A new mathematical equation characterizing the compression of pharmaceutical materials is presented. This equation presumed that the rate of change of the compressible volume of powder with respect to the pressure is proportional to the compressible volume. The new model provided a good fit to several model substances employing non-linear regression techniques. The validity of the model had been verified with experimental results of various pharmaceutical powders according to the Akaikes informatics criterion (AIC) and the sum of squared deviations (SS). The parameter of the new model might reflect quantitatively the fundamental compression behaviors of the powders. It had demonstrated that the proposed model could well predict the compaction characteristics of solid particles like the Kawakita model.
Compressive Strength ; Nonlinear Dynamics ; Powders ; chemistry ; Pressure

A modelling scheme for the stress analysis taking into account load transfer characteristics of the osseointegrated interfaces between dental implant and surrounding alveolar bone was investigated. Main aim was to develop a more realistic simulation methodology for the load transfer at the interfaces than the prefect bonding assumption at the interfaces which might end up the reduced level in the stress result. In the present study, characteristics of osseointegrated bone/implant interfaces was modelled with material nonlinearity assumption. Bones at the interface were given different stiffness properties as functions of stresses. Six different models, i.e. tens0, tens20, tens40, tens60, tens80, and tens100 of which the tensile moduli of the bones forming the bone/implant interfaces were specified from 0, 20, 40, 60, 80, and 100 percents, respectively, of the compressive modulus were analysed. Comparisons between each model were made to study the effect of the tensile load carrying abilities, i.e. the effectivity of load transfer, of interfacial bones on the stress distribution. Results of the present study showed significant differences in the bone stresses across the interfaces. The peak stresses, however, were virtually the same regardless of the difference in the effectivity of load transfer, indicating the conventional linear modelling scheme which assumes perfect bonding at the bone/implant interface can be used without causing significant errors in the stress levels.
Dental Implants* ; Lifting ; Linear Models ; Nonlinear Dynamics*

The aim of this study was to produce a simple and inexpensive technique for estimating the obturator foramen area (OFA) from young calves based on the hypothesis that OFA can be extrapolated from simple linear measurements. Three linear measurements - dorsoventral height, craneocaudal width and total perimeter of obturator foramen - were obtained from 55 bovine hemicoxae. Different algorithms for determining OFA were then produced with a regression analysis (curve fitting) and statistical analysis software. The most simple equation was OFA (mm2) = [3,150.538 + (36.111*CW)] - [147,856.033/DH] (where CW = craneocaudal width and DH = dorsoventral height, both in mm), representing a good nonlinear model with a standard deviation of error for the estimate of 232.44 and a coefficient of multiple determination of 0.846. This formula may be helpful as a repeatable and easily performed estimation of the obturator foramen area in young bovines. The area of the obturator foramen magnum can thus be estimated using this regression formula.
Biometry ; Foramen Magnum ; Nonlinear Dynamics ; Osteology

Edema is a common pathological symptom, but its development mechanism is unknown. Based on the bearings of pressure upon interstitium structure and substantial exchange between plasma and interstitial fluid, a dymamics model describing the development of edema was set up. The model's theoretical results showed that the variations of interstitium pressure and structure due to imbalance of substantial exchange may lead to the development of edema, which is in accordance with recent clinical researches. Discussions on the dynamic mechanism of the development of edema proposed that the best way to prevent edema is instituting treatment before the interstitial structure being destroyed.
Edema ; physiopathology ; Humans ; Models, Biological ; Nonlinear Dynamics

The use of non-invasive blood glucose detection techniques can help diabetic patients to alleviate the pain of intrusive detection, reduce the cost of detection, and achieve real-time monitoring and effective control of blood glucose. Given the existing limitations of the minimally invasive or invasive blood glucose detection methods, such as low detection accuracy, high cost and complex operation, and the laser source's wavelength and cost, this paper, based on the non-invasive blood glucose detector developed by the research group, designs a non-invasive blood glucose detection method. It is founded on dual-wavelength near-infrared light diffuse reflection by using the 1 550 nm near-infrared light as measuring light to collect blood glucose information and the 1 310 nm near-infrared light as reference light to remove the effects of water molecules in the blood. Fourteen volunteers were recruited for
Blood Glucose ; Diabetes Mellitus ; Humans ; Nonlinear Dynamics

Electroencephalogram (EEG) is the primary tool in investigation of the brain science. It is necessary to carry out a deepgoing study into the characteristics and information hidden in EEGs to meet the needs of the clinical research. In this paper, we present a wavelet-nonlinear dynamic methodology for analysis of nonlinear characteristic of EEGs and delta, theta, alpha, and beta sub-bands. We therefore studied the effectiveness of correlation dimension (CD), largest Lyapunov exponen, and approximate entropy (ApEn) in differentiation between the interictal EEG and ictal EEG based on statistical significance of the differences. The results showed that the nonlinear dynamic char acteristic of EEG and EEG subbands could be used as effective identification statistics in detecting seizures.
Brain ; physiopathology ; Electroencephalography ; Entropy ; Epilepsy ; physiopathology ; Humans ; Nonlinear Dynamics ; Seizures

Biomedical signal analysis often needs to separate the trend component from the non-trend component to achieve different purposes and applications in signal analysis. This article introduces three kinds of detrending nonlinear component methods used in the process of biomedical signal analysis: wavelet analysis, empirical mode decomposition, smoothness priors approach as well as the application in the separation of the actual biomedical data. The different separation methods should be selected according to different research goals as well as the feature of the signal.
Algorithms ; Nonlinear Dynamics ; Signal Processing, Computer-Assisted ; Wavelet Analysis

Stochastic resonance (SR) is given to a phenomenon that is manifest in nonlinear systems whereby generally feeble input information can be amplified and optimized by the assistance of noise. First, the basic concepts and the characteristic quantities of SR are introduced in this paper. Second, SR in biological system and its applications are reviewed in detail. At last, a summary is presented and the future researches on SR are prospected.
Animals ; Biology ; trends ; Humans ; Models, Theoretical ; Nonlinear Dynamics ; Stochastic Processes

Traditional sample entropy fails to quantify inherent long-range dependencies among real data. Multiscale sample entropy (MSE) can detect intrinsic correlations in data, but it is usually used in univariate data. To generalize this method for multichannel data, we introduced multivariate multiscale entropy into multiscale signals as a reflection of the nonlinear dynamic correlation. But traditional multivariate multiscale entropy has a large quantity of computation and costs a large period of time and space for more channel system, so that it can not reflect the correlation between variables timely and accurately. In this paper, therefore, an improved multivariate multiscale entropy embeds on all variables at the same time, instead of embedding on a single variable as in the traditional methods, to solve the memory overflow while the number of channels rise, and it is more suitable for the actual multivariate signal analysis. The method was tested in simulation data and Bonn epilepsy dataset. The simulation results showed that the proposed method had a good performance to distinguish correlation data. Bonn epilepsy dataset experiment also showed that the method had a better classification accuracy among the five data set, especially with an accuracy of 100% for data collection of Z and S.
Algorithms ; Electroencephalography ; Entropy ; Epilepsy ; diagnosis ; Humans ; Multivariate Analysis ; Nonlinear Dynamics

In intensive care units (ICU) , the occurrence of acute hypotensive episodes (AHE) is the key problem for the clinical research and it is meaningful for clinical care if we can use appropriate computational technologies to predict the AHE. In this study, based on the records of patients in ICU from the MIMIC II clinical data, the chaos signal analysis method was applied to the time series of mean artery pressure, and then the patient's Lyapunov exponent curve was drawn ultimately. The research showed that a curve mutation appeared before AHE symptoms took place. This is powerful and clear basis for AHE determination. It is also expected that this study may offer a reference to research of AHE theory and clinical application.
Humans ; Hypotension ; diagnosis ; Intensive Care Units ; Nonlinear Dynamics ; Software