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In this paper, we propose a new behavioral thermal modeling technique for high-performance microprocessors at package level. Firstly, the new approach applies the subspace identification method with the consideration of practical power maps with correlated power signals. We show that the input power signal needs to meet an independence requirement to ensure the model predictability and propose an iterative process to build the models with given error bounds. Secondly, we show that thermal systems fundamentally are nonlinear and then propose a piecewise linear (PWL) scheme to deal with nonlinear effects. The experimental results validated the proposed method on a realistic packaged integrated system modeled by the multi-domain/physics commercial tool, COMSOL. The new piecewise linear models can model thermal behaviors over wide temperature ranges or over different thermal boundary convective conditions due to different fan speeds. Further, the PWL modeling technique can lead to much smaller model order without accuracy loss, which translates to significant savings in both the simulation time and the time required to identify the reduced models compared to the simple modeling method by using the high order models. © 2013 Elsevier B.V. All rights reserved.

This paper proposes a new thermal modeling method for package design of high-performance microprocessors. The new approach builds the thermal behavioral models from the given accurate temperature and power information by means of the subspace method. The subspace method, however, may suffer predictability problem when the practical power is given as a number of power maps where power inputs are spatially correlated. We show that the input power signal needs to meet some dependency requirements to ensure model predictability. We develop a new algorithm, which generates independent power maps to meet the spatial rank requirement and can also automatically select the order of the resulting thermal models for the given error bounds. Experimental results validates the proposed method on a practical microprocessor package constructed via COMSOL software under practical power signal inputs.

Aims: The dysregulation of TGF‐β signaling is a crucial pathophysiological process in tumorigenesis and progression. LncRNAs have diverse biological functions and are significant participants in the regulation of tumor signaling pathways. However, the clinical value of lncRNAs related to TGF‐β signaling in glioma is currently unclear. Methods: Data on glioma's RNA‐seq transcriptome, somatic mutation, DNA methylation data, and clinicopathological information were derived from the CGGA and TCGA databases. A prognostic lncRNA signature was constructed by Cox and LASSO regression analyses. TIMER2.0 database was utilized to deduce immune infiltration characteristics. "ELMER v.2" was used to reconstruct TF‐methylation‐gene regulatory network. Immunotherapy and chemotherapy response predictions were implemented by the TIDE algorithm and GDSC database, respectively. In vitro and in vivo experiments were conducted to verify the results and clarify the regulatory mechanism of lncRNA. Results: In glioma, a TGF‐β signaling‐related 15‐lncRNA signature was constructed, including AC010173.1, HOXA‐AS2, AC074286.1, AL592424.1, DRAIC, HOXC13‐AS, AC007938.1, AC010729.1, AC013472.3, AC093895.1, AC131097.4, AL606970.4, HOXC‐AS1, AGAP2‐AS1, and AC002456.1. This signature proved to be a reliable prognostic tool, with high risk indicating an unfavorable prognosis and being linked to malignant clinicopathological and genomic mutation traits. Risk levels were associated with different immune infiltration landscapes, where high risk was indicative of high levels of macrophage infiltration. In addition, high risk also suggested better immunotherapy and chemotherapy response. cg05987823 was an important methylation site in glioma progression, and AP‐1 transcription factor family participated in the regulation of signature lncRNA expression. AGAP2‐AS1 knockdown in in vitro and in vivo experiments inhibited the proliferation, migration, and invasion of glioma cells, as well as the growth of glioma, by downregulating the expression levels of NF‐κB and ERK 1/2 in the TGF‐β signaling pathway. Conclusions: A prognostic lncRNA signature of TGF‐β signaling was established in glioma, which can be used for prognostic judgment, immune infiltration status inference, and immunotherapy response prediction. AGAP2‐AS1 plays an important role in glioma progression. [ABSTRACT FROM AUTHOR]

Artefacts in high‐resolution multidimensional nuclear magnetic resonance (NMR) spectra, known as t1 noise, can significantly downgrade the spectral quality and remain a significant noise source, limiting the sensitivity of most two‐dimensional NMR experiments. In addition to highly sensitive hardware and experimental designs, data post‐processing is a relatively simple and cost‐effective method for suppressing t1 noise. In this study, histograms and quantiles were used to obtain a robust estimation of noise level. We constructed a weighted matrix to suppress the t1 noise. The weighted matrix was calculated from the logistic functions, which were adaptively computed from the spectrum. The proposed method is robust and effective in both simulations and actual experiments. Further, it can maintain the quantitative relationship of the spectrogram and is suitable for various complex peak types. [ABSTRACT FROM AUTHOR]

A survey of a group of distance graduate students showed their strong preference for easy and fast information retrieval and a significant association between motivation for using information and field of study. Motivation and field of study also explained differences in primary information source selection and use of home institution libraries.

This paper discusses the applications and importance of content-based information retrieval technology in digital libraries. It generalizes the process and analyzes current examples in four areas of the technology. Content-based […]

Introduction: Retinitis pigmentosa (RP) caused by the photoreceptor cell degeneration is currently incurable and leads to partial or complete blindness eventually. 3,5-dimethoxy-4-hydroxy myricanol (DM) is a novel compound isolated from the leaves of Micromelum integerrimum, with proliferative activities on NIH3T3 cells. This study was to investigate whether DM could mitigate retinal degeneration of rd10 mice, a well-characterized mouse model of RP. Materials and method: Rd10 mice were treated with DM daily by intraperitoneal injection from postnatal day 12 (P12) to P26. Electroretinography (ERG) reflects the mass response of photoreceptor cells and was used to test the outer retinal function after DM treatment. Haematoxylin and Eosin staining was used to show the retinal morphology and evaluate the rod photoreceptor cell loss. TUNEL assay was used to detect the apoptosis-positive cells. Inflammatory factors were measured by ELISA to show the inflammatory response. Real-time PCR and western blot were applied to measure the gene and protein change to explore the underlying mechanisms. Results: Results showed that DM significantly improved the retinal function by increasing the ERG amplitude, preserving the retinal morphology, reducing photoreceptor cell apoptosis, decreasing inflammatory response, and inhibiting endoplasmic reticulum stress in rd10 mice. Conclusion: This is the first time when the protective effects of DM against photoreceptor cell degeneration of rd10 mice have been demonstrated, providing scientific rationale to develop DM as a potential agent to treat RP. [ABSTRACT FROM AUTHOR]