SECURITY AND OTHER VULNERABILITY PREDICTION USING NOVEL DEEP REPRESENTATION OF SOURCE CODE WITH ACTIVE FEEDBACK LOOP

Since the cost of fixing vulnerabilities can be thirty times greater after an application has been deployed, it is recognized that properly-written code can yield potentially large savings. Accordingly, approaches presented herein apply machine learning and Artificial Intelligence (AI) techniques to improve developer experience by enabling developers to avoid introducing potential bugs and/or vulnerabilities while coding. Billions of lines of source code, which have already been written, are utilized as examples of how to write functional and secure code that is easy to read and to debug. By leveraging this wealth of available data, which is complemented with state-of-art machine learning models, enterprise-level software solutions can be developed that have a high standard of coding and are potentially bug-free

On the breakage of high aspect ratio crystals in filter beds under continuous percolation

Purpose This work details experimental observations on the effect of liquid flow percolating through packed beds of crystals to elucidate how the filtration pressure severely alters the size distribution and crystal shape. Pressure filtration is widely used in the pharmaceutical industry, and frequently results in undesired size distribution changes that hinder further processing. Methods The percolation methodology presented fixes fluid flow through a bed of crystals, resulting in a pressure over the bed. X-ray computed tomography (XCT) provided detailed observations of the bed structure. Detailed 2D particle size data was obtained using automated microscopy and was analysed using an in-house developed tool. Results Crystal breakage is observed when the applied pressure exceeds a critical pressure: 0.5–1 bar for ibuprofen, 1–2 bar for β-L glutamic acid (LGA) and 2–2.5 bar for para amino benzoic acid (PABA). X-ray computed tomography showed significant changes in bed density under the applied pressure. Size analysis and microscope observations showed two modes of breakage: (i) snapping of long crystals and (ii) shattering of crystals. Conclusion LGA and PABA have a similar breakage strength (50 MPa), ibuprofen is significantly weaker (9 MPa). Available breakage strength data may be correlated to the volumetric Gibbs free energy. Data from 12 and 35 mm bed diameters compares well to literature data in a 80 mm filter; the smaller, easy to operate percolation unit is a versatile tool to assess crystal breakage in filtration operations

Breaking size-segregation waves and mobility feedback in dense granular avalanches

Through experiments and discrete particle method (DPM) simulations we present evidence for the existence of a recirculating structure, that exists near the front of dense granular avalanches, and is known as a breaking size-segregation (BSS) wave. This is achieved through the study of three-dimensional bidisperse granular flows in a moving-bed channel. Particle-size segregation gives rise to the formation of a large-particle-rich front and a small-particle-rich tail with a BSS wave positioned between the tail and front. We experimentally resolve the structure of the BSS wave using refractive-index matched scanning and find that it is qualitatively similar to the structure observed in DPM simulations. Our analysis demonstrates a relation between the concentration of small particles in the flow and the amount of basal slip, in which the structure of the BSS wave plays a key role. This leads to a feedback between the mean bulk flow velocity and the process of particle-size segregation. Ultimately, these findings shed new light on the recirculation of large and small grains near avalanche fronts and the effects of this behaviour on the mobility of the bulk flow

New methods for automated laboratory based temporal CT

<p>These are the accompanying datasets from the paper "<strong>New software protocols for enabling </strong><strong>laboratory based</strong><strong> temporal CT</strong>". There are two datasets: the germination of a mung bean captured using 54 uninterrupted time-lapse tomograms, and the precipitation of barite in a porous media with continuous golden-ratio projections.</p> <p>The data was collected using software extensions written for Nikon Metrology CT systems using IPC. These software extensions implemented the protocols highlighted in the paper, and can be found in the following GitHub repositories:</p> <p>Uninterrupted Time-Lapse CT: <a href="https://github.com/parmeshgajjar/TemporalCT-TimeLapse.Uninterrupted.git">https://github.com/parmeshgajjar/TemporalCT-TimeLapse.Uninterrupted.git</a></p> <p>Continuous Golden Ratio Acquisition CT: <a href="https://github.com/parmeshgajjar/TemporalCT-ContinuousGR.Acqusition">https://github.com/parmeshgajjar/TemporalCT-ContinuousGR.Acqusition</a></p