Miracle-dz/UniFAR-FTUs huggingface dataset:
'Computer' and 'Information and Communication Technology': Students' Culture Specific Interpretations

Given the use of information and communication technology (ICT) and computer as synonyms in ICTintegration research on the one hand, and the potential problems in doing so on the other, this contribution tries to gain insight in the understanding of the words computer and ICT in different settings. In five different countries (Belgium, Finland, Germany, Ghana and South-Africa) participants engaged in a word-association study. Each study addressed the following research question “Can the notion ‘computer’ be used as a proxy for the notion ‘information and communication technology’? A word-association task with ‘computer’ and ‘information and communication technology’ as stimuli words was used in the different studies. Data gathering methods followed the same basic principles but were adopted to diverse contexts of study. In order to analyse the data a shared classification scheme was developed. A chi square test was used to check the similarities and dissimilarities of the categories. In the results, while similar associations are generated by the two stimulus words, it is also clear that computer has a more technical connotation and ICT a broader, more communicationoriented connotation. Different findings in the different cultural settings constitute a warning for naive use of culture-specific research instruments.
Electrospun Fibers in Composite Materials for Medical Applications

Sem PDF conforme Despacho. The authors acknowledge Portuguese Science and Technology Foundation (FCT-MCTES) for the financial support through the Strategic Project PEstC/CTM/LA0025/2013-14. Ana C. Baptista also acknowledges FCT-MCTES for the doctoral grant SFRH/BD/69306/2010.
Heavy Ion Irradiation Effects on Cadmium Oxide (CdO) Quantum Dots Prepared by Quenching Method

Cadmium oxide (CdO) quantum dots were synthesized in the laboratory by quenching method using CdO powder sintered at 9000C and ethyl alcohol kept at ice cold temperature. X-ray diffraction investigations reveal the NaCl cubic structure of CdO quantum dots. Addition of ethylenediamine to a portion of reaction mixture containing quantum dots results in the conversion of nanoparticles to nanorods. Heavy ion irradiation using 90 MeV Carbon (C+6) ion beam accelerated at 15 UD Pelletron, with fluence varying from 1011 to 1013 ions/cm2 , produced enlargement in the size of quantum dots revealed by TEM investigations. Heavy ion irradiation effects need to be investigated further, in view of industrial applications of quantum dots.
Solvable local and stochastic volatility models: supersymmetric methods in option pricing

In this paper we provide an extensive classification of one- and two-dimensional diffusion processes which admit an exact solution to the Kolmogorov (and hence Black–Scholes) equation (in terms of hypergeometric functions). By identifying the one-dimensional solvable processes with the class of integrable superpotentials introduced recently in supersymmetric quantum mechanics, we obtain new analytical solutions. In particular, by applying supersymmetric transformations on a known solvable diffusion process (such as the Natanzon process for which the solution is given by a hypergeometric function), we obtain a hierarchy of new solutions. These solutions are given by a sum of hypergeometric functions, generalizing the results obtained in a paper by Albanese et al. (Albanese, C., Campolieti, G., Carr, P. and Lipton, A., Black–Scholes goes hypergeometric. Risk Mag., 2001, 14, 99–103). For two-dimensional processes, more precisely stochastic volatility models, the classification is achieved for a specific class called gauge-free models including the Heston model, the 3 / 2-model and the geometric Brownian model. We then present a new exact stochastic volatility model belonging to this class.
Robust Behavior-Based Control for Distributed Multi-Robot Collection Tasks

Abstract : We demonstrate the effectiveness of behavior-based control in facilitating the development and evaluation of multi-robot controllers that are: (1) robust to robot failures, and(2) easily modified to facilitate development of the controller variation that sufficiently satisfies the design requirements for the task. Our experimental focus here is distributed multi-robot collection, a class of tasks that includes de-mining and toxic waste clean-up. We demonstrate a basic multi-robot controller for the collection task, then show how to easily derive two spatio-temporal variations with markedly different performance properties. We evaluate the desirability of these controllers with respect to design requirements involving inter-robot interference, time-to-completion, and energy expenditure. The data for evaluation come from experiments using four physical mobile robots performing the three variations of the collection task.
Reveal Gene Expression Dynamics Via State-Space Model Based on the Decomposition of Functional Modules

Advances of high-throughput experimental techniques have generated large amounts of gene expression data. Biologically meaningful dynamic structures are expected to be hidden in these data, which are important for understanding the mechanism of cellular activities and identifying the function of genes. In this paper, a novel scheme is presented to reveal the dynamics of gene expression. State-Space Model(SSM) is developed based on the modern control theory. Based on the decomposition of functional modules, an effective strategy is designed to determine the SSM’s parameters. Via SSM, gene expression dynamics can be well revealed. To validate our approach and demonstrate its application, numerical experiments are designed by using cell cycle-regulated gene data sets of Yeast Saccharomyces cerevisiae.
Preservice Performance Assessment and Teacher Early Career Effectiveness : Preliminary Findings on the Performance Assessment for California Teachers

This study presents preliminary findings on the relationship between beginning teacher’s scores on the Performance Assessment for California Teachers (PACT), a preservice performance assessment of a wide range of teaching skills, and their subsequent teaching effectiveness measured by students’ value-added achievement gains in English Language Arts (ELA). Linking PACT scores and four separate value-added estimates for 14 firstand second-year teachers with 259 students in third through sixth grade in an urban school district, total PACT score correlated approximately . 50 with teacher value-added (ranging from .46 to .53, depending on the model), and subscores for the assessment dimension of the portfolio (evaluating candidates’ ability to use assessment data to support student learning) correlated . 58 to . 66 with value-added. PACT scores predicted very substantial differences in teacher value-added. For each additional point a teacher scored on PACT (evaluated on a 44-point scale), her students averaged a gain of one percentile point per year on the California Standards Tests as compared with similar students. Thus, students taught by a teacher at the top of the scale (44) scored, on average, 20 percentile points higher than those taught by a teacher receiving the lowest passing score (24). In this limited sample, PACT was a strong predictor of teacher effectiveness measured by students’ value-added achievement gains. Future studies will seek to increase the sample sizes with more complete data.
Monitoring Vertical Land Motions in Southwestern Taiwan with Retracked Topex/Poseidon and Jason-2 Satellite Altimetry

This study successfully uses satellite altimetry, including Topex/Poseidon and Jason-2, retrieved by novel retrackers to monitor vertical land motions in Southwestern Taiwan. Satellite altimetry was originally designed to measure open oceans, so waveform retracking should be applied to overcome the complex waveforms reflected from lands. Modified threshold and improved subwaveform threshold retrackers were used in the study to improve the accuracy of altimetric land surface heights (LSHs) in Southwestern Taiwan. Results indicate that the vertical motion rates derived from both retrackers coincide with those calculated by 1843 precise leveling points, with a correlation coefficient of 0.96 and mean differences of 0.43 and 0.52 cm/yr (standard deviations: 0.61 and 0.69 cm/yr). In addition, wet troposphere delay by precise point positioning with the use of Global Navigation Satellite System data was employed to evaluate the impact of the delay on the estimates of vertical motion rates compared with that traditionally derived from the European Center for Medium-Range Weather Forecasts model when the microwave radiometer is non-functional over lands. The accuracies of retracked altimetric land motion rates corrected by wet troposphere delays derived from both models show no remarkable differences in the Tuku and Yuanchang areas because the accuracy of retracked altimetric LSHs is significantly worse than that of wet troposphere delays.
The RNA helicase DHH1 is central to the correct expression of many developmentally regulated mRNAs in trypanosomes

In trypanosomes, the predominant mechanisms of regulation of gene expression are post-transcriptional. The DEAD-box RNA helicase DHH1 was identified in a screen for gene products that are necessary for the instability of the GPI-PLC mRNA in insect-stage trypanosomes. Expression of an ATPase-deficient dhh1 mutant caused a rapid growth arrest associated with a decrease in polysomes, an increase in P-bodies and a slight decrease in average mRNA levels. However, the effect of dhh1 mutant expression on both turnover and translational repression of mRNAs was selective. Whereas there was little effect on the stability of constitutive mRNAs, the control of a large cohort of developmentally regulated mRNAs was reversed; many mRNAs normally downregulated in insect-stage trypanosomes were stabilized and many mRNAs normally upregulated decreased in level. One stabilised mRNA, ISG75, was characterised further. Despite the overall decrease in polysomes, the proportion of the ISG75 mRNA in polysomes was unchanged and the result was ISG75 protein accumulation. Our data show that specific mRNAs can escape DHH1-mediated translational repression. In trypanosomes, DHH1 has a selective role in determining the levels of developmentally regulated mRNAs.
H19 long noncoding RNA controls the mRNA decay promoting function of KSRP

Significance Long noncoding RNAs (lncRNAs) provide new layers of complexity to gene expression control. We report on the functional consequences of the interaction between the ssRNA-binding protein K homology-type splicing regulatory protein (KSRP) with H19 lncRNA (H19) in multipotent C2C12 cells able to differentiate in culture toward myotubes in response to activation of cell signaling pathways, including AKT. KSRP and H19 interact exclusively in undifferentiated C2C12 cells, and this favors KSRP’s ability to interact with the promyogenic transcript myogenin and to favor its degradation. AKT activation induces KSRP dissociation from H19 and, as a consequence, from myogenin mRNA that is stabilized. H19 likely acts as a scaffold that favors KSRP-mediated degradation of myogenin to contribute to the maintenance of the undifferentiated state of C2C12 cells. Long noncoding RNAs (lncRNAs) interact with protein factors to regulate different layers of gene expression transcriptionally or posttranscriptionally. Here we report on the functional consequences of the unanticipated interaction of the RNA binding protein K homology-type splicing regulatory protein (KSRP) with the H19 lncRNA (H19). KSRP directly binds to H19 in the cytoplasm of undifferentiated multipotent mesenchymal C2C12 cells, and this interaction favors KSRP-mediated destabilization of labile transcripts such as myogenin. AKT activation induces KSRP dismissal from H19 and, as a consequence, myogenin mRNA is stabilized while KSRP is repurposed to promote maturation of myogenic microRNAs, thus favoring myogenic differentiation. Our data indicate that H19 operates as a molecular scaffold that facilitates effective association of KSRP with myogenin and other labile transcripts, and we propose that H19 works with KSRP to optimize an AKT-regulated posttranscriptional switch that controls myogenic differentiation.
A circular model for song motor control in Serinus canaria

Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture.
Resonance-based task space controller for multi-joint robot with adjustable equilibrium angle of elastic element

This paper proposes a task space trajectory tracking controller based on resonance for multi-joint robots. This controller generates desired motions, which are specified in the task space, while adjusting stiffness of mechanical elastic elements installed in each joint of the robots. This controller also adjusts equilibrium angles of the elastic elements. These parameter adjustments minimize actuator torque. Advantages of the proposed controller are to work without using exact parameter values of the controlled systems nor huge numerical calculations. We mathematically discuss stability of the controlled systems. Simulation results demonstrate the effectiveness of the proposed controller.
Optimal Quantum Sample Complexity of Learning Algorithms

$ \newcommand{\eps}{\varepsilon} $In learning theory, the VC dimension of a concept class $C$ is the most common way to measure its "richness. " In the PAC model $$ \Theta\Big(\frac{d}{\eps} + \frac{\log(1/\delta)}{\eps}\Big) $$ examples are necessary and sufficient for a learner to output, with probability $1-\delta$, a hypothesis $h$ that is $\eps$-close to the target concept $c$. In the related agnostic model, where the samples need not come from a $c\in C$, we know that $$ \Theta\Big(\frac{d}{\eps^2} + \frac{\log(1/\delta)}{\eps^2}\Big) $$ examples are necessary and sufficient to output an hypothesis $h\in C$ whose error is at most $\eps$ worse than the best concept in $C$. Here we analyze quantum sample complexity, where each example is a coherent quantum state. This model was introduced by Bshouty and Jackson, who showed that quantum examples are more powerful than classical examples in some fixed-distribution settings. However, Atici and Servedio, improved by Zhang, showed that in the PAC setting, quantum examples cannot be much more powerful: the required number of quantum examples is $$ \Omega\Big(\frac{d^{1-\eta}}{\eps} + d + \frac{\log(1/\delta)}{\eps}\Big)\mbox{ for all }\eta> 0. $$ Our main result is that quantum and classical sample complexity are in fact equal up to constant factors in both the PAC and agnostic models. We give two approaches. The first is a fairly simple information-theoretic argument that yields the above two classical bounds and yields the same bounds for quantum sample complexity up to a $\log(d/\eps)$ factor. We then give a second approach that avoids the log-factor loss, based on analyzing the behavior of the "Pretty Good Measurement" on the quantum state identification problems that correspond to learning. This shows classical and quantum sample complexity are equal up to constant factors.
Writer–Reader Contagion of Inspiration and Related States: Conditional Process Analyses Within a Cross-Classified Writer × Reader Framework

A longstanding tradition in the humanities holds that a writer’s inspiration is infectious, but this thesis has not been tested. We hypothesized that (a) inspiration is infectious, such that inspired writers are more inspiring to the average reader; (b) contagion is mediated by the insightfulness of the text; and (c) contagion is moderated by readers’ openness to experience, such that open readers are more prone to contagion. To test these hypotheses, a sample of 195 student writers, each of whom wrote 1 poem, was crossed with a sample of 220 student readers, who read all poems. Data were available for 36,020 cells of the resulting Writer × Reader matrix. Our analytic approach integrated cross-classified multilevel modeling with conditional process analysis. As hypothesized, writers who were more inspired elicited higher levels of inspiration in the average reader. Inspiration contagion was mediated by the insightfulness and pleasantness of the text and was partially suppressed by originality. Inspiration contagion was moderated by reader openness. Moderated mediation analyses indicated that open readers were prone to contagion because they were tolerant of the originality and sublimity of inspired writing. Additional analyses differentiated contagion of inspiration from contagion of its covariates (awe, positive affect), documented effects of writer inspiration on reader enthrallment (awe, chills), and showed that writer effort is a poor predictor of reader states. The infectiousness of inspiration—through poetry, if not also through scripture and academic writing—suggests that a given instance of inspiration may have far-reaching cultural implications, including dissemination of innovations and ideologies.
Solving Reservoir Simulation Equations

Reservoir simulation is a necessary tool for making decisions. It is through numerical simulation that one can obtain knowledge pertaining to the processes occurring in the interior of an oil reservoir and hence, to enable an analysis of the various recovery strategies in order to guarantee optimal exploitation. History matching, optimization, and what-if scenarios require the simulation of large numbers of complex field-scale models.
Adaptive & parallel simulated annealing genetic algorithm based on cloud model

Due to the “premature” phenomenon and poor local search ability of genetic algorithm, an improved genetic algorithm, adaptive and parallel simulated annealing genetic algorithm based on cloud model (PCASAGA), is proposed in this paper. This algorithm integrates cloud model, multi-populations optimization mechanism, parallel techniques, simulated annealing algorithm and adaptive mechanism. It applies qualitative reasoning technology - cloud model to the regulation of crossover probability and mutation probability to improve the adaptive ability. The use of new multi-threading building blocks TBB parallel technology has greatly enhanced the operational efficiency of the algorithm. simulation results illustrate that PCASAGA has better convergence speed and optimal results than original genetic algorithm, and takes full advantage of the current multi-core resources of computers.
Citalopram may reduce sympathoadrenal hyperactivity in elderly depressed patients: an open multicenter study in Belgium and Luxembourg.

INTRODUCTION Through effects of catecholamines upon the heart, blood vessels and platelets, sympathoadrenal hyperactivity contributes to the development of cardiovascular diseases in elderly depressed patients. To assess the cardiovascular effect of Citalopram in elderly depressed patients, data from an open multicenter study in Belgium and Luxembourg, in which a total of 811 patients were evaluated, was retrospectively analysed. Although the aim of the study was to assess the efficacy and safety of Citalopram, blood pressure and heart rate were also monitored. SUBJECT AND METHODS Patients included in the study were referred either by psychiatrists, geriatricians or general practitioners. Clinical assessment included ratings on the Hamilton Rating Depression Scale, the Clinical Global Impression Scale, the UKU Side effect rating scale and the assessment of side effects spontaneously reported. RESULTS With few side effects, Citalopram significantly improves the clinical condition of elderly patients suffering from depressive symptoms. A series of repeated multivariate analyses of covariance were performed on heart rate and blood pressure controlling for the effect of age. Interestingly, a sustained decrease of these parameters was shown during the whole study period reaching significance for systolic blood pressure (p<0.05). These effects were observed both in responding as well as non-responding patients, and were somewhat more marked in responders for heart rate (p=0.058). CONCLUSION The slight but significant decrease in systolic blood pressure and heart rate suggests that citalopram may reduce sympathoadrenal hyperactivity and the related increased cardiovascular morbidity and mortality associated with depression.
Finescale Evaluation of Drought in a Tropical Setting: Case Study in Sri Lanka

In regions of climatic heterogeneity, finescale assessment of drought risk is needed for policy making and drought management, mitigation, and adaptation. The relationship between drought relief payments (a proxy for drought risk) and meteorological drought indicators is examined through a retrospective analysis for Sri Lanka (1960‐2000) based on records of district-level drought relief payments and a dense network of 284 rainfall stations. The standardized precipitation index and a percent-of-annual-average index for rainfall accumulated over 3, 6, 9, and 12 months were used, gridded to a spatial resolution of 10 km. An encouraging correspondence was identified between the spatial distribution of meteorological drought occurrence and historical drought relief payments at the district scale. Time series of drought indices averaged roughly over the four main climatic zones of Sri Lanka showed statistically significant (p , 0.01) relationships with the occurrence of drought relief. The 9-month cumulative drought index provided the strongest relationships overall, although 6- and 12-month indicators provided generally similar results. Some cases of appreciable drought without corresponding relief payments could be attributed to fiscal pressures, as during the 1970s. Statistically significant relationships between drought indicators and relief payments point to the potential utility of meteorological drought assessments for disaster risk management. In addition, the study provides an empirical approach to testing which meteorological drought indicators bear a statistically significant relationship to drought relief across a wide range of tropical climates.
Performance Analysis and Synchronization Failures in Deep sub Micron Technology

-Synchronizers were required when reading an asynchronous input. In a multi clock system, synchronizers are required when on-chip data cross the clock domain boundaries which guard against synchronization failures but introduce latency in processing the asynchronous input. We use method that hides synchronization latency by overlapping it with computation cycles Synchronous logic is designed such that state bit transitions have sufficient time to propagate to subsequent flip-flops by the time of the following clock edge. If one flip-flop k becomes metastable and produces a transition whose clock-to-q delay is longer than expected, this transition may not have sufficient time to reach all destination flip-flops .