Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Analysis of 3T DRAM Using FinFET Based with Leakage Reduction Techniques at 45 nm Technology

The proposed area of research is to reduce the power consumption, leakage voltage, leakage current and leakage power of DRAM while maintaining the competitive performance. The Fin FET approach is used in DRAM for high performance. Fin type field effect transistors (Fin FET) are capable substitutes for bulk CMOS at the nano-scale. Fin FET are double gate device. A Fin FET uses an intrinsic body. It greatly suppresses the device-performance variability caused by the fluctuation in the number of dopant ions, while a planar-bulk MOSFET requires a heavily doped channel which causes serious process variability. A Fin FET based DRAM memory design has been proposed as an alternative solution to the bulk devices. Fin FET is suitable for future nano-scale memory circuit design due to its reduced short channel effects (SCE) and leakage current. Fin FET DRAM cells can reduce area and leakage power. Z` `By using the Fin FET CMOS technology we investigate that it provide low leakage and high performance operation by utilizing high speed, low Vt transistor for logic cell and low leakage.
Credibility Evaluation of Web Big Data Information Based on Particle Swarm Optimization

In order to improve the credibility evaluation effectiveness of web big data information, the improved particle swarm optimization is established. Firstly, framework of web big data is designed to include web big data source, data storage, data processing and data analysis. The global credibility calculation formula of whole web is established. Secondly, the improved particle swarm algorithm is constructed through updating weight and training factor, introducing cross and mutation operations into the algorithm, and improving population diversification based on mountain climbing algorithm. Finally, ten sample industries and one hundred sample stocks are selected to carry out experiment analysis, and the results show that the proposed algorithm can effectively distinguish trusted and untrustworthy records. And the proposed algorithm of calculating credibility of web big data has high reasonableness.
JHPPL 25.1-09.Nichols

Of all the different health insurance venues in the United States, small group and individual markets consistently engender the most complaints. Compared to large group purchasers, small groups and individuals suffer more from administrative diseconomies of scale, difficulties in spreading risk among themselves, and the absence of bargaining power with insurers and providers alike. These conditions lead to higher and more volatile premiums for the same or less generous benefits than large group purchasers usually obtain. Volatility and the apparently inexorable upward trend of health premium costs have led to considerable interest in reform of these markets, of which the recent national debate over comprehensive reform, in retrospect, was but a brief interlude in a history of federalism that spans half of the twentieth century (Nichols and Blumberg 1998). Because of its relative size and organized interests, most of the attention of health insurance market reformers and critics has been focused on the small group market, rather than on individual markets. Over fortyfive states have passed small group reform laws since 1989, though only twenty-five states had implemented individual market reforms prior to the Health Insurance Portability and Accountability Act of 1996. This federal law compelled all states to either pass certain conforming acts or to suffer direct federal regulation of their insurance markets for the first time. Recently, empirical and case studies of the effects of small group reforms have begun to appear (Jensen and Morrisey 1996; Sloan and Conover 1998; Marsteller et al. 1998; Hall 1998). This article, along with the other essays in this issue, attempts to redress this relative imbalance by focusing exclusively on the individual market.
JSP/16.2/2nd proofs

Toleration is a pragmatic response to the practical need to coexist with others who have different conceptions of the good. Toleration develops out of the recognition that in practice diversity cannot be eradicated by either philosophical argument or political force. We see this pragmatic approach in both the history of discussions of toleration and contemporary accounts. Locke argued, for example, that since it was not practically possible to produce orthodoxy by way of coercion, the state should tolerate dissent. Locke’s approach became more clearly defined in the nineteenth century with Mill’s account of the practical need to tolerate dissenting opinions. Both Locke and Mill base their argument for toleration upon an account of human psychology and epistemology. While Locke rejects coercion in belief formation, Mill emphasizes that belief in the truth will be stronger if the truth has been tempered by argument and dissent (1998, chap. 2). Although Mill’s psychology of belief is similar to Locke’s, his tolerant attitude goes beyond Locke. Mill celebrates diversity as such. Mill thus foreshadows the way in which toleration would develop in the twentieth century. Today we encounter radical diversity with tolerant eyes opened by the horrors of those “final solutions” that have sought to eliminate it. We no longer believe that it is practically possible to unify human life under one concept or idea. Toleration should not, however, be confused with “heterophilia,” or love of difference. ” Toleration does not need to be based upon essential claims about diversity in human nature. Rather, as I shall argue, toleration is a pragmatic reaction to the concrete fact that diversity exists. It seeks to deal with this fact without necessarily making any further claims about the essential goodness of diversity. In an effort to clarify this point, I will consider recent discussions of both toleration and pragmatism. Along the way I will show that there is broad agreement among
Taurus: a data plane architecture for per-packet ML

Emerging applications---cloud computing, the internet of things, and augmented/virtual reality---demand responsive, secure, and scalable datacenter networks. These networks currently implement simple, per-packet, data-plane heuristics (e.g., ECMP and sketches) under a slow, millisecond-latency control plane that runs data-driven performance and security policies. However, to meet applications' service-level objectives (SLOs) in a modern data center, networks must bridge the gap between line-rate, per-packet execution and complex decision making. In this work, we present the design and implementation of Taurus, a data plane for line-rate inference. Taurus adds custom hardware based on a flexible, parallel-patterns (MapReduce) abstraction to programmable network devices, such as switches and NICs; this new hardware uses pipelined SIMD parallelism to enable per-packet MapReduce operations (e.g., inference). Our evaluation of a Taurus switch ASIC---supporting several real-world models---shows that Taurus operates orders of magnitude faster than a server-based control plane while increasing area by 3.8% and latency for line-rate ML models by up to 221 ns. Furthermore, our Taurus FPGA prototype achieves full model accuracy and detects two orders of magnitude more events than a state-of-the-art control-plane anomaly-detection system.
Robust Mean Estimation in High Dimensions: An Outlier Fraction Agnostic and Efficient Algorithm

The problem of robust mean estimation in high dimensions is studied, in which a certain fraction (less than half) of the datapoints can be arbitrarily corrupted. Motivated by compressive sensing, the robust mean estimation problem is formulated as the minimization of the ℓ0-‘norm’ of an outlier indicator vector, under a second moment constraint on the datapoints. The ℓ0-‘norm’ is then relaxed to the ℓp-norm (0 < p ≤ 1) in the objective, and it is shown that the global minima for each of these objectives are order-optimal and have optimal breakdown point for the robust mean estimation problem. Furthermore, a computationally tractable iterative ℓp-minimization and hard thresholding algorithm is proposed that outputs an order-optimal robust estimate of the population mean. The proposed algorithm (with breakdown point ≈0.3) does not require prior knowledge of the fraction of outliers, in contrast with most existing algorithms, and for p = 1 it has near-linear time complexity. Both synthetic and real data experiments demonstrate that the proposed algorithm outperforms state-of-the-art robust mean estimation methods.
Bias vs Structure of Polynomials in Large Fields, and Applications in Information Theory

Let <inline-formula> <tex-math notation="LaTeX">$f$ </tex-math></inline-formula> be a polynomial of degree <inline-formula> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> in <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> variables over a finite field <inline-formula> <tex-math notation="LaTeX">$\mathbb {F}$ </tex-math></inline-formula>. The polynomial is said to be unbiased if the distribution of <inline-formula> <tex-math notation="LaTeX">$f(x)$ </tex-math></inline-formula> for a uniform input <inline-formula> <tex-math notation="LaTeX">$x \in \mathbb {F} ^{n}$ </tex-math></inline-formula> is close to the uniform distribution over <inline-formula> <tex-math notation="LaTeX">$\mathbb {F}$ </tex-math></inline-formula>, and is called biased otherwise. The polynomial is said to have low rank if it can be expressed as a composition of a few lower degree polynomials. Green and Tao [Contrib. Discrete Math 2009] and Kaufman and Lovett [FOCS 2008] showed that bias implies low rank for fixed degree polynomials over fixed prime fields. This lies at the heart of many tools in higher order Fourier analysis. In this work, we extend this result to all prime fields (of size possibly growing with <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>). We also provide a generalization to nonprime fields in the large characteristic case. However, we state all our applications in the prime field setting for the sake of simplicity of presentation. Using the above generalization to large fields as a starting point, we are also able to settle the list decoding radius of fixed degree Reed-Muller codes over growing fields. The case of fixed size fields was solved by Bhowmick and Lovett [STOC 2015], which resolved a conjecture of Gopalan-Klivans-Zuckerman [STOC 2008]. Here, we show that the list decoding radius is equal the minimum distance of the code for all fixed degrees, even when the field size is possibly growing with <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>. Additionally, we effectively resolve the weight distribution problem for Reed-Muller codes of fixed degree over all fields, first raised in 1977 in the classic textbook by MacWilliams and Sloane [Research Problem 15.1 in Theory of Error Correcting Codes].
Distributional data analysis of accelerometer data from the NHANES database using nonparametric survey regression models

Accelerometers enable an objective measurement of physical activity levels among groups of individuals in free-living environments, providing high-resolution detail about physical activity changes at different time scales. Current approaches used in the literature for analyzing such data typically employ summary measures such as total inactivity time or compositional metrics. However, at the conceptual level, these methods have the potential disadvantage of discarding important information from recorded data when calculating these summaries and metrics since these typically depend on cut-offs related to exercise intensity zones chosen subjectively or even arbitrarily. Furthermore, much of the data collected in these studies follow complex survey designs. Then, using specific estimation strategies adapted to a particular sampling mechanism is mandatory. The aim of this paper is two-fold. First, a new functional representation of a distributional nature accelerometer data is introduced to build a complete individualized profile of each subject’s physical activity levels. Second, we extend two nonparametric functional regression models, kernel smoothing and kernel ridge regression, to handle survey data and obtain reliable conclusions about the influence of physical activity in the different analyses performed in the complex sampling design NHANES cohort and so, show representation advantages.
Integration of adaptive control and reinforcement learning approaches for real-time control and learning ∗

This paper considers the problem of real-time control and learning in dynamic systems subjected to parametric uncertainties and proposes a controller that combines Adaptive Control (AC) in the inner loop and a Reinforcement Learning (RL) based policy in the outer loop. Two classes of nonlinear dynamic systems are considered, both of which are control-aﬃne. The ﬁrst class of dynamic systems utilizes equilibrium points with expansion forms around these points and employs a Lyapunov approach. The second class of nonlinear systems uses contraction theory as the underlying framework. For both classes of systems, the AC-RL controller is shown to lead to online policies that guarantee stability, and leverage accelerated convergence properties using a high-order tuner. Additionally, for the second class of systems, the AC-RL controller is shown to lead to parameter learning with persistent excitation. Numerical validations of all algorithms are carried out using a quadrotor landing task on a moving platform and other academic examples. All results clearly point out the advantage of the proposed integrative AC-RL approach.
Role of Precision Oncology in Type II Endometrial and Prostate Cancers in the African Population: Global Cancer Genomics Disparities

Precision oncology can be defined as molecular profiling of tumors to identify targetable alterations. Emerging research reports the high mortality rates associated with type II endometrial cancer in black women and with prostate cancer in men of African ancestry. The lack of adequate genetic reference information from the African genome is one of the major obstacles in exploring the benefits of precision oncology in the African context. Whilst external factors such as the geography, environment, health-care access and socio-economic status may contribute greatly towards the disparities observed in type II endometrial and prostate cancers in black populations compared to Caucasians, the contribution of African ancestry to the contribution of genetics to the etiology of these cancers cannot be ignored. Non-coding RNAs (ncRNAs) continue to emerge as important regulators of gene expression and the key molecular pathways involved in tumorigenesis. Particular attention is focused on activated/repressed genes and associated pathways, while the redundant pathways (pathways that have the same outcome or activate the same downstream effectors) are often ignored. However, comprehensive evidence to understand the relationship between type II endometrial cancer, prostate cancer and African ancestry remains poorly understood. The sub-Saharan African (SSA) region has both the highest incidence and mortality of both type II endometrial and prostate cancers. Understanding how the entire transcriptomic landscape of these two reproductive cancers is regulated by ncRNAs in an African cohort may help elucidate the relationship between race and pathological disparities of these two diseases. This review focuses on global disparities in medicine, PCa and ECa. The role of precision oncology in PCa and ECa in the African population will also be discussed.
Time to reach health-care facility and hospital exit outcome among road traffic accident victims attending a tertiary care hospital, Puducherry

BACKGROUND: In India, most of the deaths due to road traffic accidents (RTAs) occur within 24 h of the accident. Hence, this study aimed to assess the proportion of RTA victims reaching the health-care facilities within the golden hour. MATERIALS AND METHODS: This cross-sectional study was conducted in a tertiary care center in South India between August and September 2017. All RTA victims who were admitted for treatment in the emergency department during the study period were included. Data were collected using structured, pretested, and validated pro forma. Hospital exit outcomes between those who reached within 1 h and those who did not were expressed as proportion with a 95% confidence interval (CI). The factors associated with hospital exit outcomes were analyzed using a Chi-square test. RESULTS: Among 626 RTA victims, the mean (standard deviation) age was 37.4 (2.6) years, and about 83% (n = 521) were male. More than one-third (37%) of the RTAs occurred on urban roads (n = 235, 37.5%). A total of 424 (67.7%) were referred from other hospitals. The mean time taken for RTA victims to reach any health-care facility was 3 h. More than half (n = 346, 55% [95% CI: 51.3–59.2]) of the RTA victims had reached a health-care facility within the golden hour. Among those who reached beyond the golden hour, one-fourth (n = 77, 27.5%) were delayed due to the unavailability of transporting vehicles. Delay in communication (n = 59, 21.1%), prolonged travel (n = 41, 14.6%), lack of knowledge about nearby facilities (n = 39, 13.9%), nonavailability of attenders (n = 35, 12.5%) and financial issues (n = 29, 10.4%) were the other reasons for the delay. CONCLUSION: Almost half of the RTA victims reached the health-care facilities after the golden hour. Unavailability of ambulances or vehicles for transport and delay in communication were the important factors that played a role in the delay.
Epigenetics in the Uterine Environment: How Maternal Diet and ART May Influence the Epigenome in the Offspring with Long-Term Health Consequences

The societal burden of non-communicable disease is closely linked with environmental exposures and lifestyle behaviours, including the adherence to a poor maternal diet from the earliest preimplantation period of the life course onwards. Epigenetic variations caused by a compromised maternal nutritional status can affect embryonic development. This review summarises the main epigenetic modifications in mammals, especially DNA methylation, histone modifications, and ncRNA. These epigenetic changes can compromise the health of the offspring later in life. We discuss different types of nutritional stressors in human and animal models, such as maternal undernutrition, seasonal diets, low-protein diet, high-fat diet, and synthetic folic acid supplement use, and how these nutritional exposures epigenetically affect target genes and their outcomes. In addition, we review the concept of thrifty genes during the preimplantation period, and some examples that relate to epigenetic change and diet. Finally, we discuss different examples of maternal diets, their effect on outcomes, and their relationship with assisted reproductive technology (ART), including their implications on epigenetic modifications.
Significance of Pelvic Fluid Observed during Ovarian Cancer Screening with Transvaginal Sonogram

The primary objective was to examine the role of pelvic fluid observed during transvaginal ultrasonography (TVS) in identifying ovarian malignancy. A single-institution, observational study was conducted within the University of Kentucky Ovarian Cancer Screening trial from January 1987 to September 2019. We analyzed true-positive (TP), false-positive (FP), true-negative (TN), and false-negative (FN) groups for the presence of pelvic fluid during screening encounters. Measured outcomes were the presence and duration of fluid over successive screening encounters. Of the 48,925 women surveyed, 2001 (4.1%) had pelvic fluid present during a TVS exam. The odds ratio (OR) of detecting fluid in the comparison group (TN screen; OR = 1) significantly differed from that of the FP cases (benign pathology; OR: 13.4; 95% confidence interval (CI): 9.1–19.8), the TP cases with a low malignant potential (LMP; OR: 28; 95% CI: 26.5–29.5), TP ovarian cancer cases (OR: 50.4; 95% CI: 27.2–93.2), and FN ovarian cancer cases (OR: 59.3; 95% CI: 19.7–178.1). The mean duration that pelvic fluid was present for women with TN screens was 2.2 ± 0.05 encounters, lasting 38.7 ± 1.3 months. In an asymptomatic screening population, free fluid identified in TVS exams was more associated with ovarian malignancy than in the control group or benign ovarian tumors. While pelvic free fluid may not solely discriminate malignancy from non-malignancy, it appears to be clinically relevant and warrants thoughtful consideration.
Supplementation with a Highly Concentrated Docosahexaenoic Acid (DHA) in Non-Proliferative Diabetic Retinopathy: A 2-Year Randomized Double-Blind Placebo-Controlled Study

We assessed the effect of a 2-year supplementation with a highly concentrated docosahexaenoic acid (DHA) product with antioxidant activity on non-proliferative diabetic retinopathy (NPDR) in a randomized double-blind placebo-controlled study. A total of 170 patients with diabetes were randomly assigned to the DHA group (n = 83) or the placebo group (n = 87). NPDR was diagnosed using non-contact slit lamp biomicroscopy examination, and classified into mild, moderate, and severe stages. Patients in the DHA group received a high rich DHA triglyceride (1050 mg/day) nutritional supplement, and those in the placebo group received olive oil capsules. The percentages of mild NPDR increased from 61.7% at baseline to 75.7% at the end of the study in the DHA group, and from 61.9% to 73.1% in the placebo group. Moderate NPDR stages decreased from 35.1% at baseline to 18.7% at the end of the study in the DHA group, and from 36.8% to 26.0% in the placebo group. In the DHA group, there were five eyes with severe NPDR at baseline, which increased to one more at the end of the study. In the placebo group, of two eyes with severe NPDR at baseline, one eye remained at the end of the study. Changes in visual acuity were not found. There were improvements in the serum levels of HbA1c in both groups, but significant differences between the DHA and the placebo groups were not found. In this study, the use of a DHA triglyceride nutraceutical supplement for 2 years did not appear to influence the slowing of the progression of NPDR.
Trends in Smoking Prevalence and Intensity between 2010 and 2018: Implications for Tobacco Control in China

Background: China is the world’s largest producer and consumer of cigarettes. Since 2010, the Chinese government has implemented many policies to combat the tobacco epidemic, yet little is known about their overall impacts. This study aims to investigate the trends in smoking prevalence and intensity between 2010 and 2018. Methods: We use five waves of data from China Family Panel Studies (CFPS), a nationally representative survey, to examine the trends in smoking prevalence and intensity. We use the chi-square test and t-test to examine differences across waves. Binary logistic regressions and linear regressions are applied to examine the association between smoking behaviors and risk factors. Results: The current smoking prevalence dropped from 30.30% in 2010 (90% CI 29.47–31.31) to 28.69% (90% CI 27.69–29.69) in 2018. As for smoking intensity, the average daily cigarettes consumption decreased steadily from 16.96 cigarettes (90% CI 16.55–17.36) in 2010 to 15.12 cigarettes (90% CI 15.07–15.94) in 2018. Smoking risk factors for men included marriage status, education level, employment status, alcohol consumption, and physical activities. The smoking risk was higher for women with a lower education level, lower household income, unemployment status, and alcohol consumption behavior. Conclusions: Our study shows declined trends in both smoking prevalence and intensity between 2010 and 2018, suggesting some positive progress in tobacco control in China. Nonetheless, to achieve the goal of reducing smoking prevalence among people aged 15 and above to less than 20% by 2030, the Chinese government needs to take stronger anti-tobacco measures.