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In this paper, we study the interconnect design problem under a distributed RC delay model. We study the impact of technology factors on the interconnect designs and present general formulations of the interconnect topology design and wiresizing problems. We show that interconnect topology optimization can be achieved by computing optimal generalized rec-

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In this paper, a Spectral Stochastic Collocation Method(SSCM) is proposed for the capacitance extraction of interconnects with stochastic geometric variations for nanometer process technology. The proposed SSCM has several advantages over the existing methods. Firstly, compared with the PFA (Principal Factor Analysis) modeling of geometric variations, the K-L (Karhunen-Loeve) expansion involved in SSCM can be independent of the discretization of conductors, thus significantly reduces the computation cost. Secondly, compared with the perturbation method, the stochastic spectral method based on Homogeneous Chaos expansion has optimal (exponential) convergence rate, which makes SSCM applicable to most geometric variation cases. Furthermore, Sparse Grid combined with a MST (Minimum Spanning Tree) representation is proposed to reduce the number of sampling points and the computation time for capacitance extraction at each sampling point. Numerical experiments have demonstrated that SSCM can achieve higher accuracy and faster convergence rate compared with the perturbation method.

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SummaryNumerous studies have suggested the importance of leptin against autoimmune diseases such as systemic lupus erythematosus (SLE), multiple sclerosis (MS) and psoriasis. To summarize our current understanding of the role of leptin in inflammatory responses and rheumatoid arthritis (RA), a systematic review was conducted to assess the discrepancy of leptin in RA and its effect on immunity according to different studies. Recently, emerging data have indicated that leptin is involved in the pathological function of RA, which is common in autoimmune disorders. This review discusses the possible consequences of leptin levels in RA. Blocking the key signal pathways of leptin and inhibiting the leptin activity-like leptin antagonist may be a promising way for potential therapeutic treatment of RA at risk of detrimental effects. However, leptin was increased in patients with RA and may also regulate joint damage. Thus, more understanding of the mechanism of leptin in RA would be advantageous in the future.

This paper aims to explore RLC equivalent circuit synthesis method for reduced-order models of interconnect circuits obtained by Krylov subspace based model order reduction (MOR) methods. To guarantee pure RLC equivalent circuits can be synthesized for the reduced-order models, both the structures of input and output incidence matrices and the block structure of the circuit matrices should be preserved in the reduced-order models. Block structure preserving MOR methods such as SPRIM [1] and SAPOR [2] have been well established. In this paper, we propose an embeddable Input-Output structure Preserving Order Reduction (IOPOR) technique to further preserve the structures of input and output incidence matrices in the reduced-order models. By combining block structure preserving MOR methods and IOPOR technique, we develop an RLC equivalent circuit synthesis method RLCSYN (RLC SYNthesis). Inline diagonalization and regularization techniques are specifically proposed to enhance the robustness of inductance synthesis. The pure RLC model, high modeling accuracy, passivity guaranteed property and SPICE simulation robustness make RLCSYN more applicable in interconnect analysis, either for digital IC design or mixed signal IC simulation.

BackgroundLong-term continuous systolic blood pressure (SBP) and heart rate (HR) monitors are of tremendous value to medical (cardiovascular, circulatory and cerebrovascular management), wellness (emotional and stress tracking) and fitness (performance monitoring) applications, but face several major impediments, such as poor wearability, lack of widely accepted robust SBP models and insufficient proofing of the generalization ability of calibrated models.MethodsThis paper proposes a wearable cuff-less electrocardiography (ECG) and photoplethysmogram (PPG)-based SBP and HR monitoring system and many efforts are made focusing on above challenges. Firstly, both ECG/PPG sensors are integrated into a single-arm band to provide a super wearability. A highly convenient but challenging single-lead configuration is proposed for weak single-arm-ECG acquisition, instead of placing the electrodes on the chest, or two wrists. Secondly, to identify heartbeats and estimate HR from the motion artifacts-sensitive weak arm-ECG, a machine learning-enabled framework is applied. Then ECG-PPG heartbeat pairs are determined for pulse transit time (PTT) measurement. Thirdly, a PTT&HR-SBP model is applied for SBP estimation, which is also compared with many PTT-SBP models to demonstrate the necessity to introduce HR information in model establishment. Fourthly, the fitted SBP models are further evaluated on the unseen data to illustrate the generalization ability. A customized hardware prototype was established and a dataset collected from ten volunteers was acquired to evaluate the proof-of-concept system.ResultsThe semi-customized prototype successfully acquired from the left upper arm the PPG signal, and the weak ECG signal, the amplitude of which is only around 10% of that of the chest-ECG. The HR estimation has a mean absolute error (MAE) and a root mean square error (RMSE) of only 0.21 and 1.20 beats per min, respectively. Through the comparative analysis, the PTT&HR-SBP models significantly outperform the PTT-SBP models. The testing performance is 1.63 ± 4.44, 3.68, 4.71 mmHg in terms of mean error ± standard deviation, MAE and RMSE, respectively, indicating a good generalization ability on the unseen fresh data.ConclusionsThe proposed proof-of-concept system is highly wearable, and its robustness is thoroughly evaluated on different modeling strategies and also the unseen data, which are expected to contribute to long-term pervasive hypertension, heart health and fitness management.