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VLSI Test Principles and Architectures - Design for Testability
This book is a comprehensive guide to new design for testability (DFT) methods that will show the readers how to design a testable and quality product, drive down test cost, improve product quality and yield, and speed up time-to-market and time-to-volume. Key features include up-to-date coverage of design for testability, coverage of industry practices commonly found in commercial DFT tools but not discussed in other books, and numerous, practical examples in each chapter illustrating basic VLSI test principles and DFT architectures. Practitioners/Researchers in VLSI design and testing; design or test engineers, as well as research institutes will benefit from this book. This book is also appropriate for undergraduate and graduate-level courses in electronic testing, digital systems testing, digital logic test and simulation, and VLSI design.
eBook
Very-large-scale integrated quantum graph photonics
Graphs have provided an expressive mathematical tool to model quantum-mechanical devices and systems. In particular, it has been recently discovered that graph theory can be used to describe and design quantum components, devices, setups and systems, based on the two-dimensional lattice of parametric nonlinear optical crystals and linear optical circuits, different to the standard quantum photonic framework. Realizing such graph-theoretical quantum photonic hardware, however, remains extremely challenging experimentally using conventional technologies. Here we demonstrate a graph-theoretical programmable quantum photonic device in very-large-scale integrated nanophotonic circuits. The device monolithically integrates about 2,500 components, constructing a synthetic lattice of nonlinear photon-pair waveguide sources and linear optical waveguide circuits, and it is fabricated on an eight-inch silicon-on-insulator wafer by complementary metal–oxide–semiconductor processes. We reconfigure the quantum device to realize and process complex-weighted graphs with different topologies and to implement different tasks associated with the perfect matching property of graphs. As two non-trivial examples, we show the generation of genuine multipartite multidimensional quantum entanglement with different entanglement structures, and the measurement of probability distributions proportional to the modulus-squared hafnian (permanent) of the graph’s adjacency matrices. This work realizes a prototype of graph-theoretical quantum photonic devices manufactured by very-large-scale integration technologies, featuring arbitrary programmability, high architectural modularity and massive manufacturing scalability.A graph-theoretical programmable quantum photonic device composed of about 2,500 components is fabricated on a silicon substrate within a 12 mm × 15 mm footprint. It shows the generation, manipulation and certification of genuine multiphoton multidimensional entanglement, as well as the implementations of scattershot and Gaussian boson sampling.
Journal Article
Alternative Splicing Plays a Critical Role in Maintaining Mineral Nutrient Homeostasis in Rice (Oryza sativa)
Alternative splicing (AS) of pre-mRNAs promotes transcriptome and proteome diversity and plays important roles in a wide range of biological processes. However, the role of AS in maintaining mineral nutrient homeostasis in plants is largely unknown. To clarify this role, we obtained whole transcriptome RNA sequencing data from rice (Oryza sativa) roots grown in the presence or absence of several mineral nutrients (Fe, Zn, Cu, Mn, and P). Our systematic analysis revealed 13,291 alternatively spliced genes, representing ∼53.3% of the multiexon genes in the rice genome. As the overlap between differentially expressed genes and differentially alternatively spliced genes is small, a molecular understanding of the plant’s response to mineral deficiency is limited by analyzing differentially expressed genes alone. We found that the targets of AS are highly nutrient-specific. To verify the role of AS in mineral nutrition, we characterized mutants in genes encoding Ser/Arg (SR) proteins that function in AS. We identified several SR proteins as critical regulators of Zn, Mn, and P nutrition and showed that three SR protein-encoding genes regulate P uptake and remobilization between leaves and shoots of rice, demonstrating that AS has a key role in regulating mineral nutrient homeostasis in rice.
Journal Article
Transistors based on two-dimensional materials for future integrated circuits
Field-effect transistors based on two-dimensional (2D) materials have the potential to be used in very large-scale integration (VLSI) technology, but whether they can be used at the front end of line or at the back end of line through monolithic or heterogeneous integration remains to be determined. To achieve this, multiple challenges must be overcome, including reducing the contact resistance, developing stable and controllable doping schemes, advancing mobility engineering and improving high-
κ
dielectric integration. The large-area growth of uniform 2D layers is also required to ensure low defect density, low device-to-device variation and clean interfaces. Here we review the development of 2D field-effect transistors for use in future VLSI technologies. We consider the key performance indicators for aggressively scaled 2D transistors and discuss how these should be extracted and reported. We also highlight potential applications of 2D transistors in conventional micro/nanoelectronics, neuromorphic computing, advanced sensing, data storage and future interconnect technologies.
This Review examines the development of field-effect transistors based on two-dimensional materials and considers the challenges that need to be addressed for the devices to be incorporated into very large-scale integration (VLSI) technology.
Journal Article
Diagnostics and correction of batch effects in large‐scale proteomic studies: a tutorial
Advancements in mass spectrometry‐based proteomics have enabled experiments encompassing hundreds of samples. While these large sample sets deliver much‐needed statistical power, handling them introduces technical variability known as batch effects. Here, we present a step‐by‐step protocol for the assessment, normalization, and batch correction of proteomic data. We review established methodologies from related fields and describe solutions specific to proteomic challenges, such as ion intensity drift and missing values in quantitative feature matrices. Finally, we compile a set of techniques that enable control of batch effect adjustment quality. We provide an R package, \"proBatch\", containing functions required for each step of the protocol. We demonstrate the utility of this methodology on five proteomic datasets each encompassing hundreds of samples and consisting of multiple experimental designs. In conclusion, we provide guidelines and tools to make the extraction of true biological signal from large proteomic studies more robust and transparent, ultimately facilitating reliable and reproducible research in clinical proteomics and systems biology.
Graphical Abstract
In mass spectrometry‐based proteomics, handling large sample sets introduces technical variability known as batch effects. This tutorial provides guidelines and tools for the assessment, normalization, and batch correction of proteomics data.
Journal Article
Integrating Coexpression Networks with GWAS to Prioritize Causal Genes in Maize
Genome-wide association studies (GWAS) have identified loci linked to hundreds of traits in many different species. Yet, because linkage equilibrium implicates a broad region surrounding each identified locus, the causal genes often remain unknown. This problem is especially pronounced in nonhuman, nonmodel species, where functional annotations are sparse and there is frequently little information available for prioritizing candidate genes. We developed a computational approach, Camoco, that integrates loci identified by GWAS with functional information derived from gene coexpression networks. Using Camoco, we prioritized candidate genes from a large-scale GWAS examining the accumulation of 17 different elements in maize (Zea mays) seeds. Strikingly, we observed a strong dependence in the performance of our approach based on the type of coexpression network used: expression variation across genetically diverse individuals in a relevant tissue context (in our case, roots that are the primary elemental uptake and delivery system) outperformed other alternative networks. Two candidate genes identified by our approach were validated using mutants. Our study demonstrates that coexpression networks provide a powerful basis for prioritizing candidate causal genes from GWAS loci but suggests that the success of such strategies can highly depend on the gene expression data context. Both the software and the lessons on integrating GWAS data with coexpression networks generalize to species beyond maize.
Journal Article
Profiling of Accessible Chromatin Regions across Multiple Plant Species and Cell Types Reveals Common Gene Regulatory Principles and New Control Modules
The transcriptional regulatory structure of plant genomes remains poorly defined relative to animals. It is unclear how many cis-regulatory elements exist, where these elements lie relative to promoters, and how these features are conserved across plant species. We employed the assay for transposase-accessible chromatin (ATAC-seq) in four plant species (Arabidopsis thaliana, Medicago truncatula, Solanum lycopersicum, and Oryza sativa) to delineate open chromatin regions and transcription factor (TF) binding sites across each genome. Despite 10-fold variation in intergenic space among species, the majority of open chromatin regions lie within 3 kb upstream of a transcription start site in all species.We find a common set of four TFs that appear to regulate conserved gene sets in the root tips of all four species, suggesting that TF-gene networks are generally conserved. Comparative ATAC-seq profiling of Arabidopsis root hair and non-hair cell types revealed extensive similarity as well as many cell-type-specific differences. Analyzing TF binding sites in differentially accessible regions identified a MYB-driven regulatory module unique to the hair cell, which appears to control both cell fate regulators and abiotic stress responses. Our analyses revealed common regulatory principles among species and shed light on the mechanisms producing cell-type-specific transcriptomes during development.
Journal Article
Genome-Wide Association Studies Reveal the Genetic Basis of Ionomic Variation in Rice
Rice (Oryza sativa) is an important dietary source of both essential micronutrients and toxic trace elements for humans. The genetic basis underlying the variations in the mineral composition, the ionome, in rice remains largely unknown. Here, we describe a comprehensive study of the genetic architecture of the variation in the rice ionome performed using genome-wide association studies (GWAS) of the concentrations of 17 mineral elements in rice grain from a diverse panel of 529 accessions, each genotyped at ∼6.4 million single nucleotide polymorphism loci. We identified 72 loci associated with natural ionomic variations, 32 that are common across locations and 40 that are common within a single location. We identified candidate genes for 42 loci and provide evidence for the causal nature of three genes, the sodium transporter gene Os-HKT1;5 for sodium, Os-MOLYBDATE TRANSPORTER1;1 for molybdenum, and Grain number, plant height, and heading date7 for nitrogen. Comparison of GWAS data from rice versus Arabidopsis (Arabidopsis thaliana) also identified well-known as well as new candidates with potential for further characterization. Our study provides crucial insights into the genetic basis of ionomic variations in rice and serves as an important foundation for further studies on the genetic and molecular mechanisms controlling the rice ionome.
Journal Article