Miracle-dz/UniFAR-FTUs huggingface dataset:
On Temporality in Discourse Annotation: Theoretical and Practical Considerations

Temporal information is one of the prominent features that determine the coherence in a discourse. That is why we need an adequate way to deal with this type of information during discourse annotation. In this paper, we will argue that temporal order is a relational rather than a segment-specific property, and that it is a cognitively plausible notion: temporal order is expressed in the system of linguistic markers and is relevant in both acquisition and language processing. This means that temporal relations meet the requirements set by the Cognitive approach of Coherence Relations (CCR) to be considered coherence relations, and that CCR would need a way to distinguish temporal relations within its annotation system. We will present merits and drawbacks of different options of reaching this objective and argue in favor of adding temporal order as a new dimension to CCR.
Design of near-infrared fluorescent bioactive conjugated functional iron oxide nanoparticles for optical detection of colon cancer

Background Colon cancer is one of the major causes of death in the Western world. Early detection significantly improves long-term survival for patients with the disease. Near- infrared (NIR) fluorescent nanoparticles hold great promise as contrast agents for tumor detection. NIR offers several advantages for bioimaging compared with fluorescence in the visible spectrum, ie, lower autofluorescence of biological tissues, lower absorbance, and consequently deeper penetration into biomatrices. Methods and results NIR fluorescent iron oxide nanoparticles with a narrow size distribution were prepared by nucleation, followed by controlled growth of thin iron oxide films onto cyanine NIR dye conjugated gelatin-iron oxide nuclei. For functionalization, and in order to increase the NIR fluorescence intensity, the NIR fluorescent iron oxide nanoparticles obtained were coated with human serum albumin containing cyanine NIR dye. Leakage of the NIR dye from these nanoparticles into phosphate-buffered saline solution containing 4% albumin was not detected. The work presented here is a feasibility study to test the suitability of iron oxide-human serum albumin NIR fluorescent nanoparticles for optical detection of colon cancer. It demonstrates that encapsulation of NIR fluorescent dye within these nanoparticles significantly reduces photobleaching of the dye. Tumor-targeting ligands, peanut agglutinin and anticarcinoembryonic antigen antibodies (αCEA), were covalently conjugated with the NIR fluorescent iron oxide-human serum albumin nanoparticles via a poly(ethylene glycol) spacer. Specific colon tumor detection was demonstrated in chicken embryo and mouse models for both nonconjugated and the peanut agglutinin-conjugated or αCEA-conjugated NIR fluorescent iron oxide-human serum albumin nanoparticles. Conclusion Conjugation of peanut agglutinin or αCEA to the nanoparticles significantly increased the fluorescence intensity of the tagged colon tumor tissues relative to the nonconjugated nanoparticles.
Susan Bauer's 2003 Theory of Well-Educated Mind: Could the Classical Approach to Teaching History Work in Southern California History K12 Classrooms?

The main purpose of this research evolved from the publication of S. W. Bauer Well-educated mind, a study of the significance of new methods of teaching history course. Bauer (2003) argues that the grammarian approach of simple recognition and memorization removes students from reading primary sources. This theory suggests a new methodology for the instructors and students through the three-stage process of grammar, dialectic, and rhetoric preparation with aid of primary sources or “great books list”. This paper supports Bauer’s thesis and provides evidence through extensive interviews that indeed this concept of pedagogy is present in Southern California schools. The statistical data from the Department of Education tend to piece together all social sciences, including history, into summary reports or longitudinal studies. In general, however, more graduating high school students earned their greater share of credits in the social studies and history (Townsend, 2010). In the span of this decade, the data and statistical analyses were derived only from the measurable trends embedded in the state-level standards and their measurements (Townsend, 2010). The Department of Education electronic publications on all education reforms show that “the social studies and history are only valued as test-worthy in 11 states” (Townsend, 2010, p 1101). In comparison, all of the states test for English, math, and science (USDE, 2005). Most of the analysis of this (NAEP 2002) report expressed concern that many students possessed a below basic knowledge of American history and history in general. History courses are a critical part of our nation's school curriculum. “it is through history that we understand our past and contemplate our future” (Ravitch, 2002, p. 2). Ravitch (2002) estimated that all “published questions that stumped so many students involved the most fundamental concepts of our democracy, our growth as a nation, and our role in the world” (p. 2). Ravitch insists in her call by invoking President Bush's No Child Left Behind Act of 2001, and criticizing those who said the administration was not spending enough on education, it must be pointed out that education spending has risen from $23 billion in 1996 to $50 billion in the 2002 budget. (p. 2) Furthermore, Ravitch’s assessment showed that “use of primary sources was related to higher student achievement among eighth-grade students, and twelfth-graders who read biographies performed better than students who did not” (p. 2). 1 Stanek: Well-Educated Mind concept by Bauer (2003) and California Schools
Evaluation of the VITEK 2 System for Rapid Identification of Yeasts and Yeast-Like Organisms

ABSTRACT The new VITEK 2 system is a fully automated system dedicated to the identification and susceptibility testing of microorganisms. In conjunction with the VITEK ID-YST card the VITEK 2 system allows the identification of clinically important yeasts and yeast-like organisms in 15 h due to a sensitive fluorescence-based technology. The ID-YST card consists of 47 biochemical reactions. The database comprises 51 taxa, including newly described species. In this study we evaluated the reliability of the VITEK ID-YST card for the identification of yeasts and yeast-like organisms encountered in a clinical microbiology laboratory. A total of 241 strains representing 21 species were studied. The strains were isolated from clinical samples within a period of 60 days prior to the identification. The tests were performed using 24-h to 55-h subcultures on Sabouraud-gentamicin-chloramphenicol agar. Each strain was tested in parallel using the ID 32C strip as a comparison method combined with microscopic morphology and an agglutination test for C. krusei. Overall, 222 strains (92.1%) were unequivocally identified including 11 isolates (4.6%) identified with low discrimination resolved by simple additional tests. Ten strains (4.1%) for which results were given with low discrimination could not be unequivocally identified with supplemental tests, 4 strains (1.7%) were misidentified and 5 strains (2.1%) could not be identified. In conclusion, we found that the VITEK 2 system is a rapid and accurate method for the identification of medically important yeasts and yeast-like organisms.
Students' Ethical Awareness and Conceptions of Research Ethics

The study focused on university students' understanding and conceptions of ethical issues in research. Domain-specific and domain-transcending measures were developed to gauge the students' awareness of ethical issues. Responses were obtained from 269 undergraduate and graduate students at a U.S. regional university. Participant withdrawal, the debriefing of research participants, the dissemination of findings, and giving credit to co-contributors were the most challenging ethical issues for the students. Ethical awareness was predicted by professional and organizational socialization, and perspective taking. Contextualization greatly improved the students' ability to recognize ethical issues. Simulations and role-taking are suggested as the means with which to teach students about the ethical issues perceived as challenging.
Principal Component Analysis, A Powerful Unsupervised Learning Technique

Data mining is a collection of analytical techniques to uncover new trends and patterns in massive databases. These data mining techniques stress visualization to thoroughly study the structure of data and to check the validity of the statistical model fit which leads to proactive decision making. Principal component analysis (PCA) is one of the unsupervised data mining tools used to reduce dimensionality in multivariate data. In PCA, dimensionality of multivariate data is reduced by transforming the correlated variables into linearly transformed uncorrelated variables. PCA summarizes the variation in a correlated multi-attribute to a set of uncorrelated components, each of which is a particular linear combination of the original variables. The extracted uncorrelated components are called principal components (PC) and are estimated from the eigenvectors of the covariance or correlation matrix of the original variables. Therefore, the objective of PCA is to achieve parsimony and reduce dimensionality by extracting the smallest number components that account for most of the variation in the original multivariate data and to summarize the data with little loss of information. A user-friendly SAS application utilizing the latest capabilities of SAS macro to perform PCA is presented here. Previously published diabetes screening data containing multi-attributes is used to reduce multi attributes into few dimensions.
Optimizing Call Center Staffing Using Simulation and Analytic Center Cutting-Plane Methods

We consider the problem of minimizing staffing costs in an inbound call center, while maintaining an acceptable level of service in multiple time periods. The problem is complicated by the fact that staffing level in one time period can affect the service levels in subsequent periods. Moreover, staff schedules typically take the form of shifts covering several periods. Interactions between staffing levels in different time periods, as well as the impact of shift requirements on the staffing levels and cost, should be considered in the planning. Traditional staffing methods based on stationary queueing formulas do not take this into account. We present a simulation-based analytic center cutting-plane method to solve a sample average approximation of the problem. We establish convergence of the method when the service-level functions are discrete pseudoconcave. An extensive numerical study of a moderately large call center shows that the method is robust and, in most of the test cases, outperforms traditional staffing heuristics that are based on analytical queueing methods.
Representing Sentence Structure in Hidden Markov Models for Information Extraction

We study the application of Hidden Markov Models (HMMs) to learning information extractors for -ary relations from free text. We propose an approach to representing the grammatical structure of sentences in the states of the model. We also investigate using an objective function during HMM training which maximizes the ability of the learned models to identify the phrases of interest. We evaluate our methods by deriving extractors for two binary relations in biomedical domains. Our experiments indicate that our approach learns more accurate models than several baseline approaches.
Scatter Reduction and Correction for Dual-Source Cone-Beam CT Using Prepatient Grids

Purpose: Scatter significantly limits the application of the dual-source cone-beam computed tomography by inducing scatter artifacts and degrading contrast-to-noise ratio, Hounsfield-unit accuracy, and image uniformity. Although our previously developed interleaved acquisition mode addressed the cross scatter between the 2 X-ray sources, it doubles the scanning time and doesn’t address the forward scatter issue. This study aims to develop a prepatient grid system to address both forward scatter and cross scatter in the dual-source cone-beam computed tomography. Methods: Grids attached to both X-ray sources provide physical scatter reduction during the image acquisition. Image data were measured in the unblocked region, while both forward scatter and cross scatter were measured in the blocked region of the projection for postscan scatter correction. Complementary projections were acquired with grids at complementary locations and were merged to form complete projections for reconstruction. Experiments were conducted with different phantom sizes, grid blocking ratios, image acquisition modes, and reconstruction algorithms to investigate their effects on the scatter reduction and correction. The image quality improvement by the prepatient grids was evaluated both qualitatively through the artifact reduction and quantitatively through contrast-to-noise ratio, Hounsfield-unit accuracy, and uniformity using a CATphan 504 phantom. Results: Scatter artifacts were reduced by scatter reduction and were removed by scatter correction method. Contrast-to-noise ratio, Hounsfield-unit accuracy, and image uniformity were improved substantially. The simultaneous acquisition mode achieved comparable contrast-to-noise ratio as the interleaved and sequential modes after scatter reduction and correction. Higher grid blocking ratio and smaller phantom size led to higher contrast-to-noise ratio for the simultaneous mode. The iterative reconstruction with total variation regularization was more effective than the Feldkamp, Davis, and Kress method in reducing noise caused by the scatter correction to enhance contrast-to-noise ratio. Conclusion: The prepatient grid system is effective in removing the scatter effects in the simultaneous acquisition mode of the dual-source cone-beam computed tomography, which is useful for scanning time reduction or dual energy imaging.
An App Visualization design based on IoT Self-diagnosis Micro Control Unit for car accident prevention

This paper proposes an App Visualization (AppV) based on IoT Self-diagnosis Micro Control Unit (ISMCU) for accident prevention. It collects a current status of a vehicle through a sensor, visualizes it on a smart phone and prevents vehicles from accident. The AppV consists of 5 components. First, a Sensor Layer (SL) judges noxious gas from a current vehicle and a driver’s driving habit by collecting data from various sensors such as an Accelerator Position Sensor, an O2 sensor, an Oil Pressure Sensor, etc. and computing the concentration of the CO collected by a semiconductor gas sensor. Second, a Wireless Sensor Communication Layer (WSCL) supports Zigbee, Wi-Fi, and Bluetooth protocol so that it may transfer the sensor data collected in the SL to ISMCU and the data in the ISMCU to a Mobile. Third, an ISMCU integrates the transferred sensor information and transfers the integrated result to a Mobile. Fourth, a Mobile App Block Programming Tool (MABPT) is an independent App generation tool that changes to visual data just the vehicle information which drivers want from a smart phone. Fifth, an Embedded Module (EM) records the data collected through a Smart Phone real time in a Cloud Server. Therefore, because the AppV checks a vehicle’ fault and bad driving habits that are not known from sensors and performs self-diagnosis through a mobile, it can reduce time and cost spending on accidents caused by a vehicle’s fault and noxious gas emitted to the outside.
Managerial Response to Changing Environments: Perspectives on Problem Sensing from Social Cognition.

1982 by Cornell University. 000 1-8392/82/2704-0548/$00.7 5 This paper characterizes managerial problem sensing, a necessary precondition for managerial activity directed toward organizational adaptation, as composed of noticing, interpreting, and incorporating stimuli. It then reviews the constituent social cognition processes that make certain kinds of problem-sensing behavior, including errors, relatively likely to occur. Implications for the organizational issues of crisis, chance events, break points, and extreme change are explored.
Data embedding in hardcopy images via halftone-dot orientation modulation

The principal challenge in hardcopy data hiding is achieving robustness to the print-scan process. Conventional robust hiding schemes are not well-suited because they do not adapt to the print-scan distortion channel, and hence are fundamentally limited in a detection theoretic sense. We consider data embedding in images printed with clustered dot halftones. The input to the print-scan channel in this scenario is a binary halftone image, and hence the distortions are also intimately tied to the nature of the halftoning algorithm employed. We propose a new framework for hardcopy data hiding based on halftone dot orientation modulation. We develop analytic halftone threshold functions that generate elliptically shaped halftone dots in any desired orientation. Our hiding strategy then embeds a binary symbol as a particular choice of the orientation. The orientation is identified at the decoder via statistically motivated moments following appropriate global and local synchronization to adress the geometric distortion introduced by the print scan channel. A probabilistic model of the print-scan process, which conditions received moments on input orientation, allows for Maximum Likelihood (ML) optimal decoding. Our method bears similarities to the paradigms of informed coding and QIM, but also makes departures from classical results in that constant and smooth image areas are better suited for embedding via our scheme as opposed to busy or "high entropy" regions. Data extraction is automatically done from a scanned hardcopy, and results indicate significantly higher embedding rate than existing methods, a majority of which rely on visual or manual detection.
A Population Pharmacokinetic Analysis of the Penetration of the Prostate by Levofloxacin

ABSTRACT Prostatitis has remained a pathological entity that is difficult to treat. Part of the difficulty revolves about the putative offending pathogens. For acute prostatitis, members of theEnterobacteriaceae, particularly Escherichia coli, play a central role, while intracellular pathogens such asChlamydia are more frequently seen in chronic prostatitis. Consequently, a drug needs to be able to penetrate to this specialized site in both the acute and chronic infection forms of the disease and also have potent activity against the most common causative pathogens, both intracellular and extracellular. Levofloxacin has such an activity profile. We wished to document its ability to penetrate to the site of infection. Patients undergoing prostatectomies were administered 500 mg of levofloxacin orally every 24 h for 2 days prior to surgery, and then on the day of surgery, 500 mg was administered as an hour-long, constant-rate intravenous (i.v.) infusion. A set of blood samples was obtained as guided by stochastic optimal design theory. Prostate biopsy times were determined by randomizing subjects into one of four groups, based on the interval after the i.v. dose. All plasma and prostate drug concentrations were comodeled by a population modeling program, BigNPEM, implemented on the Cray T3E Supercomputer housed at the Supercomputer Center at the University of California at San Diego. Penetration was determined as the ratio of the area under the concentration-time curve (AUC) of levofloxacin in the prostate to the plasma levofloxacin AUC. When calculated from the mean population parameters, this penetration ratio was 2.96. We also performed a 1,000-subject Monte Carlo simulation from the mean parameter vector and covariance matrix. The mean penetration ratio here was 4.14 with a 95% confidence interval of 0.20 to 19.6. Over 70% of the population had a penetration ratio in excess of 1.0. Levofloxacin adequately penetrates a noninflamed prostate and should be evaluated for the therapy of prostatitis.
Molecular phylogenetic evidence for the evolution of specialization in anemonefishes

Anemonefishes (genera: Amphiprion and Premnas; family Pomacentridae) are a group of 28 species of coral reef fishes that are found in obligate symbiosis with large tropical sea anemones. A phylogenetic hypothesis based on morphological analyses of this group suggests that the ancestral anemonefish was a generalist with similar morphology to other pomacentrids, and that it gave rise to other anemonefish species that were more specialized for living with particular species of host anemones. To test this hypothesis we constructed a molecular phylogeny for the anemonefishes by sequencing 1140 base pairs of the cytochrome b gene and 522 base pairs of the 16S rRNA gene for six species of anemonefishes (representatives of all subgenera and species complexes) and two other pomacentrid species. Three methods of phylogenetic analysis all strongly supported the conclusion that anemonefishes are a monophyletic group. The molecular phylogeny differs from the tree based on morphological data in that the two species of specialized anemonefishes (Premnas biaculeatus and Amphiprion ocellaris) were assigned to a basal position within the clade, and the extreme host generalist (Amphiprion clarkii) to a more derived position. Thus, the initial anemonefish ancestors were probably host specialists and subsequent speciation events led to a combination of generalist and specialist groups. Further phylogenetic studies of additional anemonefish species are required to substantiate this hypothesis.
Interactive Effects of Presentation Modality and Message-Generated Imagery on Recall of Advertising Information

We argue that imaging is a cognitive process that uses the same mental resources as perception. Therefore, when imaging and perception compete for the same resources, message elaboration and learning should be undermined. Two experiments are reported that provide support for this theorizing. In the first experiment, the learning of visual or auditory imagery-provoking information is adversely affected by reading or listening, respectively. In the second experiment, information with high levels of visual imagery is found to be learned better than information with low levels of visual imagery when the information is presented auditorily, but the reverse occurs when information is present visually. Copyright 1996 by the University of Chicago.
Analysis of Modified Dielectric Frequency Selective Surfaces Under 3-D Plane Wave Excitation Using a Multimode Equivalent Network Approach

In this paper, a novel modified dielectric frequency selective surface (MDFSS) is proposed and analyzed under 3-D plane wave incidence. Unlike classic DFSS, this MDFSS can easily be developed. The electromagnetic analysis is carried out using the multimode equivalent network (MEN) approach. A new development of electromagnetic fields in non homogeneous dielectric regions is proposed in order to correctly define the Z matrix of these blocks. Results are shown for an MDFSS which ensures total reflection with a larger bandwidth than the classic DFSS. Bandwidth can be enlarged and modified by doubling the MDFSS. Similarly, two MDFSS can be combined to ensure total reflection for elliptically polarized wave incidence.