Miracle-dz/UniFAR-FTUs huggingface dataset:
ESD protection for pHEMT MMIC amplifiers

In this paper, we discuss ESD characterization data on typical circuit elements used in GaAs pHEMT MMIC amplifiers. At microwave and mm-wave frequencies, basic circuit performance considerations drive design decisions. Human body model (HBM) data for basic circuit elements can provide guidance for layout and topology trade-offs to improve ESD performance. Critical circuit elements include a) closely spaced conductors, b) FETs, and c) capacitors. Construction details and spacing affect ESD performance of passive conductors. Total FET gate width is the critical factor for FETs. Area and dielectric thickness are critical for capacitors. On-chip diode networks can provide practical protection for gate bias terminals, easily exceeding 2000 V HBM.
The influence of the 2010 World Cup on the Tygerberg Poison Information Centre

Introduction. The soccer World Cup is one of the biggest sporting events in the world, but data on the effect of sporting events of such a magnitude on the service demand on Poison Information Centres (PICs) are limited. Objective. The aim of this study was to determine the influence of the 2010 World Cup on the workload of the Tygerberg Poison Information Centre (TPIC). Methods. Data were collected prospectively for three time periods during 2010: (1) 31 days preceding the World Cup (10 May–10 June); (2) 31 days during the World Cup (11 June–11 July); and (3) 31 days after the World Cup (12 July–11 August). The calls received during 2010 were compared to calls received during corresponding time periods in 2008 and 2009. Collected data included date and time, caller's location and medical background, patient's age and gender, intent of exposure, route of exposure and specific toxin class. Results. During the study, 3888 calls related to human poisoning were received (1162 in 2010, 1412 in 2009 and 996 in 2008). The mean daily call volume between 2010 (12.49; 95% CI 11.57–13.42) and 2009 (13.23; 95% CI 12.30–14.15) did not differ significantly (p = 0.25). The mean daily call volume during the World Cup was 11.13 (95% CI 9.59–12.67; n = 345) compared to 14.26 (95% CI 12.71–15.80; n = 442) for the similar period in 2009 (p = 0.08). The mean daily call volume before and after the World Cup was 12.74 (95% CI 11.20–14.29; n = 395) and 13.61 (95% CI 12.07–15.16; n = 422); p = 1.00 and p = 0.39, respectively, when compared with the World Cup period. Discussion. An unexpected finding of this study was that the hosting of the 2010 World Cup resulted in fewer calls to the TPIC. This decrease could be attributed to the high visibility of policing, an extended school holiday and the positive attitudes of South Africans towards making the World Cup a success. Conclusion. PICs should be consulted during the planning stages of major sporting events. Contingency plans should still be in place to overcome any unexpected rise in call volume.
Enhanced detection of feigned cognitive impairment using per item response time measurements in the Word Memory Test

ABSTRACT Response time (RT) is a less obvious outcome measure than conventional accuracy measures used in performance validity tests (PVTs). It is also under less conscious control and is affected by cognitive processes associated with deception. Studies that assessed the utility of RT for the detection of feigned cognitive impairment are however numbered. Moreover, RT variability was not assessed in a clinically used PVT. In the current study, we assessed the utility of RT measures for the detection of feigned cognitive impairment in the Word Memory Test (WMT). Healthy participants (N = 90) were randomly assigned to a simulation or control condition and their per-item RTs were recorded while they performed the WMT’s immediate recognition (IR) subtest. Simulators had longer mean RTs and larger RT variance than controls. Combining RT measures and the IR-subtest’s accuracy score enabled a highly accurate detection of simulators. Moreover, the combined scale demonstrated incremental value (though slight) in predicting group membership beyond the use of the accuracy score as the sole PVT measure. The findings tentatively point toward the usefulness of RT measures to enhance the detection of feigned cognitive impairment. Further studies are needed, however, in order to explore the utility of these measures in clinical settings.
Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the Nt transmit and Nr receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., the NtNr channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.
Boundary Effects in the Discrete Bass Model

To study the effect of boundaries on diffusion of new products, we introduce two novel analytic tools: The indifference principle, which enables us to explicitly compute the aggregate diffusion on various networks, and the dominance principle, which enables us to rank the diffusion on different networks. Using these principles, we prove our main result that on a finite line, one-sided diffusion (i.e., when each consumer can only be influenced by her left neighbor) is strictly slower than two-sided diffusion (i.e., when each consumer can be influenced by her left and right neighbor). This is different from the periodic case of diffusion on a circle, where one-sided and two-sided diffusion are identical. We observe numerically similar results in higher dimensions.
Long-Run Mortality Effects of Vietnam-Era Army Service: Evidence from Australia's Conscription Lotteries

We estimate the effect of Vietnam-era Army service on mortality, exploiting Australia's conscription lotteries for identification. We utilize population data on deaths during 1994-2007 and military personnel records. The estimates are identified by over 51,000 compliers induced to enlist in the Army. We find no statistically significant effects on mortality overall, nor for any cause of death. The estimated relative risk (RR) of death associated with Army service is 1.03 (95% CI: 0.92, 1.19). On the assumption that Army service affected mortality only for those who served in Vietnam, the estimated RR is 1.06 (95% CI: 0.81, 1.51).
Deep Learning Backend for Single and Multisession i-Vector Speaker Recognition

The lack of labeled background data makes a big performance gap between cosine and Probabilistic Linear Discriminant Analysis (PLDA) scoring baseline techniques for i-vectors in speaker recognition. Although there are some unsupervised clustering techniques to estimate the labels, they cannot accurately predict the true labels and they also assume that there are several samples from the same speaker in the background data that could not be true in reality. In this paper, the authors make use of Deep Learning (DL) to fill this performance gap given unlabeled background data. To this goal, the authors have proposed an impostor selection algorithm and a universal model adaptation process in a hybrid system based on deep belief networks and deep neural networks to discriminatively model each target speaker. In order to have more insight into the behavior of DL techniques in both single- and multisession speaker enrollment tasks, some experiments have been carried out in this paper in both scenarios. Experiments on National Institute of Standards and Technology 2014 i-vector challenge show that 46% of this performance gap, in terms of minimum of the decision cost function, is filled by the proposed DL-based system. Furthermore, the score combination of the proposed DL-based system and PLDA with estimated labels covers 79% of this gap.
On the Conditional Rényi Entropy

The Rényi entropy of general order unifies the well-known Shannon entropy with several other entropy notions, like the min-entropy or collision entropy. In contrast to the Shannon entropy, there seems to be no commonly accepted definition for the conditional Rényi entropy: several versions have been proposed and used in the literature. In this paper, we reconsider the definition for the conditional Rényi entropy of general order as proposed by Arimoto in the seventies. We show that this particular notion satisfies several natural properties. In particular, we show that it satisfies monotonicity under conditioning, meaning that conditioning can only reduce the entropy, and (a weak form of) chain rule, which implies that the decrease in entropy due to conditioning is bounded by the number of bits one conditions on. None of the other suggestions for the conditional Rényi entropy satisfies both these properties. Finally, we show a natural interpretation of the conditional Rényi entropy in terms of (unconditional) Rényi divergence, and we show consistency with a recently proposed notion of conditional Rényi entropy in the quantum setting.
Predictors of Peritraumatic Reactions and PTSD Following the September 11th Terrorist Attacks

Abstract In this study the authors characterize peritraumatic reactions of residents of New York City during and immediately following the September 11th terrorist attacks, identify predictors of those reactions, and identify predictors of PTSD 4 months later. A cross—sectional sample of New York residents (n = 2,001) responded to questions about sociodemographics, historical factors, event—related exposure; acute cognitive, emotional, and physiological reactions to the September 11th terrorist attacks; and current (past month) PTSD symptoms. Factor analyses of peritraumatic reactions yielded three related, but distinct, peritraumatic response patterns — dissociation, emotional reactions, and panic/physiological arousal. Several demographic, historical, and exposure—related variables predicted one or more peritraumatic reaction patterns. After controlling for demographic, historical, and exposure factors, each of the peritraumatic reactions factors, one historical factor and one event—related exposure factor remained as significant predictors of PTSD. These results support a growing literature concerning the predictive value of peritraumatic reactions in relation to PTSD. Implications for preventive efforts and suggestions for future research are discussed.
Hot HB stars in globular clusters - Physical parameters and consequences for theory. VI. The second parameter pair M 3 and M 13

We present the results of spectroscopic analyses of hot horizontal branch (HB) stars in M 13 and M 3, which form a famous ``second parameter'' pair. From the spectra and Stroemgren photometry we derived -- for the first time in M 13 -- atmospheric parameters (effective temperature and surface gravity). For stars with Stroemgren temperatures between 10,000 and 12,000 K we found excellent agreement between the atmospheric parameters derived from Stroemgren photometry and those derived from Balmer line profile fits. However, for cooler stars there is a disagreement in the parameters derived by the two methods, for which we have no satisfactory explanation. Stars hotter than 12,000 K show evidence for helium depletion and iron enrichment, both in M 3 and M 13. Accounting for the iron enrichment substantially improves the agreement with canonical evolutionary models, although the derived gravities and masses are still somewhat too low. This remaining discrepancy may be an indication that scaled-solar metal-rich model atmospheres do not adequately represent the highly non-solar abundance ratios found in blue HB stars affected by diffusion. We discuss the effects of an enhancement in the envelope helium abundance on the atmospheric parameters of the blue HB stars, as might be caused by deep mixing on the red giant branch or primordial pollution from an earlier generation of intermediate mass asymptotic giant branch stars.
Risk Compensation Is Not Associated with Male Circumcision in Kisumu, Kenya: A Multi-Faceted Assessment of Men Enrolled in a Randomized Controlled Trial

Background Three randomized controlled trials (RCTs) have confirmed that male circumcision (MC) significantly reduces acquisition of HIV-1 infection among men. The objective of this study was to perform a comprehensive, prospective evaluation of risk compensation, comparing circumcised versus uncircumcised controls in a sample of RCT participants. Methods and Findings Between March 2004 and September 2005, we systematically recruited men enrolled in a RCT of MC in Kenya. Detailed sexual histories were taken using a modified Timeline Followback approach at baseline, 6, and 12 months. Participants provided permission to obtain circumcision status and laboratory results from the RCT. We evaluated circumcised and uncircumcised men's sexual behavior using an 18-item risk propensity score and acquisition of incident infections of gonorrhea, chlamydia, and trichomoniasis. Of 1780 eligible RCT participants, 1319 enrolled (response rate = 74%). At the baseline RCT visit, men who enrolled in the sub-study reported the same sexual behaviors as men who did not. We found a significant reduction in sexual risk behavior among both circumcised and uncircumcised men from baseline to 6 (p<0.01) and 12 (p = 0.05) months post-enrollment. Longitudinal analyses indicated no statistically significant differences between sexual risk propensity scores or in incident infections of gonorrhea, chlamydia, and trichomoniasis between circumcised and uncircumcised men. These results are based on the most comprehensive analysis of risk compensation yet done. Conclusion In the context of a RCT, circumcision did not result in increased HIV risk behavior. Continued monitoring and evaluation of risk compensation associated with circumcision is needed as evidence supporting its' efficacy is disseminated and MC is widely promoted for HIV prevention.
Teacher-learner & Multi-objective Genetic Algorithm Based Query Optimization Approach for Heterogeneous Distributed Database Systems

Growing database demands more technological developments and computing paradigms, as Grid and Cloud computing, unleashed new developments in the database technology sector. Query Optimization is essentially a complex search task to obtain the best possible plan from the enormously increasing databases. Heterogeneous Distributed database management systems (DDBMS) are amongst the most important and successful software developments where the query processing is more difficult since large number of parameters effect the performance of the queries. Thus, the author attempted to introduce a new approach for Query Optimization in Heterogeneous DDBMS both for local and global optimization separately. In this paper, two stochastic approaches such as multi-objective genetic algorithm for local optimization and teacher-learner based optimization for global optimization is employed. The local optimization approach deals with optimization within the local sites whereas global optimization works with the sites at different locations globally. Join ordering cost (JOC), Total Local Processing Cost (TLPC) and Total Communication Cost (TCC) are used to obtain the optimal query plans amongst the relation between the query sites. The Experimental Analysis of the proposed approach showed that it has better performance i.e. less cost when compared with other heterogeneous DDBMS and has more cost when compared with the other existing homogeneous approaches.
ShRNA-Targeted Centromere Protein A Inhibits Hepatocellular Carcinoma Growth

Background Centromere protein A (CENP-A) plays important roles in cell-cycle regulation and genetic stability. Herein, we aimed to investigate its expression pattern, clinical significance, and biological function in hepatocellular carcinoma (HCC). Methodology/Principal Findings CENP-A expression at the mRNA and protein levels was examined in 20 pairs of fresh HCCs and corresponding nontumor liver tissues. Immunohistochemistry for CENP-A was performed on 80 paraffin-embedded HCC specimens, and the clinical significance of its expression was analyzed. A human HCC cell line HepG2 with high abundance of CENP-A was used to study the effects of manipulating CENP-A on HCC growth. Quantitative real-time polymerase chain reaction arrays and Western blot analysis were employed to identify the cell-cycle control- and apoptosis-related genes regulated by CENP-A. The results showed that CENP-A was aberrantly overexpressed in HCCs relative to adjacent nontumor tissues. This overexpression was significantly associated with positive serum HBsAg status, increased histological grade, high Ki-67 index and P53 immunopositivity. Knockdown of CENP-A in HepG2 cells reduced cell proliferation, blocked cell cycle at the G1 phase, and increased apoptosis. The antiproliferative effects of CENP-A silencing were also observed in vivo. Conversely, CENP-A overexpression promoted HCC cell growth and reduced apoptosis. Furthermore, many genes implicated in cell-cycle regulation and apoptosis, including CHK2, P21waf1, P27 Kip1, SKP2, cyclin G1, MDM2, Bcl-2, and Bax, were deregulated by manipulating CENP-A. Conclusions/Significance Overexpression of CENP-A is frequently observed in HCC. Targeting CENP-A can inhibit HCC growth, likely through the regulation of a large number genes involved in cell-cycle progression and apoptosis, and thereby represents a potential therapeutic strategy for this malignancy.
Mechanisms of Hepatitis C Virus Infection

Hepatitis C virus (HCV) is the major causative agent of chronic non-A, non-B hepatitis. The life cycle of HCV is largely unknown because a reliable culture system has not yet been established. HCV presumably binds to specific receptor(s) and enters cells through endocytosis, as do other members of Flaviviridae. The viral genome is translated into a precursor polyprotein after uncoating, and viral RNA is synthesized by a virus-encoded polymerase complex. Progeny viral particles are released into the luminal side of the endoplasmic reticulum and secreted from the cell after passage through the Golgi apparatus. Understanding the mechanisms of HCV infection is essential to the development of effective new therapies for chronic HCV infection. Several host membrane proteins have been identified as receptor candidates for HCV. Recent advances using pseudotype virus systems have provided information surrounding the initial steps of HCV infection. An HCV RNA replicon system has been useful for elucidating the replication mechanism of HCV. In this review, we summarize our current understanding of the mechanisms of HCV infection and discuss potential antiviral strategies against HCV infection.
Long-lasting multifunctional CD8+ T cell responses in end-stage melanoma patients can be induced by dendritic cell vaccination

ABSTRACT Cytotoxic T cells are considered crucial for antitumor immunity and their induction is the aim of various immunotherapeutic strategies. High frequencies of tumor-specific CD8+ T cells alone, however, are no guarantee for long-term tumor control. Here, we analyzed the functionality of tumor-specific CD8+ T cells in melanoma patients upon dendritic cell vaccination by measuring multiple T cell effector functions considered crucial for anticancer immunity, including the expression of pro-inflammatory cytokines, chemokines and cytotoxic markers (IFNγ, TNFα, IL-2, CCL4, CD107a). We identified small numbers of multifunctional (polyfunctional) tumor-specific CD8+ T cells in several patients and dendritic cell therapy was able to improve the functionality of these pre-existing tumor-specific CD8+ T cells. Generated multifunctional CD8+ T cell responses could persist for up to ten years and within the same patient functionality could vary greatly for the different vaccination antigens. Importantly, after one cycle of DC vaccination highly functional CD8+ T cells were only detected in patients displaying prolonged overall survival. Our results shed light on the dynamics of multifunctional tumor-specific CD8+ T cells during metastatic melanoma and reveal a new feature of dendritic cell vaccination in vivo.
Bayesian Population Decoding of Motor Cortical Activity Using a Kalman Filter

Effective neural motor prostheses require a method for decoding neural activity representing desired movement. In particular, the accurate reconstruction of a continuous motion signal is necessary for the control of devices such as computer cursors, robots, or a patient's own paralyzed limbs. For such applications, we developed a real-time system that uses Bayesian inference techniques to estimate hand motion from the firing rates of multiple neurons. In this study, we used recordings that were previously made in the arm area of primary motor cortex in awake behaving monkeys using a chronically implanted multielectrode microarray. Bayesian inference involves computing the posterior probability of the hand motion conditioned on a sequence of observed firing rates; this is formulated in terms of the product of a likelihood and a prior. The likelihood term models the probability of firing rates given a particular hand motion. We found that a linear gaussian model could be used to approximate this likelihood and could be readily learned from a small amount of training data. The prior term defines a probabilistic model of hand kinematics and was also taken to be a linear gaussian model. Decoding was performed using a Kalman filter, which gives an efficient recursive method for Bayesian inference when the likelihood and prior are linear and gaussian.In off-line experiments, the Kalman filter reconstructions of hand trajectory were more accurate than previously reported results.The resulting decoding algorithm provides a principled probabilistic model of motor-cortical coding, decodes hand motion in real time, provides an estimate of uncertainty, and is straightforward to implement. Additionally the formulation unifies and extends previous models of neural coding while providing insights into the motor-cortical code.