carcinoma Based on Various Shapes of Gold Nanoparticles Using Photothermal Therapy.

Due to increased exposure to ultraviolet radiation caused by increased outdoor activities, the incidence of skin cancer is increasing. Incision is the most typical method for treating skin cancer, and various treatments that can minimize the risks of incision surgery are being investigated. Among them, photothermal therapy is garnering attention because it does not cause bleeding and affords rapid recovery. In photothermal therapy, tumor death is induced via temperature increase. In this study, a numerical study based on heat transfer theory was conducted to investigate the death of squamous cell carcinoma located in the skin layer based on various shapes of gold nanoparticles (AuNPs) used in photothermal therapy. The quantitative correlation between the conditions of various AuNPs and the laser intensity that yields the optimal photothermal treatment effect was derived using the effective apoptosis ratio. It was confirmed that optimal conditions exist for maximizing apoptosis within a tumor tissue and minimizing the thermal damage to surrounding normal tissues when using AuNPs under various conditions. Furthermore, it is envisioned that research result will be utilized as a standard for photothermal treatment in the future.

Analysis of the Influence of the Geometrical Parameters of the Body Scanner on the Accuracy of Reconstruction of the Human Figure Using the Photogrammetry Technique.

This article concerns the research of the HUBO full-body scanner, which includes the analysis and selection of the scanner's geometrical parameters in order to obtain the highest possible accuracy of the reconstruction of a human figure. In the scanner version analyzed in this paper, smartphone cameras are used as sensors. In order to process the collected photos into a 3D model, the photogrammetry technique is applied. As part of the work, dependencies between the geometrical parameters of the scanner are derived, which allows to significantly reduce the number of degrees of freedom in the selection of its geometrical parameters. Based on these dependencies, a numerical analysis is carried out, as a result of which the initial values of the geometrical parameters are pre-selected and distribution of scanner cameras is visualized. As part of the experimental research, the influence of selected scanner parameters on the scanning accuracy is analyzed. For the experimental research, a specially prepared dummy was used instead of the participation of a real human, which allowed to ensure the constancy of the scanned object. The accuracy of the object reconstruction was assessed in relation to the reference 3D model obtained with a scanner of superior measurement uncertainty. On the basis of the conducted research, a method for the selection of the scanner's geometrical parameters was finally verified, leading to the arrangement of cameras around a human, which guarantees high accuracy of the reconstruction. Additionally, to quantify the results, the quality rates were used, taking into account not only the obtained measurement uncertainty of the scanner, but also the processing time and the resulting efficiency.

Numerical Study on Entropy Generation of the Multi-Stage Centrifugal Pump.

The energy loss of the multi-stage centrifugal pump was investigated by numerical analysis using the entropy generation method with the RNG k-ε turbulence model. Entropy generation due to time-averaged motion and velocity fluctuation was mainly considered. It was found that the entropy generation of guide vanes and impellers account for 71.2% and 23.3% of the total entropy generation under the designed flow condition. The guide vanes are the main hydraulic loss domains and their entropy generation is about 9 W/K, followed by impellers. There are vortices at the tongue of the guide vane inlet as well as flow separations in the impellers, which lead to entropy generation. The fluid impacts the outer surface of the guide vanes, resulting in the increase in entropy generation. There are refluxes near the guide vane tongues which also increase the entropy generation of this part. The entropy generation distribution of the guide vanes and impellers was investigated, which found that the positive guide vane has more entropy generation compared with the reverse guide. The entropy generation of the blade suction surface is higher compared with the pressure surface. This study indicated that the entropy generation method has distinct advantages in the assessment of hydraulic loss.

Analysis of Energy Loss Characteristics of Vertical Axial Flow Pump Based on Entropy Production Method under Partial Conditions.

The energy loss of the vertical axial flow pump device increases due to the unstable internal flow, which reduces the efficiency of the pump device and increases its energy consumption of the pump device. The research results of the flow loss characteristics of the total internal conduit are still unclear. Therefore, to show the internal energy loss mechanism of the axial flow pump, this paper used the entropy production method to calculate the energy loss of the total conduit of the pump device to clarify the internal energy loss mechanism of the pump device. The results show that the energy loss of the impeller is the largest under various flow conditions, accounting for more than 40% of the total energy loss of the pump device. The variation trend of the volume average entropy production and the energy loss is similar under various flow coefficients (KQ). The volume average entropy production rate (EPR) and the energy loss decrease first and then increase with the increase of flow, the minimum volume average entropy production is 378,000 W/m3 at KQ = 0.52, and the area average EPR of the impeller increases gradually with the increase of flow. Under various flow coefficient KQ, the energy loss of campaniform inlet conduit is the smallest, accounting for less than 1% of the total energy loss. Its maximum value is 63.58 W. The energy loss of the guide vane and elbow increases with the increase of flow coefficient KQ, and the maximum ratio of energy loss to the total energy loss of the pump device is 29% and 21%, respectively, at small flow condition KQ = 0.38. The energy loss of straight outlet conduit reduces first and then increases with the increase of flow coefficient KQ. When flow coefficient KQ = 0.62, it accounts for 27% of the total energy loss of the pump device, but its area average entropy production rate (EPR) and volume average entropy production rate (EPR) are small. The main entropy production loss in the pump device is dominated by entropy production by turbulent dissipation (EPTD), and the proportion of entropy production by direct dissipation (EPDD) is the smallest.

How and why to build a mathematical model: A case study using prion aggregation.

Biological systems are inherently complex, and the increasing level of detail with which we are able to experimentally probe such systems continually reveals new complexity. Fortunately, mathematical models are uniquely positioned to provide a tool suitable for rigorous analysis, hypothesis generation, and connecting results from isolated in vitro experiments with results from in vivo and whole-organism studies. However, developing useful mathematical models is challenging because of the often different domains of knowledge required in both math and biology. In this work, we endeavor to provide a useful guide for researchers interested in incorporating mathematical modeling into their scientific process. We advocate for the use of conceptual diagrams as a starting place to anchor researchers from both domains. These diagrams are useful for simplifying the biological process in question and distinguishing the essential components. Not only do they serve as the basis for developing a variety of mathematical models, but they ensure that any mathematical formulation of the biological system is led primarily by scientific questions. We provide a specific example of this process from our own work in studying prion aggregation to show the power of mathematical models to synergistically interact with experiments and push forward biological understanding. Choosing the most suitable model also depends on many different factors, and we consider how to make these choices based on different scales of biological organization and available data. We close by discussing the many opportunities that abound for both experimentalists and modelers to take advantage of collaborative work in this field.

Age- and gender-dependent variability in the geometry of middle cerebral artery bifurcations.

The goal of this study was to analyze trends in the geometric parameters of blood vessels with age in a randomly selected group of 200 computed tomography angiography studies of radiologically healthy individuals using dedicated statistical techniques. A quantitative description of cerebral vascular geometry with numerical parameters (bifurcation angle, branching angle, co-planarity index, average curvature, and average torsion) was proposed. The changes and variability in geometry were analyzed according to age. The bifurcation angle, branching angle, and average curvature increased with age, whereas the co-planarity index and average torsion decreased with age. For equal-diameter branches, women comparing to men presented lower bifurcation angles in the 4th decade of life, and lower values for the co-planarity index in the 3rd and 4th decades of life. In non-equal-diameter branches, the opposite relationship was observed for bifurcation angle in the 4th decade of life comparing both groups. All analyzed parameters showed clearly visible trends with patient age. Deviations in specific decades of life were detected; these deviations could be linked to the development of aneurysms in specific age groups.

Improvement of hemolysis performance in a hydrodynamically levitated centrifugal blood pump by optimizing a shroud size.

We have developed a hydrodynamically levitated centrifugal blood pump. In the blood pump having hydrodynamic bearings, the narrow bearing gap has a potential for high hemolysis. The purpose of the this study is to improve hemolysis performance in a hydrodynamically levitated centrifugal blood pump by optimizing a shroud size. The impeller was levitated passively at the position where the thrust forces acting on the impeller were balanced. We focused on a size of a bottom shroud with a hydrodynamic bearing that could change the bottom hydrodynamic force to balance the thrust force at the wide bearing gap for reducing hemolysis. Five test models with various shroud size were compared: 989 mm2 (HH-10.5), 962 mm2 (HH-12), 932 mm2 (HH-13.5), 874 mm2 (HH-16), and 821 mm2 (HH-18). A numerical analysis was first performed to estimate the bearing gaps in the test model. The bearing gaps were then measured to validate the numerical analysis. Finally, an in vitro hemolysis test was performed. The numerical analysis revealed that the HH-13.5 model had the widest bearing gap of 129 µm. In the measurement test, the estimation error for the bearing gap was less than 10%. In the hemolysis test, the HH-13.5 model achieved the lowest hemolysis level among the five models. The present study demonstrated that the numerical analysis was found to be effective for determining the optimal should size, and the HH-13.5 model had the optimal shroud size in the developed hydrodynamically levitated centrifugal blood pump to reduce hemolysis.