A Review of Bayesian Methods in Electronic Design Automation

The utilization of Bayesian methods has been widely acknowledged as a viable solution for tackling various challenges in electronic integrated circuit (IC) design under stochastic process variation, including circuit performance modeling, yield/failure rate estimation, and circuit optimization. As the post-Moore era brings about new technologies (such as silicon photonics and quantum circuits), many of the associated issues there are similar to those encountered in electronic IC design and can be addressed using Bayesian methods. Motivated by this observation, we present a comprehensive review of Bayesian methods in electronic design automation (EDA). By doing so, we hope to equip researchers and designers with the ability to apply Bayesian methods in solving stochastic problems in electronic circuits and beyond.Comment: 24 pages, a draft version. We welcome comments and feedback, which can be sent to [email protected]

The Structure and Expression of the Gene Coding for Bindin, a Species Specific Sea Urchin Protein

Bindin is a major protein of the sea urchin sperm acrosome granule which mediates the species-specific adhesion and binding of sperm to the egg. Bindin protein has been purified from the sperm of the sea urchin Strongylocentrotus purpuratus (S. purpuratus) and the protein has been partially sequenced. The work presented in this thesis is the isolation and the sequence analysis of bindin cDNA and gene, and the study of the expression of the bindin gene. A λgt10 cDNA library was constructed from S. purpuratus testes poly(A)+ RNA. The library which was screened with a synthetic DNA probe prepared according to the known protein sequence yielded clones representing bindin cDNA. One of these clones containing an 1873 base pair (bp) insert was sequenced and found to code for a bindin precursor (prebindin) which is twice as large as the mature bindin protein. Upon immunoprecipitation with bindin antibody, the testes poly(A)+ RNA in vitro translation product yields a larger precursor. The bind in cDNA was used to study the tissue specificity of expression. The results show that bindin is a sperm specific protein -- its messenger RNA is not detected in the eggs, ovaries, early embryos, coelomocytes, tubefeet, lantern tissue or intestine that we tested. Sperm DNA isolated from several individuals was probed with bindin cDNA and reveals that there is one bindin gene per haploid genome. Haploid female coelomocyte DNA also possesses one bindin gene. Bindin cDNA was used to screen an EcoRI partially digested sea urchin S. purpuratus DNA charon 4A library. A clone containing a 14 kilobase (Kb) insert hybridized to the 3' end of the bindin cDNA. It also has overlapping restriction enzyme recognition sites with the 3' end of the bindin cDNA. There is an intron in the genomic clone upstream of this overlapping region since it did not hybridize with bindin cDNA. A λgt10 mini-genomic library was made and a 1.3 Kb genomic DNA clone which hybridized with bindin cDNA has been characterized and partially sequenced. It contains a 219 bp exon in which the 5' end lies 2 bp upstream of the AUG translation initiation codon. This exon is flanked by introns on either side. Thus, there are at least three introns in the bindin gene.</p

Rare Event Probability Learning by Normalizing Flows

A rare event is defined by a low probability of occurrence. Accurate estimation of such small probabilities is of utmost importance across diverse domains. Conventional Monte Carlo methods are inefficient, demanding an exorbitant number of samples to achieve reliable estimates. Inspired by the exact sampling capabilities of normalizing flows, we revisit this challenge and propose normalizing flow assisted importance sampling, termed NOFIS. NOFIS first learns a sequence of proposal distributions associated with predefined nested subset events by minimizing KL divergence losses. Next, it estimates the rare event probability by utilizing importance sampling in conjunction with the last proposal. The efficacy of our NOFIS method is substantiated through comprehensive qualitative visualizations, affirming the optimality of the learned proposal distribution, as well as a series of quantitative experiments encompassing $10$ distinct test cases, which highlight NOFIS's superiority over baseline approaches.Comment: 16 pages, 5 figures, 2 table

Research and Simulation of DC Microgrid Three-Phase AC-DC Converter Control Strategy Based on Double Loop

The new voltage and current double loop control strategy is proposed to solve the DC microgrid bus voltage fluctuation caused by loads fluctuation, parameters perturbation and unbalanced three-phase power supply. Firstly, the dq axis mathematical model of three-phase AC-DC bidirectional converter in DC microgrid is analyzed and established, and then the controllers are designed according to the dq axis mathematical model. The outer loop is a voltage loop based on variable gain linear extended state observer (VGLESO) and sliding mode theory. VGLESO can not only effectively overcome the problem of peak output of traditional high-gain LESO in the initial stage of operation, and ensure that the system has good startup characteristics, but also quickly track and compensate the total disturbance of the system without additional current sensors. The inner loop is a current loop based on adaptive PI, which can eliminate the influence of system parameters perturbation on bus voltage and improve the system\u27s adaptability. Under the action of the inner and outer loops, the system has good dynamic and static characteristics. Finally, the feasibility and correctness of the control strategy are verified by Matlab/Simulink

Nominality Score Conditioned Time Series Anomaly Detection by Point/Sequential Reconstruction

Time series anomaly detection is challenging due to the complexity and variety of patterns that can occur. One major difficulty arises from modeling time-dependent relationships to find contextual anomalies while maintaining detection accuracy for point anomalies. In this paper, we propose a framework for unsupervised time series anomaly detection that utilizes point-based and sequence-based reconstruction models. The point-based model attempts to quantify point anomalies, and the sequence-based model attempts to quantify both point and contextual anomalies. Under the formulation that the observed time point is a two-stage deviated value from a nominal time point, we introduce a nominality score calculated from the ratio of a combined value of the reconstruction errors. We derive an induced anomaly score by further integrating the nominality score and anomaly score, then theoretically prove the superiority of the induced anomaly score over the original anomaly score under certain conditions. Extensive studies conducted on several public datasets show that the proposed framework outperforms most state-of-the-art baselines for time series anomaly detection.Comment: NeurIPS 2023 (https://neurips.cc/virtual/2023/poster/70582

Provable Routing Analysis of Programmable Photonics

Programmable photonic integrated circuits (PPICs) are an emerging technology recently proposed as an alternative to custom-designed application-specific integrated photonics. Light routing is one of the most important functions that need to be realized on a PPIC. Previous literature has investigated the light routing problem from an algorithmic or experimental perspective, e.g., adopting graph theory to route an optical signal. In this paper, we also focus on the light routing problem, but from a complementary and theoretical perspective, to answer questions about what is possible to be routed. Specifically, we demonstrate that not all path lengths (defined as the number of tunable basic units that an optical signal traverses) can be realized on a square-mesh PPIC, and a rigorous realizability condition is proposed and proved. We further consider multi-path routing, where we provide an analytical expression on path length sum, upper bounds on path length mean/variance, and the maximum number of realizable paths. All of our conclusions are proven mathematically. Illustrative potential optical applications using our observations are also presented

Rare solid and cystic presentation of hemangiopericytoma/ solitary fibrous tumor: A case report

Hemangiopericytoma/Solitary Fibrous Tumor (HPC/SFT) is a rare fibroblastic sarcoma characterized by hyper-vasculature and STAT6 trans-nuclear localization. Cystic HPC/SFT is extremely rare. Due to the scarcity of cystic HPC/SFT cases, diagnostic and treatment guidelines are not well established. To our knowledge, we present the first case of cystic HPC/SFT observed in the liver. In addition, the patient had over 6 years of recurrent hypervascular solid HPC/SFT in the brain, bone, leptomeninges, liver and lung prior to developing a cystic HPC/SFT. Briefly, a 37-year-old Caucasian female with a history of HPC/SFT presented with several enlarging cystic hepatic lesions on surveillance MRI. The cystic/nonenhancing nature of these liver metastases were confirmed by contrast-enhanced ultrasound. Due to diagnostic uncertainty, two of these hepatic cysts were removed laparoscopically and pathology confirmed cystic HPC/SFT with a high MIB-1 index. Previously, in 2014, the patient was diagnosed with solid intracranial grade III pseudopapillary mesenchymal HPC/SFT in the posterior fossa and underwent subtotal resection followed by external beam radiation. In 2017, she had recurrent intracranial, vertebral, and intraspinal intradural extramedullary HPC/SFTs followed by surgery, proton therapy, and SRS radiotherapy. In 2019, after an uneventful pregnancy and birth, routine surveillance revealed metastases in the liver requiring an extended right hepatectomy. In 2020-2021 two solid hypervascular hepatic HPC/SFT were found and treated with microwave ablation. Shortly afterwards, several rapidly growing hepatic cystic HPC/SFT lesions developed. Of note, she has not taken any systemic therapy, indicating the cystic tumors are from metastases rather than cystic degradation as a sequela of therapy. Overall, this case highlights that cystic metastasis are a potential clinical manifestation of solid HPC/SFT. Moreover, cystic HPC/SFT can co-exist with the more typical primary solid hypervascular HPC/SFTs in the same patient. Lastly, in this case cystic HPC/SFT had a higher growth rate and propensity to metastasize as compared to the solid equivalent.Peer reviewe

Isothiocyanates induce oxidative stress and suppress the metastasis potential of human non-small cell lung cancer cells

<p>Abstract</p> <p>Background</p> <p>Isothiocyanates are natural compounds found in consumable cruciferous vegetables. They have been shown to inhibit chemical carcinogenesis by a wide variety of chemical carcinogens in animal models. Recent studies have also shown that isothiocyanates have antitumor activity, inhibiting the growth of several types of cultured human cancer cells. Our previous study showed that PEITC inhibited human leukemia cells growth by inducing apoptosis. However, the effect of isothiocyanates on lung cancer cell metastasis has not been studied. In the present study, we investigated the inhibitory effects of BITC and PEITC on metastatic potential of highly metastatic human lung cancer L9981 cells.</p> <p>Methods</p> <p>Cell migration and invasion were measured by wound healing assay and transwell chemotaxis assay. Expression of metastasis-related genes was assessed by quantitative RT-PCR and Western blotting. The mechanisms of action were evaluated by flow cytometry, reporter assay and Western blotting.</p> <p>Results</p> <p>Our data showed that both BITC and PEITC inhibited L9981 cell growth in a dose-dependent manner, the IC50 values were 5.0 and 9.7 μM, respectively. Cell migrations were reduced to 8.1% and 16.5% of control, respectively; and cell invasions were reduced to 2.7% and 7.3% of control, respectively. Metastasis-related genes MMP-2, Twist and β-catenin were also modulated. BITC and PEITC inhibited cell survival signaling molecules Akt and NFκB activation. Moreover, BITC and PEITC increased ROS generation and caused GSH depletion. Pretreatment with NAC blocked BITC and PEITC induced ROS elevation and NFκB inhibition.</p> <p>Conclusion</p> <p>Our results indicated that BITC and PEITC suppress lung cancer cell metastasis potential by modulation of metastasis-related gene expression, inhibition of Akt/NFκB pathway. Induction of oxidative stress may play an important role.</p

A Genome-Wide Screen for Promoter Methylation in Lung Cancer Identifies Novel Methylation Markers for Multiple Malignancies

BACKGROUND: Promoter hypermethylation coupled with loss of heterozygosity at the same locus results in loss of gene function in many tumor cells. The “rules” governing which genes are methylated during the pathogenesis of individual cancers, how specific methylation profiles are initially established, or what determines tumor type-specific methylation are unknown. However, DNA methylation markers that are highly specific and sensitive for common tumors would be useful for the early detection of cancer, and those required for the malignant phenotype would identify pathways important as therapeutic targets. METHODS AND FINDINGS: In an effort to identify new cancer-specific methylation markers, we employed a high-throughput global expression profiling approach in lung cancer cells. We identified 132 genes that have 5′ CpG islands, are induced from undetectable levels by 5-aza-2′-deoxycytidine in multiple non-small cell lung cancer cell lines, and are expressed in immortalized human bronchial epithelial cells. As expected, these genes were also expressed in normal lung, but often not in companion primary lung cancers. Methylation analysis of a subset (45/132) of these promoter regions in primary lung cancer (n = 20) and adjacent nonmalignant tissue (n = 20) showed that 31 genes had acquired methylation in the tumors, but did not show methylation in normal lung or peripheral blood cells. We studied the eight most frequently and specifically methylated genes from our lung cancer dataset in breast cancer (n = 37), colon cancer (n = 24), and prostate cancer (n = 24) along with counterpart nonmalignant tissues. We found that seven loci were frequently methylated in both breast and lung cancers, with four showing extensive methylation in all four epithelial tumors. CONCLUSIONS: By using a systematic biological screen we identified multiple genes that are methylated with high penetrance in primary lung, breast, colon, and prostate cancers. The cross-tumor methylation pattern we observed for these novel markers suggests that we have identified a partial promoter hypermethylation signature for these common malignancies. These data suggest that while tumors in different tissues vary substantially with respect to gene expression, there may be commonalities in their promoter methylation profiles that represent targets for early detection screening or therapeutic intervention

Radar Maneuvering Target Detection Based on Product Scale Zoom Discrete Chirp Fourier Transform

Long-time coherent integration works to significantly increase the detection probability for maneuvering targets. However, during the observation time, the problems that often tend to occur are range cell migration (RCM) and Doppler frequency cell migration (DFCM), due to the high velocity and acceleration of the maneuvering target, which can reduce the detection of the maneuvering targets. In this regard, we propose a new coherent integration approach, based on the product scale zoom discrete chirp Fourier transform (PSZDCFT). Specifically, by introducing the zoom operation into the modified discrete chirp Fourier transform (MDCFT), the zoom discrete chirp Fourier transform (ZDCFT) can correctly estimate the centroid frequency and chirp rate of the linear frequency-modulated signal (LFM), regardless of whether the parameters of the LFM signal are outside the estimation scopes. Then, the scale operation, combined with ZDCFT, is performed on the radar echo signal in the range frequency slow time domain, to remove the coupling. Thereafter, a product operation is executed along the range frequency to inhibit spurious peaks and reinforce the true peak. Finally, the velocity and acceleration of the target estimated from the true peak position, are used to construct a phase compensation function to eliminate the RCM and DFCM, thus achieving coherent integration. The method is a linear transform without energy loss, and is suitable for low signal-to-noise (SNR) environments. Moreover, the method can be effectively fulfilled based on the chirp-z transform (CZT), which prevents the brute-force search. Thus, the method reaches a favorable tradeoff between anti-noise performance and computational load. Intensive simulations demonstrate the effectiveness of the proposed method