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Detecting cellular morphological changes through light scattering patterns: comparison of methods
Get PDFSeveral methods, including the azimuthally-averaged angular distribution of the scattered light intensity, two bi-parameter scatter plots and three image texture analysis algorithms of the Haralick features, Laws energy measures, and Gabor filters, are compared for their effectiveness in correlating changes in light scattering patterns from biological cells to variations in their morphological features. A series of analytic cell models with variations in main cell structure and mitochondrial characteristics are created to imitate biological cells of different structural attributes. Numerical simulations of light scattering are performed using the discrete dipole approximation (DDA). Our results show that Gabor filter analysis combined with the biparameter scatter plots can provide significant insight into cellular morphology
Influence of Water and Humidity on Wood Modification with Lactic Acid
Get PDFImpregnation of dry wood with pure lactic acid oligomers (OLAs) followed by heat treatment confers promising properties to wood because of OLA's good diffusion, in-situ polymerization and persistence in cell walls. Treatment provides drastic reduction of the equilibrium moisture content, high dimensional stability and good durability. The presence of water during treatment has been evaluated. Curing of OLA impregnated dry wood in humid atmosphere leads to a strong and global degradation of the material. OLA treatment of wet wood only impacts the water leaching rate negatively. Treatment of dry wood with OLA diluted in water additionally decreases the biological resistance and is not efficient for decreasing hygroscopicity. Treatment of dry wood with lactic acid solution leads to a lower polymerization level but confers good properties
The Mechanical and Crystallographic Evolution of Stipatenacissima Leaves During In-Soil Biodegradation
Get PDFThe in-soil biodegradation of Stipa tenacissima (alfa) leaves was examined. Non-linear mechanical testing was performed at various biodegradation stages. Tensile strength, loading and unloading Young's moduli and dissipation energy decreased with the burial time, whereas plasticity increased. Field-emission scanning electron microscopy (FE-SEM) showed that the fracture cracks propagated in the longitudinal direction in the raw material, resulting in a fracture mode consisting of a mixture of middle lamella delamination and fiber pull-out. In contrast, the cracks were perpendicular to the stem axis in the biodegraded material, demonstrating an important strength loss of the load-bearing fibers. This strength loss was correlated with rapid cellulose degradation. A novel X-ray diffraction (XRD) model was implemented in order to take into account anisotropic size broadening. For the first time, XRD demonstrated the action of biodegradation on unrefined plant tissues under quasi in-situ conditions. Biodegradation induced a progressive loss of crystalline cellulose accompanied with anisotropic crystallite thinning
Reactive Compatibilization of Short-Fiber Reinforced Poly(lactic acid) Biocomposites
Get PDFPoor interfacial adhesion between biobased thermoplastics and natural fibers is recognized as a major drawback for biocomposites. To be applicable for the large-scale production, a simple method to handle is of importance. This work presented poly(lactic acid) (PLA) reinforced with short-fiber and three reactive agents including anhydride and epoxide groups were selected as compatibilizers. Biocomposites were prepared by one-step melt-mixing methods. The influence of reactive agents on mechanical, dynamic mechanical properties and morphology of PLA biocomposites were investigated. Tensile strength and storage modulus of PLA biocomposites incorporated with epoxide-based reactive agent was increased 13.9% and 37.4% compared to non-compatibilized PLA biocomposite, which was higher than adding anhydride-based reactive agent. SEM micrographs and Molau test exhibited an improvement of interfacial fiber-matrix adhesion in the PLA biocomposites incorporated with epoxide-based reactive agent. FTIR revealed the chemical reaction between the fiber and PLA with the presence of epoxide-based reactive agents
Patient-Specific Echo-Based Fluid-Structure Interaction Modeling Study of Blood Flow in the Left Ventricle with Infarction and Hypertension
No full textUnderstanding cardiac blood flow behaviors is of importance for cardiovascular research and clinical assessment of ventricle functions. Patient-specific Echo-based left ventricle (LV) fluid-structure interaction (FSI) models were introduced to perform ventricle mechanical analysis, investigate flow behaviors, and evaluate the impact of myocardial infarction (MI) and hypertension on blood flow in the LV. Echo image data were acquired from 3 patients with consent obtained: one healthy volunteer (P1), one hypertension patient (P2), and one patient who had an inferior and posterior myocardial infarction (P3). The nonlinear Mooney-Rivlin model was used for ventricle tissue with material parameter values chosen to match echo-measure LV volume data. Using the healthy case as baseline, LV with MI had lower peak flow velocity (30% lower at begin-ejection) and hypertension LV had higher peak flow velocity (16% higher at begin-filling). The vortex area (defined as the area with vorticity>0) for P3 was 19% smaller than that of P1. The vortex area for P2 was 12% smaller than that of P1. At peak of filling, the maximum flow shear stress (FSS) for P2 and P3 were 390% higher and 63% lower than that of P1, respectively. Meanwhile, LV stress and strain of P2 were 41% and 15% higher than those of P1, respectively. LV stress and strain of P3 were 36% and 42% lower than those of P1, respectively. In conclusion, FSI models could provide both flow and structural stress/strain information which would serve as the base for further cardiovascular investigations related to disease initiation, progression, and treatment strategy selections. Large-scale studies are needed to validate our findings
AdaBoosting Neural Network for Short-Term Wind Speed Forecasting Based on Seasonal Characteristics Analysis and Lag Space Estimation
No full textHigh accurary in wind speed forcasting remains hard to achieve due to wind’s random distribution nature and its seasonal characteristics. Randomness, intermittent and nonstationary usually cause the portion problem of the wind speed forecasting. Seasonal characteristics of wind speed means that its feature distribution is inconsistent. This typically results that the persistence of excitation for modeling can not be guaranteed, and may severely reduce the possibilities of high precise forecasting model. In this paper, we proposed two effective solutions to solve the problems caused by the randomness and seasonal characteristics of the wind speed. (1) Wavelet analysis is used to extract the robust components of time series and reduce the influence of randomness. (2) Based on the energy distribution about the extracted amplitude and associated frequency, seasonal characteristics of wind speed are analyzed based on self-similarity in periodogram under scales range generated by wavelet transformation. Thus, the original dataset is reasonably divided into subsest which can effectively reflect the seasonal distribution characteristics of wind speed. In addition, two strategies are given to optimal model structure and improve the forecasting accuracy: (1) The forecasting model’s lag space is approximately estimated by the Lipschitz quotient to improve the generality ability of the feedforward neural network. (2) The forecasting accuracy and model robustness are further improved by the wavelet decomposition combined with AdaBoosting neural network. Finally, experimental evaluation based on the dataset from National Renewable Energy Laboratory (NREL) is given to demonstrate the performance of the proposed approach
The Reduced Space Method for Calculating the Periodic Solution of Nonlinear Systems
No full textA hybrid method combined the reduced Sequential Quadratic Programming (SQP) method with the harmonic balance method has been developed to analyze the characteristics of mode localization and internal resonance of nonlinear bladed disks. With the aid of harmonic balance method, the nonlinear equality constraints for the constrained optimization problem are constructed. The reduced SQP method is then utilized to deal with the original constrained optimization problem. Applying the null space decomposition technique to the harmonic balance algebraic equations results in the vanishing of the nonlinear equality constraints and a simple optimization problem involving only upper and lower bound constraints on the optimization variables is formed and solved. Finally, numerical results are given for several test examples to validity the proposed method. The efficiency of the solution method to trace the family of energy dependent nonlinear modes is illustrated. The localization nonlinear normal modes of bladed disks related to various types of internal resonances are explored
Extrapolation Method for Cauchy Principal Value Integral with Classical Rectangle Rule on Interval
No full textIn this paper, the classical composite middle rectangle rule for the computation of Cauchy principal value integral (the singular kernel 1/(x-s)) is discussed. With the density function approximated only while the singular kernel is calculated analysis, then the error functional of asymptotic expansion is obtained. We construct a series to approach the singular point. An extrapolation algorithm is presented and the convergence rate of extrapolation algorithm is proved. At last, some numerical results are presented to confirm the theoretical results and show the efficiency of the algorithms
Modeling the Spike Response for Adaptive Fuzzy Spiking Neurons with Application to a Fuzzy XOR
No full textA spike response model (SRM) based on the spikes generator circuit (SGC) of adaptive fuzzy spiking neurons (AFSNs) is developed. The SRM is simulated in MatlabTM environment. The proposed model is applied to a configuration of a fuzzy exclusive or (fuzzy XOR) operator, as an illustrative example. A description of the comparison of AFSNs with other similar methods is given. The novel method of the AFSNs is used to determine the value of the weights or parameters of the fuzzy XOR, first with dynamic weights or self-tuning parameters that adapt continuously, then with fixed weights obtained after training, finally with fixed weights and a dynamic gain or self-tuning gain for a fine adjustment of amplitude
Diabetic nephropathy, autophagy and proximal tubule protein endocytic transport: A potentially harmful relationship
No full textDiabetic nephropathy (DN) is the most frequent cause of chronic renal failure. Until now, the
pathophysiological mechanisms that determine its development and progression have not yet been elucidated. In the
present study, we evaluate the role of autophagy at early stages of DN, induced in type 2 diabetes mellitus (T2DM)
mouse, and its association with proximal tubule membrane endocytic receptors, megalin and cubilin. In T2DM
animals we observed a tubule-interstitial injury with significantly increased levels of urinary GGT and ALP, but an
absence of tubulointerstitial fibrosis. Kidney proximal tubule cells of T2DM animals showed autophagic vesicles
larger than those observed in the control group, and an increase in the number of these vesicles marked with LBPA
by immunofluorescence. Furthermore, a significant decrease in the ratio of LC3II/LC3I isoforms and in p62 protein
expression in DN affected animals is shown. Finally, we observed a marked increase in urinary albumin and vitamin D
binding-protein levels in T2DM animals as well as a significant decrease in expression of megalin in the renal cortex.
These results indicate an alteration of the tubular endocytic transporters in DN, which could be related to autophagic
dysfunction, which would in turn result in impaired organelle recycling, thus contributing to the progression of this
disease