scholarly journals Micromechanical properties of beech cell wall measured by micropillar compression test and nanoindentation mapping

Holzforschung ◽  
2020 ◽  
Vol 74 (9) ◽  
pp. 899-904
Author(s):  
Petr Klímek ◽  
Václav Sebera ◽  
Darius Tytko ◽  
Martin Brabec ◽  
Jaroslav Lukeš
Keyword(s):  
Cell Wall ◽  
Yield Stress ◽  
Compression Test ◽  
State Of The Art ◽  
Middle Lamella ◽  
Uniaxial Stress ◽  
Wood Structure ◽  
Micropillar Compression ◽  
The Mean ◽  
Insight Into

AbstractWood exhibits very different behavior and properties at different scales. One important scale is the cell wall (CW) that is commonly tested by nanoindentation. Common nanoindentation provides important insight into the material but has limitations because it does not apply uniaxial stress and provides data from single spots. Therefore, the aim was to examine beech CW using two state-of-the-art techniques: micropillar compression (MCo) and nanoindentation mapping (NIP). The mean strength of the beech CW was found to be about 276 MPa and the mean yield stress was 183 MPa. These values were higher than those in most cited literature, which was attributed to the fact that libriform fibers from beech late wood were measured. Mean E obtained from MCo was about 7.95 GPa, which was lower than the values obtained on a macrolevel and about 61% of the value obtained from NIP. NIP also showed that E of the CW around the middle lamella (ML) was about 64% of the value at the location attributed to the S2 layer. Lower E from MCo may be caused by sinking of the micropillar into the wood structure under the load. Failure of the micropillars showed gradual collapse into themselves, with debonding at the S3 layer or the MLs.

Estimation of plant cell wall thickness and cell size by image skeletonization

1993 ◽  
Vol 120 (3) ◽  
pp. 279-287 ◽  
Author(s):  
A. J. Travis ◽  
S. D. Murison ◽  
A. Chesson
Keyword(s):  
Cell Wall ◽  
Image Analysis ◽  
Wall Thickness ◽  
Plant Cell Wall ◽  
Middle Lamella ◽  
Binary Image ◽  
Cell Wall Thickness ◽  
Wall Material ◽  
Connected Set ◽  
The Mean

SUMMARYA system for automatically measuring the mean cell-wall thickness in a user-defined area of plant tissue has been developed using image analysis. The digitized grey-level image of a tissue section is first segmented using a histogram-partitioning algorithm. The resulting binary image is then repeatedly thinned until the minimum connected set of pixels, or ‘skeleton’, remains. A nearestneighbour length estimator is used to calculate the total length of the skeleton which approximates to the location of the middle lamella in the original section. The length of the skeleton and the number of nodes it contains are used to estimate the mean cell radius, and mean cell-wall thickness using the area of cell-wall material in the segmented binary image. The method has been used to estimate mean cell-wall thickness along a newly extended Zea mays internode, and the results are compared to measurements obtained manually using a micrometer ‘line’. The techniques of rapidly assessing mean cell-wall thickness and cell dimensions using image analysis are needed to assess how much of the variation in nutritive value between forage cultivars can be ascribed to changes in cell-wall chemistry and how much to anatomical differences.

Silicification of wood-cell walls

1994 ◽  
Vol 52 ◽  
pp. 428-429
Author(s):  
S. E. Keckler ◽  
D. M. Dabbs ◽  
N. Yao ◽  
I. A. Aksay
Keyword(s):  
Electron Microscopy ◽  
Cell Wall ◽  
Cell Walls ◽  
Lignin Content ◽  
Resin Composite ◽  
Middle Lamella ◽  
Cellulose Fibers ◽  
Complex Structures ◽  
Rich Region ◽  
Inorganic Precursors

Cellular organic structures such as wood can be used as scaffolds for the synthesis of complex structures of organic/ceramic nanocomposites. The wood cell is a fiber-reinforced resin composite of cellulose fibers in a lignin matrix. A single cell wall, containing several layers of different fiber orientations and lignin content, is separated from its neighboring wall by the middle lamella, a lignin-rich region. In order to achieve total mineralization, deposition on and in the cell wall must be achieved. Geological fossilization of wood occurs as permineralization (filling the void spaces with mineral) and petrifaction (mineralizing the cell wall as the organic component decays) through infiltration of wood with inorganics after growth. Conversely, living plants can incorporate inorganics into their cells and in some cases into the cell walls during growth. In a recent study, we mimicked geological fossilization by infiltrating inorganic precursors into wood cells in order to enhance the properties of wood. In the current work, we use electron microscopy to examine the structure of silica formed in the cell walls after infiltration of tetraethoxysilane (TEOS).

Some Explicit Results for the Mean Spherical Approximation for Mixtures of Yukawa Fluids

2008 ◽  
Vol 73 (3) ◽  
pp. 424-438 ◽  
Author(s):  
Douglas J. Henderson ◽  
Osvaldo H. Scalise
Keyword(s):  
Integral Equation ◽  
Spherical Approximation ◽  
Mean Spherical Approximation ◽  
Inverse Temperature ◽  
Temperature Expansion ◽  
Yukawa Fluid ◽  
The Mean ◽  
Full Solution ◽  
Insight Into ◽  
Reasonable Model

The mean spherical approximation (MSA) is of interest because it produces an integral equation that yields useful analytical results for a number of fluids. One such case is the Yukawa fluid, which is a reasonable model for a simple fluid. The original MSA solution for this fluid, due to Waisman, is analytic but not explicit. Ginoza has simplified this solution. However, Ginoza's result is not quite explicit. Some years ago, Henderson, Blum, and Noworyta obtained explicit results for the thermodynamic functions of a single-component Yukawa fluid that have proven useful. They expanded Ginoza's result in an inverse-temperature expansion. Even when this expansion is truncated at fifth, or even lower, order, this expansion is nearly as accurate as the full solution and provides insight into the form of the higher-order coefficients in this expansion. In this paper Ginoza's implicit result for the case of a rather special mixture of Yukawa fluids is considered. Explicit results are obtained, again using an inverse-temperature expansion. Numerical results are given for the coefficients in this expansion. Some thoughts concerning the generalization of these results to a general mixture of Yukawa fluids are presented.

scholarly journals A Deep Learning Approach to Predict Autism Spectrum Disorder Using Multisite Resting-State fMRI

2021 ◽  
Vol 11 (8) ◽  
pp. 3636
Author(s):  
Faria Zarin Subah ◽  
Kaushik Deb ◽  
Pranab Kumar Dhar ◽  
Takeshi Koshiba
Keyword(s):  
Autism Spectrum Disorder ◽  
Resting State ◽  
State Of The Art ◽  
Resting State Fmri ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Bootstrap Analysis ◽  
Proposed Model ◽  
Art Methods ◽  
The Mean

Autism spectrum disorder (ASD) is a complex and degenerative neuro-developmental disorder. Most of the existing methods utilize functional magnetic resonance imaging (fMRI) to detect ASD with a very limited dataset which provides high accuracy but results in poor generalization. To overcome this limitation and to enhance the performance of the automated autism diagnosis model, in this paper, we propose an ASD detection model using functional connectivity features of resting-state fMRI data. Our proposed model utilizes two commonly used brain atlases, Craddock 200 (CC200) and Automated Anatomical Labelling (AAL), and two rarely used atlases Bootstrap Analysis of Stable Clusters (BASC) and Power. A deep neural network (DNN) classifier is used to perform the classification task. Simulation results indicate that the proposed model outperforms state-of-the-art methods in terms of accuracy. The mean accuracy of the proposed model was 88%, whereas the mean accuracy of the state-of-the-art methods ranged from 67% to 85%. The sensitivity, F1-score, and area under receiver operating characteristic curve (AUC) score of the proposed model were 90%, 87%, and 96%, respectively. Comparative analysis on various scoring strategies show the superiority of BASC atlas over other aforementioned atlases in classifying ASD and control.

scholarly journals Significance of Mast Cell Formed Extracellular Traps in Microbial Defense

2021 ◽  
Author(s):  
Daniel Elieh Ali Komi ◽  
Wolfgang M. Kuebler
Keyword(s):  
State Of The Art ◽  
Extracellular Dna ◽  
Cellular Mechanisms ◽  
Extracellular Traps ◽  
Synthetic Chemicals ◽  
Dna Strands ◽  
Associated Proteins ◽  
Microbial Defense ◽  
And Function ◽  
Insight Into

AbstractMast cells (MCs) are critically involved in microbial defense by releasing antimicrobial peptides (such as cathelicidin LL-37 and defensins) and phagocytosis of microbes. In past years, it has become evident that in addition MCs may eliminate invading pathogens by ejection of web-like structures of DNA strands embedded with proteins known together as extracellular traps (ETs). Upon stimulation of resting MCs with various microorganisms, their products (including superantigens and toxins), or synthetic chemicals, MCs become activated and enter into a multistage process that includes disintegration of the nuclear membrane, release of chromatin into the cytoplasm, adhesion of cytoplasmic granules on the emerging DNA web, and ejection of the complex into the extracellular space. This so-called ETosis is often associated with cell death of the producing MC, and the type of stimulus potentially determines the ratio of surviving vs. killed MCs. Comparison of different microorganisms with specific elimination characteristics such as S pyogenes (eliminated by MCs only through extracellular mechanisms), S aureus (removed by phagocytosis), fungi, and parasites has revealed important aspects of MC extracellular trap (MCET) biology. Molecular studies identified that the formation of MCET depends on NADPH oxidase-generated reactive oxygen species (ROS). In this review, we summarize the present state-of-the-art on the biological relevance of MCETosis, and its underlying molecular and cellular mechanisms. We also provide an overview over the techniques used to study the structure and function of MCETs, including electron microscopy and fluorescence microscopy using specific monoclonal antibodies (mAbs) to detect MCET-associated proteins such as tryptase and histones, and cell-impermeant DNA dyes for labeling of extracellular DNA. Comparing the type and biofunction of further MCET decorating proteins with ETs produced by other immune cells may help provide a better insight into MCET biology in the pathogenesis of autoimmune and inflammatory disorders as well as microbial defense.

Towards Interconnected Blockchains

2021 ◽  
Vol 54 (7) ◽  
pp. 1-39
Author(s):  
Ankur Lohachab ◽  
Saurabh Garg ◽  
Byeong Kang ◽  
Muhammad Bilal Amin ◽  
Junmin Lee ◽  
...  
Keyword(s):  
State Of The Art ◽  
The State ◽  
Future Research ◽  
Missing Link ◽  
Layered Architecture ◽  
Blockchain Technology ◽  
Wide Scale ◽  
Effective Development ◽  
Insight Into ◽  
Game Changer

Unprecedented attention towards blockchain technology is serving as a game-changer in fostering the development of blockchain-enabled distinctive frameworks. However, fragmentation unleashed by its underlying concepts hinders different stakeholders from effectively utilizing blockchain-supported services, resulting in the obstruction of its wide-scale adoption. To explore synergies among the isolated frameworks requires comprehensively studying inter-blockchain communication approaches. These approaches broadly come under the umbrella of Blockchain Interoperability (BI) notion, as it can facilitate a novel paradigm of an integrated blockchain ecosystem that connects state-of-the-art disparate blockchains. Currently, there is a lack of studies that comprehensively review BI, which works as a stumbling block in its development. Therefore, this article aims to articulate potential of BI by reviewing it from diverse perspectives. Beginning with a glance of blockchain architecture fundamentals, this article discusses its associated platforms, taxonomy, and consensus mechanisms. Subsequently, it argues about BI’s requirement by exemplifying its potential opportunities and application areas. Concerning BI, an architecture seems to be a missing link. Hence, this article introduces a layered architecture for the effective development of protocols and methods for interoperable blockchains. Furthermore, this article proposes an in-depth BI research taxonomy and provides an insight into the state-of-the-art projects. Finally, it determines possible open challenges and future research in the domain.

A reduced-peak equivalence for queues with a mixture of light-tailed and heavy-tailed input flows

2003 ◽  
Vol 35 (03) ◽  
pp. 793-805 ◽  
Author(s):  
Sem Borst ◽  
Bert Zwart
Keyword(s):  
Service Rate ◽  
Opposite Case ◽  
Peak Rate ◽  
Workload Distribution ◽  
The Mean ◽  
Heavy Tailed ◽  
Insight Into

We determine the exact large-buffer asymptotics for a mixture of light-tailed and heavy-tailed input flows. Earlier studies have found a ‘reduced-load equivalence’ in situations where the peak rate of the heavy-tailed flows plus the mean rate of the light-tailed flows is larger than the service rate. In that case, the workload is asymptotically equivalent to that in a reduced system, which consists of a certain ‘dominant’ subset of the heavy-tailed flows, with the service rate reduced by the mean rate of all other flows. In the present paper, we focus on the opposite case where the peak rate of the heavy-tailed flows plus the mean rate of the light-tailed flows is smaller than the service rate. Under mild assumptions, we prove that the workload distribution is asymptotically equivalent to that in a somewhat ‘dual’ reduced system, multiplied by a certain prefactor. The reduced system now consists of only the light-tailed flows, with the service rate reduced by the peak rate of the heavy-tailed flows. The prefactor represents the probability that the heavy-tailed flows have sent at their peak rate for more than a certain amount of time, which may be interpreted as the ‘time to overflow’ for the light-tailed flows in the reduced system. The results provide crucial insight into the typical overflow scenario.

scholarly journals Contour Detection for Fibre of Preserved Szechuan Pickle Based on Dilated Convolution

2019 ◽  
Vol 9 (13) ◽  
pp. 2684 ◽  
Author(s):  
Hongyang Li ◽  
Lizhuang Liu ◽  
Zhenqi Han ◽  
Dan Zhao
Keyword(s):  
Edge Detection ◽  
State Of The Art ◽  
Contour Detection ◽  
Experimental Results ◽  
Contour Method ◽  
Class Differences ◽  
Dilated Convolution ◽  
The Mean ◽  
Art Performance

Peeling fibre is an indispensable process in the production of preserved Szechuan pickle, the accuracy of which can significantly influence the quality of the products, and thus the contour method of fibre detection, as a core algorithm of the automatic peeling device, is studied. The fibre contour is a kind of non-salient contour, characterized by big intra-class differences and small inter-class differences, meaning that the feature of the contour is not discriminative. The method called dilated-holistically-nested edge detection (Dilated-HED) is proposed to detect the fibre contour, which is built based on the HED network and dilated convolution. The experimental results for our dataset show that the Pixel Accuracy (PA) is 99.52% and the Mean Intersection over Union (MIoU) is 49.99%, achieving state-of-the-art performance.

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