Journal: Materials

Article Title: Numerical Analysis of Fatigue Crack Growth Path and Life Predictions for Linear Elastic Material

doi: 10.3390/ma13153380

Figure Lengend Snippet: Predicted crack growth direction of CTS01: ( a ) current study result, ( b ) experimental and numerical results of , ( c ) BemCracker2D and ( d ) Quebra2D .

Article Snippet: As shown in the figures, the crack growth paths are almost identical to the path predicted experimentally and numerically [ ] and [ ], using boundary element method (BEM) with BemCracker2D software (which is a special purpose educational program for simulating two-dimensional crack growth based on the dual boundary element method, written in C++ with a MATLAB graphic user interface developed by [ , ] and finite element method with Quebra2D (which is a finite element based software developed by [ , ]).

Techniques:

Journal: Materials

Article Title: Numerical Analysis of Fatigue Crack Growth Path and Life Predictions for Linear Elastic Material

doi: 10.3390/ma13153380

Figure Lengend Snippet: Predicted crack growth direction of CTS02: ( a ) current study result, ( b ) experimental and numerical results of , ( c ) BemCracker2D and ( d ) Quebra2D .

Article Snippet: As shown in the figures, the crack growth paths are almost identical to the path predicted experimentally and numerically [ ] and [ ], using boundary element method (BEM) with BemCracker2D software (which is a special purpose educational program for simulating two-dimensional crack growth based on the dual boundary element method, written in C++ with a MATLAB graphic user interface developed by [ , ] and finite element method with Quebra2D (which is a finite element based software developed by [ , ]).

Techniques:

Journal: Materials

Article Title: Numerical Analysis of Fatigue Crack Growth Path and Life Predictions for Linear Elastic Material

doi: 10.3390/ma13153380

Figure Lengend Snippet: Predicted crack growth direction of CTS03: ( a ) current study result, ( b ) experimental and numerical results of , ( c ) BemCracker2D and ( d ) Quebra2D .

Article Snippet: As shown in the figures, the crack growth paths are almost identical to the path predicted experimentally and numerically [ ] and [ ], using boundary element method (BEM) with BemCracker2D software (which is a special purpose educational program for simulating two-dimensional crack growth based on the dual boundary element method, written in C++ with a MATLAB graphic user interface developed by [ , ] and finite element method with Quebra2D (which is a finite element based software developed by [ , ]).

Techniques:

Journal: Materials

Article Title: Numerical Analysis of Fatigue Crack Growth Path and Life Predictions for Linear Elastic Material

doi: 10.3390/ma13153380

Figure Lengend Snippet: Predicted crack growth direction of CTS04: ( a ) current study result, ( b ) experimental and numerical results of , ( c ) BemCracker2D and ( d ) Quebra2D .

Article Snippet: As shown in the figures, the crack growth paths are almost identical to the path predicted experimentally and numerically [ ] and [ ], using boundary element method (BEM) with BemCracker2D software (which is a special purpose educational program for simulating two-dimensional crack growth based on the dual boundary element method, written in C++ with a MATLAB graphic user interface developed by [ , ] and finite element method with Quebra2D (which is a finite element based software developed by [ , ]).

Techniques:

Journal: Cell calcium

Article Title: PunctaSpecks: A Tool for Automated Detection, Tracking, and Analysis of Multiple Types of Fluorescently Labeled Biomolecules

doi: 10.1016/j.ceca.2020.102224

Figure Lengend Snippet: Various steps used by PunctaSpecks for noise removal and puncta identification. (A) Synthetic movie stack containing dynamical activity of objects under investigation (only 5 frames are shown). (B) Maximum intensity profile (MIP) image of the whole movie. (C) Puncta identified by PunctaSpecks using a given algorithm (Otsu in this case) are encircled on the MIP image to ease the visualization and further adjustment of parameters for accurate detection of all puncta. Histograms of the areas (D), mean fluorescence intensity (E) of all puncta, and (F) mean square displacement as a function of time for the mobile puncta.

Article Snippet: We have developed an all-in-one MATLAB-based tool called PunctaSpecks, with a graphical user interface (GUI), that implements algorithms for identifying and characterizing fluorescently labeled objects in time-lapse image stacks.

Techniques: Activity Assay, Fluorescence

Journal: Cell calcium

Article Title: PunctaSpecks: A Tool for Automated Detection, Tracking, and Analysis of Multiple Types of Fluorescently Labeled Biomolecules

doi: 10.1016/j.ceca.2020.102224

Figure Lengend Snippet: Verifying the performance of PunctaSpecks using synthetic data. (A) Frame-by-frame signal to noise ratio of the synthetic data at two different noise levels. Histograms of areas (B), mean open times (log scale) (C), and dwell times (log scale) (D) of all puncta with true (blue) and those from PunctaSpecks at noise levels 25 (green) and 150 (red). (E) Histogram of mean intensities of all puncta with true values (blue) and those from PunctaSpecks at noise level of 25 (green) and 150 (red). The actual trajectory of a sample mobile punctum (blue) and the one identified by PunctaSpecks at noise level of 150 (red) (F).

Article Snippet: We have developed an all-in-one MATLAB-based tool called PunctaSpecks, with a graphical user interface (GUI), that implements algorithms for identifying and characterizing fluorescently labeled objects in time-lapse image stacks.

Techniques: