Discrete Layers Research Articles

Design optimization of automotive carbon fiber composite material floor laminate based on PSO-BFO algorithm

In response to the current challenges of low precision and efficiency in the optimization of composite material layups, the insufficient lightweight of automotive body floors, and the high cost of carbon fiber composites, this study introduces an optimized design method for carbon fiber composite flooring layups. Based on implicit parametric technology, a hybrid PSO-BFO (Particle Swarm Optimization-Bacterial Foraging Optimization) algorithm is employed. This approach achieves an integrated optimization of materials, processes, and structures, thereby balancing and reducing costs. The SFE-CONCEPT is utilized to establish an implicit parameterization model for the body floor, which is validated through experiments and finite element simulation analysis. Concept design and modeling of the carbon fiber composite material floor laminate are performed. Continuous variable optimization is employed to determine the thickness, tile shape, and number of layers for the front, middle, and rear floors. A continuous variable discretization rounding strategy is used to obtain the discrete layer numbers for each laminate orientation of the composite material floor. The continuous fiber lamination strategy is applied to create different shared lamination regions. The PSO-BFO hybrid optimization method is proposed to optimize the lamination sequence as a multi-objective optimization, addressing the challenges of discrete lamination sequence, explosive combinations, and multiple variables in the optimization design of carbon fiber composite material floor laminates. The optimization results demonstrate improvements of 34.4% in floor quality M, 6.0% in static bending stiffness BS, and 5.3% in lightweight coefficient QLX using the proposed PSO-BFO method. PSO-BFO and PSO-GA (Particle Swarm Optimization-Genetic Algorithm) methods are more capable of obtaining global optimal solutions for complex optimization problems than single optimization algorithms. Still, the results obtained by the PSO-BFO method are more balanced.

Low temperature powder bed fusion of polyamide 6: transient process characteristics and process-dependent part properties

AbstractThe powder-based additive manufacturing of high-melting polyamides is impeded by unfavorable fracture properties and oxidation tendencies, limiting the technical applicability and the reuse of unfused powder. Overcoming these limitations through new processing strategies provides the opportunity for significantly extending the range of materials applicable for powder bed fusion processes. Based on fractal, locally quasi-simultaneous exposure strategies, a mesoscale compensation of thermal and crystallization-induced shrinkage is obtained, enabling the non-isothermal processing and stable layer formation of polyamide 6 at powder bed temperatures of 25 °C, 50 °C, and 75 °C. Thermographic in situ investigations reveal the layerwise quenching of discrete layers, leading to cooling rates exceeding − 250 K s−1 at 130 °C. Based on microscopic, mechanical, thermal, and spectroscopic investigations, insights into the structure formation and corresponding mechanical properties can be obtained, yielding reduced fractions of α-PA6 while increasing the elongation at break. The inherent layerwise quenching promotes the formation of microspherulitic morphologies while minimizing oxidation-induced material degradation, reflected in infrared spectroscopic material characteristics. Relying on obtained findings, process optimization strategies can be derived that enable the processability of high-melting polyamides at reduced temperatures, reducing the energy consumption of the build process while adapting underlying material characteristics based on accelerated intermediate cooling conditions.

Implementation of PMDL and DRM in OpenSees for Soil-Structure Interaction Analysis

It is widely acknowledged that the effects of soil-structure interaction (SSI) can have substantial implications during periods of intense seismic activity; therefore, accurate quantification of these effects is of paramount importance in the design of earthquake-resistant structures. The analysis of SSI is typically conducted using either direct or substructure methods. Both of these approaches involve the use of numerical models with truncated or reduced-order computational domains. To ensure effective truncation, it is crucial to employ boundary representations that are capable of perfectly absorbing outgoing waves and allowing for the consistent application of input motions. At present, such capabilities are not widely available to researchers and practicing engineers. In order to address this issue, this study implemented the Domain Reduction Method (DRM) and Perfectly Matched Discrete Layers (PMDLs) in OpenSees. The accuracy and stability of these implementations were verified through the use of vertical and inclined incident SV waves in a two-dimensional problem. In terms of computational efficiency, PMDLs require a shorter analysis time (e.g., with PMDLs, the analysis concluded in 35 min as compared to 250 min with extended domain method) and less computational power (one processor for PMDLs against 20 processors for the extended domain method) thus offering a balance between accuracy and efficiency. Furthermore, illustrative examples of the aforementioned implemented features are presented, namely the response analysis of single-cell and double-cell tunnels exposed to plane waves inclined at an angle.

Vibration analysis of functionally graded carbon nanotube‐reinforced composite open cylindrical shells with damping film embedded

AbstractIn the present study, a discrete layer model was established to explore the vibration performance of Functionally Graded Carbon Nanotube‐Reinforced Composite (FG‐CNTRC) open cylindrical shells with damping film embedded based on the first‐order shell theory. There are four configurations of stacking arrangements considered for FG‐CNTRC open cylindrical shells with damping film embedded. The equivalent structural parameters of the top and bottom FG‐CNTRC panels are generated by implementing the extended mixing rule. Governing equations are derived based on the Hamilton principle and solved with the Naiver solution. Subsequently, after verifying the validity of this paper's solution by comparing it with the published literature, a parametric elaborated investigation discloses the variation patterns of vibration performance of four FG‐CNTRC open cylindrical shells with damping film embedded. The conclusions of the study can be used as a useful guide about open cylindrical composite shell structures with the design of high strength and damping.Highlights Discrete layer vibration model was bulit based on first‐order shell theory. Vbration performance of FG‐CNTRC open sandwich shells was studied. Variation patterns of frequency and loss factor was disclosed.

Post-glacial stratigraphy and late Holocene record of great Cascadia earthquakes in Ozette Lake, Washington, USA

Ozette Lake is an ~100-m-deep coastal lake located along the outer coast of the Olympic Peninsula (Washington, USA); it is situated above the locked portion of the northern Cascadia megathrust but also relatively isolated from active crustal faults and intraslab earthquakes. Here we present a suite of geophysical and geological evidence for earthquake-triggered mass transport deposits (MTDs) and related turbidite deposition in Ozette Lake since ca. 14 ka. Comprehensive high-resolution bathymetry data, seismic reflection profiles, and sediment cores are used to characterize the post-glacial stratigraphic framework and examine paleoseismic evidence in the lacustrine sediments. Stacked sequences of MTDs along the steep eastern flanks of the lake appear to grade basin-ward from thick, chaotic, blocky masses to thin, parallel-bedded turbidite beds. The discrete turbidite event layers are separated by fine-grained (silt and clay) lake sedimentation. The event layers are observed throughout the lake, but the physical characteristics of the deposits vary considerably depending on proximity to primary depocenters, steep slopes, and subaqueous deltas. A total of 30–34 event deposits are observed in the post-glacial record. Radiometric dating was used to reconstruct a detailed sedimentation history over the last ~5.5 k.y., develop an age model, and estimate the recurrence (365–405 yr) for the most recent 12 event layers. Based on sedimentological characteristics, temporal overlap with other regional paleoseismic chronologies, and recurrence estimates, at least 10 of the dated event layers appear to be sourced from slope failures triggered by intense shaking during megathrust ruptures; the recurrence interval for these 10 events is 440–560 yr. Thus, Ozette Lake contains one of the longest and most robust geological records of repeated shaking along the northern Cascadia subduction zone.

Thickness-dependent Relative Dielectric Constant of Organic Ultrathin Films.

In formulas employed for analysis of organic electronic devices, the relative dielectric constant value of the semiconductor organic films is often assumed rather than measured, even though it is a fundamental parameter for a correct interpretation. This is particularly true for ultrathin films made of discrete molecular layers. In this work, Spectroscopy Ellipsometry and Scanning Capacitance Microscopy were used to study thin films made of N,N'-bis(n-octyl)-x:y,dicyanoperylene-3,4:9,10-bis(dicarboximide). The relative dielectric constant presents a non-monotonic trend with thickness: it is equal to 2.1 for one molecular layer, saturating at 3.2 for increasing thickness. This maximum value, equivalent to the bulk one, occurs when the coverage is in between the third to the fourth layer. In this range, the growth switches from a Frank-Van der Merwe (2D growth) to a Volmer-Weber mode (3D growth); in addition, the molecular configuration assumes a bent/distorted geometry with respect to the initial edge-on one. These results establish a morphological dependence of the dielectric constant, especially in the vicinity of the substrate interface, that disappears at a certain distance from it.

The Caenorhabditis elegans cuticle and precuticle: a model for studying dynamic apical extracellular matrices in vivo.

Apical extracellular matrices (aECMs) coat the exposed surfaces of animal bodies to shape tissues, influence social interactions, and protect against pathogens and other environmental challenges. In the nematode Caenorhabditis elegans, collagenous cuticle and zona pellucida protein-rich precuticle aECMs alternately coat external epithelia across the molt cycle and play many important roles in the worm's development, behavior, and physiology. Both these types of aECMs contain many matrix proteins related to those in vertebrates, as well as some that are nematode-specific. Extensive differences observed among tissues and life stages demonstrate that aECMs are a major feature of epithelial cell identity. In addition to forming discrete layers, some cuticle components assemble into complex substructures such as ridges, furrows, and nanoscale pillars. The epidermis and cuticle are mechanically linked, allowing the epidermis to sense cuticle damage and induce protective innate immune and stress responses. The C. elegans model, with its optical transparency, facilitates the study of aECM cell biology and structure/function relationships and all the myriad ways by which aECM can influence an organism.

Local probing of the nanoscale hydration landscape of kaolinite basal facets in the presence of ions

The interface between aqueous solutions and the facets of kaolinite plays an important role in a wide range of technological applications including tribology, paper production, oil recovery, waste water treatment and medical devices. This is made possible by kaolinite's layered structure, with its two basal surfaces -aluminol and siloxane-exhibiting different properties and reactivity. Using a combination of high-resolution atomic force microscopy (AFM) and atomistic molecular dynamics (MD) simulations, we probe in situ the hydration structure over both facets, in water and in the presence of added NaCl. The AFM images reflect the facets' first hydration layer, as confirmed from simulations. Complementary AFM spectroscopy measurements show an excellent agreement between the conservative component and MD's water density profiles, with discrete hydration layers on both facets and little sensitivity to added ions. The dissipative component of the measured tip-sample interactions is more sensitive to the presence of ions, with MD suggesting a link with the local water dynamics and transient instabilities between stable hydration layers. These effects are facet-dependant and more pronounced on the aluminol facet where the first water layer is better defined. Increasing the salt concentration allows hydrated ions to form more stable layers, with hints of organised ionic domains. The results provide unique insights into both the equilibrium molecular structure and dynamics of the kaolinite facets, potentially informing applications involving interfacial processes.

Illitization of montmorillonite in ammonium solutions under hydrothermal conditions

In diagenetic solutions, ammonium may be incorporated into smectites as an exchangeable cation and become fixed within the interlayer space of illites and other white micas. To study the potential impact of NH4+ on the smectite-to-illite transformation reaction, a series of hydrothermal experiments were carried out at 100, 150 and 200 °C, spanning reaction duration from 15 to 90 days, and two NH4+ concentrations (0.1 and 0.2 M). The solids resulting from these alteration experiments were characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), and transmission and analytical electron microscopy (TEM and AEM). The XRD analysis revealed that, under the specified experimental conditions, smectite incorporates NH4+ in the structure, leading to the formation of non-swelling layers, resulting in partial transformation to illite layers and producing packets of disordered illite/smectite (I/S). In addition, a minor XRD peak at ∼10 Å suggests the formation of discrete illite crystals. The FTIR spectra demonstrated the uptake of NH4+, with deformation bands observed at 1400 and 1430 cm−1, corresponding to exchangeable NH4+ in smectite and fixed NH4+ in high-charge layers, respectively. TEM analysis revealed that smectite particles exhibited wavy stacks comprising a few layers with abundant defects and lateral discontinuities. The interlayer spacing in these particles ranged from 12 to 15 Å and became thinner and more plate-like with increasing temperature and time. Moreover, they contained inclusions of 10–10.3 Å layers, either as discrete layers or in packets of several layers, indicating the formation of disordered mixed-layer illite-smectite. Lateral transitions from 12 to 15 Å to 10 Å layers were frequently observed and interpreted as reaction fronts due to local rearrangement. At 150 and 200 °C, isolated packets of 10 Å layers were identified as discrete illite crystals that precipitated directly from solution. Analysis of the chemical composition of individual particles revealed an increase in octahedral charge (MgVI for AlVI substitution) in smectite particles, followed by increase in tetrahedral charge in I/S particles. Interlayer NH4+ played a stabilizing role in the high-charge layers and favored the smectite-to-illite conversion process.

Discrete heat equation for a periodic layered system with allowance for the interfacial thermal resistance: General formulation and dispersion analysis.

Discrete heat equations for the multilayered periodic systems with allowance for the thermal resistance between the layers and corresponding dispersion relations in ω-k space have been derived and analyzed. The discrete equations imply a finite velocity of thermal disturbances and guarantee the positiveness of the solutions. Analytical expressions for the attenuation distance, and phase and group velocities have been obtained as functions of frequency and thermal resistance between the discrete layers. These functions demonstrate unusual behavior at high frequency compared to the continuum case. Furthermore, the maximum allowed frequency and wave number for the discrete heat equation are limited, whereas there are no such limits in a continuum. The discrete equation contains an infinite hierarchy of continuous partial differential equations, which starts with the Fourier law, proceeds with the hyperbolic equation, the Guyer-Krumhansl (or Jeffreys type) equation, and then with higher-order equations. The partial differential equations with a finite number of terms are only approximations of the discrete equation, which implies that on the ultrashort space and timescales the discrete approach is preferable. This work provides a relatively simple, easy-to-adopt, conceptual tool, together with analytical expressions allowing one to study ultrafast wavelike heat conduction regimes in periodic multilayered metamaterials.

Bottom simulating reflections across the northern Gulf of Mexico slope

Bottom simulating reflections (BSRs) are widely used indicators for natural gas hydrate in reflection seismic data. BSRs, however, are typically studied on a local scale at a single site and less frequently on a large, regional scale. Herein, we map and describe BSRs over a 68,000 km2 area across the northern Gulf of Mexico slope, using publicly released industry-acquired 3D seismic data. We map 74 BSR zones that cover a total area of 2060 km2. To understand the characteristics of these BSR zones, we classify them based on their BSR characteristics in the seismic data (continuous, discontinuous, and clustered) and the geological settings in which they appear (structural, stratigraphic, and venting). The most common type of BSRs are discontinuous BSRs; such BSRs were mapped over ∼60% of the total BSR area. Discontinuous BSRs occur most commonly in structural or stratigraphic settings. Discontinuous BSRs indicate that gas and hydrate are likely concentrated in discrete layers crossing the base of the hydrate stability zone (HSZ). Continuous BSRs occur in 27% of the total BSR area and they primarily occur in venting and stratigraphic settings. At vent sites, hydrate formation likely reduces sediment permeability and focuses fluid flow laterally underneath the base of the HSZ, likely resulting in a continuous BSR along the area of lateral gas flow. Clustered BSRs, chaotic sequences of high amplitude reflections, occur in only 13% of the total BSR area and are only found within structural settings. In addition, the majority of clustered BSR zones are close to paleochannels, suggesting that clustered BSRs may be more common where coarser-grained sediments exist.

Gaussian-discrete restricted Boltzmann machine with sparse-regularized hidden layer

AbstractOverfitting is a critical concern in machine learning, particularly when the representation capabilities of learning models surpass the complexities present in the training datasets. To mitigate overfitting, curtailing the representation power of the model through suitable techniques such as regularization is necessary. In this study, a sparse-regularization method for Gaussian–Discrete restricted Boltzmann machines (GDRBMs) is considered. A GDRBM is a variant of restricted Boltzmann machines that comprises a continuous visible layer and discrete hidden layer. In the proposed model, sparse GDRBM (S-GDRBM), a sparse prior that encourages sparse representations of the hidden layer is employed. The strength of the prior (i.e., the sparse-regularization strength) can be tuned within the standard scenario of maximum likelihood learning; that is, the strength can be adaptively tuned based on the complexities of the datasets during training. We validated the proposed S-GDRBM using numerical experiments.

A Siderophore Mimicking Gelation Component for Capturing and Self-Separation of Fe(III) from an Aqueous Solution of Mixture of Metal Ions.

The carbohydrazide-based gelation component N2,N4,N6-(1,3,5-triazine-2,4,6-triyl)tris(benzene-1,3,5-tricarbohydrazide) (CBTC) was synthesized and characterized using various spectroscopic tools. CBTC and trimesic acid (TMA) get self-assembled to form metallogel with Fe3+, specifically through various noncovalent interactions in a DMSO and H2O mixture. The self-assembly shows remarkable specificity toward Fe(III) among different transition metal salts. It is pertinent to point out that the binding specificity for Fe3+ can also be found in nature in the form of siderophores, as they are mainly involved in scavenging iron selectively from the surroundings. DFT studies have been used to investigate the possible interaction between the different components of the iron metallogel. To determine the selectivity of CBTC for iron, CBTC, along with trimesic acid, is used to interact with other metal ions, including Fe(III) ions, in a single system. The gelation components CBTC and TMA selectively bind with iron(III), which leads to the formation of metallogel and gets separated as a discrete layer, leaving the other metal ions in the solution. Therefore, CBTC and TMA together show iron-scavenging properties. This selective scavenging property is explored through FE-SEM, XPS, PXRD, IR, and ICP-AES analysis. The FE-SEM analysis shows a flower-petal-like morphology for the Fe(III) metallogel. The resemblance in the CBTC-TMA-Fe metallogel and metallogel obtained from the mixture of different metal salts is established through FE-SEM images and XPS analysis. The release of iron from the metallogel is achieved with the help of ascorbic acid, which converts Fe3+ to Fe2+. In biological systems, iron also gets released similarly from siderophores. This is the first report where the synthesized gelation component CBTC molecule is capable of scavenging out iron in the form of metallogel and self-separating from the aqueous mixture in the presence of various other metal ions.

Block-flexure toppling failure of rock slopes using an equivalent deformation compatibility method

Block-flexure toppling constitutes the predominant form of toppling failure in rock slopes. Although it has been extensively studied, the current theoretical models are often oversimplified by treating rock layers as rigid bodies that diverge from actual conditions. The proposed Equivalent Deformation Compatibility Method (EDCM) offers a fresh approach to assess the stability of rock slopes prone to block-flexure toppling. EDCM posits that blocky rock layers, with their inability to withstand significant bending and role in merely transferring forces, can be modeled as intact layers with a reduced modulus. The method simplifies the complex issue of analyzing discrete and continuous rock layers to the study of layered soft and hard rock, establishing deformation compatibility equations subsequently. Validation of the EDCM was achieved through numerical models, physical model testing, and application to an actual slope. The factor of safety (FS) for slopes corresponds with the results from both models and the actual slope, demonstrating the method's applicability for evaluating susceptibility to block-flexure toppling. When applying the EDCM, it is advised to set the elastic modulus reduction coefficient for blocky layers at a value below 0.1.

Sensitivity of Phonation Onset Pressure to Vocal Fold Stiffness Distribution.

Phonation onset is characterized by the unstable growth of vocal fold (VF) vibrations that ultimately results in self-sustained oscillation and the production of modal voice. Motivated by histological studies, much research has focused on the role of the layered structure of the vocal folds in influencing phonation onset, wherein the outer "cover" layer is relatively soft and the inner "body" layer is relatively stiff. Recent research, however, suggests that the body-cover (BC) structure over-simplifies actual stiffness distributions by neglecting important spatial variations, such as inferior-superior (IS) and anterior-posterior gradients and smooth transitions in stiffness from one histological layer to another. Herein, we explore sensitivity of phonation onset to stiffness gradients and smoothness. By assuming no a priori stiffness distribution and considering a second-order Taylor series sensitivity analysis of phonation onset pressure with respect to stiffness, we find two general smooth stiffness distributions most strongly influence onset pressure: a smooth stiffness containing aspects of BC differences and IS gradients in the cover, which plays a role in minimizing onset pressure, and uniform increases in stiffness, which raise onset pressure and frequency. While the smooth stiffness change contains aspects qualitatively similar to layered BC distributions used in computational studies, smooth transitions in stiffness result in higher sensitivity of onset pressure than discrete layering. These two general stiffness distributions also provide a simple, low-dimensional, interpretation of how complex variations in VF stiffness affect onset pressure, enabling refined exploration of the effects of stiffness distributions on phonation onset.

Cerebellar granule cell migration and folia development require Mllt11/Af1q/Tcf7c.

The organization of neurons into distinct layers, known as lamination, is a common feature of the nervous system. This process, which arises from the direct coupling of neurogenesis and neuronal migration, plays a crucial role in the development of the cerebellum, a structure exhibiting a distinct folding cytoarchitecture with cells arranged in discrete layers. Disruptions to neuronal migration can lead to various neurodevelopmental disorders, highlighting the significance of understanding the molecular regulation of lamination. We report a role Mllt11/Af1q/Tcf7c (myeloid/lymphoid or mixed-lineage leukemia; translocated to chromosome 11/All1 fused gene from chromosome 1q, also known as Mllt11 transcriptional cofactor 7; henceforth referred to Mllt11) in the migration of cerebellar granule cells (GCs). We now show that Mllt11 plays a role in both the tangential and radial migration of GCs. Loss of Mllt11 led to an accumulation of GC precursors in the rhombic lip region and a reduction in the number of GCs successfully populating developing folia. Consequently, this results in smaller folia and an overall reduction in cerebellar size. Furthermore, analysis of the anchoring centers reveals disruptions in the perinatal folia cytoarchitecture, including alterations in the Bergmann glia fiber orientation and reduced infolding of the Purkinje cell plate. Lastly, we demonstrate that Mllt11 interacts with non-muscle myosin IIB (NMIIB) and Mllt11 loss-reduced NMIIB expression. We propose that the dysregulation of NMIIB underlies altered GC migratory behavior. Taken together, the findings reported herein demonstrate a role for Mllt11 in regulating neuronal migration within the developing cerebellum, which is necessary for its proper neuroanatomical organization.

Gradient-based surface nuclear magnetic resonance for groundwater investigation

In medical magnetic resonance imaging, spatial localization (imaging) is based upon the application of controlled magnetic field gradients on top of the main magnetic field to spatially modulate the frequency and/or phase of the nuclear magnetic resonance (NMR) signal across the volume of investigation. In this work, we have applied similar physical principles to produce controlled magnetic field gradients during surface NMR-based groundwater investigations. In this approach, a gradient pulse of variable amplitude or duration is applied immediately after the excitation pulse to cause predictable phase encoding of the NMR signal as a function of depth. This approach is also applicable to emerging surface NMR detection methods that use a prepolarization field with fast nonadiabatic turn-off to generate detectable NMR signals from the shallow subsurface. In this case, the gradient pulse is applied after terminating the prepolarization field and provides a heretofore unavailable means of localizing the NMR response as a function of depth. The application of gradients can also be combined with tip-angle-based modulation to yield higher imaging resolution than can be achieved through either gradient- or tip-angle-based imaging alone. We implemented this new gradient-based capability into a surface NMR gradient generation accessory that is compatible with the GMR-Flex instrument and developed surface NMR-specific forward modeling and linear inverse models. We validated the accuracy of this novel gradient-based sNMR technology using computer simulations, experiments using a small pool filled with a discrete layer of bulk water, and field experiments at well-characterized groundwater test sites along Ebey Island, WA, and Larned, KS. The gradient-based sNMR imaging observations were compared with high-resolution direct push NMR results observed at these sites. The results of computer simulations and field experiments indicate improvements in both the detection (signal-to-noise ratio) and spatial resolution of shallow subsurface water content using gradient-based surface NMR, compared with traditional surface NMR imaging methods.

Lightweight polypropylene/BaTiO3 composite foams with tunable dielectric constant

Lightweight dielectric foam materials with tunable dielectric constant of 2–1 have broad application prospects in the field of Luneburg lens. Expandable polystyrene (EPS) foam is commonly used for fabricating discrete dielectric layers of Luneburg lens, while its temperature resistance and mechanical properties are poor. EPS foam with dielectric constant of >1.5 is also difficult to prepare because of its low expansion ratio. In this work, choosing polypropylene (PP) with better temperature resistance and mechanical properties as polymer matrix, PP/BaTiO3 composite foams are fabricated by subcritical CO2 batch foaming and steam-chest molding. Through the dual regulation of expansion ratio and mold-opening distance, the dielectric constant of PP/BaTiO3 foams can be tunable from ∼1.19 to ∼1.91, with the density increasing from ∼0.14 to ∼0.59 g/cm3. Compared with EPS foams, PP/BaTiO3 foams have lower density under the similar dielectric constant, indicating the weight reduction of polymer dielectric foam materials by introducing high dielectric fillers.

Mast cell distribution and prevalence in the murine urinary bladder

BackgroundMast cells have been implicated in the pathology of various urinary bladder disorders. However, the distribution of mast cells throughout urinary bladder tissue remains uncertain despite mast cell prevalence being relatively well-defined. Using a mouse tissue model, this study aims to characterise the prevalence and distribution of mast cells throughout the urinary bladder.MethodsBladder tissues were collected from six C57BL/6J female mice. Mast cell prevalence was quantified by flow cytometry, based on the expression of the following characteristic markers: CD45, CD117 and FcɛRIα. The toluidine blue stain assessed mast cell distribution, size, and proximity to vasculature. A repeated measures one-way ANOVA was used to evaluate the density of mast cells between the discrete layers of the urinary bladder, and an ordinary one-way ANOVA was used to assess potential differences between mast cell size across the urinary bladder wall.ResultsIt was determined that mast cells compose less than 4% of all live leukocytes in the urinary bladder. They were also found to be more prominent in the lamina propria and detrusor muscle layers, compared to the urothelium and adventitia. In addition, 20.89% of mast cells were located near vasculature, which may be an important factor in consideration of their function and potential to contribute to various bladder pathologies, such as cystitis or overactive bladder.ConclusionThese findings provide a baseline understanding of mast cell prevalence and distribution throughout the urinary bladder.

EOSA-Net: A deep learning framework for enhanced multi-class skin cancer classification using optimized convolutional neural networks

Most cancer diagnoses are inevitably fatal, and an increasing number of genetic and metabolic abnormalities are being identified by experts as the disease’s cause. Every organ in the body is susceptible to the invasion and spread of cancerous cells, which pose a major threat to health. So, considering the frequency of skin cancer is rising quickly, it is recommended to undergo a screening. The multi-class approach of deep learning (DL) may provide more comprehensive data and insights into the underlying causes and risk factors of all different skin cancer classes, which can aid in developing fresh therapies or preventative measures. DL is one of the best methods for rapidly and reliably detecting skin cancer. The ISIC 2018 and 2019 public datasets were used in the present research to identify and detect multi-class skin cancer by employing an Improved canny edge for detection and an optimized deep learning technique convolution neural network (CNN) for classification. To enhance the detection of the affected area from the input image, the pre-processing stage is conducted using an improved canny edge detector. The control parameters for the canny edge detector are selected using the coronavirus optimization algorithm (CVOA), and the proposed model has three discrete hidden layers, each with a corresponding channel size (16, 32, and 64). A learning version of the Ebola Optimization Search Algorithm (EOSA) with a learning rate of 0.001 is included in the suggested model. Both the mathematical and propagation models were modified to create the new metaheuristic technique. The proposed EOSA algorithm has been brought towards as a robust mechanism for achieving a balance between exploration and exploitation to determine the optimal solution to problems. With an accuracy of 99%, the proposed model performs the best when classifying the skin lesions in the ISIC dataset into eight categories. The results obtained are superior to the present system of skin cancer categorization.