Miracle-dz/UniFAR-FTUs huggingface dataset:
A high-quality analog oscillator using oversampling D/A conversion techniques

A high-quality analog oscillator designed specifically for audio applications is described. Except for a rather imprecise low-pass filter and a 1-b digital-analog converter, the proposed circuit is entirely digital, providing accurate control over its oscillation frequency and amplitude. Experimental results indicate an effective dynamic range of approximately 70 dB, equaling the behavior of a Hewlett-Packard HP3254A high-performance signal generator. <<ETX>>
Interactive Mining of Functional MRI Data

Discovery of the image voxels of the brain that represent real activity is, in general, very difficult because of a weak signal-to-noise ratio and the presence of artifacts. The first tests of the classical data mining algorithms in this field showed low performances and weak quality of recognition. In this article, a new interactive data-driven approach to functional magnetic resonance imagery mining is presented, allowing the observation of cerebral activity. Several non-supervised classification algorithms have been developed and tested on sequences of fMRI images. The results of the tests have shown that the number of classes, signal-to-noise ratio, and volumes of activated and explored zones have a strong influence on the classifier performances.
Discrete-time filtering for nonlinear polynomial systems

This paper presents a suboptimal filtering problem solution for a class of discrete-time nonlinear polynomial systems over linear observations. The solution is obtained splitting the whole problem into finding a-priori and a-posteriori equations for state estimates and gain matrices. The closed-form filtering equations for the state estimate and gain matrix are obtained in case of a third-degree polynomial system. Numerical simulations are carried out to show effectiveness of the proposed filter. The obtained filter is compared to the extended Kalman-like filter.
Body fat location and cardiovascular disease risk factors in overweight female adolescents and eutrophic female adolescents with a high percentage of body fat

Abstract Background: Excessive body fat, mainly abdominal fat, is associated with higher cardiovascular risk. However, a fat localisation measurement that would be more indicative of risk in adolescents has not yet been established. Objective: This study was conducted in order to evaluate the correlation between body fat location measurements and cardiovascular disease risk factors in female adolescents. Materials and methods: A total of 113 girls – 38 eutrophic according to their body mass index but with a high percentage of body fat, 40 eutrophic with adequate body fat, and 35 with excessive weight – were evaluated using 15 anthropometrical measurements and 10 cardiovascular risk factors. Results: The central skinfold was the best measurement for predicting variables such as glycaemia and high-density lipoprotein; waist circumference for insulin and homeostasis model assessment; coronal diameter for total cholesterol and low-density lipoprotein; sagittal abdominal diameter for triglycerides and leptin; hip circumference for blood pressure; and the central/peripheral skinfold ratio for homocysteine. The correlation between the measurements and the number of risk factors showed that waist circumference and the waist/stature ratio produced the best results. Conclusions: The results suggest that the body fat distribution in adolescents is relevant in the development of cardiovascular risk factors. Simple measurements such as waist circumference and the waist/stature ratio were the best predictors of a risk of disease and they should therefore be associated with the body mass index in clinical practice in order to identify those adolescents at higher risk.
TLR-Independent Induction of Dendritic Cell Maturation and Adaptive Immunity by Negative-Strand RNA Viruses1

TLR signaling leads to dendritic cell (DC) maturation and immunity to diverse pathogens. The stimulation of TLRs by conserved viral structures is the only described mechanism leading to DC maturation after a virus infection. In this report, we demonstrate that mouse myeloid DCs mature normally after in vivo and in vitro infection with Sendai virus (SeV) in the absence of TLR3, 7, 8, or 9 signaling. DC maturation by SeV requires virus replication not necessary for TLR-mediated triggering. Moreover, DCs deficient in TLR signaling efficiently prime for Th1 immunity after infection with influenza or SeV, generating IFN-γ-producing T cells, CTLs and antiviral Abs. We have previously demonstrated that SeV induces DC maturation independently of the presence of type I IFN, which has been reported to mature DCs in a TLR-independent manner. The data presented here provide evidence for the existence of a novel intracellular pathway independent of TLR-mediated signaling responsible for live virus triggering of DC maturation and demonstrate its critical role in the onset of antiviral immunity. The revelation of this pathway should stimulate invigorating research into the mechanism for virus-induced DC maturation and immunity.
Event-Based Leader-following Consensus of Multi-Agent Systems with Input Time Delay

The event-based control strategy is an effective methodology for tackling the distributed control of multi-agent systems with limited on-board resources. This technical note focuses on event-based leader-following consensus for multi-agent systems described by general linear models and subject to input time delay between controller and actuator. For each agent, the controller updates are event-based and only triggered at its own event times. A necessary condition and two sufficient conditions on leader-following consensus are presented, respectively. It is shown that continuous communication between neighboring agents can be avoided and the Zeno-behavior of triggering time sequences is excluded. A numerical example is presented to illustrate the effectiveness of the obtained theoretical results.
An evaluation framework for cross‐platform mobile application development tools

The mobile application market is becoming increasingly fragmented with the availability of multiple mobile platforms that differ in development procedures. Developers are forced to choose to support only some platforms and specific devices because of limited development resources. To address these challenges, numerous tools have been created to aid developers in building cross‐platform applications; however, there is no metric to evaluate the quality of these tools or the applications produced by them. This paper introduces a framework for evaluating the features, performance, and development experience of existing and future cross‐platform development tools. The framework is implemented by benchmarking several tools, and the results identify a disparity in the features and performance of applications built using different development tools. Copyright © 2014 John Wiley & Sons, Ltd.
Synchrony state generation : an approach using stochastic synapses

In this study, the generation of temporal synchrony within an artificial neural network is examined considering a stochastic synaptic model. A network is introduced and driven by Poisson distributed trains of spikes along with white-Gaussian noise that is added to the internal synaptic activity representing the background activity (neuronal noise). A Hebbian-based learning rule for the update of synaptic parameters is introduced. Only arbitrarily selected synapses are allowed to learn, i.e. update parameter values. Results show that a network using such a framework is able to achieve different states of synchrony via learning. Thus, the plausibility of using stochastic-based models in modeling the neural process is supported. It is also consistent with arguments claiming that synchrony is a part of the memory-recall process and copes with the accepted framework in biological neural systems.
Activity Modelling using Email and Web Page Classification

This work explores the modelling of a user’s current activity using a single document and a very small collection of classified documents. A model called WeMAC was developed, which accretes evidence from heterogeneous sources to give a final classification of the user’s activity. The evidence sources considered here are the different attributes of a document. We evaluate the WeMAC model using two different document types: emails and web pages; assess its performance on both tiny document sets and larger sets; and assess its performance against a “one bag” approach. The WeMAC model compared well with existing results for systems with similar tasks and larger datasets, with an average F1 value of 0.5-0.7.
Identification of differentially expressed genes associated with changes in the morphology of Pichia fermentans on apple and peach fruit.

Pichia fermentans (strain DISAABA 726) is an effective biocontrol agent against Monilinia fructicola and Botrytis cinerea when inoculated in artificially wounded apple fruit but is an aggressive pathogen when inoculated on wounded peach fruit, causing severe fruit decay. Pichia fermentans grows as budding yeast on apple tissue and exhibits pseudohyphal growth on peach tissue, suggesting that dimorphism may be associated with pathogenicity. Two complementary suppressive subtractive hybridization (SSH) strategies, that is, rapid subtraction hybridization (RaSH) and PCR-based subtraction, were performed to identify genes differentially expressed by P. fermentans after 24-h growth on apple vs. peach fruit. Gene products that were more highly expressed on peach than on apple tissue, or vice versa, were sequenced and compared with available yeast genome sequence databases. Several of the genes more highly expressed, when P. fermentans was grown on peach, were related to stress response, glycolysis, amino acid metabolism, and alcoholic fermentation but surprisingly not to cell wall degrading enzymes such as pectinases or cellulases. The dual activity of P. fermentans as both a biocontrol agent and a pathogen emphasizes the need for a thorough risk analysis of potential antagonists to avoid unpredictable results that could negatively impact the safe use of postharvest biocontrol strategies.
Bradshaw and Bayes: Towards a Timetable for the Neolithic

The importance of chronology is reasserted as a means to achieving history and a sense of temporality. A range of current methods for estimating the dates and durations of archaeological processes and events are considered, including visual inspection of graphs and tables of calibrated dates and the summing of the probability distributions of calibrated dates. These approaches are found wanting. The Bayesian statistical framework is introduced, and a worked example presents simulated radiocarbon dates as a demonstration of the explicit, quantified, probabilistic estimates now possible on a routine basis. Using this example, the reliability of the chronologies presented for the five long barrows considered in this series of papers is explored. It is essential that the ‘informative’ prior beliefs in a chronological model are correct. If they are not, the dating suggested by the model will be incorrect. In contrast, the ‘uninformative’ prior beliefs have to be grossly incorrect before the outputs of the model are importantly wrong. It is also vital that the radiocarbon ages included in a model are accurate, and that their errors are correctly estimated. If they are not, the dating suggested by a model may also be importantly wrong. Strenuous effort and rigorous attention to archaeological and scientific detail are inescapable if reliable chronologies are to be built. The dates presented in the following papers are based on models. ‘All models are wrong, some models are useful’ (Box 1979, 202). We hope readers will find them useful, and will employ ‘worry selectivity’ to determine whether and how each model may be importantly wrong. The questions demand the timetable, and our prehistories deserve both.
The impact of land use change on ecosystem service value in Lanzhou region of Gansu Province

Through changing ecosystem's internal structure and functiong, land use change has affected the supply of ecosystem services. Taking Lanzhou as a study area, this paper used the land use dynamic degree model and ecosystem service value evaluation model to analyse the characteristic of land use change and evaluate the ecosystem service value of Lanzhou from 1997 to 2005. And sensitivity index was introduced to verify the reliability of ecological value coefficient. The results show:Firstly,there were greater changes in the dissimilar land use types during the period of 1997-2005. The area of garden plot, forestland,residential land, industrial and mining land and traffic land increased. In contrast, the area of cultivated land,grassland,water region and unutilized land land decreased. Among which the changes of area and speed of residential Land and industrial and mining land were all the largest, with the land use dynamic degree of 18.15%, and its area changes to 119395.09 hm2 from 48689.79hm2 in the study period. Secondly, the ecosystem service value presented rising trend totally with the trend rate of 0.13%, which indicates that environmental effect by afforestation and conversion of cropland to forest has won initial success in Lanzhou.
Electrical modeling and analysis of carbon based three dimensional integration

Based on extracted equivalent circuit parameters, this paper established the power delivery network model of carbon-based three-dimensional (3-D) integration and derived analytical formulas to predict the voltage drop in the proposed 3-D circuit, in which the horizontal interconnects and vertical TSVs are built with multi-layer graphene nanoribbons (MLGNRs) and carbon nanotubes (CNTs), respectively. Comparison in electrical performance shows that the voltage drop of 3-D integration is dominated by vertical components and therefore increasing the total number of signal/ground TSVs used for power delivery can significantly decrease the maximum voltage drop in 3-D integration. For present fabrication limits, only carbon based 3D integration built with larger diameter MWCNT TSVs and MLGNRs can obtain lower voltage drops in comparison to Cu interconnects. The proposed results would provide some design guides for future carbon-based 3-D integration.
Evolution of the cAMP-dependent protein kinase (PKA) catalytic subunit isoforms

The 3’,5’-cyclic adenosine monophosphate (cAMP)-dependent protein kinase, or protein kinase A (PKA), pathway is one of the most versatile and best studied signaling pathways in eukaryotic cells. The two paralogous PKA catalytic subunits Cα and Cβ, encoded by the genes PRKACA and PRKACB, respectively, are among the best understood model kinases in signal transduction research. In this work, we explore and elucidate the evolution of the alternative 5’ exons and the splicing pattern giving rise to the numerous PKA catalytic subunit isoforms. In addition to the universally conserved Cα1/Cβ1 isoforms, we find kinase variants with short N-termini in all main vertebrate classes, including the sperm-specific Cα2 isoform found to be conserved in all mammals. We also describe, for the first time, a PKA Cα isoform with a long N-terminus, paralogous to the PKA Cβ2 N-terminus. An analysis of isoform-specific variation highlights residues and motifs that are likely to be of functional importance.
Lysine144 is essential for the catalytic activity of Saccharomyces cerevisiae transaldolase

Replacement of lysine144 by glutamine in the pentose phosphate pathway enzyme transaldolase of Saccharomyces cerevisiae is associated with the complete loss of activity indicating the essential role in catalysis. Neither histidine nor cysteine is important for catalytic activity as proposed for the Candida utilis enzyme. Also we could not find any evidence for a half‐site character of the enzyme as described for transaldolase of C. utilis. Therefore, the reaction mechanisms for the two enzymes are different.
Web Object Mining Based on Entropy Pruning

Currently, a large number of Web information on the Internet is presented in structured objects. Mining object information from Web is of great importance for Web data management. MDR algorithm is a fully automated data records mining method. The algorithm can successfully detect data records in pages, but the effect is not very ideal because the noise existing in the page can not be eliminated. The paper introduced information entropy theory based on MDR algorithm and presents a new Web object mining method. Firstly, a Web page is divided to blocks and we construct a semantic DOM tree for each block. Then we compute the entropy value of the Web page and find topic regions using entropy pruning algorithm. Lastly, data records are mined from topic regions. Experiment proved the effectiveness and practicality of the method.
A hierarchy control strategy of distributed generation systems

An alternative energy supply to assist the main power stations in future power systems is expected to be distributed generation (DG), which is based on renewable energy sources (RESs). However, the rapid growth of power supply systems must also improve its reliability and supply quality. Interconnecting the DG systems to each other and to conventional power systems to operate in parallel in order to back each other up is an option. The key responsibility of the interconnected system is to control and maintain frequency and voltage of the power system. This is currently done using synchronous generators in many interconnected power systems. Doing this role with other DG technologies through their interface unit to the grid, namely the inverter is possible. This paper presents a control strategy of DG systems in interconnected grids. This proposed strategy is developed based on the control methodology of the interconnected conventional power systems. The results show that the proposed strategy is modular, flexible, and reliable and can simply be integrated into interconnected grids.
Estimating a just-noticeable difference for ocular comfort in contact lens wearers.

PURPOSE To estimate the just-noticeable difference (JND) in ocular comfort rating by human, contact lens-wearing subjects using 1 to 100 numerical scales. METHODS Ostensibly identical, new contact lenses were worn simultaneously in both eyes by 40 subjects who made individual comfort ratings for each eye using a 100-point numerical ratings scale (NRS). Concurrently, interocular preference was indicated on a five-point Likert scale (1 to 5: strongly prefer right, slightly prefer right, no preference, slightly prefer left, strongly prefer left, respectively). Differences in NRS comfort score (ΔC) between the right and left eyes were determined for each Likert scale preference criteria. The distribution of group ΔC scores was examined relative to alternative definitions of JND as a means of estimating its value. RESULTS For Likert scores indicating the presence of a slight interocular preference, absolute ΔC ranged from 1 to 30 units with a mean of 7.4 ± 1.3 (95% confidence interval) across all lenses and trials. When there was no Likert scale preference expressed between the eyes, absolute ΔC did not exceed 5 units. CONCLUSIONS For ratings of comfort using a 100-point numerical rating scale, the inter-ocular JND is unlikely to be less than 5 units. The estimate for the average value in the population was approximately 7 to 8 units. These numbers indicate the lowest level at which changes in comfort measured with such scales are likely to be clinically significant.
Hemingway's for Whom the Bell Tolls: Fact into Fiction

In writing For Whom the Bell Tolls, Ernest Hemingway drew upon his experiences as a war correspondent during the Spanish Civil War much more extensively than is generally recognized. Many of the characters, as well as the events and places of the novel, are based on historical fact and on the exploits of people Hemingway knew or heard of while he was covering the war. It is in this masterful blend of fact and fiction that For Whom the Bell Tolls achieves the status of a classic war novel.
Solution structure of the human HSPC280 protein

The human HSPC280 protein belongs to a new family of low molecular weight proteins, which is only present in eukaryotes, and is absent in fungi. The solution structure of HSPC280 was determined using multidimensional NMR spectroscopy. The overall structure consists of three α‐helices and four antiparallel β‐strands and has a winged helix‐like fold. However, HEPC280 is not a typical DNA‐binding winged helix protein in that it lacks DNA‐binding activity. Unlike most winged‐helix proteins, HSPC280 has an unusually long 13‐residue (P62–V74) wing 1 loop connecting the β3 and β4 strands of the protein. Molecules of HSPC280 have a positively charged surface on one side and a negatively charged surface on the other side of the protein structure. Comparisons with the C‐terminal 80‐residue domain of proteins in the Abra family reveal a conserved hydrophobic groove in the HSPC280 family, which may allow HSPC280 to interact with other proteins.
Pilgrims to the Eurozone: How Far, How Fast?

In our analysis, we re-examine the nominal and real convergence of all recent 10 European Union (EU) members to EU standards. Testing for monetary convergence has significant implications for interim optimal exchange rate and monetary policies before a formal and permanent link to the euro, while real convergence is the ultimate objective of economic integration. Novel features of the paper include broader measures of real convergence in both euro as well as local currencies, an examination of inflation and interest rate convergence with respect to the Maastricht benchmarks, and employment of more appropriate tests of convergence allowing for structural breaks. The results indicate slow but steady per-capita real income convergence towards EU standards. On the other hand, evidence indicates significant strong inflation and interest rate convergence. Policy implications of the paper are also discussed.
Identifying salient points

The definition of "important" or salient points on a shape is an old and fundamental problem in computer graphics. Important points, which we will term key points, can be used for representing a shape (e.g. as vertices of a polyline or as knots of a spline). Key points that correspond to perceptually salient points are useful as handles for editing. Key points are also good points to retain in simplifying a shape.
Rule Based Ensembles Using Pair Wise Neural Network Classifiers

In value estimation, the inexperienced people's estimation average is good approximation to true value, provided that the answer of these individual are independent. Classifier ensemble is the implementation of mentioned principle in classification tasks that are investigated in two aspects. In the first aspect, feature space is divided into several local regions and each region is assigned with a highly competent classifier and in the second, the base classifiers are applied in parallel and equally experienced in some ways to achieve a group consensus. In this paper combination of two methods are used. An important consideration in classifier combination is that much better results can be achieved if diverse classifiers, rather than similar classifiers, are combined. To achieve diversity in classifiers output, the symmetric pairwise weighted feature space is used and the outputs of trained classifiers over the weighted feature space are combined to inference final result. In this paper MLP classifiers are used as the base classifiers. The Experimental results show that the applied method is promising.