Scalable Analysis, Verification and Design of IC Power Delivery

Due to recent aggressive process scaling into the nanometer regime, power delivery network design faces many challenges that set more stringent and specific requirements to the EDA tools. For example, from the perspective of analysis, simulation efficiency for large grids must be improved and the entire network with off-chip models and nonlinear devices should be able to be analyzed. Gated power delivery networks have multiple on/off operating conditions that need to be fully verified against the design requirements. Good power delivery network designs not only have to save the wiring resources for signal routing, but also need to have the optimal parameters assigned to various system components such as decaps, voltage regulators and converters. This dissertation presents new methodologies to address these challenging problems. At first, a novel parallel partitioning-based approach which provides a flexible network partitioning scheme using locality is proposed for power grid static analysis. In addition, a fast CPU-GPU combined analysis engine that adopts a boundary-relaxation method to encompass several simulation strategies is developed to simulate power delivery networks with off-chip models and active circuits. These two proposed analysis approaches can achieve scalable simulation runtime. Then, for gated power delivery networks, the challenge brought by the large verification space is addressed by developing a strategy that efficiently identifies a number of candidates for the worst-case operating condition. The computation complexity is reduced from O(2^N) to O(N). At last, motivated by a proposed two-level hierarchical optimization, this dissertation presents a novel locality-driven partitioning scheme to facilitate divide-and-conquer-based scalable wire sizing for large power delivery networks. Simultaneous sizing of multiple partitions is allowed which leads to substantial runtime improvement. Moreover, the electric interactions between active regulators/converters and passive networks and their influences on key system design specifications are analyzed comprehensively. With the derived design insights, the system-level co-design of a complete power delivery network is facilitated by an automatic optimization flow. Results show significant performance enhancement brought by the co-design

Global Structure-Aware Diffusion Process for Low-Light Image Enhancement

This paper studies a diffusion-based framework to address the low-light image enhancement problem. To harness the capabilities of diffusion models, we delve into this intricate process and advocate for the regularization of its inherent ODE-trajectory. To be specific, inspired by the recent research that low curvature ODE-trajectory results in a stable and effective diffusion process, we formulate a curvature regularization term anchored in the intrinsic non-local structures of image data, i.e., global structure-aware regularization, which gradually facilitates the preservation of complicated details and the augmentation of contrast during the diffusion process. This incorporation mitigates the adverse effects of noise and artifacts resulting from the diffusion process, leading to a more precise and flexible enhancement. To additionally promote learning in challenging regions, we introduce an uncertainty-guided regularization technique, which wisely relaxes constraints on the most extreme regions of the image. Experimental evaluations reveal that the proposed diffusion-based framework, complemented by rank-informed regularization, attains distinguished performance in low-light enhancement. The outcomes indicate substantial advancements in image quality, noise suppression, and contrast amplification in comparison with state-of-the-art methods. We believe this innovative approach will stimulate further exploration and advancement in low-light image processing, with potential implications for other applications of diffusion models. The code is publicly available at https://github.com/jinnh/GSAD.Comment: Accepted to NeurIPS 202

Enhanced production of highly methylated brGDGTs linked to anaerobic bacteria from sediments of the Mariana Trench

Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are bacterial membrane lipids that are widely used in terrestrial paleoclimatic reconstructions. Recent studies have reported that brGDGTs can also be produced by marine bacteria. However, the environmental factors influencing marine-derived brGDGTs and their source organisms remain largely unknown. Here, we investigated the distribution and composition of brGDGTs and a suite of their putative derivatives called overly branched GDGTs (obGDGTs) in the Mariana Trench core sediments (water depth 8300 m, core length 320 cm), as well as the composition of bacterial communities. The ratio of the branched over isoprenoid tetraethers (BIT) was 0.03-0.21 (average 0.07; SD = 0.04; n = 21) and the ratio ΣIIIa/ΣIIa of brGDGTs was 0.93-7.47 (average 3.39; SD = 1.73; n = 21), which support the in situ production of brGDGTs. Co-occurrence network analysis revealed that a total of 33 types of bacteria at the order level (e.g., Armatimonadota DG-56, Proteobacteria Rhodospirillales, Chloroflexi SAR202_clade) were closely related to the distribution of brGDGTs and obGDGTs, which could be potential sources for these compounds. The abrupt increase in brGDGT and obGDGT concentrations in deeper oxygen-depleted sediments and their good correlations with anaerobic bacterial abundances suggest that these brGDGTs and obGDGTs may be produced by anaerobic bacteria residing in the anoxic sediments. Considerable variation in the degrees of methylation and cyclization of brGDGTs (obGDGTs) under different redox conditions indicate that sediment oxygen levels may have a profound impact on the presence and abundance of brGDGTs and obGDGTs, which should be considered when applying them for paleo-temperature or pH reconstructions. This study shows that brGDGTs and obGDGTs obtained from the Mariana Trench were probably produced by a variety of bacterial phyla indigenous in the hadal ocean, which are different from Acidobacteria commonly considered to be major terrestrial sources of brGDGTs

A Study of Young Chinese Intentions to Purchase “Online Paid Knowledge”: An Extended Technological Acceptance Model

Under the catalysis of knowledge anxiety and cognitive surplus, knowledge sharing platforms has experienced rapid growth, which has accelerated the integration of knowledge resources online. As with all new successful and sustainable business products, the consumers will play an important role in the future development of online paid knowledge. Therefore, we constructed an extended technological acceptance model by examining factors that influence young Chinese people's willingness to pay for online paid knowledge. The study surveyed 405 young Chinese participants, in which the extended technological acceptance model was tested by using structural equation modeling. Findings indicate that perceived ease of use is positively associated with perceived usefulness and associated attitudes, whereas perceived usefulness and attitude is positively associated with purchase intention. Perceived risk and group conformity are found to indirectly affect consumers' willingness to pay. The study advances the current body of knowledge by empirically testing the impact of perceived risk and the role of cultural influence (group conformity) on purchasing intention. Finally, theoretical and practical implications are discussed

NLRP3 Inflammasome as a Molecular Marker in Diabetic Cardiomyopathy

Diabetic cardiomyopathy (DCM), a common consequence of longstanding diabetes mellitus, is initiated by death of cardiomyocyte. Hyperglycemia-induced reactive oxygen species (ROS) overproduction is a major contributor of the chronic low-grade inflammation that characterizes as the DCM. ROS may promote the activation of nucleotide-binding oligomerization domain like receptor (NLR) pyrin domain containing 3 (NLRP3) inflammasome, a novel regulator of inflammation and cell death, by nuclear factor-kB (NF-κB) and thioredoxin interacting/inhibiting protein (TXNIP). NLRP3 inflammasome regulates the death of cardiomyocyte and activation of fibroblast in DCM, which is involved in the structural and functional disorder of DCM. However, comprehensive understanding of molecular mechanisms linking NLRP3 inflammasome and disorder of cardiomyocyte and fibroblast in DCM is lacking. Here, we review the molecular mechanism(s) of NLRP3 inflammasome activation in response to hyperglycemia in DCM

Correlation Analysis Between Required Surgical Indexes and Complications in Patients With Coronary Heart Disease

A total of 215 patients with coronary heart disease (CHD) were analyzed with SPSS. Samples of different genders showed significance in the obtuse marginal branch of the left circumflex branch × 1, the diagonal branch D1 × 1, and the ms PV representation. Patients with left circumflex branch occlusion are more male and tend to be younger. Age displayed a positive correlation with left intima-media thickness (IMT) and right IMT. This indicated that as age increases, the values of left IMT and right IMT increase. Samples of different CHD types showed significance in the obtuse marginal branch of the left circumflex branch × 1, the middle part of RCA × 1, and the middle part of the left anterior descending branch × 1.5. For non-ST-segment elevation angina pectoris with acute total vascular occlusion, the left circumflex artery is the most common, followed by the right coronary artery and anterior descending branch. Ultrasound of carotid IMT in patients with CHD can predict changes in left ventricular function, but no specific correlation between left and right common carotid IMT was found. Samples with or without the medical history of ASCVD showed significance in the branch number of coronary vessel lesions. The value of the branch number of coronary vessel lesions in patients with atherosclerotic cardiovascular disease (ASCVD) was higher than in those without ASCVD. The occurrence of complication is significantly relative with the distance of left circumflex branch × 1, the middle segment of left anterior descending branch × 1.5, and the distance of left anterior descending branch × 1. For patients without complications, the values in the distal left circumflex branch × 1, the middle left anterior descending branch × 1.5, and the distal left anterior descending branch × 1 were higher than those for patients with complications. The VTE scores showed a positive correlation with the proximal part of RCA × 1, the branch number of coronary vessel lesions, the posterior descending branch of left circumflex branch × 1, the distal part of left circumflex branch × 1, and the middle part of left anterior descending branch × 1.5

An integrative multi-platform analysis for discovering biomarkers of osteosarcoma

<p>Abstract</p> <p>Background</p> <p>SELDI-TOF-MS (Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry) has become an attractive approach for cancer biomarker discovery due to its ability to resolve low mass proteins and high-throughput capability. However, the analytes from mass spectrometry are described only by their mass-to-charge ratio (<it>m</it>/<it>z</it>) values without further identification and annotation. To discover potential biomarkers for early diagnosis of osteosarcoma, we designed an integrative workflow combining data sets from both SELDI-TOF-MS and gene microarray analysis.</p> <p>Methods</p> <p>After extracting the information for potential biomarkers from SELDI data and microarray analysis, their associations were further inferred by link-test to identify biomarkers that could likely be used for diagnosis. Immuno-blot analysis was then performed to examine whether the expression of the putative biomarkers were indeed altered in serum from patients with osteosarcoma.</p> <p>Results</p> <p>Six differentially expressed protein peaks with strong statistical significances were detected by SELDI-TOF-MS. Four of the proteins were up-regulated and two of them were down-regulated. Microarray analysis showed that, compared with an osteoblastic cell line, the expression of 653 genes was changed more than 2 folds in three osteosarcoma cell lines. While expression of 310 genes was increased, expression of the other 343 genes was decreased. The two sets of biomarkers candidates were combined by the link-test statistics, indicating that 13 genes were potential biomarkers for early diagnosis of osteosarcoma. Among these genes, cytochrome c1 (CYC-1) was selected for further experimental validation.</p> <p>Conclusion</p> <p>Link-test on datasets from both SELDI-TOF-MS and microarray high-throughput analysis can accelerate the identification of tumor biomarkers. The result confirmed that CYC-1 may be a promising biomarker for early diagnosis of osteosarcoma.</p