scholarly journals Insights to enhance the examination of tool marks in human cartilage

2021 ◽  
Author(s):  
Matthias Weber ◽  
Anja Niehoff ◽  
Markus A. Rothschild
Keyword(s):  
Light Microscope ◽  
Cross Correlation ◽  
Costal Cartilage ◽  
Correlation Coefficients ◽  
Human Cartilage ◽  
Cut Marks ◽  
Tool Marks ◽  
The Cross ◽  
Cleaning Methods ◽  
The Individual

AbstractThis work deals with the examination of tool marks in human cartilage. We compared the effectiveness of several cleaning methods on cut marks in porcine cartilage. The method cleaning by multiple casts achieved the significantly highest scores (P = 0.02). Furthermore, we examined the grain-like elevations (dots) located on casts of cut cartilage. The results of this study suggest that the casting material forms these dots when penetrating cartilage cavities, which are areas where the strong collagen fibres leave space for the chondrocytes. We performed fixation experiments to avoid this, without success. In addition, 31 casting materials were compared regarding contrast under light-microscope and 3D tool marks scanner. Under the light-microscope, brown materials achieved significantly higher values than grey (P = 0.02) or black (P = 0.00) whereas under the 3D scanner, black materials reached higher contrast values than grey (P = 0.04) or brown (P = 0.047). To compare the accuracy and reproducibility of 6 test materials for cartilage, we used 10 knives to create cut marks that were subsequently scanned. During the alignment of the individual signals of each mark, the cross-correlation coefficients (Xmax) and lags (LXmax) were calculated. The signals of the marks in agarose were aligned with significantly fewer lags and achieved significantly higher cross-correlation coefficients compared to all tested materials (both P = 0.00). Moreover, we determined the cross-correlation coefficients (XC) for known-matches (KM) per material. Agarose achieved significantly higher values than AccuTrans®, Clear Ballistics™, and gelatine (all P = 0.00). The results of this work provide valuable insights for the forensic investigation of marks in human costal cartilage.

scholarly journals Advancements of the examination of tool marks in human cartilage

2021 ◽  
Author(s):  
Matthias Weber ◽  
Anja Niehoff ◽  
Markus A. Rothschild
Keyword(s):  
Light Microscope ◽  
Cross Correlation ◽  
Costal Cartilage ◽  
Correlation Coefficients ◽  
Human Cartilage ◽  
Cut Marks ◽  
Tool Marks ◽  
The Cross ◽  
Cleaning Methods ◽  
The Individual

Abstract This work deals with the examination of tool marks in human cartilage. We compared the effectiveness of several cleaning methods on cut marks in porcine cartilage. The method cleaning by multiple casts achieved the significantly highest scores (P = 0.02). Furthermore, we examined the grain-like elevations (dots) located on casts of cut cartilage. The results of this study suggest that the casting material forms these dots when penetrating cartilage cavities, which are areas where the strong collagen fibers leave space for the chondrocytes. We performed fixation experiments to avoid this, without success. In addition, 31 casting materials were compared regarding contrast under light-microscope and 3D tool marks scanner. Under the light-microscope, brown materials achieved significantly higher values than grey (P = 0.02) or black (P = 0.00) whereas under the 3D scanner, black materials reached higher contrast values than grey (P = 0.04) or brown (P = 0.047). To compare the accuracy and reproducibility of 6 test materials for cartilage, we used 10 knives to create cut marks that were subsequently scanned. During the alignment of the individual signals of each mark, the cross-correlation coefficients (Xmax) and lags (LXmax) were calculated. The signals of the marks in agarose were aligned with significantly fewer lags and achieved significantly higher cross-correlation coefficients compared to all tested materials (both P = 0.00). Moreover, we determined the cross-correlation coefficients (XC) for known-matches (KM) per material. Agarose achieved significantly higher values than AccuTrans®, Clear Ballistics™, and gelatine (all P = 0.00). The results of this work provide valuable insights for the forensic investigation of marks in human costal cartilage.

Dynamic Behavior and Synchronization of an Automobile as a Complex System

2014 ◽  
Author(s):  
Claudia A. González-Cruz ◽  
Juan C. Jáuregui-Correa ◽  
Carlos S. López-Cajún ◽  
Mihir Sen
Keyword(s):  
Complex System ◽  
Wavelet Transforms ◽  
Cross Correlation ◽  
Correlation Coefficients ◽  
The Other ◽  
Accelerometer Data ◽  
Hilbert Transforms ◽  
The Road ◽  
The Individual ◽  
Analytical Tools

A complex system is composed of many interacting components, but the behavior of the system as a whole can be quite different from that of the individual components. An automobile is an example of a common mechanical system composed of a large number of individual components that are mechanically connected in some way and hence transmit vibrations to each other. This paper proposes a variety of inter-related analytical tools for the study of experimental data from such systems. In this work, experimental results of accelerometer data acquired at two locations in the automobile for two different kinds of tests are analyzed. One test is the response to impact on a stationary vehicle, and the other is the road-response to the vehicle being driven on a flat road at different speeds. Signals were processed via Fourier and wavelet transforms, cross-correlation coefficients were computed, and Hilbert transforms and Kuramoto order parameters were determined. A new parameter representing synchronization deficit is introduced. There is indeed some degree of synchronization that can be quantified between the accelerations measured at these two locations in the vehicle.

AN ANALOG SEISMlC CORRELATOR

Geophysics ◽  
1961 ◽  
Vol 26 (3) ◽  
pp. 298-308 ◽  
Author(s):  
F. N. Tullos ◽  
L. C. Cummings
Keyword(s):  
Seismic Data ◽  
Cross Correlation ◽  
Correlation Coefficients ◽  
Analog Computer ◽  
Signal Power ◽  
Arrival Times ◽  
Data Points ◽  
The Cross ◽  
Correlation Process ◽  
Total Average

An analog computer has been built to compute the cross‐correlation coefficients of multi‐trace seismograms. The evaluation program has shown that the computer has greater accuracy than is normally required to compute the cross‐correlation functions of short samples of data. Points on the correlation curves are computed and plotted at the rate of approximately 50 points per minute. Scanning is in difference of arrival times (Δt) across the record, with increments of [Formula: see text] to 16 millisecond. The correlation process is completely automatic with the exception of normalization, which is approximated by holding the total average signal power constant with a ganged attenuator. Analysis of synthetic and actual seismic data indicates that the correlation will be an interpretational aid in areas where the data are poor.

Research on Feature Recognition of Nuclear Power Equipment Based on the Optimal Wavelet Basis

2013 ◽  
Author(s):  
Bin Li ◽  
Hong Xia
Keyword(s):  
Nuclear Power ◽  
Cross Correlation ◽  
Feature Recognition ◽  
Correlation Coefficients ◽  
Frequency Component ◽  
Discrete Wavelet ◽  
Wavelet Basis ◽  
Cracked Rotor ◽  
Coolant Pump ◽  
The Cross

Touching upon that the crack fault of the rotor may occur after the reactor coolant pump (RCP) has operated a long time, the fault feature can be identified effectively by the method of the wavelet analysis. In this research, based on the simulation signal of crack fault and the method of discrete wavelet transform (DWT), the cross-correlation coefficients between the fault signal and the different wavelet basis which are selected from the wavelet basis library can be computed. After confirming the maximum of the cross-correlation coefficients, the optimal wavelet basis applied to the fault signal of the cracked rotor will be found. And the main frequency component of the fault feature is recognized by use of the wavelet packet transform (WPT) based on the optimal wavelet basis. The results of simulation illustrate that the wavelet basis selected by the maximum cross-correlation coefficients can become the optimal wavelet basis, and the fault feature of the cracked rotor can be recognized effectively.

ON THE APPLICATION OF THE CROSS-CORRELATIONS IN THE CHINESE FUND MARKET: DESCRIPTIVE PROPERTIES AND SCALING BEHAVIORS

2011 ◽  
Vol 14 (01) ◽  
pp. 97-109
Author(s):  
WEIBING DENG ◽  
WEI LI ◽  
XU CAI ◽  
QIUPING A. WANG
Keyword(s):  
Correlation Matrix ◽  
Cross Correlation ◽  
Matrix Theory ◽  
Factorial Moment ◽  
Correlation Coefficients ◽  
Mean Value ◽  
Distribution Of Eigenvalues ◽  
Cross Correlations ◽  
The Cross ◽  
Simple Definition

On the basis of the relative daily logarithmic returns of 88 different funds in the Chinese fund market (CFM) from June 2005 to October 2009, we construct the cross-correlation matrix of the CFM. It is shown that the logarithmic returns follow an exponential distribution, which is commonly shared by some emerging markets. We hereby analyze the statistical properties of the cross-correlation coefficients in different time periods, such as the distribution, the mean value, the standard deviation, the skewness and the kurtosis. By using the method of the scaled factorial moment, we observe the intermittence phenomenon in the distribution of the cross-correlation coefficients. Also by employing the random matrix theory (RMT), we find a few isolated large eigenvalues of the cross-correlation matrix, and the distribution of eigenvalues exhibits the power-law tails. Furthermore, we study the features of the correlation strength with a simple definition.

Changes in Kinematic Coupling Among the Rearfoot, Midfoot, and Forefoot Segments During Running and Walking

2018 ◽  
Vol 108 (1) ◽  
pp. 45-51 ◽  
Author(s):  
Tomoya Takabayashi ◽  
Mutsuaki Edama ◽  
Erika Yokoyama ◽  
Chiaki Kanaya ◽  
Takuma Inai ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Three Dimensional ◽  
Correlation Coefficients ◽  
Frontal Plane ◽  
Vector Coding ◽  
Kinematic Coupling ◽  
Foot Model ◽  
The Cross ◽  
Coupling Angle ◽  
Rearfoot Eversion

Background: Understanding the concept of kinematic coupling is essential when selecting the appropriate therapeutic strategy and grasping mechanisms for the occurrence of injuries. A previous study reported that kinematic coupling between the rearfoot and shank during running and walking were different. However, because foot mobility involves not only the rearfoot but also the midfoot or forefoot, kinematic coupling is likely to occur among the rearfoot, midfoot, and forefoot segments. We investigated changes in kinematic coupling among the rearfoot, midfoot, and forefoot segments during running and walking. Methods: Ten healthy young men were instructed to run (2.5 ms–1) and walk (1.3 ms–1) on a treadmill at speeds set by the examiner. The three-dimensional joint angles of the rearfoot, midfoot, and forefoot were calculated based on the Leardini foot model Kinematic coupling was evaluated with the absolute value of the cross-correlation coefficients and coupling angles obtained by using a vector coding technique. Results: The cross-correlation coefficient between rearfoot eversion/inversion and midfoot dorsiflexion/plantarflexion was significantly higher during running (r = 0.79) than during walking (r = 0.58), suggesting that running requires stronger kinematic coupling between rearfoot eversion/inversion and midfoot plantarflexion/dorsiflexion than walking. Furthermore, the coupling angle between midfoot eversion/inversion and forefoot eversion/inversion was significantly less during running (30.0°) than during walking (40.7°) (P < .05). Hence, the magnitude of midfoot frontal plane excursion during running was greater than that during walking. Conclusions: Excessive rearfoot eversion during running is likely to lead to excessive midfoot dorsiflexion, and such abnormal kinematic coupling between the rearfoot and midfoot may be associated with mechanisms for the occurrence of injuries.

A METHOD OF DETERMINING CROSS-CORRELATION COEFFICIENTS OF TIME-VARYING SIGNALS

1966 ◽  
Vol 44 (2) ◽  
pp. 415-422
Author(s):  
F. H. Palmer ◽  
G. F. Lyon
Keyword(s):  
Correlation Coefficient ◽  
Input Signal ◽  
Cross Correlation ◽  
Correlation Coefficients ◽  
Time Varying ◽  
Pulse Counting ◽  
Pulse Trains ◽  
The Cross

Pulse-counting techniques allow the cross-correlation coefficient between two time-varying signals to be rapidly evaluated, if the two signals are first converted to pulse trains whose repetition frequencies are proportional to the respective amplitudes. Equipment using this technique is described. Estimates are given of the overall accuracy of the device for various types of input signal and for various signal durations. Provided the depth of modulation of the signals is over 50%, their cross-correlation coefficient may be determined to an accuracy of ± 0.05 for sample lengths of 2 minutes. The application of the system to the determination of cross-correlation coefficients of v.h.f. forward-scattered signals received on spaced antennae is also described.

scholarly journals DrumCorr program for selecting volcanic earthquake multiplets based on cross-correlation analysis

2021 ◽  
Vol 2094 (3) ◽  
pp. 032048
Author(s):  
I A Zavedevkin ◽  
A A Shakirova ◽  
P P Firstov
Keyword(s):  
Seismic Data ◽  
Cross Correlation ◽  
Correlation Coefficients ◽  
Volcanic Earthquake ◽  
Primary Analysis ◽  
Volcanic Earthquakes ◽  
Cross Correlation Analysis ◽  
Wave Forms ◽  
The Cross ◽  
Correlation Detector

Abstract The DrumCorr program based on cross-correlation detection has been developed to identify multiplets of the volcanic earthquakes. The program is implemented in Python 3 and reads ASCII and MiniSEED seismic data formats. The article presents the algorithm of the program, describing the cross-correlation detector and an example of subsequent processing of seismic data. The program was applied to volcanic earthquakes of the «drumbeats» seismic regime and allowed to identify earthquake multiplets characterized by various wave forms. The article presents the algorithm of the program, describing the cross-correlation detector, the features of the weak volcanic earthquakes selection by the STA/LTA method. And the primary analysis of the values of the correlation coefficients with the calculation of their standard errors depending on different signal-to-noise ratios.

scholarly journals Lobster (Panulirus argus) captures and their relation with environmental variables obtained by orbital sensors for Cuban waters (1997-2005)

2008 ◽  
Vol 56 (3) ◽  
pp. 225-237 ◽  
Author(s):  
Regla Duthit Somoza ◽  
Milton Kampel ◽  
Frederico de Moraes Rudorff ◽  
Ronald B. Sousa ◽  
Susana Cobas
Keyword(s):  
Environmental Variables ◽  
Cross Correlation ◽  
Correlation Coefficients ◽  
Panulirus Argus ◽  
Spatial And Temporal Variability ◽  
Wide Field ◽  
Chl A ◽  
Cross Correlation Analysis ◽  
The Cross ◽  
Almost All

Chlorophyll concentrations (Chl a) data obtained from the Sea Viewing Wide Field of View Sensor (SeaWIFS) ocean color monthly images, Sea Surface Temperature (SST) pathfinder data obtained from the Advanced Very High Resolution Radiometer (AVHRR) sensors, and lobster (Panulirus argus) captures at the Cuban shelf were examined in order to analyze their spatial and temporal variability. A cross-correlation analysis was made between the standardized anomalies of the environmental variables (Chl a and SST) and the standardized anomalies of lobster captures for each fishery zones for the period between 1997 and 2005. For the deep waters adjacent to the fishing zones it was not observed a clear Chl a seasonality and on average the lowest values occurred south of the Island. It is with the three years lag that Chl a had the greatest numbers of significant correlation coefficients for almost all fishing zones. However, the cross-correlation coefficients with SST showed higher values with 1,5 year lag at all zones. Since the two environmental variables obtained by satellite sensors (SST and Chl a) influence the lobsters mainly during the planktonic life cycle, the cross-correlation with lobster captures begin to show significant indexes with lags of 1.5 years or more.

scholarly journals On studying relations between time series in climatology

2015 ◽  
Vol 6 (1) ◽  
pp. 389-397 ◽  
Author(s):  
V. Privalsky
Keyword(s):  
Time Series ◽  
Cross Correlation ◽  
Multivariate Time Series ◽  
Correlation Coefficients ◽  
Atlantic Multidecadal Oscillation ◽  
Regression Equations ◽  
Full Time ◽  
The Cross ◽  
Domain Description ◽  
Bivariate Time Series

Abstract. Relationships between time series are often studied on the basis of cross-correlation coefficients and regression equations. This approach is generally incorrect for time series, irrespective of the cross-correlation coefficient value, because relations between time series are frequency-dependent. Multivariate time series should be analyzed in both time and frequency domains, including fitting a parametric (preferably, autoregressive) stochastic difference equation to the time series and then calculating functions of frequency such as spectra and coherent spectra, coherences, and frequency response functions. The example with a bivariate time series "Atlantic Multidecadal Oscillation (AMO) – sea surface temperature in Niño area 3.4 (SST3.4)" proves that even when the cross correlation is low, the time series' components can be closely related to each other. A full time and frequency domain description of this bivariate time series is given. The AMO–SST3.4 time series is shown to form a closed-feedback loop system with a 2-year memory. The coherence between AMO and SST3.4 is statistically significant at intermediate frequencies where the coherent spectra amount up to 55 % of the total spectral densities. The gain factors are also described. Some recommendations are offered regarding time series analysis in climatology.

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