6 resultados para Programmable calculators.
em Duke University
Resumo:
OBJECTIVES: To compare the predictive performance and potential clinical usefulness of risk calculators of the European Randomized Study of Screening for Prostate Cancer (ERSPC RC) with and without information on prostate volume. METHODS: We studied 6 cohorts (5 European and 1 US) with a total of 15,300 men, all biopsied and with pre-biopsy TRUS measurements of prostate volume. Volume was categorized into 3 categories (25, 40, and 60 cc), to reflect use of digital rectal examination (DRE) for volume assessment. Risks of prostate cancer were calculated according to a ERSPC DRE-based RC (including PSA, DRE, prior biopsy, and prostate volume) and a PSA + DRE model (including PSA, DRE, and prior biopsy). Missing data on prostate volume were completed by single imputation. Risk predictions were evaluated with respect to calibration (graphically), discrimination (AUC curve), and clinical usefulness (net benefit, graphically assessed in decision curves). RESULTS: The AUCs of the ERSPC DRE-based RC ranged from 0.61 to 0.77 and were substantially larger than the AUCs of a model based on only PSA + DRE (ranging from 0.56 to 0.72) in each of the 6 cohorts. The ERSPC DRE-based RC provided net benefit over performing a prostate biopsy on the basis of PSA and DRE outcome in five of the six cohorts. CONCLUSIONS: Identifying men at increased risk for having a biopsy detectable prostate cancer should consider multiple factors, including an estimate of prostate volume.
Resumo:
While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.
In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.
By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.
Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.
Resumo:
BACKGROUND: Antibodies (Abs) to the HPV16 proteome increase risk for HPV-associated OPC (HPVOPC). The goal of this study was to investigate the association of a panel of HPV16 Abs with risk for OPC as well as the association of these Abs with tumor HPV and smoking status among patients with OPC. METHODS: IgG Abs to the HPV16 antigens E1, E2, E4, E5, E6, E7, L1, L2 were quantified using a programmable ELISA assay. Sera were obtained from 258 OPC patients at diagnosis and 250 healthy controls. HPV16 tumor status was measured by PCR for 137 cases. Multivariable logistic regression was used to calculate odds ratios for the association of HPV16 Abs with risk for OPC. RESULTS: HPV16 E1, E2, E4, E5, E6, E7 and L1-specific IgG levels were elevated in OPC patients compared to healthy controls (p<0.05). After multivariable adjustment, Ab positivity for NE2, CE2, E6, and/or E7 was associated with OPC risk (OR [95% CI], 249.1 [99.3-624.9]). Among patients with OPC, Ab positivity for these antigens was associated with tumor HPV status, especially among never or light smokers (OR [95% CI], 6.5 [2.1-20.1] and OR [95% CI], 17.5 [4.0-77.2], respectively). CONCLUSIONS: Antibodies to HPV16 proteins are associated with increased risk for HPVOPC. Among patients with OPC, HPV16 Abs are associated with tumor HPV status, in particular among HPV positive patients with no or little smoking history.
Resumo:
The unprecedented and relentless growth in the electronics industry is feeding the demand for integrated circuits (ICs) with increasing functionality and performance at minimum cost and power consumption. As predicted by Moore's law, ICs are being aggressively scaled to meet this demand. While the continuous scaling of process technology is reducing gate delays, the performance of ICs is being increasingly dominated by interconnect delays. In an effort to improve submicrometer interconnect performance, to increase packing density, and to reduce chip area and power consumption, the semiconductor industry is focusing on three-dimensional (3D) integration. However, volume production and commercial exploitation of 3D integration are not feasible yet due to significant technical hurdles.
At the present time, interposer-based 2.5D integration is emerging as a precursor to stacked 3D integration. All the dies and the interposer in a 2.5D IC must be adequately tested for product qualification. However, since the structure of 2.5D ICs is different from the traditional 2D ICs, new challenges have emerged: (1) pre-bond interposer testing, (2) lack of test access, (3) limited ability for at-speed testing, (4) high density I/O ports and interconnects, (5) reduced number of test pins, and (6) high power consumption. This research targets the above challenges and effective solutions have been developed to test both dies and the interposer.
The dissertation first introduces the basic concepts of 3D ICs and 2.5D ICs. Prior work on testing of 2.5D ICs is studied. An efficient method is presented to locate defects in a passive interposer before stacking. The proposed test architecture uses e-fuses that can be programmed to connect or disconnect functional paths inside the interposer. The concept of a die footprint is utilized for interconnect testing, and the overall assembly and test flow is described. Moreover, the concept of weighted critical area is defined and utilized to reduce test time. In order to fully determine the location of each e-fuse and the order of functional interconnects in a test path, we also present a test-path design algorithm. The proposed algorithm can generate all test paths for interconnect testing.
In order to test for opens, shorts, and interconnect delay defects in the interposer, a test architecture is proposed that is fully compatible with the IEEE 1149.1 standard and relies on an enhancement of the standard test access port (TAP) controller. To reduce test cost, a test-path design and scheduling technique is also presented that minimizes a composite cost function based on test time and the design-for-test (DfT) overhead in terms of additional through silicon vias (TSVs) and micro-bumps needed for test access. The locations of the dies on the interposer are taken into consideration in order to determine the order of dies in a test path.
To address the scenario of high density of I/O ports and interconnects, an efficient built-in self-test (BIST) technique is presented that targets the dies and the interposer interconnects. The proposed BIST architecture can be enabled by the standard TAP controller in the IEEE 1149.1 standard. The area overhead introduced by this BIST architecture is negligible; it includes two simple BIST controllers, a linear-feedback-shift-register (LFSR), a multiple-input-signature-register (MISR), and some extensions to the boundary-scan cells in the dies on the interposer. With these extensions, all boundary-scan cells can be used for self-configuration and self-diagnosis during interconnect testing. To reduce the overall test cost, a test scheduling and optimization technique under power constraints is described.
In order to accomplish testing with a small number test pins, the dissertation presents two efficient ExTest scheduling strategies that implements interconnect testing between tiles inside an system on chip (SoC) die on the interposer while satisfying the practical constraint that the number of required test pins cannot exceed the number of available pins at the chip level. The tiles in the SoC are divided into groups based on the manner in which they are interconnected. In order to minimize the test time, two optimization solutions are introduced. The first solution minimizes the number of input test pins, and the second solution minimizes the number output test pins. In addition, two subgroup configuration methods are further proposed to generate subgroups inside each test group.
Finally, the dissertation presents a programmable method for shift-clock stagger assignment to reduce power supply noise during SoC die testing in 2.5D ICs. An SoC die in the 2.5D IC is typically composed of several blocks and two neighboring blocks that share the same power rails should not be toggled at the same time during shift. Therefore, the proposed programmable method does not assign the same stagger value to neighboring blocks. The positions of all blocks are first analyzed and the shared boundary length between blocks is then calculated. Based on the position relationships between the blocks, a mathematical model is presented to derive optimal result for small-to-medium sized problems. For larger designs, a heuristic algorithm is proposed and evaluated.
In summary, the dissertation targets important design and optimization problems related to testing of interposer-based 2.5D ICs. The proposed research has led to theoretical insights, experiment results, and a set of test and design-for-test methods to make testing effective and feasible from a cost perspective.
Resumo:
Gene regulation is a complex and tightly controlled process that defines cell function in physiological and abnormal states. Programmable gene repression technologies enable loss-of-function studies for dissecting gene regulation mechanisms and represent an exciting avenue for gene therapy. Established and recently developed methods now exist to modulate gene sequence, epigenetic marks, transcriptional activity, and post-transcriptional processes, providing unprecedented genetic control over cell phenotype. Our objective was to apply and develop targeted repression technologies for regenerative medicine, genomics, and gene therapy applications. We used RNA interference to control cell cycle regulation in myogenic differentiation and enhance the proliferative capacity of tissue engineered cartilage constructs. These studies demonstrate how modulation of a single gene can be used to guide cell differentiation for regenerative medicine strategies. RNA-guided gene regulation with the CRISPR/Cas9 system has rapidly expanded the targeted repression repertoire from silencing single protein-coding genes to modulation of genes, promoters, and other distal regulatory elements. In order to facilitate its adaptation for basic research and translational applications, we demonstrated the high degree of specificity for gene targeting, gene silencing, and chromatin modification possible with Cas9 repressors. The specificity and effectiveness of RNA-guided transcriptional repressors for silencing endogenous genes are promising characteristics for mechanistic studies of gene regulation and cell phenotype. Furthermore, our results support the use of Cas9-based repressors as a platform for novel gene therapy strategies. We developed an in vivo AAV-based gene repression system for silencing endogenous genes in a mouse model. Together, these studies demonstrate the utility of gene repression tools for guiding cell phenotype and the potential of the RNA-guided CRISPR/Cas9 platform for applications such as causal studies of gene regulatory mechanisms and gene therapy.
Resumo:
Secure Access For Everyone (SAFE), is an integrated system for managing trust
using a logic-based declarative language. Logical trust systems authorize each
request by constructing a proof from a context---a set of authenticated logic
statements representing credentials and policies issued by various principals
in a networked system. A key barrier to practical use of logical trust systems
is the problem of managing proof contexts: identifying, validating, and
assembling the credentials and policies that are relevant to each trust
decision.
SAFE addresses this challenge by (i) proposing a distributed authenticated data
repository for storing the credentials and policies; (ii) introducing a
programmable credential discovery and assembly layer that generates the
appropriate tailored context for a given request. The authenticated data
repository is built upon a scalable key-value store with its contents named by
secure identifiers and certified by the issuing principal. The SAFE language
provides scripting primitives to generate and organize logic sets representing
credentials and policies, materialize the logic sets as certificates, and link
them to reflect delegation patterns in the application. The authorizer fetches
the logic sets on demand, then validates and caches them locally for further
use. Upon each request, the authorizer constructs the tailored proof context
and provides it to the SAFE inference for certified validation.
Delegation-driven credential linking with certified data distribution provides
flexible and dynamic policy control enabling security and trust infrastructure
to be agile, while addressing the perennial problems related to today's
certificate infrastructure: automated credential discovery, scalable
revocation, and issuing credentials without relying on centralized authority.
We envision SAFE as a new foundation for building secure network systems. We
used SAFE to build secure services based on case studies drawn from practice:
(i) a secure name service resolver similar to DNS that resolves a name across
multi-domain federated systems; (ii) a secure proxy shim to delegate access
control decisions in a key-value store; (iii) an authorization module for a
networked infrastructure-as-a-service system with a federated trust structure
(NSF GENI initiative); and (iv) a secure cooperative data analytics service
that adheres to individual secrecy constraints while disclosing the data. We
present empirical evaluation based on these case studies and demonstrate that
SAFE supports a wide range of applications with low overhead.