Constraint-driven RF test stimulus generation and built-in test

With the explosive growth in wireless applications, the last decade witnessed an ever-increasing test challenge for radio frequency (RF) circuits. While the design community has pushed the envelope far into the future, by expanding CMOS process to be used with high-frequency wireless devices, test methodology has not advanced at the same pace. Consequently, testing such devices has become a major bottleneck in high-volume production, further driven by the growing need for tighter quality control. RF devices undergo testing during the prototype phase and during high-volume manufacturing (HVM). The benchtop test equipment used throughout prototyping is very precise yet specialized for a subset of functionalities. HVM calls for a different kind of test paradigm that emphasizes throughput and sufficiency, during which the projected performance parameters are measured one by one for each device by automated test equipment (ATE) and compared against defined limits called specifications. The set of tests required for each product differs greatly in terms of the equipment required and the time taken to test individual devices. Together with signal integrity, precision, and repeatability concerns, the initial cost of RF ATE is prohibitively high. As more functionality and protocols are integrated into a single RF device, the required number of specifications to be tested also increases, adding to the overall cost of testing, both in terms of the initial and recurring operating costs. In addition to the cost problem, RF testing proposes another challenge when these components are integrated into package-level system solutions. In systems-on-packages (SOP), the test problems resulting from signal integrity, input/output bandwidth (IO), and limited controllability and observability have initiated a paradigm shift in high-speed analog testing, favoring alternative approaches such as built-in tests (BIT) where the test functionality is brought into the package. This scheme can make use of a low-cost external tester connected through a low-bandwidth link in order to perform demanding response evaluations, as well as make use of the analog-to-digital converters and the digital signal processors available in the package to facilitate testing. Although research on analog built-in test has demonstrated hardware solutions for single specifications, the paradigm shift calls for a rather general approach in which a single methodology can be applied across different devices, and multiple specifications can be verified through a single test hardware unit, minimizing the area overhead. Specification-based alternate test methodology provides a suitable and flexible platform for handling the challenges addressed above. In this thesis, a framework that integrates ATE and system constraints into test stimulus generation and test response extraction is presented for the efficient production testing of high-performance RF devices using specification-based alternate tests. The main components of the presented framework are as follows: Constraint-driven RF alternate test stimulus generation: An automated test stimulus generation algorithm for RF devices that are evaluated by a specification-based alternate test solution is developed. The high-level models of the test signal path define constraints in the search space of the optimized test stimulus. These models are generated in enough detail such that they inherently define limitations of the low-cost ATE and the I/O restrictions of the device under test (DUT), yet they are simple enough that the non-linear optimization problem can be solved empirically in a reasonable amount of time. Feature extractors for BIT: A methodology for the built-in testing of RF devices integrated into SOPs is developed using additional hardware components. These hardware components correlate the high-bandwidth test response to low bandwidth signatures while extracting the test-critical features of the DUT. Supervised learning is used to map these extracted features, which otherwise are too complicated to decipher by plain mathematical analysis, into the specifications under test. Defect-based alternate testing of RF circuits: A methodology for the efficient testing of RF devices with low-cost defect-based alternate tests is developed. The signature of the DUT is probabilistically compared with a class of defect-free device signatures to explore possible corners under acceptable levels of process parameter variations. Such a defect filter applies discrimination rules generated by a supervised classifier and eliminates the need for a library of possible catastrophic defects.Ph.D.Committee Chair: Chatterjee, Abhijit; Committee Member: Durgin, Greg; Committee Member: Keezer, David; Committee Member: Milor, Linda; Committee Member: Sitaraman, Sures

Aeronautical engineering: A continuing bibliography with indexes (supplement 318)

This bibliography lists 217 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1995. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Instrumentation and Controls Division Progress Report for the Period July 1, 1994, to December 31, 1997: Working Together on New Horizons

The ORNL I&C Division was created to support DOE-funded research. We have since broadened our mission to include other sponsors as the need for our services has grown. This report summarizes some of the work we have been conducting on behalf of DOE, other federal agencies, and the private sector during the past three and a half years. Because we take on nearly 750 individual projects every year, much of our work cannot be reported in detail. We hope that these summaries are of interest and demonstrate that our work, rooted in DOE scientific and technological programs, can also benefit the nation, its industry, and its citizens in direct and tangible ways

Gene expression analysis reveals a 5-gene signature for progression-free survival in prostate cancer

This is the final version. Available on open access from Frontiers Media via the DOI in this recordProstate cancer (PCa) is the second most common male cancer worldwide, but effective biomarkers for the presence or progression risk of disease are currently elusive. In a series of nine matched histologically confirmed PCa and benign samples, we carried out an integrated transcriptome-wide gene expression analysis, including differential gene expression analysis and weighted gene co-expression network analysis (WGCNA), which identified a set of potential gene markers highly associated with tumour status (malignant vs. benign). We then used these genes to establish a minimal progression-free survival (PFS)-associated gene signature (GS) (PCBP1, PABPN1, PTPRF, DANCR, and MYC) using least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox regression analyses from The Cancer Genome Atlas prostate adenocarcinoma (TCGA-PRAD) dataset. Our signature was able to predict PFS over 1, 3, and 5 years in TCGA-PRAD dataset, with area under the curve (AUC) of 0.64–0.78, and our signature remained as a prognostic factor independent of age, Gleason score, and pathological T and N stages. A nomogram combining the signature and Gleason score demonstrated improved predictive capability for PFS (AUC: 0.71–0.85) and was superior to the Cambridge Prognostic Group (CPG) model alone and some conventionally used clinicopathological factors in predicting PFS. In conclusion, we have identified and validated a novel five-gene signature and established a nomogram that effectively predicted PFS in patients with PCa. Findings may improve current prognosis tools for PFS and contribute to clinical decision-making in PCa treatment.National Institute for Health Research (NIHR

Sex-Specific Modulation of Gene Expression Networks in Murine Hypothalamus

The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ significantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantified gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to define hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a). Transcripts associated with the endocrine system and neuropeptide signaling also differ significantly. Sex-differentiated transcripts often have well delimited expression within specific hypothalamic nuclei that have roles in reproduction. For instance, the estrogen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-specific hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modification and gene transcription. In females, the X chromosome paralog, Kdm6a, takes the place of Uty in the same network. We also find significant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-specific modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-specific modulators

Multi-omics analysis of early molecular mechanisms of type 1 diabetes

Type 1 diabetes (T1D) is a complicated autoimmune disease with largely unknown disease mechanisms. The diagnosis is preceded by a long asymptomatic period of autoimmune activity in the insulin-producing pancreatic islets. Currently the only clinical markers used for T1D prediction are islet autoantibodies, which are a sign of already-broken immune tolerance. The focus of this dissertation is on the early asymptomatic period preceding seroconversion to islet autoantibody positivity. The genetic risk of type 1 diabetes has been thoroughly mapped in genome-wide association studies, but environmental factors and molecular mechanisms that mediate the risk are less well understood. According to the hygiene hypothesis, the risk of immune-mediated disorders is increased by the lack of exposure to pathogens in modern environments. Within a study on the hygiene hypothesis, we compared umbilical cord blood gene expression patterns between children born in environments with contrasting standards of living and type 1 diabetes incidences (Finland, Russia, and Estonia). The differentially expressed genes were associated with innate immunity and immune maturation. Our results suggest that the environment influences the immune system development already in-utero. Furthermore, we analyzed genome-wide DNA methylation and gene expression profiles in samples collected prospectively from Finnish children and newborn infants at risk of type 1 diabetes. Bisulfite sequencing analysis did not show any association of neonatal DNA methylation with later progression to T1D. However, antiviral type I interferon response in early childhood was found to be a risk factor of T1D. This transcriptomic signature was detectable in the peripheral blood already before islet autoantibodies, and the main observations were confirmed in an independent German study. These results contributed to the hypothesis that virus infections might play a role in T1D. Additionally, this dissertation contributed to transcriptomic and epigenomic data analysis workflows. Simple probe-level analysis of exon array data was shown to improve the reproducibility, specificity, and sensitivity of detected differential exon inclusion events. Type 1 error rate was markedly reduced by permutation-based significance assessment of differential methylation in bisulfite sequencing studies.Tyypin 1 diabeteksen varhaisten molekulaaristen mekanismien multiomiikka-analyysi Tyypin 1 diabetes (T1D) on autoimmuunitauti, jonka taustalla olevista mekanismeista tiedetään vähän. Diagnoosia edeltää pitkä oireeton jakso, jonka aikana insuliinia tuottaviin beetasoluihin kohdistuva autoimmuunireaktio etenee haiman saarekkeissa. Tämä väitöskirjatutkimus keskittyy T1D:n varhaiseen oireettomaan ajanjaksoon, joka edeltää serokonversiota autovasta-ainepositiiviseksi. Tyypin 1 diabeteksen geneettiset riskitekijät on kartoitettu perusteellisesti genominlaajuisissa assosiaatiotutkimuksissa, mutta ympäristön riskitekijöistä ja riskiä välittävistä molekyylimekanismeista tiedetään vähemmän. Hygieniahypoteesin mukaan vähäinen altistuminen taudinaiheuttajille lisää immuunijärjestelmän häiriöiden riskiä. Hygieniahypoteesiin liittyvässä osatyössä vertasimme hygienian ja T1D:n ilmaantuvuuden suhteen erilaisissa ympäristöissä (Suomi, Venäjä ja Viro) syntyneiden lasten napaveren geeniekpressioprofiileja. Erilaisesti ekspressoituneet geenit liittyivät synnynnäiseen immuniteettiin ja immuunijärjestelmän maturaatioon. Näiden tulosten perusteella ympäristö saattaa vaikuttaa immuunijärjestelmän kehitykseen jo raskauden aikana. Genominlaajuista DNA-metylaatiota ja geeniekspressiota analysoitiin näytteistä, jotka oli kerätty laajassa suomalaisessa seurantatutkimuksessa T1D:n riskiryhmään kuuluvilta lapsilta ja vastasyntyneiltä. Bisulfiittisekvensointianalyysin perusteella vastasyntyneen DNA-metylaation ja lapsuuden aikana kehittyvän T1D:n välillä ei ollut yhteyttä. Sen sijaan RNA:n tasolla havaittava viruksiin kohdistuva tyypin 1 interferonivaste varhaislapsuudessa todettiin T1D:n riskitekijäksi. Tämä havainto tehtiin perifeerisestä verestä jo ennen saarekevasta-aineiden ilmaantumista, ja päähavainnot vahvistettiin saksalaisessa tutkimuksessa. Nämä tulokset vahvistivat hypoteesia, jonka mukaan virukset voivat vaikuttaa T1D:n puhkeamiseen. T1D-tutkimuksen ohella tämä väitöskirjatyö kehitti transkriptomiikkaan ja epigenomiikkaan sopivia analyysimenetelmiä. Eksonimikrosirujen koetintasoisen analyysin todettiin parantavan toistettavuutta, sensitiivisyyttä ja tarkkuutta vaihtoehtoisen silmukoinniin kartoittamisessa. Tilastollisen merkitsevyyden permutaatiopohjainen analyysi vähensi tyypin 1 virhettä bisulfiittisekvensointidatan analyysissa

Annotation and function of switch-like genes in health and disease

Gene expression microarrays provide transcript-level measurements across entire genomes and are traditionally used for differential expression analysis between health and disease or classification of disease subtypes. The abundance of gene expression microarray data currently available to the scientific community makes it possible to assess gene transcript levels among diverse tissue types for an entire genome. Gene expression is controlled over a wide range at the transcript level through complex interplay between DNA and regulatory proteins, resulting in gene expression profiles that can be represented as normal, graded, and bimodal (switch-like) distributions. It is our assertion that these distributions of gene expression, notably the bimodal distribution, result from biologically relevant regulation events. We have performed genome-scale identification and annotation of genes with bimodal, switch-like expression at the transcript level in human and mouse, using large microarray datasets for healthy tissue, in order to study the cellular pathways and regulatory mechanisms involving this class of genes. Our method implemented a likelihood ratio test to identify bimodal genes by comparing the best-fit two-component normal mixture, estimated using the expectation maximization algorithm, against a single-component normal distribution for each gene. This procedure identified roughly 15% of genes in human and mouse as bimodal, with a substantial overlap between human genes and their orthologous mouse counterparts. A survey of biological pathways revealed that the set of bimodal genes plays a role in cell communication and signaling with the external environment. Our analysis of regulatory sequence regions for bimodal genes revealed characteristics including enrichment of TATA boxes and an increased number of alternative transcription start sites. In addition to regulatory sequence analysis, we explored aspects of epigenetic regulation for their activity among the set of bimodal genes. We performed meta-analysis of gene expression microarray, DNA methylation, and histone methylation datasets representing human stem cells and liver tissue to reveal that the mode of expression within switch-like genes is primarily associated with histone methylation status. These results provide insight to normal patterns of histone methylation in healthy, differentiated tissue types. Aberrant methylation is a known marker in the progression of cancer, so these switch-like genes may also provide a valuable reference in disease diagnosis and prognosis. The method presented for bimodal gene identification also allows for an alternate approach to differential gene expression analysis between tissues and disease subtypes.Ph.D., Biomedical Engineering -- Drexel University, 200

Annotation and function of switch-like genes in health and disease

Gene expression microarrays provide transcript-level measurements across entire genomes and are traditionally used for differential expression analysis between health and disease or classification of disease subtypes. The abundance of gene expression microarray data currently available to the scientific community makes it possible to assess gene transcript levels among diverse tissue types for an entire genome. Gene expression is controlled over a wide range at the transcript level through complex interplay between DNA and regulatory proteins, resulting in gene expression profiles that can be represented as normal, graded, and bimodal (switch-like) distributions. It is our assertion that these distributions of gene expression, notably the bimodal distribution, result from biologically relevant regulation events. We have performed genome-scale identification and annotation of genes with bimodal, switch-like expression at the transcript level in human and mouse, using large microarray datasets for healthy tissue, in order to study the cellular pathways and regulatory mechanisms involving this class of genes. Our method implemented a likelihood ratio test to identify bimodal genes by comparing the best-fit two-component normal mixture, estimated using the expectation maximization algorithm, against a single-component normal distribution for each gene. This procedure identified roughly 15% of genes in human and mouse as bimodal, with a substantial overlap between human genes and their orthologous mouse counterparts. A survey of biological pathways revealed that the set of bimodal genes plays a role in cell communication and signaling with the external environment. Our analysis of regulatory sequence regions for bimodal genes revealed characteristics including enrichment of TATA boxes and an increased number of alternative transcription start sites. In addition to regulatory sequence analysis, we explored aspects of epigenetic regulation for their activity among the set of bimodal genes. We performed meta-analysis of gene expression microarray, DNA methylation, and histone methylation datasets representing human stem cells and liver tissue to reveal that the mode of expression within switch-like genes is primarily associated with histone methylation status. These results provide insight to normal patterns of histone methylation in healthy, differentiated tissue types. Aberrant methylation is a known marker in the progression of cancer, so these switch-like genes may also provide a valuable reference in disease diagnosis and prognosis. The method presented for bimodal gene identification also allows for an alternate approach to differential gene expression analysis between tissues and disease subtypes.Ph.D., Biomedical Engineering -- Drexel University, 200

Technology 2004, Vol. 2

Proceedings from symposia of the Technology 2004 Conference, November 8-10, 1994, Washington, DC. Volume 2 features papers on computers and software, virtual reality simulation, environmental technology, video and imaging, medical technology and life sciences, robotics and artificial intelligence, and electronics