Development of a micro-extruder with vibration mode for microencapsulation of human keratinocytes in calcium alginate

Microencapsulation is a promising technique to form microtissues. The existing cell microencapsulation technologies that involved extrusion and vibration are designed with complex systems and required the use of high energy. A micro-extruder with an inclusion of simple vibrator that has the commercial value for creating a 3D cell model has been developed in this work. This system encapsulates human keratinocytes (HaCaT) in calcium alginate and the size of the microcapsules is controllable in the range of 500-800 µm by varying the flow rates of the extruded solution and frequency of the vibrator motor ( I 0-63 Hz). At 0.13 ml/min of flow rate and vibration rate of 26.4 Hz, approximately 40 ± IO pieces of the alginate microcapsules in a size 632.14 ± I 0.35 µm were produced. Approximately I 00 µm suspension of cells at different cells densities of 1.55 x I 05 cells/ml and 1.37 x I 07 cells/ml were encapsulated for investigation of microtissues formation. Fourier transform infrared spectroscopy (FTIR) analysis showed the different functional groups and chemistry contents of the calcium alginate with and without the inclusion of HaCaT cells in comparison to the monolayers of HaCaT cells. From Field Emission Scanning Electron Microscope (FESEM) imaging, calcium alginate microcapsules were characterised by spherical shape and homogenous surface morphology. Via the nuclei staining, the distance between cells was found reduced as the incubation period increased. This indicated that the cells merged into microtissues with good cell-cell adhesions. After 15 days of culture, the cells were still viable as indicated by the fluorescence green expression of calcein­acetoxymethyl. Replating experiment indicated that the cells from the microtissues were able to migrate and has the tendency to form monolayer of cells on the culture flask. The system was successfully developed and applied to encapsulate cells to produce 3D microtissues

Identification and recovery of video fragments for forensics file carving

In digital forensics, file carving of video files is an important process in the recovery of video evidence needed for many criminal cases. Traditional carving techniques recover video files based on their file structure. However, these techniques fail in cases where the file is split into several fragments, especially if some of the fragments were overwritten. In this paper, we present a method for identification and recovery process of video fragments if the video Codec specifications were overwritten. It consists of two parts which are detector and validators. The detector looks for sequences of bytes that could be video fragments in forensics image. The validator decides to accept or reject that a given fragment is a part of a video file. Based on the proposed method we implement a prototype which is called VidCarve. We have conducted several experiments to evaluate the proposed method with current video carving tools. Experimental results show that the discussed method can identify video fragments with high rates of precision and recall. The overall performance rate can produce forensically sound evidence and play a vital role in the process of recovery of digital evidence in many criminal cases

Use of forensic corpora in validation of data carving on solid-state drives.

The need for greater focus on the validation and verification of tools has become more evident in recent years. The research in this area has been minimal. Continued research regarding the validation of digital forensics tools is necessary to help meet demands from both the law enforcement and scientific communities and to bring digital forensics in line with other forensic disciplines (as cited in Guo, et al., 2009). One of the most effective ways to perform validation and verification of digital forensics tools is to enlist the use of standardized data sets, also known as forensic corpora. This study focused on the use of forensic corpora to validate the file carving function of a common digital forensics tool, Access Data's Forensic Tool Kit (FTK). The study centers specifically on FTK's ability to recover data on solid-state drives (SSDs). The goal of this study was to both evaluate the use of forensic corpora in the validation and verification of digital forensic tools, as well as a serve as a validation study of FTK's carving function on solid-state drives

Reconstructing Textual File Fragments Using Unsupervised Machine Learning Techniques

This work is an investigation into reconstructing fragmented ASCII files based on content analysis motivated by a desire to demonstrate machine learning\u27s applicability to Digital Forensics. Using a categorized corpus of Usenet, Bulletin Board Systems, and other assorted documents a series of experiments are conducted using machine learning techniques to train classifiers which are able to identify fragments belonging to the same original file. The primary machine learning method used is the Support Vector Machine with a variety of feature extractions to train from. Additional work is done in training committees of SVMs to boost the classification power over the individual SVMs, as well as the development of a method to tune SVM kernel parameters using a genetic algorithm. Attention is given to the applicability of Information Retrieval techniques to file fragments, as well as an analysis of textual artifacts which are not present in standard dictionaries