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POC GTFO. Volume II
\"This is the second volume of collected works from the prestigious International Journal of Proof of Concept or Get the funk out, a publication for ladies and gentlemen with an interest in reverse engineering, file format polyglots, radio, operating systems, and other assorted technical subjects.\"--Introduction.
Book
How we created neuromorphic engineering
Neuromorphic engineering aims to create computing hardware that mimics biological nervous systems, and it is expected to play a key role in the next era of hardware development. Carver Mead recounts how it all began.
Journal Article
Mastering reverse engineering : re-engineer your ethical hacking skills
If you want to analyze software in order to exploit its weaknesses and strengthen its defenses, then you should explore reverse engineering. Reverse Engineering is a hackerfriendly tool used to expose security flaws and questionable privacy practices.In this book, you will learn how to analyse software even without having access to its source code or design documents. You will start off by learning the low-level language used to communicate with the computer and then move on to covering reverse engineering techniques. Next, you will explore analysis techniques using real-world tools such as IDA Pro and x86dbg. As you progress through the chapters, you will walk through use cases encountered in reverse engineering, such as encryption and compression, used to obfuscate code, and how to to identify and overcome anti-debugging and anti-analysis tricks. Lastly, you will learn how to analyse other types of files that contain code. By the end of this book, you will have the confidence to perform reverse engineering. -- back cover.
Book
How we made the Li-ion rechargeable battery
Progress in portable and ubiquitous electronics would not be possible without rechargeable batteries. John B. Goodenough recounts the history of the lithium-ion rechargeable battery.
Journal Article
Digital modelmaking : laser cutting, 3D printing and reverse engineering
Digital manufacturing has become an intrinsic part of the modelmaking profession, so today's practitioner must be skilled in both traditional hand-making techniques and digital technology. Relevant to a wide variety of creative industries, including film and television, theatre, architecture and product design, Digital Modelmaking offers a comprehensive insight into the manufacturing processes and technologies used within contemporary modelmaking. Each chapter contains an in-depth explanation of each topic, presents examples of how each process is used and includes case studies from professional modelmakers and students. Topics covered include: making models using a laser cutter, 3D printer and CNC milling machinery; generating 3D digital data using a 3D scanner and photogrammetry; two-and three- dimensional drawing software such as CAD; designing models for digital manufacturing; selecting materials based on their suitability for modelmaking; combining traditional hand-making skills with digital manufacturing; painting and finishing models, and finally, moulding and casting using silicone and resin. This invaluable book will be of great interest for students, young professionals and everyone with a passion for design and making. It is superbly illustrated with 234 colour photographs and 32 line artworks giving numerous examples of the design process. Helen Lansdown has worked professionally as a modelmaker and designer for thirty years and is a lecturer at Herefordshire University teaching on the Model Design programme.
Book
Adaptive laboratory evolution of Yarrowia lipolytica improves ferulic acid tolerance
Yarrowia lipolytica strain is a promising cell factory for the conversion of lignocellulose to biofuels and bioproducts. Despite the inherent robustness of this strain, further improvements to lignocellulose-derived inhibitors toxicity tolerance of Y. lipolytica are also required to achieve industrial application. Here, adaptive laboratory evolution was employed with increasing concentrations of ferulic acid. The adaptive laboratory evolution experiments led to evolve Y. lipolytica strain yl-XYL + *FA*4 with increased tolerance to ferulic acid as compared to the parental strain. Specifically, the evolved strain could tolerate 1.5 g/L ferulic acid, whereas 0.5 g/L ferulic acid could cause about 90% lethality of the parental strain. Transcriptome analysis of the evolved strain revealed several targets underlying toxicity tolerance enhancements. YALI0_E25201g, YALI0_F05984g, YALI0_B18854g, and YALI0_F16731g were among the highest upregulated genes, and the beneficial contributions of these genes were verified via reverse engineering. Recombinant strains with overexpressing each of these four genes obtained enhanced tolerance to ferulic acid as compared to the control strain. Fortunately, recombinant strains with overexpression of YALI0_E25201g, YALI0_B18854g, and YALI0_F16731g individually also obtained enhanced tolerance to vanillic acid. Overall, this work demonstrated a whole strain improvement cycle by “non-rational” metabolic engineering and presented new targets to modify Y. lipolytica for microbial lignocellulose valorization.Key points• Adaptive evolution improved the ferulic acid tolerance of Yarrowia lipolytica• Transcriptome sequence was applied to analyze the ferulic acid tolerate strain• Three genes were demonstrated for both ferulic acid and vanillic acid tolerance
Journal Article
From predictive modelling to machine learning and reverse engineering of colloidal self-assembly
An overwhelming diversity of colloidal building blocks with distinct sizes, materials and tunable interaction potentials are now available for colloidal self-assembly. The application space for materials composed of these building blocks is vast. To make progress in the rational design of new self-assembled materials, it is desirable to guide the experimental synthesis efforts by computational modelling. Here, we discuss computer simulation methods and strategies used for the design of soft materials created through bottom-up self-assembly of colloids and nanoparticles. We describe simulation techniques for investigating the self-assembly behaviour of colloidal suspensions, including crystal structure prediction methods, phase diagram calculations and enhanced sampling techniques, as well as their limitations. We also discuss the recent surge of interest in machine learning and reverse-engineering methods. Although their implementation in the colloidal realm is still in its infancy, we anticipate that these data-science tools offer new paradigms in understanding, predicting and (inverse) design of novel colloidal materials.
This Review provides an overview of computational tools and strategies, from simulation methods to machine learning and reverse-engineering approaches, used for the design of soft materials made from self-assembling colloids and nanoparticles.
Journal Article
Classical system approach to reverse engineering
The paper presents one of the possible solutions of the reverse engineering problem from the point of view of the classical system approach, as well as highlights the direction for the development of a complex software product. This approach will make it possible to change the modern practice of reverse engineering, which is applied everywhere. This practice requires expert evaluation by operator teams on non-acceptance basis. The approach proposed by the authors will significantly minimize human participation in this process.
Journal Article
How we made the IGZO transistor
Thin-film transistors made from indium gallium zinc oxide (IGZO) are driving the next evolution in active-matrix flat panel displays. Hideo Hosono recounts how demand for a high-performance alternative to amorphous silicon transistors led to their development.
Journal Article
Damage detection and reconstruction algorithm in repairing compressor blade by direct metal deposition
Aero-engine blade repair is challenging due to its complicated geometry and unique defects after serving in a harsh environment. Traditional manual-based remanufacturing processes are not capable of yielding consistently repaired part quality, significantly limiting the application of repair technologies. For building up materials on damaged blades, it is required to detect and extract the repair volume and generate corresponding tool path for additive manufacturing. Therefore, the objective of this paper is to propose an automated damage detection and reconstruction algorithm for jet engine blade repair. Reverse engineering was utilized to reconstruct models of nominal and damaged blades. The reconstructed damaged model was best fitted with the nominal model by transformation matrix and using overlapping area comparison method. Through area comparison method, the damaged blade was separated into intact section and damaged section. A set of parallel and equidistant casting rays were used to intersect with damaged layers to extract the repair volume. Laser scanning tracks were generated according to the extracted geometry. The laser-assisted direct metal deposition process was performed to deposit Ti-6Al-4V particles on the damaged region. Finally, microstructure analysis was carried out to evaluate the repaired part quality. The repair experiment validated that the proposed algorithm is suitable and efficient for automated repair of curved blades.
Journal Article