CMOS RF front-end design for terrestrial and mobile digital television systems

With the increasing demand for high quality TV service, digital television (DTV) is replacing the conventional analog television. DTV tuner is one of the most critical blocks of the DTV receiver system; it down-converts the desired DTV RF channel to baseband or a low intermediate frequency with enough quality. This research is mainly focused on the analysis and realization of low-cost low-power front-ends for ATSC terrestrial DTV and DVB-H mobile DTV tuner systems. For the design of the ATSC terrestrial tuner, a novel double quadrature tuner architecture, which can not only minimize the tuner power consumption but also achieve the fully integration, has been proposed. A double quadrature down-converter has been designed and fabricated with TSMC 0.35õm CMOS technology; the measurement results verified the proposed concepts. For the mobile DTV tuner, a zero-IF architecture is used and it can achieve the DVB-H specifications with less than 200mW power consumption. In the implementation of the mobile DVB-H tuner, a novel RF variable gain amplifier (RFVGA) and a low flicker noise current-mode passive mixer have been proposed. The proposed RFVGA achieves high dynamic range and robust input impedance matching performance, which is the main design challenge for the traditional implementations. The current-mode passive mixer achieves high-gain, low noise (especially low flicker noise) and high-linearity (over 10dBm IIP3) with low power supplies; it is believed that this is a promising topology for low voltage high dynamic range mixer applications. The RFVGA has been fabricated in TSMC 0.18õm CMOS technology and the measurement results agree well with the theoretical ones

Support vector machine for classification of meiotic recombination hotspots and coldspots in Saccharomyces cerevisiae based on codon composition

BACKGROUND: Meiotic double-strand breaks occur at relatively high frequencies in some genomic regions (hotspots) and relatively low frequencies in others (coldspots). Hotspots and coldspots are receiving increasing attention in research into the mechanism of meiotic recombination. However, predicting hotspots and coldspots from DNA sequence information is still a challenging task. RESULTS: We present a novel method for classification of hot and cold ORFs located in hotspots and coldspots respectively in Saccharomyces cerevisiae, using support vector machine (SVM), which relies on codon composition differences. This method has achieved a high classification accuracy of 85.0%. Since codon composition is a fusion of codon usage bias and amino acid composition signals, the ability of these two kinds of sequence attributes to discriminate hot ORFs from cold ORFs was also investigated separately. Our results indicate that neither codon usage bias nor amino acid composition taken separately performed as well as codon composition. Moreover, our SVM based method was applied to the full genome: We predicted the hot/cold ORFs from the yeast genome by using cutoffs of recombination rate. We found that the performance of our method for predicting cold ORFs is not as good as that for predicting hot ORFs. Besides, we also observed a considerable correlation between meiotic recombination rate and amino acid composition of certain residues, which probably reflects the structural and functional dissimilarity between the hot and cold groups. CONCLUSION: We have introduced a SVM-based novel method to discriminate hot ORFs from cold ones. Applying codon composition as sequence attributes, we have achieved a high classification accuracy, which suggests that codon composition has strong potential to be used as sequence attributes in the prediction of hot and cold ORFs

Linking key intervention timing to rapid decline of the COVID-19 effective reproductive number to quantify lessons from mainland China

Effective reproductive numbers (Rt) were calculated from data on the COVID-19 outbreak in China and linked to dates in 2020 when different interventions were enacted. From a maximum of 3.98 before the lockdown in Wuhan City, the values of Rt declined to below 1 by the second week of February, after the construction of hospitals dedicated to COVID-19 patients. The Rt continued to decline following additional measures in line with the policy of “early detection, early report, early quarantine, and early treatment.” The results provide quantitative evaluations of how intervention measures and their timings succeeded, from which lessons can be learned by other countries dealing with future outbreaks

Modelling the impact of antibody-dependent enhancement on disease severity of Zika virus and dengue virus sequential and co-infection

Human infections with viruses of the genus Flavivirus, including dengue virus (DENV) and Zika virus (ZIKV), are of increasing global importance. Owing to antibody-dependent enhancement (ADE), secondary infection with one Flavivirus following primary infection with another Flavivirus can result in a significantly larger peak viral load with a much higher risk of severe disease. Although several mathematical models have been developed to quantify the virus dynamics in the primary and secondary infections of DENV, little progress has been made regarding secondary infection of DENV after a primary infection of ZIKV, or DENV-ZIKV co-infection. Here, we address this critical gap by developing compartmental models of virus dynamics. We first fitted the models to published data on dengue viral loads of the primary and secondary infections with the observation that the primary infection reaches its peak much more gradually than the secondary infection. We then quantitatively show that ADE is the key factor determining a sharp increase/decrease of viral load near the peak time in the secondary infection. In comparison, our simulations of DENV and ZIKV co-infection (simultaneous rather than sequential) show that ADE has very limited influence on the peak DENV viral load. This indicates pre-existing immunity to ZIKV is the determinant of a high level of ADE effect. Our numerical simulations show that (i) in the absence of ADE effect, a subsequent co-infection is beneficial to the second virus; and (ii) if ADE is feasible, then a subsequent co-infection can induce greater damage to the host with a higher peak viral load and a much earlier peak time for the second virus, and for the second peak for the first virus.Fil: Tang, Biao. University of York; Reino Unido. University of Toronto; CanadáFil: Xiao, Yanni. Xi'an Jiaotong University; ChinaFil: Sander, Beate. University of Toronto; CanadáFil: Kulkarni, Manisha A.. University of Ottawa; CanadáFil: Wu, Jianhong. University of York; Reino UnidoFil: Miretti, Marcos Mateo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; Argentin

Large amplitude and multiple stable periodic oscillations in treatment–donation–stockpile dynamics

A transmission–treatment–donation–stockpile model was originally formulated for the 2014–2015 West Africa Ebola outbreak in order to inform policy complication of large scale use and collection of convalescent blood as an empiric treatment. Here we reduce this model to a three dimensional system with a single delay counting for the duration between two consecutive donations. The blood unit reproduction number R0 is calculated and interpreted biologically. Using the LaSalle’s invariance principle we show that the zero blood bank storage equilibrium is globally asymptotically stable if R0 1, the system has a non-zero equilibrium with potential occurrence of Hopf bifurcations. The geometric approach previously developed is applied to guide the location of critical bifurcation points. Numerical analysis shows that variations of the single delay parameter can trigger bi-stable large amplitude periodic solutions. We therefore suggest that this time lag must be carefully chosen and maintained to attain stable treatment availability during outbreaks

Large amplitude and multiple stable periodic oscillations in treatment-donation-stockpile dynamics

A transmission-treatment-donation-stockpile model was originally formulated for the 2014-2015 West Africa Ebola outbreak in order to inform policy complication of large scale use and collection of convalescent blood as an empiric treatment. Here we reduce this model to a three dimensional system with a single delay counting for the duration between two consecutive donations. The blood unit reproduction number $R_0$ is calculated and interpreted biologically. Using the LaSalle's invariance principle we show that the zero blood bank storage equilibrium is globally asymptotically stable if $R_01$, the system has a non-zero equilibrium with potential occurrence of Hopf bifurcations. The geometric approach previously developed is applied to guide the location of critical bifurcation points. Numerical analysis shows that variations of the single delay parameter can trigger bi-stable large amplitude periodic solutions. We therefore suggest that this time lag must be carefully chosen and maintained to attain stable treatment availability during outbreaks

Modeling Cross-Contamination During Poultry Processing: Dynamics in The Chiller Tank

Understanding mechanisms of cross-contamination during poultry processing is vital for effective pathogen control. As an initial step toward this goal, we develop a mathematical model of the chilling process in a typical high speed Canadian processing plant. An important attribute of our model is that it provides quantifiable links between processing control parameters and microbial levels, simplifying the complexity of these relationships for implementation into risk assessment models. We apply our model to generic, non-pathogenic Escherichia coli contamination on broiler carcasses, connecting microbial control with chlorine sanitization, organic load in the water, and pre-chiller E. coli levels on broiler carcasses. In particular, our results suggest that while chlorine control is important for reducing E. coli levels during chilling, it plays a less significant role in the management of cross-contamination issues

Quantitative interpretation of coal industrial components using a gray system and geophysical logging data: A case study from the Qinshui Basin, China

The content of industrial components of coalbeds, one of the main parameters of coalbed methane (CBM) reservoirs, is crucial in the entire coal mine resource exploration and exploitation process. Currently, using geophysical logging data to determine the content of industrial components is the most widely implemented method. In this study, the PZ block in the Qinshui Basin was employed as a target block to evaluate ash (Aad), fixed carbon (FCad), volatile matter (Vdaf), and moisture (Mad) under the air-dry (AD) base condition based on the autocorrelation between the geophysical logging curves and industrial component contents combined with the OBGM (1, N) model. The results indicate that 1) the geophysical logging curves combined with the OBGM (1, N) model can accurately predict the Aad and FCad contents and an increase in geophysical logging curve types can effectively improve the model performance, compared to using a single geophysical logging curve for prediction. 2) When predicting the Vdaf content, using the geophysical logging curves combined with Aad and FCad contents had the highest prediction accuracy. Further, prediction bias does not exist, compared to using only the geophysical logging curve or the autocorrelation between the industrial component contents. The entire evaluation process begins with an assessment of the Aad and FCad contents. Then, the Vdaf content was assessed using the content of these two industrial components combined with geophysical logging data. Finally, the Mad content was calculated using the volumetric model. Accurate application results were obtained for the verification of new wells, demonstrating the efficacy of the method and procedure described in this study. 3) The OBGM (1, N) model has the highest prediction accuracy compared with the multiple regression and GM (0, N) models, which have the same computational cost. The geophysical logging interpretation model of the proposed coalbed industrial component contents is simple to calculate and suitable for small samples, providing a new method for the evaluation process of industrial component contents

A Combined Experimental and Computational Study of the Cu/C (sp2) Interface

Interface optimization is the most important and eternal research issue in preparation of the metal matrix composites (MMCs). For nano sp2-carbon material (NSCM)/metal composites, interfacial precipitates are usually formed intentionally or unintentionally, however, the effect of the interface structure and precipitates on the electron transport properties is still unclear, which is especially important for Cu-based material due to the electronic and electrical applications. In this paper, a series of interface models were constructed based on the transmission electron microscopy (TEM) observation of NSCM/Cu composite and calculated through density functional theory (DFT). The geometric structure, interfacial charge transfer, work function, Bader charges, electron differential density distribution and electronic density of states of Cu/graphene (GR), Cu2O/GR, Cu/Cu2O and Cu/Cu2O/GR interfaces were discussed in detail, we conclude that the Cu2O precipitates at the Cu/GR interface can reduce the average distance and increase the binding energy between Cu and GR. Besides, the formation of Cu2O can improve the electronic transport between Cu2O and copper instead of the weak binding of the Cu and graphene, but Schottky barrier at the interface remains an obstacle need to be overcome. The results can provide reference for the interface design of MMCs and the improvement of the composite properties

A general model of hormesis in biological systems and its application to pest management

Hormesis, a phenomenon whereby exposure to high levels of stressors is inhibitory but low (mild, sublethal and subtoxic) doses are stimulatory, challenges decision-making in the management of cancer, neurodegenerative diseases, nutrition and ecotoxicology. In the latter, increasing amounts of a pesticide may lead to upsurges rather than declines of pests, ecological paradoxes that are difficult to predict. Using a novel re-formulation of the Ricker population equation, we show how interactions between intervention strengths and dose timings, dose–response functions and intrinsic factors can model such paradoxes and hormesis. A model with three critical parameters revealed hormetic biphasic dose and dose timing responses, either in a J-shape or an inverted U-shape, yielding a homeostatic change or a catastrophic shift and hormetic effects in many parameter regions. Such effects were enhanced by repeated pulses of low-level stimulations within one generation at different dose timings, thereby reducing threshold levels, maximum responses and inhibition. The model provides insights into the complex dynamics of such systems and a methodology for improved experimental design and analysis, with wide-reaching implications for understanding hormetic effects in ecology and in medical and veterinary treatment decision-making. We hypothesized that the dynamics of a discrete generation pest control system can be determined by various three parameter spaces, some of which reveal the conditions for occurrence of hormesis, and confirmed this by fitting our model to both hormetic data from the literature and to a non-hormetic dataset on pesticidal control of mirid bugs in cotton