Miracle-dz/UniFAR-FTUs huggingface dataset:
Speech-filtered bubble ray: improving target acquisition on display walls

The rapid development of large interactive wall displays has been accompanied by research on methods that allow people to interact with the display at a distance. The basic method for target acquisition is by ray casting a cursor from one's pointing finger or hand position; the problem is that selection is slow and error-prone with small targets. A better method is the bubble cursor that resizes the cursor's activation area to effectively enlarge the target size. The catch is that this technique's effectiveness depends on the proximity of surrounding targets: while beneficial in sparse spaces, it is less so when targets are densely packed together. Our method is the speech-filtered bubble ray that uses speech to transform a dense target space into a sparse one. Our strategy builds on what people already do: people pointing to distant objects in a physical workspace typically disambiguate their choice through speech. For example, a person could point to a stack of books and say "the green one". Gesture indicates the approximate location for the search, and speech 'filters' unrelated books from the search. Our technique works the same way; a person specifies a property of the desired object, and only the location of objects matching that property trigger the bubble size. In a controlled evaluation, people were faster and preferred using the speech-filtered bubble ray over the standard bubble ray and ray casting approach.
Diskussionspapiere Discussion Papers Discussion Paper No . 228 Aggregation and Seasonal Adjustment Empirical Results for EMU Quarterly National Accounts

This paper investigates the differences between directly and indirectly seasonally adjusted aggregates. This difference is derived analytically for linear seasonal adjustment methods. GDP data for five European countries and three classes of seasonal adjustment methods are used to show empirically the differences between both approaches. For this purpose cointegration methods and cross-spectral analysis are applied. The analysis shows that there are no differences in the long-run components of directly and indirectly adjusted aggregates, whereas differences in the short-run components depend strongly on the seasonal adjustment methods applied in the indirect and direct approaches. JEL classification: C49
Bubble Nasal CPAP, Early Surfactant Treatment, and Rapid Extubation Are Associated With Decreased Incidence of Bronchopulmonary Dysplasia in Very-Low-Birth-Weight Newborns: Efficacy and Safety Considerations

BACKGROUND: Current literature has been inconsistent in demonstrating that minimizing the duration of mechanical ventilation in very-low-birth-weight (VLBW) newborns reduces lung damage. OBJECTIVE: To determine if introduction of bubble nasal CPAP (bnCPAP), early surfactant treatment, and rapid extubation (combined bnCPAP strategy) in our community-based neonatal ICU reduced bronchopulmonary dysplasia (BPD). METHODS: This was a 7-year retrospective, single-institution review of respiratory outcomes in 633 VLBW babies before and after introduction of the combined bnCPAP strategy. Coincident changes in newborn care were taken into account with a logistic regression model. RESULTS: The average percentage of VLBW newborns with BPD decreased to 25.8% from 35.4% (P = .02), reaching a minimum in the last post-bnCPAP year of 22.1% (P = .02). When other coincident changes in newborn care during the study years were taken into account, VLBW babies in the post-bnCPAP years had a 43% lower chance of developing BPD (P = .003, odds ratio 0.43, 95% CI 0.25–0.75). Decreases occurred in mechanical ventilation and the percentage of infants discharged on diuretics and on supplemental oxygen. Among the subset of extremely-low-birth-weight newborns, improved respiratory outcomes in the post-bnCPAP years, as compared to outcomes in the pre-bnCPAP years, included an increase in the percentage alive and off mechanical ventilation at 1 week postnatal age (P < .001), a more rapid extubation rate (P < .03), a decrease in the median days on mechanical ventilation (P = .002), and a decrease in the percentage with BPD plus died (P = .01). Post-bnCPAP extremely-low-birth-weight babies had a statistically significant decrease in retinopathy of prematurity, an increase in low-grade intraventricular hemorrhage, and a decrease in ductal ligations. CONCLUSIONS: A combined BnCPAP strategy may contribute to a reduction of BPD, after adjusting for concurrent treatments.
The art of selective killing: plasmid toxin/antitoxin systems and their technological applications.

Most bacterial strains harbor plasmids that are maintained with remarkable stability. A large variety of plasmids encode systems that act when other control mechanisms have failed, i.e., when plasmid-free progeny is generated during replication. The mechanisms that control plasmid maintenance by T/A loci are well known: the antagonistic regulators that neutralize the toxins are metabolically unstable. Rapid depletion of these unstable regulators occurs in newborn, plasmid-free cells. As the same cells have inherited stable toxin molecules from the mother cell, the toxin will no longer be neutralized by the antitoxin, leading to the killing of the plasmid-free cells. This mechanism effectively reduces the proliferation of plasmid-free cells in growing bacterial populations (1). The most widely studied T/A system so far is the ccd system located on the F plasmid (2). The ccd system is composed of two genes, ccdA and ccdB, encoding small proteins: the CcdA antidote (8.7 kDa) and the CcdB toxin (11.7 kDa). The CcdB protein acts as a poison because it selectively targets the Escherichia coli DNA gyrase, a bacterial topoisomerase II. Early studies of this T/A system were performed at the Universite Libre de Bruxelles (ULB). Today new applications are commercialized by Delphi Genetics SA, a spin off company of the ULB founded by the researchers who developed the use of T/A systems as selectable markers. POSITIVE SELECTION VECTORS
Classification with probabilistic targets

Modern robotic platforms, deployed for environmental monitoring and mapping, are able to rapidly accumulate large data sets. Whilst the data sets collected by these platforms are highly descriptive, they are often too large for human experts to analyse exhaustively. Although the large data sets could be analysed by humans in principle, the amount of labour and time required to process them is not cost effective. In this paper we focus on the classification task of learning the relationship between low resolution, remotely sensed data and categories derived from direct observations of the same phenomenon. To reduce the labour requirements of categorising the direct observations we forgo human supervision and rely on an unsupervised clustering model to segregate the observations into similar groups of data. Rather than using the discrete cluster labels to train a conventional classifier, we develop a new Gaussian process classifier capable of accepting probabilistic training targets. This allows the probabilistic information generated during clustering to be preserved during classification. We demonstrate the new model, in an environmental monitoring application, using data collected by an autonomous underwater vehicle.
External Validation of a Measurement Tool to Assess Systematic Reviews (AMSTAR)

Background Thousands of systematic reviews have been conducted in all areas of health care. However, the methodological quality of these reviews is variable and should routinely be appraised. AMSTAR is a measurement tool to assess systematic reviews. Methodology AMSTAR was used to appraise 42 reviews focusing on therapies to treat gastro-esophageal reflux disease, peptic ulcer disease, and other acid-related diseases. Two assessors applied the AMSTAR to each review. Two other assessors, plus a clinician and/or methodologist applied a global assessment to each review independently. Conclusions The sample of 42 reviews covered a wide range of methodological quality. The overall scores on AMSTAR ranged from 0 to 10 (out of a maximum of 11) with a mean of 4.6 (95% CI: 3.7 to 5.6) and median 4.0 (range 2.0 to 6.0). The inter-observer agreement of the individual items ranged from moderate to almost perfect agreement. Nine items scored a kappa of >0.75 (95% CI: 0.55 to 0.96). The reliability of the total AMSTAR score was excellent: kappa 0.84 (95% CI: 0.67 to 1.00) and Pearson's R 0.96 (95% CI: 0.92 to 0.98). The overall scores for the global assessment ranged from 2 to 7 (out of a maximum score of 7) with a mean of 4.43 (95% CI: 3.6 to 5.3) and median 4.0 (range 2.25 to 5.75). The agreement was lower with a kappa of 0.63 (95% CI: 0.40 to 0.88). Construct validity was shown by AMSTAR convergence with the results of the global assessment: Pearson's R 0.72 (95% CI: 0.53 to 0.84). For the AMSTAR total score, the limits of agreement were −0.19±1.38. This translates to a minimum detectable difference between reviews of 0.64 ‘AMSTAR points’. Further validation of AMSTAR is needed to assess its validity, reliability and perceived utility by appraisers and end users of reviews across a broader range of systematic reviews.
The Influence of Surface Wettability on the Adhesion Strength of Settled Spores of the Green Alga Enteromorpha and the Diatom Amphora1

Abstract In this paper we report on the effect of surface wettability on surface selection and adhesion properties of settled (adhered) spores of the biofouling marine alga Enteromorpha and cells of the diatom Amphora, through the use of patterned self-assembled monolayers (SAMs). The SAMs were formed from alkanethiols terminated with methyl (CH3) or hydroxyl (OH) groups, or mixtures of the two, creating a discontinuous gradient of wettability as measured by advancing water contact angle. In the case of Enteromorpha, primary adhesion, as measured by the transition from a motile spore to a settled, sessile organism, is strongly promoted by the hydrophobic surfaces. On the other hand, adhesion strength of the settled spores, as measured by resistance to detachment in a turbulent flow cell, is greatest on a hydrophilic surface. In the case of Amphora, there is little influence of surface wettability on the primary adhesion of this organism, but motility is inhibited at contact angles ≥60° and the cells are more strongly adhered to hydrophobic surfaces. Adhesion strength of Enteromorpha spores is also influenced by group size, spores in groups being more resistant to detachment than single spores.
A study of the source traffic generator using poisson distribution for ABR service

This paper describes modeling of the available bit rate (ABR) source traffic in asynchronous transfer mode (ATM) network using BLPos/GTEXP traffic generator, which employs Poisson distribution for modeling the burst length (BLPos) and exponential distribution for modeling the gap time (GTEXP). This traffic generator inherits the advantages of both Poisson and exponential distribution functions to achieve enhanced link performance. Analytical and simulation results for BLPos/GTEXP traffic generator have been presented and compared.
Quasi-maximum likelihood initial downlink synchronization for IEEE 802.16m

We consider initial downlink synchronization for the emerging IEEE 802.16m standard. Such synchronization involves estimation of the carrier frequency offset, signal timing, and the index of “Primary Advanced Preamble” (PA-Preamble) over a multipath channel. We first give a brief overview of some relevant signal properties in IEEE 802.16m. These properties are rather different from other recent standards to the point of needing a new synchronization algorithm. We develop a synchronization method based on the maximum likelihood (ML) principle. It turns out that the multipath channel response is also estimated along the way. The resulting method is considered quasi-ML because some approximations are used to simplify computation. Simulation results are presented to illustrate its performance.
Semantic file Systems

This paper presents our study on the integration on a semantic approach in a peer-to-peer file system implementation. Since a few years, various studies have been conducted by scientists to propose either semantic or peer-to-peer file systems approaches in separate ways. Indeed, semantic file systems deal with the ability for a system to provide flexible associative access to its contents by extracting attributes from files whereas peer-to-peer approaches aim at using the aggregate storage capacity of numerous computers gathered in a decentralized peer-to-peer network. In our work, we have tried to understand Pastis, a Java peer-to-peer file system implementation based on an open source implementation of Pastry/PAST and study the integration of a semantic concept into it for further extensions.
Improved UP Growth Algorithm for Mining of High Utility Itemsets from Transactional Databases Based on Mapreduce Framework on Hadoop.

Now a days mining of high utility itemsets especially from the big transactional databases is required task to process many day to day operations in quick time. There are many methods presented for mining the high utility itemsets from large transactional datasets are subjected to some serious limitations such as performance of this methods needs to be investigated in low memory based systems for mining high utility itemsets from large transactional datasets and hence needs to address further as well. Another limitation is these proposed methods cannot overcome the screenings as well as overhead of null transactions; hence, performance degrades drastically. During this paper, we are presenting the new approach to overcome these limitations. We presented distributed programming model for mining business-oriented transactional datasets by using an improved MapReduce framework on Hadoop, which overcomes single processor and main memory-based computing, but also unexpectedly highly scalable in terms of increasing database size. We have used this approach with existing UP-Growth and UP-Growth+ with aim of improving their performances further. In experimental studies we will compare the performances of existing algorithms UP-Growth and UP-Growth+ against the improve UP-Growth and UP-Growth+ with Hadoop.
A Model of Spatial Position Based on Extremal Points

Two sets of fundamental properties which a spatial representation should describe are the position, extent, and orientation of objects, and topological and directional relations between objects. In previous approaches, the formalization of a particular property, such as topological spatial relations, has often been studied as an independent problem. The resulting theories have been elegant and compact, but may be diicult to use because of the assumptions on available knowledge. For example, several formalizations of topologi-cal relations assume knowledge of the boundaries of objects. Yet, knowledge of exact boundaries requires the knowledge of exact shapes, a property which is very diicult to describe symbolically. Our approach was to rst deene an application, a magnetic elds problem solver capable of doing both spatial and dynamic reasoning, and a broad collection of qualitative problems to be solved before embarking on the task of deening a spatial representation. The nature of the solutions to the various problems provided clues on what spatial properties were of fundamental importance, and what information could be abstracted. We describe an adequacy criterion for abstractions of object shapes, and present a description of the spatial position and orientation of objects based on extremal points. We show that topological and directional relations may be readily described in terms of this object representation. Our spatial representation is compatible with existing tools for the qualitative simulation of dynamic systems, which allows us to reason about changes in spatial relations due to the translational and rotational motion of objects.
Multibit versus multilevel embedding in high capacity difference expansion reversible watermarking

The classical difference expansion (DE) reversible watermarking expands two times a difference in order to embed one bit of data. The upper limit of such DE schemes in a single embedding level is usually bounded by 1 bpp. In order to obtain more than 1 bpp, several embedding stages are chained. The multibit DE schemes expand n times the difference in order to embed up to log2 n bpp. This paper proposes a multibit extension of the difference expansion reversible watermarking and compares the results with the multilevel embedding case. The multibit reversible watermarking outperforms the multilevel one both in capacity and quality. Experimental results on standard test images are provided.
Using a photochemical model for the validation of NO 2 satellite measurements at different solar zenith angles

SCIAMACHY (Scanning Imaging Spectrometer for Atmospheric Chartography) aboard the recently launched Environmental Satellite (ENVISAT) of ESA is measuring solar radiance upwelling from the atmosphere and the extraterrestrial irradiance. Appropriate inversion of the ultraviolet and visible radiance measurements, observed from the atmospheric limb, yields profiles of nitrogen dioxide, NO 2, in the stratosphere (SCIAMACHY-IUP NO 2 profiles V1). In order to assess their accuracy, the resulting NO 2 profiles have been compared with those retrieved from the space borne occultation instruments Halogen Occultation Experiment (HALOE, data version v19) and Stratospheric Aerosol and Gas Experiment II (SAGE II, data version 6.2). As the HALOE and SAGE II measurements are performed during local sunrise or sunset and because NO 2 has a significant diurnal variability, the NO2 profiles derived from HALOE and SAGE II have been transformed to those predicted for the solar zenith angles of the SCIAMACHY measurement by using a 1-dimensional photochemical model. The model used to facilitate the comparison of the NO 2 profiles from the different satellite sensors is described and a sensitivity ananlysis provided. Comparisons between NO 2 profiles from SCIAMACHY and those from HALOE NO2 but transformed to the SCIAMACHY solar zenith angle, for collocations from July to October 2002, show good agreement (within +/−12%) between the altitude range from 22 to 33 km. The results from the comparison of all collocated NO 2 profiles from SCIAMACHY and those from SAGE II transformed to the SCIAMACHY solar zenith angle show a systematic negative bias of 10 to 35% between 20 km to 38 km with a small standard deviation between 5 to 14%. These results agree with those of Newchurch and Ayoub (2004), implying that above 20 km NO2 profiles from SAGE II sunset are probably somewhat high. Correspondence to: A. Bracher (bracher@uni-bremen.de)
Brokers vs. Retail Investors: Conflicting Interests and Dominated Products

I study how brokers distort household investment decisions. Using a novel convertible bond dataset, I find that consumers often purchase dominated bonds - cheap and expensive of otherwise identical bonds coexist in the market. Brokers are incentivized to sell the inferior bonds, earning two-times greater fees for selling dominated bonds on average. I develop and estimate a broker intermediated search model that rationalizes this behavior and quantifies the distortions in these markets. In the model consumer search is endogenously directed according to the incentives of brokers and brokers price discriminate based on a consumer's level of sophistication. The model estimates indicate that costly search is a key friction in retail financial markets, but the effects of search costs are compounded when brokers are incentivized to direct the search of consumers towards high fee inferior products.
Self-Efficacy of Early Childhood Teachers in Science, Technology, Engineering, and Mathematics.

Follow this and additional works at: https://digitalcommons.brandman. edu/edd_dissertations Part of the Curriculum and Instruction Commons, Early Childhood Education Commons, Educational Leadership Commons, Elementary Education Commons, Elementary Education and Teaching Commons, Other Teacher Education and Professional Development Commons, PreElementary, Early Childhood, Kindergarten Teacher Education Commons, and the Science and Mathematics Education Commons
A simple method for directional transcriptome sequencing using Illumina technology

High-throughput sequencing of cDNA has been used to study eukaryotic transcription on a genome-wide scale to single base pair resolution. In order to compensate for the high ribonuclease activity in bacterial cells, we have devised an equivalent technique optimized for studying complete prokaryotic transcriptomes that minimizes the manipulation of the RNA sample. This new approach uses Illumina technology to sequence single-stranded (ss) cDNA, generating information on both the direction and level of transcription throughout the genome. The protocol, and associated data analysis programs, are freely available from http://www.sanger. ac.uk/Projects/Pathogens/Transcriptome/. We have successfully applied this method to the bacterial pathogens Salmonella bongori and Streptococcus pneumoniae and the yeast Schizosaccharomyces pombe. This method enables experimental validation of genetic features predicted in silico and allows the easy identification of novel transcripts throughout the genome. We also show that there is a high correlation between the level of gene expression calculated from ss-cDNA and double-stranded-cDNA sequencing, indicting that ss-cDNA sequencing is both robust and appropriate for use in quantitative studies of transcription. Hence, this simple method should prove a useful tool in aiding genome annotation and gene expression studies in both prokaryotes and eukaryotes.
A Toolbox for Representational Similarity Analysis

Neuronal population codes are increasingly being investigated with multivariate pattern-information analyses. A key challenge is to use measured brain-activity patterns to test computational models of brain information processing. One approach to this problem is representational similarity analysis (RSA), which characterizes a representation in a brain or computational model by the distance matrix of the response patterns elicited by a set of stimuli. The representational distance matrix encapsulates what distinctions between stimuli are emphasized and what distinctions are de-emphasized in the representation. A model is tested by comparing the representational distance matrix it predicts to that of a measured brain region. RSA also enables us to compare representations between stages of processing within a given brain or model, between brain and behavioral data, and between individuals and species. Here, we introduce a Matlab toolbox for RSA. The toolbox supports an analysis approach that is simultaneously data- and hypothesis-driven. It is designed to help integrate a wide range of computational models into the analysis of multichannel brain-activity measurements as provided by modern functional imaging and neuronal recording techniques. Tools for visualization and inference enable the user to relate sets of models to sets of brain regions and to statistically test and compare the models using nonparametric inference methods. The toolbox supports searchlight-based RSA, to continuously map a measured brain volume in search of a neuronal population code with a specific geometry. Finally, we introduce the linear-discriminant t value as a measure of representational discriminability that bridges the gap between linear decoding analyses and RSA. In order to demonstrate the capabilities of the toolbox, we apply it to both simulated and real fMRI data. The key functions are equally applicable to other modalities of brain-activity measurement. The toolbox is freely available to the community under an open-source license agreement (http://www.mrc-cbu.cam.ac.uk/methods-and-resources/toolboxes/license/).