Differential Detection of the Tobamoviruses Tomato Mosaic Virus (ToMV) and Tomato Brown Rugose Fruit Virus (ToBRFV) Using CRISPR-Cas12a

CRISPR/Cas12a-based detection is a novel approach for the efficient, sequence-specific identification of viruses. Here we adopt the use of CRISPR/Cas12a to identify the tomato brown rugose fruit virus (ToBRFV), a new and emerging tobamovirus which is causing substantial damage to the global tomato industry. Specific CRISPR RNAs (crRNAs) were designed to detect either ToBRFV or the closely related tomato mosaic virus (ToMV). This technology enabled the differential detection of ToBRFV and ToMV. Sensitivity assays revealed that viruses can be detected from 15–30 ng of RT-PCR product, and that specific detection could be achieved from a mix of ToMV and ToBRFV. In addition, we show that this method can enable the identification of ToBRFV in samples collected from commercial greenhouses. These results demonstrate a new method for species-specific detection of tobamoviruses. A future combination of this approach with isothermal amplification could provide a platform for efficient and user-friendly ways to distinguish between closely related strains and resistance-breaking pathogens.

Sequence-specific minimizers via polar sets

Minimizers are efficient methods to sample k-mers from genomic sequences that unconditionally preserve sufficiently long matches between sequences. Well-established methods to construct efficient minimizers focus on sampling fewer k-mers on a random sequence and use universal hitting sets (sets of k-mers that appear frequently enough) to upper bound the sketch size. In contrast, the problem of sequence-specific minimizers, which is to construct efficient minimizers to sample fewer k-mers on a specific sequence such as the reference genome, is less studied. Currently, the theoretical understanding of this problem is lacking, and existing methods do not specialize well to sketch specific sequences. We propose the concept of polar sets, complementary to the existing idea of universal hitting sets. Polar sets are k-mer sets that are spread out enough on the reference, and provably specialize well to specific sequences. Link energy measures how well spread out a polar set is, and with it, the sketch size can be bounded from above and below in a theoretically sound way. This allows for direct optimization of sketch size. We propose efficient heuristics to construct polar sets, and via experiments on the human reference genome, show their practical superiority in designing efficient sequence-specific minimizers. A reference implementation and code for analyses under an open-source license are at https://github.com/kingsford-group/polarset.

EM Lifetime Constrained Optimization for Multi-Segment Power Grid Networks

This chapter provides techniques for power grid network sizing while considering electromigration reliability. Starting with power grid network and electromigration (EM) fundamentals. Specifically the concerns here are EM immortality and aging effects used as EM constraints when formulating the optimization problems. The chapter first shows that the new power/ground (P/G) optimization problem, subject to the voltage IR drop and new EM constraints, can still be formulated as an efficient sequence of linear programming (SLP) problem, where the optimization is carried out in two linear programming phases in each iteration. The new optimization will ensure that none of the wires fails if all the constraints are satisfied. However, requiring all the wires to be EM immortal can be over-constrained. To mitigate this problem, the improvement is to consider the aging effects of interconnect wires in P/G networks. The idea is to allow some short-lifetime wires to fail and optimize the rest of the wires while considering the additional resistance caused by the failed wire segments. In this way, the resulting P/G networks can be optimized such that the target lifetime of the whole P/G networks can be ensured and will become more robust and aging-aware over the expected lifetime of the chip.

3D Digital Manufacturing Applied on Drilling of 7050-T651 Aluminum Performed by Robot

With advances in automation, industry seeks for optimization while new products are developed and manufacturing processes are becoming smarter. In this sense, virtual manufacturing validations have been demanded for reducing the cost with physical prototypes, ensuring ergonomically safe processes and increasing the quality of processes by emulating it realistically, levering automation utilization in industry environments with a faster and safer manner. By that, this research proposes the use of Tecnomatix Siemens® PLM software for process simulation of 7050 aluminum drilling, material which is widely used in aerospace industry, allowing the evaluation of complexes scenarios with multi-robot integration and its conditions and variables, in order to improve the machining process and its aeronautical structural assemblies. Thus, this research provided a relevant contribution regarding the analysis of main process parameters to obtain an efficient sequence of drilling, its productivity and ergonomic conditions.