Anisotropy Coefficient Research Articles

Revealing regional variations in scleral shear modulus in a rabbit eye model using multi-directional ultrasound optical coherence elastography

The mechanical properties of the sclera play a critical role in supporting the ocular structure and maintaining its shape. However, non-invasive measurements to quantify scleral biomechanics remain challenging. Recently introduced multi-directional optical coherence elastography (OCE) combined with an air-coupled ultrasound transducer for excitation of elastic surface waves was used to estimate phase speed and shear modulus in ex vivo rabbit globes (n = 7). The scleral phase speed (12.1 ± 3.2 m/s) was directional-dependent and higher than for corneal tissue (5.9 ± 1.4 m/s). In the tested locations, the sclera proved to be more anisotropic than the cornea by a factor of 11 in the maximum of modified planar anisotropy coefficient. The scleral shear moduli, estimated using a modified Rayleigh-Lamb wave model, showed significantly higher values in the circumferential direction (65.4 ± 31.9 kPa) than in meridional (22.5 ± 7.2 kPa); and in the anterior zone (27.3 ± 9.3 kPa) than in the posterior zone (17.8 ± 7.4 kPa). The multi-directional scanning approach allowed both quantification and radial mapping of estimated parameters within a single measurement. The results indicate that multi-directional OCE provides a valuable non-invasive assessment of scleral tissue properties that may be useful in the development of improved ocular models, the evaluation of potential myopia treatment strategies, and disease characterization and monitoring.

Application of machine learning and fuzzy AHP for identification of suitable groundwater potential zones using field based hydrogeophysical and soil hydraulic factors in a complex hydrogeological terrain

The eastern section of West Bengal grapples with limited surface water availability in its hard rock terrain, compounded by a semi-arid climate, variable rainfall, and a plateau topography, prompting communities to adapt groundwater water-use practices, leading to unsustainable extraction and misuse. Thus, the novel objective of the present research was to produce groundwater potential maps by comparing machine learning techniques with a Fuzzy MCDM model using specific field-based conditioning factors. In the first step, 285 wells were identified, of which 70 percent were used for training and 30 percent for the validation of the models. Secondly, field-based conditioning factors including, longitudinal conductance (SC), longitudinal resistance (ρl), transverse resistance (TR), coefficient of electrical anisotropy (λ), resistivity of formation (ρm), fracture porosity (φf), reflection coefficients (r), hydraulic conductivity (K), transmissivity(Tr), bulk density, porosity, permeability, soil moisture content and water holding capacity were used to analyze the association between these conditioning factors and groundwater occurrences. In the following steps, the XGBoost, Random Forest, and Naïve Bayes models were executed using the training dataset, and factor weights were calculated using Fuzzy Analytical Hierarchy Process of Extent analysis method. To validate and compare the performance of four models, ROC curves, AUCs, MCAs, and correlation plots were used. In general, all four models were successful in evaluating the potential of groundwater occurrences. The predictive capability of the XGBoost techniques with the highest AUC values (0.79) and the highest correlation value (0.78) is superior to those of other machine learning and MCDM models. Geophysical survey revealed that transmissivity and hydraulic conductivity of the aquifer of the river basin range from 1.55 to 440.11 m/day and 10.15–2253 m2/day, indicating a moderate to good hydrodynamic potential. Planners and engineers can use such groundwater potential maps to manage water resources effectively.

Parametric instability analysis of rotors under anisotropic boundary conditions

Ensuring rotor stability is a major concern in engineering, as instabilities can lead to catastrophic failures. Existing literature shows that anisotropic boundary conditions significantly affect the parametric instability characteristics of rotors under periodical axial loads. However, there is little literature systematically analyzing the formation mechanism of parametric resonance under these boundary conditions or providing a detailed classification of the parametric instability regions. Therefore, this paper presents a comprehensive parametric instability analysis of a rotor subjected to periodic axial loads under anisotropic boundary conditions. A novel approach based on the multiple scales method is proposed to address anisotropy in the boundary conditions. Using this approach, the analytical boundaries of the parametric instability regions are derived, and a proof regarding the absence of certain parametric resonances is presented. These analytical solutions are validated by numerical results obtained from the discrete transition matrix method, which form the basis for systematically investigating the effects of anisotropy in direct or cross-coupling stiffness/damping coefficients on the rotor instability. The key scientific contributions of this work include: Deriving analytical instability boundaries, providing a more efficient alternative to purely numerical methods while maintaining high accuracy; Demonstrating the absence of parametric resonance of difference type under both isotropic or anisotropic boundary conditions; Discovering that anisotropy in stiffness coefficients can induce self-interaction within a given forward or backward whirl mode, as well as interaction between two forward or two backward whirl modes, leading to additional instability regions; Reducing anisotropy in direct damping coefficients may increase critical dynamic load coefficients, potentially enhancing rotor safety; If the cross-coupling stiffness coefficients exceed the threshold for triggering intrinsic instability, the rotor may become unstable in all operating conditions. All these findings offer insights into the stability management of rotors under various operating conditions and provide valuable guidance for designing and operating safer, more efficient rotor systems.

The clinical and pathological evaluation of patients with immunoglobulin A nephropathy by diffusion tensor imaging and intravoxel incoherent motion diffusion-weighted imaging.

To explore the efficacy of diffuse magnetic resonance imaging (MRI) for identifying clinicopathological changes in immunoglobulin A nephropathy (IgAN) patients. The study enrolled IgAN patients and healthy volunteers. IgAN patients were divided into Group 1 [estimated glomerular filtration rate (eGFR) ≥ 90 mL/min/1.73 m2], Group 2 (60 ≤ eGFR < 90 mL/min/1.73 m2), and Group 3 (eGFR < 60 mL/min/1.73 m2). Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion tensor imaging (DTI) were performed via 3.0 T magnetic resonance. Diffuse MRI, clinical, and pathological indicators were collected and analysed. P < .05 was considered statistically significant. Forty-six IgAN patients and twenty-seven volunteers were enrolled. The apparent diffusion coefficient, diffusion coefficient (D), perfusion fraction (f), and fractional anisotropy (FA) were significantly different among IgAN subgroups and controls. These parameters were positively correlated with eGFR and negatively with creatinine, and inversely correlated with glomerular sclerosis, interstitial fibrosis, and tubular atrophy (all P < .05). They had significantly high area under the curve (AUC) for distinguishing IgAN patients from controls, while FA had the highest AUC in identifying Group 1 IgAN patients from volunteers. DTI and IVIM-DWI had the advantage of evaluating clinical and pathological changes in IgAN patients. DTI was superior at distinguishing early IgAN patients and might be a noninvasive marker for screening early IgAN patients from healthy individuals. DTI and IVIM-DWI could evaluate clinical and pathological changes and correlated with Oxford classification in IgAN patients. They could also identify IgAN patients from healthy populations, while DTI had superiority in differentiating early IgAN patients.

MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI

White matter alterations are increasingly implicated in neurological diseases and their progression. International-scale studies use diffusion-weighted magnetic resonance imaging (DW-MRI) to qualitatively identify changes in white matter microstructure and connectivity. Yet, quantitative analysis of DW-MRI data is hindered by inconsistencies stemming from varying acquisition protocols. Specifically, there is a pressing need to harmonize the preprocessing of DW-MRI datasets to ensure the derivation of robust quantitative diffusion metrics across acquisitions. In the MICCAI-CDMRI 2023 QuantConn challenge, participants were provided raw data from the same individuals collected on the same scanner but with two different acquisitions and tasked with preprocessing the DW-MRI to minimize acquisition differences while retaining biological variation. Harmonized submissions are evaluated on the reproducibility and comparability of cross-acquisition bundlewise microstructure measures, bundle shape features, and connectomics. The key innovations of the QuantConn challenge are that (1) we assess bundles and tractography in the context of harmonization for the first time, (2) we assess connectomics in the context of harmonization for the first time, and (3) we have 10x additional subjects over prior harmonization challenge, MUSHAC and 100x over SuperMUDI. We find that bundle surface area, fractional anisotropy, connectome assortativity, betweenness centrality, edge count, modularity, nodal strength, and participation coefficient measures are most biased by acquisition and that machine learning voxel-wise correction, RISH mapping, and NeSH methods effectively reduce these biases. In addition, microstructure measures AD, MD, RD, bundle length, connectome density, efficiency, and path length are least biased by these acquisition differences. A machine learning approach that learned voxelwise cross-acquisition relationships was the most effective at harmonizing connectomic, microstructure, and macrostructure features, but requires the same subject be scanned at each site co-registered. NeSH, a spatial and angular resampling method, was also effective and has generalizable framework not reliant co-registration. Our code is available at &lt;a href='https://github.com/nancynewlin-masi/QuantConn/'&gt;https://github.com/nancynewlin-masi/QuantConn/&lt;/a&gt;

Azimuthal anisotropy of jet particles in p-Pb and Pb-Pb collisions at sNN\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{{\ extrm{s}}_{\ extrm{NN}}} $$\\end{document} = 5.02 TeV

The azimuthal anisotropy of particles associated with jets (jet particles) at midrapidity is measured for the first time in p-Pb and Pb-Pb collisions at sNN\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{{\ extrm{s}}_{\ extrm{NN}}} $$\\end{document} = 5.02 TeV down to transverse momentum (pT) of 0.5 GeV/c and 2 GeV/c, respectively, with ALICE. The results obtained in p-Pb collisions are based on a novel three-particle correlation technique. The azimuthal anisotropy coefficient v2 in high-multiplicity p-Pb collisions is positive, with a significance reaching 6.8σ at low pT, and its magnitude is smaller than in semicentral Pb-Pb collisions. In contrast to the measurements in Pb-Pb collisions, the v2 coefficient is also found independent of pT within uncertainties. Comparisons with the inclusive charged-particle v2 and with AMPT calculations are discussed. The predictions suggest that parton interactions play an important role in generating a non-zero jet-particle v2 in p-Pb collisions, even though they overestimate the reported measurement. These observations shed new insights on the understanding of the origin of the collective behaviour of jet particles in small systems such as p-Pb collisions, and provide significant stringent new constraints to models.

Analysis of the monotonicity method for an anisotropic scatterer with a conductive boundary

Abstract In this paper, we consider the inverse scattering problem associated with an anisotropic medium with a conductive boundary. We will assume that the corresponding far–field pattern is known/measured and we consider two inverse problems. First, we show that the far–field data uniquely determines the boundary coefficient. Next, since it is known that anisotropic coefficients are not uniquely determined by this data we will develop a qualitative method to recover the scatterer. To this end, we study the so–called monotonicity method applied to this inverse shape problem. This method has recently been applied to some inverse scattering problems but this is the first time it has been applied to an anisotropic scatterer. This method allows one to recover the scatterer by considering the eigenvalues of an operator associated with the far–field operator. We present some simple numerical reconstructions to illustrate our theory in two dimensions. For our reconstructions, we need to compute the adjoint of the Herglotz wave function as an operator mapping into H 1 of a small ball.

Small polaron hopping and tunneling mechanisms in Ba0.9La0.1Fe12O19 hexaferrite ceramic at low temperatures

The correlation between dielectric relaxation and conduction mechanisms in the Ba0.9La0.1Fe12O19 ceramic hexaferrite, at temperatures below 100 K was investigated. The sample was prepared using the conventional solid-state reaction method. X-ray diffraction analysis indicated that the sample is composed of a hexagonal BaFe12O19 phase (lattice parameters a = 5.8778(6) Å and c = 23.170(3) Å) and a small proportion of hematite (α-Fe2O3). The average grain size is 1.48 ± 0.4 μm, with irregular hexagonal and agglomerated grains. The magnetic hysteresis curve shows characteristics typical of ferro and ferrimagnetic materials, with an effective magnetic anisotropy coefficient of 0.960×106 emu/cm3 and an anisotropy field of 1.587×104 Oe. A dielectric relaxation process is observed between 50 and 100 K, with an activation energy of 60.4 ± 0.4 meV and a characteristic relaxation time of 2.09 ×10−10 s, mainly attributed to the electrical behavior of the grains. Two conduction mechanisms were identified: small polaron tunneling (high temperatures and low frequencies) and correlated barrier hopping of electrons (low temperatures and high frequencies). The activation energy for free polaron formation, according to the Komine-Iguchi hopping polarization model, was 7.12 ± 0.02 meV. In the dielectric modulus relaxation process between 30 and 54 K, the activation energy was 40.8 ± 0.9 meV, with a characteristic relaxation time of 2.41×10−10 s. The small polaron conductivity in the grain region was 67.52 meV and 54.0 meV in the grain boundary region. The results highlight that the polarization and conduction mechanisms in this ceramic at low temperatures are dominated by small polaron hopping and tunneling, and emphasize the influence of La3+ doping on the structural, magnetic, and electrical properties of barium hexaferrite.

Two-Dimensional Exciton Oriented Diffusion via Periodic Potentials.

Excitonic devices operate based on excitons, which can be excited by photons as well as emitting photons and serve as a medium for photon-carrier conversion. Excitonic devices are expected to combine the advantages of both the high response rate of photonic devices and the high integration of electronic devices simultaneously. However, because of the neutral feature, exciton transport is generally achieved via diffusion rather than using electric fields, and the efficient control of exciton flux directionality has always been difficult. In this work, a precisely designed one-dimensional periodic nanostructure (1DPS) is used to introduce periodic strain field along with resonant mode to the WS2 monolayer, achieving exciton oriented diffusion with a 7.6-fold exciton diffusion coefficient enhancement relative to that of intrinsic, while enhancing the excitonic emission intensity by a factor of 10 and reducing exciton saturation threshold power by 2 orders of magnitude. Based on the analysis of the density functional theory (DFT) and the finite-element method (FEM), we attribute the anisotropy of exciton diffusion to exciton funneling induced by periodic potentials, which do not require excessive potential height difference for an efficient oriented diffusion. As a result of resonant emission, the exciton diffusion is dragged into the nonlinear regime owing to the high exciton density close to saturation, which improves the exciton diffusion coefficient and diffusion anisotropy more appreciably.

Long-range near-side correlation in e+e− collisions at 183-209 GeV with ALEPH archived data

The first measurement of two-particle angular correlations for charged particles with LEP-II data is presented. The study is performed using archived hadronic e+e− data collected by ALEPH at center-of-mass energies up to 209 GeV, above the W+W− production threshold, which provide access to unprecedented charged-particle multiplicities and more complex color-string configurations if compared to previous measurements at LEP-I energies. An intriguing long-range near-side excess is observed in the correlation function measured with respect to the thrust axis in the highest multiplicity interval (Ntrk≥50). Such a structure is not predicted by the Monte-Carlo simulation. The harmonic anisotropy coefficients vn, which result from the Fourier expansion of the two-particle correlation functions, were also measured for the first time in e+e− data, and compared to pythia 6 predictions and to the results obtained in proton-proton collisions. The results presented in the Letter provide novel experimental constraints on the formation of collective phenomena in point-like e+e− collisions.

Impact of thermal treatment on the properties of assacú (Hura crepitans L.) and murici (Byrsonima crispa A.Juss.) Amazon woods

Background: White and low-density Amazon woods, such as assacú (Hura crepitans L.) and murici (Byrsonima crispa A.Juss.), have restricted use, given their low physical-mechanical strength and low natural durability. Physicochemical changes caused by heat treatment can improve different quality traits of these woods, such as changing the visual appearance from white to brown tones, improving dimensional stability, moisture control, and resistance to attack from biological organisms. Methods: Assacú and murici wood samples were heat treated (180 and 220°C) for 60 minutes in a muffle kiln. The physical (moisture, mass loss, density, shrinkage, swelling), mechanical (dynamic modulus of elasticity), and chemical (extractives, solubility in hot water, lignin, and holocellulose) properties were evaluated following treatment and compared with those measured before treatment. Results: The heat treatments T2 (180°C) and T3 (220°C) reduced the moisture content; however, the T3 treatment caused a more intense mass loss. For murici wood, this mass loss was 14%. The anisotropy coefficient was reduced for assacú wood by 1.30 and 1.03% for the T2 and T3 treatments, respectively, improving the dimensional stability of this wood. The density and modulus of elasticity were affected by the treatment, thus reducing the strength of the wood. The extractive content of the woods increased by 4.99 and 7.49% for sampled of assacú and murici, respectively, that were treated at 220°C. For the primary metabolites, holocellulose and lignin, degradation of these compounds occurred due to the decrease in their concentrations. The linear analysis of the studied variables indicated a high correlation between the physical properties and the chemical components of the woods (e.g., anisotropy coefficient x lignin and holocellulose x apparent density, r &gt; 0.95). Conclusions: The heat treatment of Amazon woods directly influenced their physical-mechanical and chemical properties. In general, the higher temperature treatment caused the greatest changes in the studied species, and the exposure to heat caused noticeable changes in their colour. Heat treatment is a useful process for the forestry sector since heat-treated wood can be used to manufacture high-value-added products, such as fine furniture, residential floors, musical instruments, and non-structural components.

Synthesizing vulnerability indices within a diverse lithological context: Corollaries for groundwater quality assurance and surface layer corrosiveness of Lokoja Geomaterials, Nigeria

ABSTRACT This study provides prototypical evaluation of groundwater vulnerability to contamination and soil corrosivity in Lokoja region, central Nigeria. By combining the aquifer vulnerability index, integrated electrical conductivity, groundwater confinement overlying strata depth to water table (GOD), and electrical anisotropy coefficient (λ) derived from lithological composition, resistivity, and layer thickness; the study identifies substantial vulnerabilities in the groundwater resources. Findings indicate that over 70% of the region is moderately to very highly vulnerable to groundwater pollution, especially in the eastern and southern parts, highlighting the need for tailored groundwater management strategies in highly vulnerable areas, covering 40% of the region. Corrosion potential varies spatially, with 80% of the upper layer being minimally corrosive and around 45% of the lower moisture-rich layer showing moderate to significant corrosiveness, emphasizing risks in central and northern zones associated with lithological compositions and moisture content. These accentuate the necessity of rigorous monitoring programs and strict land use regulations to protect aquifers and infrastructure. This research underscores the value of proactive management for safeguarding groundwater resources, providing an invaluable framework for decision-making and resource allocation to tackle contamination and corrosion risks. Importantly, the research addresses a significant research gap in a region with limited scientific exploration.

Monoexponential and advanced diffusion-weighted imaging for hepatic fibrosis staging based on high inter-examiner reliability.

To determine the diagnostic efficiencies of multiple diffusion-weighted imaging (DWI) techniques for hepatic fibrosis (HF) staging under the premise of high inter-examiner reliability. Participants with biopsy-confirmed HF were recruited and divided into the early HF (EHF) and advanced HF (AHF) groups; healthy volunteers (HVs) served as controls. Two examiners analyzed intravoxel incoherent motion (IVIM) using the IVIM-DWI and diffusion kurtosis imaging (DKI) models. Intravoxel incoherent motion-DWI, DKI, and diffusion tensor imaging parameters with intraclass correlation coefficients (ICCs) of ≥0.6 were used to create regression models: HVs vs. EHF and EHF vs. AHF. We enrolled 48 HVs, 59 EHF patients, and 38 AHF patients. Mean, radial, and axial kurtosis; fractional anisotropy; mean, radial, and axial diffusivity; and α exhibited excellent reliability (ICCs: 0.80-0.98). Fractional anisotropy of kurtosis, f, and apparent diffusion coefficient showed good reliability (ICCs: 0.69-0.92). The real (0.58-0.67), pseudo- (0.27-0.76), and distributed diffusion coefficients (0.58-0.67) showed low reliability. In the HVs versus (vs.) EHF model, α (p=0.008) and ADC (p=0.011) presented statistical differences (area under curve [AUC]: 0.710). In the EHF vs. AHF model, α (p=0.04) and distributed diffusion coefficient (p=0.02) presented significant differences (AUC: 0.758). Under the premise of high inter-examiner reliability, DWI and IVIM-derived stretched-exponential model parameters may help stage HF.

The potential of QQQ in the anisotropic background

In this work, we use the AdS/CFT correspondence to study the behavior of a triply heavy baryon within anisotropic backgrounds. Beginning with the total action of the three quarks, we derive the balance equation for the three-quark system and compute the separation distance and potential energy. Our results reveal a consistent decrease in both the separation distance and potential energy for the A configuration and the B configuration as the anisotropy coefficient a increases. This suggests that the presence of an anisotropic background promotes the dissolution of the three-quark system. Additionally, we compare the potential energies of the A and B configurations and observe that the A configuration has a slightly smaller potential energy, suggesting greater stability compared to the B configuration.

Calculation of Lateral Logging Response and Environmental Impact Factor Analysis for Small Borehole Array

This paper refines an optimized array lateral logging tool designed for small boreholes, leveraging existing technologies. The tool features four investigation depth curves, and resistivity response curves are derived through finite element model simulations considering variables such as borehole size, mud characteristics, invasion zone features, resistive annuli, formation rock properties, and formation resistivity anisotropy. The findings included the following: (1) Increasing the wellbore diameter uniformly decreased resistivity across all four investigation depths, positively correlating with borehole size. When mud resistivity (Rm) exceeded formation resistivity (Rt), resistivity curves became distorted. (2) For high- and low-invasion models, the ratio of the deepest to the shallowest investigation depth curves ranged from 1 to 8 and 0.6 to 0.9, respectively, with maximum separation at an invasion depth of 0.5–0.8 m. (3) Under invasion conditions with annuli, an invasion zone depth and annulus width around 0.4 m yield well separated the resistivity curves for all depths. Low- and high-resistivity annuli of 2 m and 0.7 m, respectively, can cause curve intersections. (4) When the formation thickness exceeded 0.2 m, the tool accurately reflected formation resistivity variations and demonstrated effective layer identification in multi-layer conditions. (5) In anisotropic formations, resistivity was negatively correlated with the anisotropy coefficient (λ) as it changed from 2 to 4. The instrument can be fully utilized in the exploration of thin interlayers in oil and gas, significantly enhancing the accuracy of resource identification and extraction technologies.

High b-Value and Ultra-High b-Value Diffusion Weighted MRI in Stroke.

To explore the application value of high-b-value and ultra-high b-value DWI in noninvasive evaluation of ischemic infarctions. Prospective. Sixty-four patients with clinically diagnosed ischemic lesions based on symptoms and DWI. 3.0 T/T2-weighted fast spin-echo, fluid-attenuated inversion recovery, pre-contrast T1-weighted magnetization prepared rapid gradient echo sequence, multi-b-value trace DWI and q-space sampling sequences. Lesions were segmented on standard b-value DWI (SB-DWI, 1000 s/mm2), high b-value DWI (HB-DWI, 4000 s/mm2) and ultra-high b-value DWI (UB-DWI, 10,000 s/mm2), and cumulative segmented areas were the final abnormality volumes. Normal white matter (WM) areas were obtained after binarization of segmented brain. In 47 patients, fractional anisotropy (FA) and apparent diffusion coefficients (ADCs) at b values of 1000, 4000, and 10,000 s/mm2 were extracted from symmetrical WM masks and lesion masks of contralateral WM (CWM) and lesion-side WM (LWM). Wilcoxon matched-pairs signed-rank test and Pearson correlation analysis. Two-tailed P-values <0.05 were considered statistically significant. Various signals of HB-/UB-DWI (hypo-, iso- or hyper-intensity) were observed in strokes compared with SB-DWI, and some areas with iso-intensity of SB-DWI manifested with hyper-intensity on HB-/UB-DWI. Abnormality volumes from SB-DWI were significantly smaller than those from HB-DWI and UB-DWI (10.32 ± 16.45 cm3, vs. 12.25 ± 19.71 cm3 and 11.83 ± 19.41 cm3), while no significant difference exist in volume between HB-DWI and UB-DWI (P = 0.32). In CWM, FA significantly correlated with ADC4000 and ADC10,000 (maximum r = -0.51 and -0.64), but did not significantly correlate with ADC1000 (maximum r = -0.20, P = 0.17). ADC1000 or ADC4000 of LWM not significant correlated with FA of CWM (maximum r = -0.28, P = 0.06), while ADC10,000 of LWM significantly correlated with FA of CWM (maximum r = -0.46). HB- and UB-DWI have potential to be supplementary tools for the noninvasive evaluation of stroke lesions in clinics. 2 TECHNICAL EFFICACY: Stage 2.

Absence of E2g Nematic Instability and Dominant A1g Response in the Kagome Metal CsV3Sb5

Ever since the discovery of the charge density wave (CDW) transition in the kagome metal CsV3Sb5, the nature of its symmetry breaking has been under intense debate. While evidence suggests that the rotational symmetry is already broken at the CDW transition temperature (TCDW), an additional electronic nematic instability well below TCDW has been reported based on the diverging elastoresistivity coefficient in the anisotropic channel (mE2g). Verifying the existence of a nematic transition below TCDW is not only critical for establishing the correct description of the CDW order parameter, but also important for understanding low-temperature superconductivity. Here, we report elastoresistivity measurements of CsV3Sb5 using three different techniques probing both isotropic and anisotropic symmetry channels. Contrary to previous reports, we find the anisotropic elastoresistivity coefficient mE2g is temperature independent, except for a step jump at TCDW. The absence of nematic fluctuations is further substantiated by measurements of the elastocaloric effect, which show no enhancement associated with nematic susceptibility. On the other hand, the symmetric elastoresistivity coefficient mA1g increases below TCDW, reaching a peak value of 90 at T*=20 K. Our results strongly indicate that the phase transition at T* is not nematic in nature and the previously reported diverging elastoresistivity is due to the contamination from the A1g channel. Published by the American Physical Society 2024

Extremely Stable, Multidirectional, All‐in‐One Piezoelectric Bending Sensor with Cycle up to Million Level

AbstractFlexible bending sensors are crucial components of flexible/wearable electronics. However, their broad application is restricted by their difficulty in sensing different bending directions and, more importantly, their significant output attenuation after long cycles. Herein, a new design of an All‐in‐One piezoelectric bending sensor is proposed, in which double‐deck, cross‐over 3D interdigital microelectrodes (silver nanowires (Ag NWs)) are embedded in a piezoelectric polymer film (poly(vinylidene fluoride‐trifluoroethylene (P(VDF‐TrFE))). The piezoelectric film with the embedded 3D microelectrodes exhibits a high anisotropy coefficient ( &gt; 1) based on dual piezoelectric modes (d31 and d33), which renders it more sensitive to different bending directions. More importantly, the homogeneous interconnected interface and heterogeneous microinterlocked interface formed inside the sensor significantly enhance its interface mechanical properties, with at least a tensile strength of 51 MPa, a shear strength of 28 MPa, and an interfacial toughness of 300 J m−2, which are nearly two orders of magnitude greater than those of conventional sandwich architectures. The prepared All‐in‐One sensor shows an extremely stable piezoelectric output over as many as 16 00 000 bending cycles, which represents a remarkable breakthrough. Furthermore, a single sensor can be used to remotely control the multidirectional motion of a smart car, demonstrating enormous potential in practical applications.

Zero dissipation limit of the anisotropic Boussinesq equations with Navier-slip and Neumann boundary conditions

In this paper, we study the vanishing dissipation limit of the 2D anisotropic Boussinesq equations with the Navier-slip boundary condition for velocity field and the fixed flux boundary condition for temperature in the upper half plane. By constructing boundary layer correctors to compensate for the discrepancies between dissipative equations and non-dissipative equations at the boundary, we prove that the solutions of the anisotropic Boussinesq equations converge to the solutions of the non-dissipative Boussinesq equations in L2-norm. Particularly, we find that the anisotropic dissipation coefficients only affect the rate of convergence, which is different from the phenomenon of the Dirichlet problem of the anisotropic Boussinesq equations in Wang & Xu (2021).

Assessment of Anisotropic Acoustic Properties in Additively Manufactured Materials: Experimental, Computational, and Deep Learning Approaches.

The influence of acoustic anisotropy on ultrasonic testing reliability poses a challenge in evaluating products from additive technologies (AT). This study investigates how elasticity constants of anisotropic materials affect defect signal amplitudes in AT products. Experimental measurements on AT samples were conducted to determine elasticity constants. Using Computational Modeling and Simulation Software (CIVA), simulations explored echo signal changes across ultrasound propagation directions. The parameters A13 (the ratio between the velocities of ultrasonic transverse waves with vertical and horizontal polarizations at a 45-degree angle to the growth direction), A3 (the ratio for waves at a 90-degree angle), and Ag (the modulus of the difference between A13 and A3) were derived from wave velocity relationships and used to characterize acoustic anisotropy. Comparative analysis revealed a strong correlation (0.97) between the proposed anisotropy coefficient Ag and the amplitude changes. Threshold values of Ag were introduced to classify anisotropic materials based on observed amplitude changes in defect echo signals. In addition, a method leveraging deep learning to predict Ag based on data from other anisotropy constants through genetic algorithm (GA)-optimized neural network (NN) architectures is proposed, offering an approach that can reduce the computational costs associated with calculating such constants.