Miracle-dz/UniFAR-FTUs huggingface dataset:
Tailored eHealth Lifestyle Promotion: Which Behavioral Modules Do Users Prefer?

Health risk behaviors are widespread among adults and often co-occur. eHealth computer-tailored technology provides individuals with personalized feedback regarding multiple lifestyle behaviors. First, the authors investigated individuals’ preferences for particular lifestyle modules and hypothesised that health preventive behavior modules would be preferred over addictive behavior modules. Second, characteristics associated with these choices were examined. A web-based questionnaire assessed demographics, health status, and five lifestyle behaviors (i.e., physical activity, fruit consumption, vegetable consumption, alcohol intake and tobacco use) among adults (N = 1,828). Responses were translated into a health risk appraisal outlining whether respondents adhered to the national guidelines for these behaviors. Next, respondents could select one of the lifestyle modules providing personalized advice. More than 60% of the participants failed to meet the guidelines for more than one lifestyle behavior. The physical activity module was the most popular, followed by the smoking and fruit modules. Young adults tended to prefer the physical activity and fruit modules, whereas the vegetable module was more popular among older adults. No consistent pattern was identified for the alcohol and smoking modules. The results support the authors’ hypothesis that health preventive behaviors—in particular, physical activity—would be preferred. Although this could imply that physical activity could serve as a gateway behavior when aiming at multiple behavior changes, it is also conceivable that other mechanisms, such as the actual success of behavior change, or the fact that people can choose, may increase chances of multiple behavior change. Hence, mechanisms leading to multiple behavior change need to be further explored.
Analysis of the Kinetics of Transcription and Replication of the Rotavirus Genome by RNA Interference

ABSTRACT Rotaviruses have a genome composed of 11 segments of double-stranded RNA (dsRNA) surrounded by three protein layers. The virus contains an RNA-dependent RNA polymerase that synthesizes RNA transcripts corresponding to all segments of the viral genome. These transcripts direct the synthesis of the viral proteins and also serve as templates for the synthesis of the complementary strand to form the dsRNA genome. In this work, we analyzed the kinetics of transcription and replication of the viral genome throughout the replication cycle of the virus using quantitative reverse transcription-PCR. The role of the proteins that form double-layered particles ([DLPs] VP1, VP2, VP3, and VP6) in replication and transcription of the viral genome was analyzed by silencing their expression in rotavirus-infected cells. All of them were shown to be essential for the replication of the dsRNA genome since in their absence there was little synthesis of viral mRNA and dsRNA. The characterization of the kinetics of RNA transcription and replication of the viral genome under conditions where these proteins were silenced provided direct evidence for a second round of transcription during the replication of the virus. Interestingly, despite the decrease in mRNA accumulation when any of the four proteins was silenced, the synthesis of viral proteins decreased when VP2 and VP6 were knocked down, whereas the absence of VP1 and VP3 did not have a severe impact on viral protein synthesis. Characterization of viral particle assembly in the absence of VP1 and VP3 showed that while the formation of triple-layered particles and DLPs was decreased, the amount of assembled lower-density particles, often referred to as empty particles, was not different from the amount in control-infected cells, suggesting that viral particles can assemble in the absence of either VP1 or VP3.
Cognitive Radio Channels with Arbitrarily Correlated Sources

Reliable transmission of a pair of arbitrarily correlated sources over a discrete memoryless cognitive radio channel is studied. We derive a sufficient condition for lossless transmission of such communication scenario using superposition coding, correlation preserving technique, random source partition, a binning scheme and joint typicality decoding. This sufficient condition reduces to the known rate regions for interference channels with independent, specially correlated and arbitrarily correlated sources.
Long-time behaviour of classical Hele-Shaw flows with injection near expanding balls

Long-time behaviour for the classical Hele-Shaw flow with injection in the origin is discussed. Domains that are small perturbations of balls are considered. Radially symmetric solutions are turned into stationary ones by suitable time-dependent scaling. An evolution equation for the motion of the domain is derived and linearised. Spectral properties of the linearisation and the principle of linearised stability are used to show that perturbations of balls decay algebraically. Convergence turns out to be faster for domains for which low Richardson moments vanish.
On the Use of Reverberation Chambers to Simulate a Rician Radio Environment for the Testing of Wireless Devices

With the proliferation of wireless devices in recent years, there is a growing need to test the operation and functionality of these various devices in different multipath environments, ranging from line-of-sight environment to a pure Rayleigh environment. In this paper we discuss how a reverberation chamber can be used to simulate a controllable Rician radio environment for the testing of a wireless device. We show that by varying the characteristics of the reverberation chamber and/or the antenna configurations in the chamber, any desired Rician K-factor can be obtained. Expressions for the desired K-factor as a function of the chamber and antenna characteristics will be presented. Experimental results are presented to illustrate the validity of these expressions, to show how the reverberation chamber can be used to simulate different multipath environments, and to show the realization of a controlled K-factor test facility. We present both a one-antenna and a two-antenna test configuration approach
A not so delicate sound of Europeanness. and the euro-dollar risk premium

Although the European Monetary Union (EMU) is mainly an economic institution, its future has always hinged upon political manoeuvres. This article examines whether and to what extent non-scheduled and scheduled political events concerning the fiscal governance framework of the EMU have influenced foreign exchange markets. In particular, we estimate how decisions made by the European Commission, the Economic and Financial Affairs Council and the European Council affected the systematic euro-dollar risk premium. Analysing daily data from 2001 to 2005 with a Component GARCH model, we show how the political rhetoric and action have influenced financial markets. Our empirical results highlight crucial shortcomings of the fiscal policy framework of the EMU. Component GARCH, exchange rates, euro, political events, risk premium, uncovered interest rate parity F31, E62, C22 * School of Economics and Business Administration, Friedrich-Schiller-University Jena; e-mail: christian.fahrholz@ uni-jena.de. # University of Konstanz, Department of Politics and Management; e-mail: gerald.schneider@uni-konstanz.de. Ch. Fahrholz, G. Schneider 6
Sociality Motivation and Anthropomorphic Thinking about Pets

ABSTRACT Sociality motivation, the need to feel socially connected with others, has been proposed as an important determinant of individual variation in anthropomorphic thinking. Specifically, it has been suggested that people who are socially isolated or disconnected will tend to infer more human-like mental states in animals and other nonhuman agents (computers, robots, metaphysical beings, etc.), than those who have higher levels of contact with other people. We investigated this hypothesis in a community-based sample of cat and dog owners, measuring degree of anthropomorphism by asking them which emotions they believed their pet was capable of experiencing, how likely they were to rely on it for social support, and how attached they were to it. Structural measures of social disconnection, including the number of other adults living in the household and the number of social contacts outside the home, were not generally associated with the tendency to think anthropomorphically about pets. However, owners living in households with no children (under the age of 16 years) reported higher levels of attachment to their pet than did those with children (B = 1.678, p < 0.001), and felt that they derived relatively more social support from it than they did from humans (F(1,244) = 4.997, p < 0.05, partial η2 = 0.020). In addition, a trait-based indicator of social disconnection (self-reported anxiety about human social relationships) was associated with a heightened tendency for owners to report turning to their pet for support (F(1,244) = 19.617, p < 0.001, partial η2 = 0.074), and attributing more human-like emotions to it (F(1,244) = 8.354, p < 0.005, partial η2 = 0.033). These findings support a link between social disconnection and anthropomorphic thinking in a community setting; they also suggest that different forms of social disconnection (structural and trait-based) may generate different types of sociality motivation, and thereby influence different facets of anthropomorphic thinking.
A Novel QAM-FBMC without Intrinsic Time-Domain Interference

In the recent fifth generation (5G) research, filter bank multi-carrier (FBMC) technique is one of the competitive substitutes to orthogonal frequency division multiplexing (OFDM). The conventional FBMC schemes, such as FBMC staggered-modulated multitone (FBMC-SMT) and frequency spreading FBMC (FS-FBMC), have the intrinsic time-domain interference which is caused by the overlap of symbols and depend on offset quadrature amplitude modulation (OQAM). In order to overcome the two drawbacks, a non-overlapping QAM-FBMC scheme is proposed based on the FBMC-SMT and analyzed in this paper. Moreover, the non-overlapping QAM-FBMC scheme not only discards cyclic prefix (CP) as other FBMC schemes, but also shortens the duration length of symbol waveforms compared with that of FS-FBMC. Therefore, its spectrum efficiency (SE) outperforms other multi-carrier systems. Simulation results indicate that non-overlapping QAM-FBMC scheme indeed improves the SE and obtains almost the same bit error rate performance as that of the FBMC-SMT as well as OFDM in multi-path fading channel.
An efficient framework for spectral-spatial classification of hyperspectral images in urban areas

Many researches have demonstrated that the spatial information can play an important role in the classification of hyperspectral imagery. Recently, an effective approach for spectral-spatial classification has been proposed using Minimum Spanning Forest (MSF) grown from automatically selected markers. This paper aims at improving this approach for classification of hyperspectral images in urban areas. The proposed framework is based on deriving the optimal spatial and spectral features of the original hyperspectral image using the Principal Component Analysis (PCA). The spatial features extracted in this study are wavelet, Gabor filter, mean, contrast, entropy, variance, homogeneity, dissimilarity, second moment, and correlation. The experimental results on three hyperspectral datasets demonstrate that compared to the original MSF-based approach, the proposed framework yields more accurate classification maps.
Universal coding for distributions over co-trees

For an arbitrary ordered set, we consider the model of all distributions P for which an element which precedes another element is considered the more significant one in the sense that the implication a ≤ b ⇒ P(a) ≥ P(b) holds. It will be shown that if the ordered set is a finite co-tree, then the universal predictor for the indicated model or, equivalently, the corresponding universal code, can be determined exactly via an algorithm of reasonably low complexity.
The complexities of convergence

This article examines the spread of multiskilling in newsrooms, and whether such practices are enskilling or deskilling journalists. It argues that rather than a simple oppositional definition it would be more fruitful to acknowledge journalists’ varying skill sets according to degree and emphasis. It draws on an ongoing longitudinal study including interviews conducted in 2009, 2010 and 2011 with journalists, editors and their managers at three BBC regional newsrooms, where multiskilled work practices have been introduced more rapidly and systematically than in national newsrooms. The study finds that a variety of organizational strategies have been adopted to enable journalists to work across platforms including radio, television and online. Both training and experience are seen as important in upholding skill levels, as well as the need to avoid the ‘decay curve’. Nevertheless, innate ability can be considered crucial too, and may dictate whether a journalist remains grounded in one discipline. Despite a reduction in numbers, the heralded demise of the ‘craftsman specialist’ has not completely come about. However, the spread of multiskilling in combination with a reduction in workforce can add to stresses on journalists, and affect quality of output.
Enhanced histamine production through the induction of histidine decarboxylase expression by phorbol ester in Jurkat cells

Histamine (HA), a mediator of inflammation, type I allergic responses and neurotransmission, is synthesized from L-histidine, the reaction of which is catalyzed by histidine decarboxylase (HDC). HDC has been reported to be induced by various stimuli, not only in mast cells and basophils, but also in T lymphocytes and macrophages. Although its mRNA has been shown to be increased in Jurkat cells when treated with phorbol 12-myristate 13-acetate (TPA), little is known concerning the induced production of HA by HDC. The present study quantified the trace amounts of intracellular HA using ultra-high liquid chromatography in combination with the 6-aminoquinoline carbamate-derivatization technique. To test whether the cellular level of HA is elevated by the induction of HDC in Jurkat cells treated with TPA, the peak corresponding to authentic HA in the cell lysate was fractioned and its molecular weight determined by matrix-assisted laser desorption/ionization quadrupole ion trap time-of-flight mass spectrometry. The results of this study show that the HA level is increased by the induction of HDC expression by TPA in Jurkat cells. Therefore, this method is useful in elucidating the physiological significance of HA production.
Clinical Utility of Five Dimensional Systems for Personality Diagnosis: A “Consumer Preference” Study

This study compares the clinical relevance and utility of five dimensional diagnostic systems for personality disorders that have been proposed for the forthcoming edition of DSM (DSM-V): (1) a criteria counting model based on current DSM-IV diagnostic criteria; (2) a prototype matching model based on current DSM-IV diagnostic criteria; (3) a prototype matching model based on the Shedler-Westen Assessment Procedure (SWAP); (4) the Five Factor Model; and (5) Cloninger's Psychobiological Model. A random national sample of psychiatrists and psychologists applied all 5 diagnostic systems to a patient in their care and rated the clinical utility of each system. The SWAP Prototype Matching and DSM-IV Prototype Matching models were judged most clinically useful and relevant. The Five Factor Model and Cloninger's Psychobiological Model were judged least useful. The prototype matching systems most faithfully capture the personality syndromes seen in clinical practice, and permit rich descriptions of diagnostic constructs without a proportionate increase in user effort. A prototype matching approach to personality diagnosis deserves consideration for DSM-V.
Of Television and Social Capital

This essay wonders anew about the issues discussed in Seducing America: How Television Charms the Modern Voter and asks if those concerns are still relevant today. The author concludes that they are. The language of political cynicism, it is argued, has become the indigenous language of television and it depletes the supply of social capital in the United States. The essay explains why this is true and what happens as a result.
Researching Policy Research

This article addresses the problems of exploring the use of research in the policy process. Measuring the impact or outcomes of policy research raises complex methodological and conceptual issues. How the task is approached and what measures are used depend, for example, on how the nature of the policy-making process is conceived, on what functions research is presumed to play in the making of policy, and on the way in which the relationship between research and policy is presented. Drawing on the wider literature in this field, this article describes and illustrates the three main methods that have been used for studying research use in the policy arena—impact studies, insider accounts, and case studies—and examines their strengths and weaknesses.
APJ1 and GRE3 Homologs Work in Concert to Allow Growth in Xylose in a Natural Saccharomyces sensu stricto Hybrid Yeast

Creating Saccharomyces yeasts capable of efficient fermentation of pentoses such as xylose remains a key challenge in the production of ethanol from lignocellulosic biomass. Metabolic engineering of industrial Saccharomyces cerevisiae strains has yielded xylose-fermenting strains, but these strains have not yet achieved industrial viability due largely to xylose fermentation being prohibitively slower than that of glucose. Recently, it has been shown that naturally occurring xylose-utilizing Saccharomyces species exist. Uncovering the genetic architecture of such strains will shed further light on xylose metabolism, suggesting additional engineering approaches or possibly even enabling the development of xylose-fermenting yeasts that are not genetically modified. We previously identified a hybrid yeast strain, the genome of which is largely Saccharomyces uvarum, which has the ability to grow on xylose as the sole carbon source. To circumvent the sterility of this hybrid strain, we developed a novel method to genetically characterize its xylose-utilization phenotype, using a tetraploid intermediate, followed by bulk segregant analysis in conjunction with high-throughput sequencing. We found that this strain’s growth in xylose is governed by at least two genetic loci, within which we identified the responsible genes: one locus contains a known xylose-pathway gene, a novel homolog of the aldo-keto reductase gene GRE3, while a second locus contains a homolog of APJ1, which encodes a putative chaperone not previously connected to xylose metabolism. Our work demonstrates that the power of sequencing combined with bulk segregant analysis can also be applied to a nongenetically tractable hybrid strain that contains a complex, polygenic trait, and identifies new avenues for metabolic engineering as well as for construction of nongenetically modified xylose-fermenting strains.
International Conference on Intelligent and Advanced Systems 2007 Forecasting KOSPI by Weighted Average Defuzzification Based on NEWFM

Fuzzy neural networks have been successfully applied to generate predictive rules for stocks forecasting. This paper presents a methodology for forecasting the daily Korea composite stock price index (KOSPI) based on the neural network with weighted fuzzy membership functions (NEWFM) and time series of KOSPI based on the defuzzyfication of weighted average method (The fuzzy model suggested by Takagi and Sugeno in 1985). NEWFM is a new model of neural networks to improve forecasting accuracy by using self adaptive weighted fuzzy membership functions. The degree of classification intensity is obtained by bounded sum of weighted fuzzy membership functions extracted by NEWFM, and then weighted average defuzzification is used for forecasting KOSPI. In this paper, the Haar wavelet function is used as a mother wavelet. A set of fIVe extracted coefficient features of the Haar WT are presented to forecast KOSPI. The total number of samples is 2928 trading days, from January 1989 to December 1998. About 80°A. of the data is used for training and 20°A. for testing. The result of classification rate is 58.0034%. The implementation of the NEWFM demonstrates an excellent capability in the field of stocks forecasting.
Fast Biped Walking with a Sensor-driven Neuronal Controller and Real-time Online Learning

In this paper, we present our design and experiments on a planar biped robot under the control of a pure sensor-driven controller. This design has some special mechanical features, for example small curved feet allowing rolling action and a properly positioned center of mass, that facilitate fast walking through exploitation of the robot's natural dynamics. Our sensor-driven controller is built with biologically inspired sensor- and motor-neuron models, and does not employ any kind of position or trajectory tracking control algorithm. Instead, it allows our biped robot to exploit its own natural dynamics during critical stages of its walking gait cycle. Due to the interaction between the sensor-driven neuronal controller and the properly designed mechanics of the robot, the biped robot can realize stable dynamic walking gaits in a large domain of the neuronal parameters. In addition, this structure allows the use of a policy gradient reinforcement learning algorithm to tune the parameters of the sensor-driven controller in real-time, during walking. This way RunBot can reach a relative speed of 3.5 leg lengths per second after only a few minutes of online learning, which is faster than that of any other biped robot, and is also comparable to the fastest relative speed of human walking.
Improving on the Independent Metropolis-Hastings algorithm

This paper proposes methods to improve Monte Carlo estimates when the Independent Metropolis-Hastings Algorithm (IMHA) is used. Our rst approach uses a control variate based on the sample generated by the proposal distribution. We derive the variance of our estimator for a xed sample size n and show that, as n tends to innit y, this variance is asymptotically smaller than the one obtained with the IMHA. Our second approach is based on Jensen's inequality. We use a Rao-Blackwellization and exploit the lack of symmetry in the IMHA. An upper bound on the improvements that we can obtain by these methods is derived.
Munich-Edinburgh-Stuttgart Submissions at WMT13: Morphological and Syntactic Processing for SMT

We present 5 systems of the MunichEdinburgh-Stuttgart 1 joint submissions to the 2013 SMT Shared Task: FR-EN, ENFR, RU-EN, DE-EN and EN-DE. The first three systems employ inflectional generalization, while the latter two employ parser-based reordering, and DE-EN performs compound splitting. For our experiments, we use standard phrase-based Moses systems and operation sequence models (OSM).
Finding regulatory modules through large-scale gene-expression data analysis

MOTIVATION The use of gene microchips has enabled a rapid accumulation of gene-expression data. One of the major challenges of analyzing this data is the diversity, in both size and signal strength, of the various modules in the gene regulatory networks of organisms. RESULTS Based on the iterative signature algorithm [Bergmann,S. , Ihmels,J. and Barkai,N. (2002) Phys. Rev. E 67, 031902], we present an algorithm-the progressive iterative signature algorithm (PISA)-that, by sequentially eliminating modules, allows unsupervised identification of both large and small regulatory modules. We applied PISA to a large set of yeast gene-expression data, and, using the Gene Ontology database as a reference, found that the algorithm is much better able to identify regulatory modules than methods based on high-throughput transcription-factor binding experiments or on comparative genomics.