Reliability Analysis of Nanocrystal Embedded High-k Nonvolatile Memories

The evolution of the MOSFET technology has been driven by the aggressive shrinkage of the device size to improve the device performance and to increase the circuit density. Currently, many research demonstrated that the continuous polycrystalline silicon film in the floating-gate dielectric could be replaced with nanocrystal (nc) embedded high-k thin film to minimize the charge loss due to the defective thin tunnel dielectric layer. This research deals with both the statistical aspect of reliability and electrical aspect of reliability characterization as well. In this study, the Zr-doped HfO2 (ZrHfO) high-k MOS capacitors, which separately contain the nanocrystalline zinc oxide (nc-ZnO), silicon (nc-Si), Indium Tin Oxide (nc-ITO) and ruthenium (nc-Ru) are studied on their memory properties, charge transportation mechanism, ramp-relax test, accelerated life tests, failure rate estimation and thermal effect on the above reliability properties. C-V hysteresis result show that the amount of charges trapped in nanocrystal embedded films is in the order of nc-ZnO\u3enc-Ru\u3enc-Si~nc-ITO, which might probably be influenced by the EOT of each sample. In addition, all the results show that the nc-ZnO embedded ZrHfO non-volatile memory capacitor has the best memory property and reliability. In this study, the optimal burn-in time for this kind of device has been also investigated with nonparametric Bayesian analysis. The results show the optimal burn-in period for nc-ZnO embedded high-k device is 5470s with the maximum one-year mission reliability

Business Value of Big Data Analytics:A Systems-Theoretic Approach and Empirical Test

Although big data analytics have been widely considered a key driver of marketing and innovation processes, whether and how big data analytics create business value has not been fully understood and empirically validated at a large scale. Taking social media analytics as an example, this paper is among the first attempts to theoretically explain and empirically test the market performance impact of big data analytics. Drawing on the systems theory, we explain how and why social media analytics create super-additive value through the synergies in functional complementarity between social media diversity for gathering big data from diverse social media channels and big data analytics for analyzing the gathered big data. Furthermore, we deepen our theorizing by considering the difference between small and medium enterprises (SMEs) and large firms in the required integration effort that enables the synergies of social media diversity and big data analytics. In line with this theorizing, we empirically test the synergistic effect of social media diversity and big data analytics by using a recent large-scale survey data set from 18,816 firms in Italy. We find that social media diversity and big data analytics have a positive interaction effect on market performance, which is more salient for SMEs than for large firms

CCDWT-GAN: Generative Adversarial Networks Based on Color Channel Using Discrete Wavelet Transform for Document Image Binarization

To efficiently extract the textual information from color degraded document images is an important research topic. Long-term imperfect preservation of ancient documents has led to various types of degradation such as page staining, paper yellowing, and ink bleeding; these degradations badly impact the image processing for information extraction. In this paper, we present CCDWT-GAN, a generative adversarial network (GAN) that utilizes the discrete wavelet transform (DWT) on RGB (red, green, blue) channel splited images. The proposed method comprises three stages: image preprocessing, image enhancement, and image binarization. This work conducts comparative experiments in the image preprocessing stage to determine the optimal selection of DWT with normalization. Additionally, we perform an ablation study on the results of the image enhancement stage and the image binarization stage to validate their positive effect on the model performance. This work compares the performance of the proposed method with other state-of-the-art (SOTA) methods on DIBCO and H-DIBCO ((Handwritten) Document Image Binarization Competition) datasets. The experimental results demonstrate that CCDWT-GAN achieves a top two performance on multiple benchmark datasets, and outperforms other SOTA methods

Correlation of Copper Interaction, Copper-Driven Aggregation, and Copper-Driven H2O2 Formation with Aβ40 Conformation

The neurotoxicity of Aβ is associated with the formation of free radical by interacting with redox active metals such as Cu2+. However, the relationship between ion-interaction, ion-driven free radical formation, and Aβ conformation remains to be further elucidated. In the present study, we investigated the correlation of Cu2+ interaction and Cu2+-driven free radical formation with Aβ40 conformation. The Cu2+-binding affinity for Aβ40 in random coiled form is 3-fold higher than that in stable helical form. Unexpectedly but interestingly, we demonstrate in the first time that the stable helical form of Aβ40 can induce the formation of H2O2 by interacting with Cu2+. On the other hand, the H2O2 generation is repressed at Aβ/Cu2+ molar ratio ≥1 when Aβ40 adopts random coiled structure. Taken together, our result demonstrates that Aβ40 adopted a helical structure that may play a key factor for the formation of free radical with Cu2+ ions

Urinary Neutrophil Gelatinase-Associated Lipocalin Is a Potential Biomarker for Renal Damage in Patients with Systemic Lupus Erythematosus

Neutrophil gelatinase-associated lipocalin (NGAL) has been demonstrated to be a novel biomarker in acute and chronic kidney disease. We hypothesized that 24-hour urinary NGAL excretion may be a predictor for renal damage in patients with systemic lupus erythematosus (SLE). Thirty-four SLE patients with renal involvement (SLE-renal group), 8 SLE patients without renal involvement (SLE-nonrenal group), 14 patients with non-SLE autoimmune diseases (disease control or DC group), and 12 healthy volunteers (normal control or NC group) were compared for 24-hour urinary excretion of NGAL and different cytokines. We found that the 24-hour urinary NGAL excretion in the SLE-renal group was higher than that in the SLE-non-renal, DC, and NC groups. However, the excretion of interleukin-10, transforming growth factor-β1, and tumor necrosis factor-α was not different between the SLE-renal and SLE-non-renal groups. Furthermore, NGAL excretion in the SLE-renal group was correlated with serum creatinine levels and creatinine clearance, but not with the SLE Disease Activity Index score. Multivariate logistic regression analysis and receiver operating characteristic curve analysis revealed that 24-hour urinary NGAL excretion is a potential biomarker for renal damage in SLE patients, with higher sensitivity and specificity than anti-dsDNA antibody titers

Certified Robustness of Quantum Classifiers against Adversarial Examples through Quantum Noise

Recently, quantum classifiers have been known to be vulnerable to adversarial attacks, where quantum classifiers are fooled by imperceptible noises to have misclassification. In this paper, we propose one first theoretical study that utilizing the added quantum random rotation noise can improve the robustness of quantum classifiers against adversarial attacks. We connect the definition of differential privacy and demonstrate the quantum classifier trained with the natural presence of additive noise is differentially private. Lastly, we derive a certified robustness bound to enable quantum classifiers to defend against adversarial examples supported by experimental results.Comment: Submitted to IEEE ICASSP 202

Adjuvant chemotherapy and survival outcomes in rectal cancer patients with good response (ypT0-2N0) after neoadjuvant chemoradiotherapy and surgery: A retrospective nationwide analysis

BackgroundFor rectal cancer, it remains unclear how to incorporate tumor response to neoadjuvant chemoradiotherapy (nCRT) when deciding whether to give adjuvant chemotherapy. In this study, we aim to determinate the survival benefit of adjuvant chemotherapy for rectal cancer patients with good response (ypT0-2N0) after nCRT and surgery.MethodsThe study cohort included 720 rectal cancer patients who had good response (ypT0-2N0) after nCRT and surgery, who did or did not receive adjuvant chemotherapy between January 2007 and December 2017, from the Taiwan Cancer Registry and National Health Insurance Research database. The Kaplan–Meier method, log-rank tests, and Cox regression analysis were performed to investigate the effect of adjuvant chemotherapy on 5-year overall survival (OS) and disease-free survival (DFS).ResultsOf 720 patients, 368 (51.1%) received adjuvant chemotherapy and 352 (48.9%) did not. Patients who received adjuvant chemotherapy were more likely to be female, younger (≤ 65), with advanced clinical T (3-4)/N (1-2) classification and ypT2 classification. No significant difference in 5-year OS (p=0.681) or DFS (p=0.942) were observed by receipt of adjuvant chemotherapy or not. Multivariable analysis revealed adjuvant chemotherapy was not associated with better OS (adjusted hazard ratio [aHR], 1.03; 95% Confidence Interval [CI], 0.88-1.21) or DFS (aHR, 1.05; 95% CI, 0.89-1.24). Stratified analysis for OS and DFS found no significant protective effect in the use of adjuvant chemotherapy, even for those with advanced clinical T or N classification.ConclusionAdjuvant chemotherapy may be omitted in rectal cancer patients with good response (ypT0-2N0) after nCRT and surgery

Hedgehog overexpression leads to the formation of prostate cancer stem cells with metastatic property irrespective of androgen receptor expression in the mouse model

<p>Abstract</p> <p>Background</p> <p>Hedgehog signalling has been implicated in prostate tumorigenesis in human subjects and mouse models, but its effects on transforming normal basal/stem cells toward malignant cancer stem cells remain poorly understood.</p> <p>Methods</p> <p>We produced pCX-shh-IG mice that overexpress Hedgehog protein persistently in adult prostates, allowing for elucidation of the mechanism during prostate cancer initiation and progression. Various markers were used to characterize and confirm the transformation of normal prostate basal/stem cells into malignant cancer stem cells under the influence of Hedgehog overexpression.</p> <p>Results</p> <p>The pCX-shh-IG mice developed prostatic intraepithelial neoplasia (PIN) that led to invasive and metastatic prostate cancers within 90 days. The prostate cancer was initiated through activation of P63⁺basal/stem cells along with simultaneous activation of Hedgehog signalling members, suggesting that P63⁺/Patch1⁺and P63⁺/Smo⁺cells may serve as cancer-initiating cells and progress into malignant prostate cancer stem cells (PCSCs). In the hyperplastic lesions and tumors, the progeny of PCSCs differentiated into cells of basal-intermediate and intermediate-luminal characteristics, whereas rare ChgA⁺neuroendocrine differentiation was seen. Furthermore, in the metastatic loci within lymph nodes, kidneys, and lungs, the P63⁺PCSCs formed prostate-like glandular structures, characteristic of the primitive structures during early prostate development. Besides, androgen receptor (AR) expression was detected heterogeneously during tumor progression. The existence of P63⁺/AR^-, CK14⁺/AR^-and CD44⁺/AR^-progeny indicates direct procurement of AR^-malignant cancer trait.</p> <p>Conclusions</p> <p>These data support a cancer stem cell scenario in which Hedgehog signalling plays important roles in transforming normal prostate basal/stem cells into PCSCs and in the progression of PCSCs into metastatic tumor cells.</p