Homogeneous Model Research Articles

A multi-parameter estimation of layered rock-soil thermal properties of borehole heat exchanger in a stratified subsurface

The high initial investment of borehole heat exchanger (BHE) prevents the popularization and application of ground-coupled heat pump system (GCHPs). As the premise of designing BHE, ground thermal properties are usually obtained using thermal response test (TRT), and parameter estimation method are applied based on homogeneous BHE model independent of geological stratification. In this paper, a multi-parameter estimation method using Bat algorithm (BA) is firstly proposed to obtain the layered rock-soil thermal properties based on the numerical layered BHE model, considering the characteristics of geological stratification. Then, a TRT experimental platform of three-layer BHE is developed to measure thermal responses of different stratified subsurface. Finally, the six thermal properties are obtained by the proposed multi-parameter estimation method based on BA, and their accuracy is validated using the experimental data in TRT. The five temperatures obtained from the numerical layered BHE model using the estimated results are compared with the corresponding experimental data, the results show that the maximum error of the inlet and outlet water temperatures of the BHE is respectively 3.32 % and 3.59 %, and it is 3.31 %, 2.38 % and 2.7 % for the coarse sand, fine sand and brown soil, respectively.

Scaling Laws for Deployable Mesh Reflector Antennas

This paper begins with the formulation of a general, rapid design method for deployable mesh reflector antennas based on the AstroMesh architecture. This method is then used to obtain estimates of the total mass, stowed envelope size, and fundamental natural frequency of vibration for antennas with a range of aperture diameters and focal lengths, assuming an operational radio frequency of 10 GHz. A study of the scaling trends of this reflector design shows that the distribution of prestress in the inner tension structure has a major impact on the mass of the outer perimeter truss. Based on this result, a prestress optimization problem to design reflectors of minimum mass is formulated, and analytical scaling laws are obtained for the mass, stowed envelope, and natural frequency of optimally prestressed reflectors with aperture diameters up to 200 m. It is then shown that aperture diameters of 70–100 m are at the limit of launchers that are currently available or under development. A semianalytical homogenization model that accurately estimates the fundamental natural frequencies for batten-supported and free-free boundary conditions is also presented.

A Miniaturized Dual-Band Circularly Polarized Implantable Antenna for Use in Hemodialysis.

Hemodialysis is achieved by implanting a smart arteriovenous graft (AVG) to build a vascular pathway, but reliability and stability in data transmission cannot be guaranteed. To address this issue, a miniaturized dual-band circularly polarized implantable antenna operating at 1.4 GHz (for energy transmission) and 2.45 GHz (for wireless telemetry), implanted in a wireless arteriovenous graft monitoring device (WAGMD), has been designed. The antenna design incorporates a rectangular serpentine structure on the radiation surface to reduce its volume to 9.144 mm3. Furthermore, matching rectangular slots on the radiation surface and the ground plane enhance the antenna's circular polarization performance. The simulated effective 3 dB axial ratio (AR) bandwidths are 11.43% (1.4 GHz) and 12.65% (2.45 GHz). The simulated peak gains of the antenna are -19.55 dBi and -22.85 dBi at 1.4 GHz and 2.45 GHz, respectively. The designed antenna is implanted in a WAGMD both in the simulation and the experiment. The performance of the system is simulated in homogeneous human tissue models of skin, fat, and muscle layers, as well as a realistic adult male forearm model. The measurement results in a minced pork environment align closely with the simulation results.

Spatiotemporally nonlocal homogenization method for viscoelastic porous metamaterial structures

The underlying size-dependent mechanism of viscoelastic porous metamaterial structures is still unclear, and the solution to their response using the high-fidelity numerical method is time-consuming, even prohibitive. This paper explores how the size-dependent effect of metamaterial structures emerges from the underlying nonlocal interactions in metamaterial microstructures, and then develops an accurate but efficient homogenization method for analyzing their size-dependent and time-dependent mechanical behaviors of viscoelastic porous metamaterial structures. By accounting for the nonlocal interaction between different representative volume elements and the history-dependent effect, a spatiotemporally nonlocal discrete element model is developed to analyze the mechanical behavior of viscoelastic porous metamaterial structures. With the help of the spatiotemporally nonlocal discrete element model, a spatiotemporally nonlocal homogenization method is proposed to accurately yet efficiently assess the size-dependent mechanical behavior of the porous metamaterial structure. The remarkable potential of the spatiotemporally nonlocal homogenization method is illustrated by simulating the stress relaxation of a viscoelastic porous metamaterial structure under axial strain. Results indicate that the size-dependent phenomenon can be significant, and the spatiotemporally nonlocal homogenization model can efficiently capture the size-dependent relaxation stress evaluated by the high-fidelity finite element model without loss of accuracy.

Full waveform inversion of cross-hole radio frequency electromagnetic data

Summary We consider application of full waveform inversion (FWI) to radio-frequency electromagnetic (EM) data. Radio-frequency imaging (RIM) is a cross-borehole technique to image electromagnetic subsurface properties from measurements of transmitted radio-frequency waves. It is used in coal seam imaging, ore exploration and various engineering and civil engineering applications. RIM operates at frequencies from 50 kHz to several tens of MHz. It differs from other geophysical EM methods, because the frequency band includes the transition between the wave propagation and diffusion regimes. RIM data are acquired in two-dimensional cross-hole sections in a reciprocal manner. Traditionally, radio-frequency data are inverted by straight ray tomography because it is inexpensive and easy to implement. It is argued that due to attenuation, the sensitivity of the transmitted electric field is the strongest within the first Fresnel zone of the ray connecting the transmitter and receiver. While straight ray tomography is a simple to implement and fast method, the non-linearity in the relationship between model parameters and data is often strong enough to warrant non-linear inversion techniques. FWI is an iterative high resolution technique, in which the physical properties are updated to minimize the misfit between the measured and modelled wavefields. Full waveform techniques have been used and extensively studied for the inversion of seismic data, and more recently, they have been applied to the inversion of GPR data. Non-linear inversion methods for RIM data are less advanced. Their use has been hindered by the high cost of full wave modelling and the high conductivity contrasts of many RIM targets, and, to some extent, by the limitations of the measuring instruments. We present the first application of this methodology to simultaneous conductivity and permittivity inversion of RIM data. We implement the inversion in the frequency domain in two dimensions using L-BFGS optimization. We analyze the sensitivity of the data to the model parameters and the parameter trade-off and validate the proposed methodology on a synthetic example with moderate conductivity variations and localized highly conductive targets. We then apply the FWI methodology to a field data set from Sudbury, Canada. For the field data set, we determine the most appropriate preprocessing steps that take into account specific peculiarities of RIM: the insufficient prior information about the subsurface and the limitations of the measuring equipment. We show that FWI is applicable under the conditions of RIM and is robust to imperfect prior knowledge: we obtain satisfactory model recoveries starting from homogeneous initial models in all of our examples. Just as other methods, FWI underestimates large conductivity contrasts due to the loss of sensitivity of the transmitted electric field to the conductivity variations as the conductivity increases above a certain level. The permittivity inside high conductors can not be recovered, however, recovering permittivity variations in the resistive zones helps obtain better focused conductivity images with fewer artifacts. Overall, FWI produces cleaner, less noisy and higher resolution reconstructions than the methods currently used in practice.

Spatiotemporal Evolution of Gas in Transmission Fluid under Acoustic Cavitation Conditions

The presence of gas in transmission fluid can disrupt the flow continuity, induce cavitation, and affect the transmission characteristics of the system. In this work, a gas void fraction model of gas–liquid two-phase flow in a transmission tube is established by taking ISO 4113 test oil, air, and vapor to accurately predict the occurrence, development, and end process of the cavitation zone as well as the transient change in gas void fraction. This model is based on the conservative homogeneous flow model, considering the temperature change caused by transmission fluid compression, and cavitation effects including air cavitation, vapor cavitation, and pseudo-cavitation. In this model, the pressure term is connected by the state equation of the gas–liquid mixture and can be applied to the closed hydrodynamic equations. The results show that in the pseudo-cavitation zone, the air void fraction decreases rapidly with pressure increasing, while in the transition zone from pseudo-cavitation to air cavitation, the air void fraction grows extremely faster and then increases slowly with decreasing pressure. However, in the vapor cavitation zone, the vapor void fraction rises slowly, grows rapidly, and then decreases, which is consistent with the explanation that rarefaction waves induce cavitation and compression waves reduce cavitation.

Spatial correlation between in vivo imaging and immunohistochemical biomarkers: A methodological study

In this study, we present a method that enables voxel-by-voxel comparison of in vivo imaging to immunohistochemistry (IHC) biomarkers. As a proof of concept, we investigated the spatial correlation between dynamic contrast enhanced (DCE-)CT parameters and IHC biomarkers Ki-67 (proliferation), HIF-1α (hypoxia), and CD45 (immune cells). 54 whole-mount tumor slices of 15 laryngeal and hypopharyngeal carcinomas were immunohistochemically stained and digitized. Heatmaps of biomarker positivity were created and registered to DCE-CT parameter maps. The adiabatic approximation to the tissue homogeneity model was used to fit the following DCE parameters: Ktrans (transfer constant), Ve (extravascular and extracellular space), and Vi (intravascular space). Both IHC and DCE maps were downsampled to 4 × 4 × 3 mm[3] voxels. The mean values per tumor were used to calculate the between-subject correlations between parameters. For the within-subject (spatial) correlation, values of all voxels within a tumor were compared using the repeated measures correlation (rrm). No between-subject correlations were found between IHC biomarkers and DCE parameters, whereas we found multiple significant within-subject correlations: Ve and Ki-67 (rrm = -0.17, P < .001), Ve and HIF-1α (rrm = -0.12, P < .001), Ktrans and CD45 (rrm = 0.13, P < .001), Vi and CD45 (rrm = 0.16, P < .001), and Vi and Ki-67 (rrm = 0.08, P = .003). The strongest correlation was found between IHC biomarkers Ki-67 and HIF-1α (rrm = 0.35, P < .001). This study shows the technical feasibility of determining the 3 dimensional spatial correlation between histopathological biomarker heatmaps and in vivo imaging. It also shows that between-subject correlations do not reflect within-subject correlations of parameters.

A New Perspective on the Homogeneous Coordinate System for Calculating Interatomic Distances and Their Derivatives in Terms of Internal Coordinates

AbstractIn many chemical physics calculations, efficient computation of interatomic distances and their derivatives using internal coordinates is essential for understanding molecular structure and dynamics. This paper explores the homogeneous coordinate system as an alternative framework to simplify these calculations. It is proven that computing interatomic distances using the Euclidean model of 3D space requires almost 60% more operations than the homogeneous model, which may represent a significant difference in molecular dynamics simulations.

Comprehensive Assessment of STGSA Generated Skeletal Mechanism for the Application in Flame-Wall Interaction and Flame-Flow Interaction

In this study, we conduct a thorough evaluation of the STGSA-generated skeletal mechanism for C2H4/air. Two STGSA-reduced mechanisms are taken into account, incorporating basic combustion models such as the homogeneous reactor model, one-dimensional flat premixed flame, and non-premixed counterflow flame. Subsequently, these models are applied to more complex combustion systems, considering factors like flame-flow interaction and flame-wall interaction. These considerations take into account additional physical parameters and processes such as mixing frequency and quenching. The results indicate that the skeletal mechanism adeptly captures the behavior of these complex combustion systems. However, it is suggested to incorporate strain rate considerations in generating the skeletal mechanism, especially when the combustion system operates under high turbulent intensity.

Novel Methods for Cost-Effectively Generating a Heterogeneous Core Model Based on Scale Change of Nuclear Magnetic Resonance and X-ray Computed Tomography Data

Summary In response to the constraint on model size imposed by computational capabilities and the inability to capture the heterogeneity within the core and its dynamic oil displacement characteristics, this paper proposes two novel methods for cost-effectively modeling heterogeneous core models based on scale changes of nuclear magnetic resonance (NMR) and X-ray computed tomography (X-CT) data, respectively. By utilizing NMR and X-CT techniques to characterize information at the subcore scale, we establish a more realistic model at the core scale. First, by using a method of setting up inactive grids, a homogeneous model is established to better represent the actual cross-section of the core. By fitting the core water displacement experimental data, a random heterogeneous core model based on the NMR-T2 spectrum is established by using the modified Schlumberger-Doll Research (SDR) model and complementarity principle. The numerical simulation results show that the random heterogeneous core model partially reflect the heterogeneity of the core, but the simulation results are unstable. Building on this, a deterministic homogeneous core model is established based on X-CT scan data by using the modified Kozeny-Carman model and pore extraction method. Sensitivity analysis results suggest that higher grid accuracy leads to a better fitting effect, with the axial plane grid accuracy impacting the model water-drive process more significantly than that of the end plane. The study paves the way for the rapid and accurate establishment of core models.

Evaluation of quasi-static and dynamic compressive properties of Ti-6Al-4 V functionally graded shell lattices with minimal surfaces

Functionally graded shell (FGS) lattices have recently captivated enormous research interest in engineering applications for their outstanding mechanical and energy-absorbing performances. This paper designs FGS lattices featuring I-WP triply periodic minimal surfaces using implicit functions. FGS and uniform shell (US) samples made of Ti-6Al-4 V powder are manufactured utilizing laser powder bed fusion technology. Quasi-static compression and drop-weight impact experiments are conducted to evaluate the mechanical and energy-absorbing performances as well as deformation mechanism of FGS and US samples. The results demonstrate that the deformation modes of the samples under both loading conditions are similar, which is basically attributed to the drop-weight impact velocities being lower than the critical speeds calculated by the rigid-power-law hardening (RPLH) model. Additionally, the effects of loading velocity on the deformation mechanisms of US and FGS lattices are simulated, and homogenization, transition, and shock deformation models are predicted by the RPLH model. The FGS sample exhibits distinct layer-by-layer failures and eliminates the abrupt shear band under dynamic and quasi-static loadings. Compared to the quasi-static results, a notable strain rate hardening effect is observed under the dynamic condition, mainly due to the hardening of the row material. Consequently, the elastic modulus, yield strength, compression strength, and cumulative energy absorption of the US sample under drop-weight impact loading improved by 18.74 %, 56.52 %, 45.31 %, and 6.62 %, respectively. However, the FGS sample shows less sensitivity to strain rate owing to the layer-by-layer deformation mechanism, and their elastic modulus, yield strength, compression strength, and cumulative energy absorption only increased by 11.84 %, 34.72 %, 36.85 %, and 3.86 %, respectively. The FGS lattices exhibit a low peak stress during the compression process, which is favorable for industrial applications in crashworthiness and energy absorption.

Modelling of heat transfer and pressure drop during flow boiling of CO2 in a horizontal tube with periodic open cellular inserts

During flow boiling in horizontal tubes, highly porous inserts can improve the wetting of the tube wall and the convective boiling. The literature focuses on solid sponge structures with irregular cell geometries. Hence, in this work the local heat transfer and pressure drop during flow boiling of CO2 in periodic open cellular structures with cubic and Kelvin cell geometry were investigated. A strong influence of the cell geometry on the heat transfer and pressure drop was found. By combining the Forchheimer term with a two-phase flow method (homogeneous model, drift flux model) a new pressure drop model is proposed. The model has a mean absolute percentage error (MAPE) of 12%. Regarding the heat transfer, high-speed video recordings and an evaluation of the local heat transfer were used to test the tube segments for complete wetting. Thereafter, the convective boiling contribution was extracted from the local data of completely wetted tube segments by subtracting the nucleate boiling contribution. A separate model of the convective boiling is proposed for each cell type. The models have a MAPE of 20%. Finally, the circumferentially averaged heat transfer coefficient was found to follow a superposition of the heat transfer of the liquid and vapor phase.

Bending shape memory properties and multi-scale viscoelastic behaviors of knitted-fabric reinforced polymer composites

Knitted fabrics with easily deformable loop structure have the potential in the development of shape memory polymeric composites with large recovery deformations. The knitted fabric reinforced shape memory epoxy polymer composites (SMPC) were prepared in this work. The effects of loop densities, orientations and bending radii on shape memory properties of SMPC were investigated. The shape fixity ratio and shape recovery ratio of SMPC subjected to U-shaped bending radius of 5 mm are above 98 %. The shape recovery force of SMPC can reach up to 5.9 N. The thermodynamic properties of SMP were also characterized to obtain mechanical parameters and a user-defined material subroutine (UMAT) of shape memory epoxy polymer (SMEP) was written. Based on viscoelastic theory and the multi-scale geometrical structures, the macroscopic homogeneous thermodynamic model and mesoscopic thermodynamic model of knitted fabric reinforced SMPC were established to study the macro-scale stress distribution and meso-scale deformation evolution during shape memory process, respectively. The neutral surface position of SMPC during bending deformation is offset inner. The unique anisotropic loop structure of knitted fabric determines the shape memory behavior of the SMPC. Finally, micro-CT characterizations of knitted fabric reinforced SMPC were conducted to further understand the loop deformation mechanism during shape memory process. This study will provide important theoretical and technical support for large deformation structure design and deformation prediction of smart composites.

Predicting mechanical heterogeneity in glassy polymer nanocomposites via an inverse computational approach based on atomistic molecular simulations and homogenization methods

Probing the mechanical behavior of the region formed between a nanoparticle reinforcement and a polymer matrix in a polymer nanocomposite structure, denoted as the “interphase”, is a main challenge as such regions are difficult to investigate by experimental methods. Here, we accurately characterize the heterogeneous mechanical behavior of polymer nanocomposites, focusing on polymer/nanofiller interphases via a combination of nanomechanical simulations and numerical homogenization techniques. Initially, the global mechanical performance of a glassy poly(ethylene oxide) polymer nanocomposite reinforced with silica nanoparticles is studied using detailed atomistic molecular dynamics simulations for 1.9% and 12.7% silica volume fractions. Next, the polymer/silica interphase thickness is identified by probing the polymer atom-based density distribution profile in the vicinity of the nanofiller at equilibrium. On the basis of this thickness, the interphase is subdivided to check the position-dependent change in mechanical properties. Then, using continuum mechanics and atomistic simulations, we proceed to compute the effective Young’s modulus and Poisson’s ratio of the polymer/nanoparticle interphase as function of the distance from the nanoparticle. In the last step, an inverse numerical homogenization model is proposed to predict the mechanical properties of the interphase on the basis of a comparison criteria with the data from MD. The results were found to be acceptable, raising the possibility of accurately and efficiently predicting interfacial properties in nanostructured materials.

Sovereign Credit Risk in Saudi Arabia, Morocco and Egypt

The purpose of this paper is to assess and predict sovereign credit risk for Egypt, Morroco and Saudi Arabia using credit default swap (CDS) spreads obtained from the DataStream database for the period from 2009 to 2022. Our approach consists of generating the implied default probability and the corresponding credit rating in order to estimate the term structure of the implied default probability using the Nelson–Siegel model. In order to validate the prediction from the probability term structure, we calculate the transition matrices based on the implied rating using the homogeneous Markov model. The main results show that, overall, the probabilities of defaulting in the long term are higher than those in the short term, which implies that the future outlook is more pessimistic given the events that occurred during the study period. Egypt seems to be the country with the most fragile economy, especially after 2009, likely because of the political events that marked the country at that time. The economies of Morocco and Saudi Arabia are more resilient in terms of both default probability and credit rating. These findings can help policymakers develop targeted strategies to mitigate economic risks and enhance stability, and they provide investors with valuable insights for managing long-term investment risks in these countries.

Detectability of hemodynamic oscillations in cerebral cortex through functional near-infrared spectroscopy: a simulation study.

We explore the feasibility of using time-domain (TD) and continuous-wave (CW) functional near-infrared spectroscopy (fNIRS) to monitor brain hemodynamic oscillations during resting-state activity in humans, a phenomenon that is of increasing interest in the scientific and medical community and appears to be crucial to advancing the understanding of both healthy and pathological brain functioning. Our general object is to maximize fNIRS sensitivity to brain resting-state oscillations. More specifically, we aim to define comprehensive guidelines for optimizing main operational parameters in fNIRS measurements [average photon count rate, measurement length, sampling frequency, and source-detector distance (SSD)]. In addition, we compare TD and CW fNIRS performance for the detection and localization of oscillations. A series of synthetic TD and CW fNIRS signals were generated by exploiting the solution of the diffusion equation for two different geometries of the probed medium: a homogeneous medium and a bilayer medium. Known and periodical perturbations of the concentrations of oxy- and deoxy-hemoglobin were imposed in the medium, determining changes in its optical properties. The homogeneous slab model was used to determine the effect of multiple measurement parameters on fNIRS sensitivity to oscillatory phenomena, and the bilayer model was used to evaluate and compare the abilities of TD and CW fNIRS in detecting and isolating oscillations occurring at different depths. For TD fNIRS, two approaches to enhance depth-selectivity were evaluated: first, a time-windowing of the photon distribution of time-of-flight was performed, and then, the time-dependent mean partial pathlength (TMPP) method was used to retrieve the hemoglobin concentrations in the medium. In the homogeneous medium case, the sensitivity of TD and CW fNIRS to periodical perturbations of the optical properties increases proportionally with the average photon count rate, the measurement length, and the sampling frequency and approximatively with the square of the SSD. In the bilayer medium case, the time-windowing method can detect and correctly localize the presence of oscillatory components in the TD fNIRS signal, even in the presence of very low photon count rates. The TMPP method demonstrates how to correctly retrieve the periodical variation of hemoglobin at different depths from the TD fNIRS signal acquired at a single SSD. For CW fNIRS, measurements taken at typical SSDs used for short-separation channel regression show notable sensitivity to oscillations occurring in the deep layer, challenging the assumptions underlying this correction method when the focus is on analyzing oscillatory phenomena. We demonstrated that the TD fNIRS technique allows for the detection and depth-localization of periodical fluctuations of the hemoglobin concentrations within the probed medium using an acquisition at a single SSD, offering an alternative to multi-distance CW fNIRS setups. Moreover, we offered some valuable guidelines that can assist researchers in defining optimal experimental protocols for fNIRS studies.

A cell-centered implicit finite difference scheme to study wave propagation in acoustic media: A numerical modeling

In the present paper, we present a Cell-Centered Implicit Finite Difference (CCIFD) operator-based numerical scheme for the propagation of acoustic waves that is very effective, accurate, and small in size. This scheme requires fewer estimation points than the traditional central difference derivative operator. Any numerical simulation is significantly impacted by the precision of a numerical derivative. Long stencils can deliver excellent accuracy while also minimizing numerical anisotropy error. However, a long stencil requires a lot of computational resources, and as these derivatives get bigger, they could start to look physically unrealistic due to contributions from nodes located extremely far, wherein the derivative is local in nature. Furthermore, using such lengthy stencils at boundary nodes may result in errors. The present article investigates a cell-centered fourth order finite difference scheme to model acoustic wave propagation which utilizes a lesser number of nodes in comparison to the traditional Central Difference (CD) operator. However, in general the implicit derivative operator has high computational cost and therefore despite its significant advantages it is generally avoided to be implemented in applications. This serves as a motivation for the present paper to explore a technique called CCIFD that significantly decreases the computational expense by nearly fifty percent. Additionally, spectral characterization of the CCIFD derivative operator has been analyzed and discussed. Finally, the wave propagation has been numerically simulated in 2-dimensional homogeneous and Marmousi model using CCIFD scheme to validate the applicability and stability of the scheme.

Characterization of petrophysical and seismic properties for CO2 storage with sensitivity analysis

Saline aquifers are considered as highly favored reservoirs for CO2 sequestration due to their favorable properties. Understanding the impact of saline aquifer properties on the migration and distribution of CO2 plume is crucial. This study focuses on four key parameters—permeability, porosity, formation pressure, and temperature—to characterize the reservoir and analyse the petrophysical and elastic response of CO2. First, we performed reservoir simulations to simulate CO2 saturation, using multiple sets of these four parameters to examine their significance on CO2 saturation and the plume migration speed. Subsequently, the effect of these parameters on the elastic properties is tested using rock physics theory. We established a relationship of compressional wave velocity (Vp) and quality factor (Qp) with the four key parameters, and conducted a sensitivity analysis to test their sensitivity to Vp and Qp. Finally, we utilized visco-acoustic wave equation simulated time-lapse seismic data based on the computed Vp and Qp models, and analysed the impact of CO2 saturation changes on seismic data. As for the above numerical simulations and analysis, we conducted sensitivity analysis using both homogeneous and heterogeneous models. Consistent results are found between homogeneous and heterogeneous models. The permeability is the most sensitive parameter to the CO2 saturation, while porosity emerges as the primary factor affecting both Qp and Vp. Both Qp and Vp increase with the porosity, which contradicts the observations in gas reservoirs. The seismic simulations highlight significant variations in the seismic response to different parameters. We provided analysis for these observations, which serves as a valuable reference for comprehensive CO2 integrity analysis, time-lapse monitoring, injection planning and site selection.

Innovación educativa con sistemas de aprendizaje adaptativo impulsados por Inteligencia Artificial

The emergence of artificial intelligence (AI) is transforming education through adaptive learning systems. These systems, based on AI algorithms, personalize the educational experience by adjusting to the needs and learning styles of each student. Using techniques such as machine learning and deep learning, they analyze large volumes of data to generate personalized learning itineraries, breaking with the homogeneous teaching model. Their implementation requires a suitable technological platform, a solid data infrastructure and the training of teachers in the use of these tools. The benefits are multiple: students receive real-time feedback and progress at their own pace, improving their motivation and learning effectiveness, while teachers can focus their efforts on higher value-added tasks and obtain valuable information on their students' progress, facilitating adaptive and personalized teaching.

An electrochemical biosensor with homogeneous dual amplification strategy for sensitive analysis of Pb2+

Herein, a homogeneous double amplified electrochemical biosensing system was designed on the basis of rolling circle amplification (RCA) and DNAzyme-assisted Pb2+ recycling amplification with the assistance of the signal molecule methylene blue (MB), which was used for highly sensitive analysis of Pb2+. In comparison with the conventional electrochemical biosensor, the homogeneous strategy adopted in this work can avoid the complex electrode modification and immobilization processes, and address the issues of the large steric hindrance and the restricted probe freedom on the sensing interface, thus achieving high recognition efficiency between recognition unit and target molecule as well as excellent detection performance of biosensor. In addition, the double amplified method assembling RCA and DNAzyme-assisted Pb2+ recycling amplification can convert a handful of target Pb2+ into abundant signal molecule MB, which would lead to the double amplification of output signal and the significantly enhanced detection sensitivity. Taking advantages of homogeneous dual amplification strategy, the constructed electrochemical biosensor for Pb2+ analysis emerged a good linear range of 50 fM to 500 nM and a detection limit of 16.7 fM with significant selectivity and desirable stability. Impressively, the result presented herein comprise a valuable reference for establishing homogeneous multiple amplification model and constructing innovative biosensing system for sensitive detection of heavy metal ions.