Porous Low-Dielectric-Constant Material for Semiconductor Microelectronics

To provide high speed, low dynamic power dissipation, and low cross-talk noise for microelectronic circuits, low-dielectric-constant (low-k) materials are required as the inter- and intra-level dielectric (ILD) insulator of the back-end-of-line interconnects. Porous low-k materials have low-polarizability chemical compositions and the introducing porosity in the film. Integration of porous low-k materials into microelectronic circuits, however, poses a number of challenges because the composition and porosity affected the resistance to damage during integration processing and reduced the mechanical strength, thereby degrading the properties and reliability. These issues arising from porous low-k materials are the subject of the present chapter

Plasma Damage on Low-k Dielectric Materials

Low dielectric constant (low-k) materials as an interconnecting insulator in integrated circuits are essential for resistance-capacitance (RC) time delay reduction. Plasma technology is widely used for the fabrication of the interconnects, such as dielectric etching, resisting ashing or stripping, barrier metal deposition, and surface treatment. During these processes, low-k dielectric materials may be exposed to the plasma environments. The generated reactive species from the plasma react with the low-k dielectric materials. The reaction involves physical and chemical effects, causing degradations for low-k dielectric materials. This is called “plasma damage” on low-k dielectric materials. Therefore, this chapter is an attempt to provide an overview of plasma damage on the low-k dielectric materials

Copper Metal for Semiconductor Interconnects

Resistance-capacitance (RC) delay produced by the interconnects limits the speed of the integrated circuits from 0.25 mm technology node. Copper (Cu) had been used to replace aluminum (Al) as an interconnecting conductor in order to reduce the resistance. In this chapter, the deposition method of Cu films and the interconnect fabrication with Cu metallization are introduced. The resulting integration and reliability challenges are addressed as well

Fabrication and Performance of MEMS-Based Pressure Sensor Packages Using Patterned Ultra-Thick Photoresists

A novel plastic packaging of a piezoresistive pressure sensor using a patterned ultra-thick photoresist is experimentally and theoretically investigated. Two pressure sensor packages of the sacrifice-replacement and dam-ring type were used in this study. The characteristics of the packaged pressure sensors were investigated by using a finite-element (FE) model and experimental measurements. The results show that the thermal signal drift of the packaged pressure sensor with a small sensing-channel opening or with a thin silicon membrane for the dam-ring approach had a high packaging induced thermal stress, leading to a high temperature coefficient of span (TCO) response of −0.19% span/°C. The results also show that the thermal signal drift of the packaged pressure sensors with a large sensing-channel opening for sacrifice-replacement approach significantly reduced packaging induced thermal stress, and hence a low TCO response of −0.065% span/°C. However, the packaged pressure sensors of both the sacrifice-replacement and dam-ring type still met the specification −0.2% span/°C of the unpackaged pressure sensor. In addition, the size of proposed packages was 4 × 4 × 1.5 mm3 which was about seven times less than the commercialized packages. With the same packaging requirement, the proposed packaging approaches may provide an adequate solution for use in other open-cavity sensors, such as gas sensors, image sensors, and humidity sensors

Repeated Small Perturbation Approach Reveals Transcriptomic Steady States

The study of biological systems dynamics requires elucidation of the transitions of steady states. A “small perturbation” approach can provide important information on the “steady state” of a biological system. In our experiments, small perturbations were generated by applying a series of repeating small doses of ultraviolet radiation to a human keratinocyte cell line, HaCaT. The biological response was assessed by monitoring the gene expression profiles using cDNA microarrays. Repeated small doses (10 J/m2) of ultraviolet B (UVB) exposure modulated the expression profiles of two groups of genes in opposite directions. The genes that were up-regulated have functions mainly associated with anti-proliferation/anti-mitogenesis/apoptosis, and the genes that were down-regulated were mainly related to proliferation/mitogenesis/anti-apoptosis. For both groups of genes, repetition of the small doses of UVB caused an immediate response followed by relaxation between successive small perturbations. This cyclic pattern was suppressed when large doses (233 or 582.5 J/m2) of UVB were applied. Our method and results contribute to a foundation for computational systems biology, which implicitly uses the concept of steady state

Scaffolding Contigs Using Multiple Reference Genomes

Scaffolding is an important step of the genome assembly and its function is to order and orient the contigs in the assembly of a draft genome into larger scaffolds. Several single reference-based scaffolders have currently been proposed. However, a single reference genome may not be sufficient alone for a scaffolder to correctly scaffold a target draft genome, especially when the target genome and the reference genome have distant evolutionary relationship or some rearrangements. This motivates researchers to develop the so-called multiple reference-based scaffolders that can utilize multiple reference genomes, which may provide different but complementary types of scaffolding information, to scaffold the target draft genome. In this chapter, we will review some of the state-of-the-art multiple reference-based scaffolders, such as Ragout, MeDuSa and Multi-CAR, and give a complete introduction to Multi-CSAR, an improved extension of Multi-CAR

Prevalence of Epidermal Conditions in Critically Endangered Indo-Pacific Humpback Dolphins (Sousa chinensis) from the Waters of Western Taiwan

The prevalence of epidermal conditions in a small critically endangered population (<100 individuals) of coastal Indo-Pacific humpback dolphins (Sousa chinensis) from the waters of western Taiwan was assessed during a photo-identification study conducted between 2006 and 2010. Of 97 individuals photographically examined, 37% were affected by one or multiple conditions. Besides, mature individuals had significantly higher prevalence than immature ones. Five different skin condition categories were considered, including pox-like lesion, pale lesion, orange film, prolonged ulcer lesion, and nodule on body. This first study to investigate epidermal conditions on S. chinensis in the world offers data for comparison with other studies in the future and new ground for discussion on the health of these animals and the potential impact of anthropogenic activities

Microarray meta-analysis database (M2DB): a uniformly pre-processed, quality controlled, and manually curated human clinical microarray database

<p>Abstract</p> <p>Background</p> <p>Over the past decade, gene expression microarray studies have greatly expanded our knowledge of genetic mechanisms of human diseases. Meta-analysis of substantial amounts of accumulated data, by integrating valuable information from multiple studies, is becoming more important in microarray research. However, collecting data of special interest from public microarray repositories often present major practical problems. Moreover, including low-quality data may significantly reduce meta-analysis efficiency.</p> <p>Results</p> <p>M²DB is a human curated microarray database designed for easy querying, based on clinical information and for interactive retrieval of either raw or uniformly pre-processed data, along with a set of quality-control metrics. The database contains more than 10,000 previously published Affymetrix GeneChip arrays, performed using human clinical specimens. M²DB allows online querying according to a flexible combination of five clinical annotations describing disease state and sampling location. These annotations were manually curated by controlled vocabularies, based on information obtained from GEO, ArrayExpress, and published papers. For array-based assessment control, the online query provides sets of QC metrics, generated using three available QC algorithms. Arrays with poor data quality can easily be excluded from the query interface. The query provides values from two algorithms for gene-based filtering, and raw data and three kinds of pre-processed data for downloading.</p> <p>Conclusion</p> <p>M²DB utilizes a user-friendly interface for QC parameters, sample clinical annotations, and data formats to help users obtain clinical metadata. This database provides a lower entry threshold and an integrated process of meta-analysis. We hope that this research will promote further evolution of microarray meta-analysis.</p

Intra- and Inter-Individual Variance of Gene Expression in Clinical Studies

BACKGROUND: Variance in microarray studies has been widely discussed as a critical topic on the identification of differentially expressed genes; however, few studies have addressed the influence of estimating variance. METHODOLOGY/PRINCIPAL FINDINGS: To break intra- and inter-individual variance in clinical studies down to three levels--technical, anatomic, and individual--we designed experiments and algorithms to investigate three forms of variances. As a case study, a group of "inter-individual variable genes" were identified to exemplify the influence of underestimated variance on the statistical and biological aspects in identification of differentially expressed genes. Our results showed that inadequate estimation of variance inevitably led to the inclusion of non-statistically significant genes into those listed as significant, thereby interfering with the correct prediction of biological functions. Applying a higher cutoff value of fold changes in the selection of significant genes reduces/eliminates the effects of underestimated variance. CONCLUSIONS/SIGNIFICANCE: Our data demonstrated that correct variance evaluation is critical in selecting significant genes. If the degree of variance is underestimated, "noisy" genes are falsely identified as differentially expressed genes. These genes are the noise associated with biological interpretation, reducing the biological significance of the gene set. Our results also indicate that applying a higher number of fold change as the selection criteria reduces/eliminates the differences between distinct estimations of variance

NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition

BACKGROUND: Biomedical named entity recognition (Bio-NER) is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes) do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML) approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized) and at least one class tag (e.g., B-protein, the beginning of a protein name). However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., "2" in the biomedical term IL2) cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target word's closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words). We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing. RESULTS: To develop our ML-based Bio-NER system, we employ conditional random fields, which have performed effectively in several well-known tasks, as our underlying ML model. Adding selected conjunction features, applying numerical normalization, and employing pattern-based post-processing improve the F-scores by 1.67%, 1.04%, and 0.57%, respectively. The combined increase of 3.28% yields a total score of 72.98%, which is better than the baseline system that only uses singleton features. CONCLUSION: We demonstrate the benefits of using the sequential forward search algorithm to select effective conjunction feature groups. In addition, we show that numerical normalization can effectively reduce the number of redundant and unseen features. Furthermore, the Smith-Waterman local alignment algorithm can help ML-based Bio-NER deal with difficult cases that need longer context windows