A Sense of Wonder: Enhancing Access to Folktales through Task and Facet Analysis

Discusses the approach taken in Phase 1 of a three-phase project Folktales, Facets and FRBR [funded by a grant from OCLC/ALISE]. This project works with the special collection of folktales at the Center for Children’s Books (CCB) at the University of Illinois at Urbana-Champaign, and the scholars who use this collection. The project aims to enhance the effectiveness and efficiency of folktale access through deep understanding of user needs. Phase 1 included facet analysis of the bibliographic records for a sample of 100 folktale books in the CCB, and task analysis of interviews with four CCB-affiliated faculty. Describes the information tasks, information seeking obstacles, and desired features for a discovery and access tool related to folktales for this initial group of scholarly users of folktales.

Analyse documentaire en milieu universitaire : deux approches générales comparées

Ce mémoire porte sur l’analyse documentaire en milieu universitaire. Deux approches générales sont d’abord étudiées : l’approche centrée sur le document (premier chapitre), prédominante dans la tradition bibliothéconomique, et l’approche centrée sur l’usager (deuxième chapitre), influencée par le développement d’outils le plus souvent associés au Web 2.0. L’opposition entre ces deux démarches reflète une dichotomie qui se trouve au cœur de la notion de sujet, c’est-à-dire les dimensions objective et subjective du sujet. Ce mémoire prend par conséquent la forme d’une dissertation dont l’avantage principal est de considérer à la fois d’importants acquis qui appartiennent à la tradition bibliothéconomique, à la fois des développements plus récents ayant un impact important sur l’évolution de l’analyse documentaire en milieu universitaire. Notre hypothèse est que ces deux tendances générales doivent être mises en relief afin d’approfondir la problématique de l’appariement, laquelle définit la difficulté d’accorder le vocabulaire qu’utilise l’usager dans ses recherches documentaires avec celui issu de l’analyse documentaire (métadonnées sujet). Dans le troisième chapitre, nous examinons certaines particularités liées à l’utilisation de la documentation en milieu universitaire dans le but de repérer certaines possibilités et certaines exigences de l’analyse documentaire dans un tel milieu. À partir d’éléments basés sur l’analyse des domaines d’études et sur la démarche analytico-synthétique, il s’agit d’accentuer l’interaction potentielle entre usagers et analystes documentaires sur le plan du vocabulaire utilisé de part et d’autre.

Type D personality and the Five-Factor Model : a facet-level analysis

Objective: This study assessed the degree to which NEO-PI-R facets contribute to understanding of Type D personality over and above the Big 5. Method: Healthy participants (n = 268) completed the DS14 and the NEO-PI-R. In addition to analyzing the Type D subscales of social inhibition and negative affectivity, we computed a continuous measure of Type D scored as the sum of the two subscales. Results: Facets provided moderate incremental prediction of Type D subscales. The facets of assertiveness, self- consciousness, and positive emotion provided incremental prediction of negative affectivity, and warmth, activity, and gregariousness provided incremental prediction of social inhibition. Facets provided minimal incremental prediction of continuous Type D. The Big 5 explained substantially more variance in continuous Type D (71%) than negative affectivity (59%) or social inhibition (61%). Conclusions: Overall, the facet-level analysis provided additional insights into the nature of Type D. The incremental prediction of the Type D subscales by facets supported the idea that Type D scales are narrower constructs than the Big 5. However, the strong prediction of continuous Type D by the Big 5 and the lack of incremental prediction by facets points to the overall Type D construct being well represented by the Big 5.

Conscientiousness, openness to experience and extraversion as predictors of nursing work performance: a facet-level analysis

AIM: This study examined the relationships between the personality traits of conscientiousness, openness and extraversion at trait and facet-levels and three indicators of work role performance; proficiency, 'adaptivity' and proactivity measured at individual, team and organisational levels. BACKGROUND: This is one of the first studies to explore the relationship between personality, measured at trait and facet-level and performance using a comprehensive range of performance indicators. METHOD: An online survey of 393 nurses from health-care organisations across Australia was conducted to test hypothesised relationships. RESULTS: Path analyses revealed numerous relationships between personality, measured at both trait and facet-levels, and work role performance. Conscientiousness was highlighted as the strongest driver of work role performance across all the indicators, with extraversion also strongly associated with work role performance. Openness to experience, previously considered a week predictor of performance, was, when examined at the facet-level, related to all of the work role performance indicators. CONCLUSIONS: Results suggests a bandwidth effect, where the personality traits drive global performance while the facets drive specific performance. IMPLICATIONS FOR NURSING MANAGEMENT: Better understanding of the relationship between personality and work role performance will help nurse managers to foster the fit between individual and organisation, improving job satisfaction, engagement, retention and performance in role.

Analysis of distrubances in large interconnected power systems

World economies increasingly demand reliable and economical power supply and distribution. To achieve this aim the majority of power systems are becoming interconnected, with several power utilities supplying the one large network. One problem that occurs in a large interconnected power system is the regular occurrence of system disturbances which can result in the creation of intra-area oscillating modes. These modes can be regarded as the transient responses of the power system to excitation, which are generally characterised as decaying sinusoids. For a power system operating ideally these transient responses would ideally would have a “ring-down” time of 10-15 seconds. Sometimes equipment failures disturb the ideal operation of power systems and oscillating modes with ring-down times greater than 15 seconds arise. The larger settling times associated with such “poorly damped” modes cause substantial power flows between generation nodes, resulting in significant physical stresses on the power distribution system. If these modes are not just poorly damped but “negatively damped”, catastrophic failures of the system can occur. To ensure system stability and security of large power systems, the potentially dangerous oscillating modes generated from disturbances (such as equipment failure) must be quickly identified. The power utility must then apply appropriate damping control strategies. In power system monitoring there exist two facets of critical interest. The first is the estimation of modal parameters for a power system in normal, stable, operation. The second is the rapid detection of any substantial changes to this normal, stable operation (because of equipment breakdown for example). Most work to date has concentrated on the first of these two facets, i.e. on modal parameter estimation. Numerous modal parameter estimation techniques have been proposed and implemented, but all have limitations [1-13]. One of the key limitations of all existing parameter estimation methods is the fact that they require very long data records to provide accurate parameter estimates. This is a particularly significant problem after a sudden detrimental change in damping. One simply cannot afford to wait long enough to collect the large amounts of data required for existing parameter estimators. Motivated by this gap in the current body of knowledge and practice, the research reported in this thesis focuses heavily on rapid detection of changes (i.e. on the second facet mentioned above). This thesis reports on a number of new algorithms which can rapidly flag whether or not there has been a detrimental change to a stable operating system. It will be seen that the new algorithms enable sudden modal changes to be detected within quite short time frames (typically about 1 minute), using data from power systems in normal operation. The new methods reported in this thesis are summarised below. The Energy Based Detector (EBD): The rationale for this method is that the modal disturbance energy is greater for lightly damped modes than it is for heavily damped modes (because the latter decay more rapidly). Sudden changes in modal energy, then, imply sudden changes in modal damping. Because the method relies on data from power systems in normal operation, the modal disturbances are random. Accordingly, the disturbance energy is modelled as a random process (with the parameters of the model being determined from the power system under consideration). A threshold is then set based on the statistical model. The energy method is very simple to implement and is computationally efficient. It is, however, only able to determine whether or not a sudden modal deterioration has occurred; it cannot identify which mode has deteriorated. For this reason the method is particularly well suited to smaller interconnected power systems that involve only a single mode. Optimal Individual Mode Detector (OIMD): As discussed in the previous paragraph, the energy detector can only determine whether or not a change has occurred; it cannot flag which mode is responsible for the deterioration. The OIMD seeks to address this shortcoming. It uses optimal detection theory to test for sudden changes in individual modes. In practice, one can have an OIMD operating for all modes within a system, so that changes in any of the modes can be detected. Like the energy detector, the OIMD is based on a statistical model and a subsequently derived threshold test. The Kalman Innovation Detector (KID): This detector is an alternative to the OIMD. Unlike the OIMD, however, it does not explicitly monitor individual modes. Rather it relies on a key property of a Kalman filter, namely that the Kalman innovation (the difference between the estimated and observed outputs) is white as long as the Kalman filter model is valid. A Kalman filter model is set to represent a particular power system. If some event in the power system (such as equipment failure) causes a sudden change to the power system, the Kalman model will no longer be valid and the innovation will no longer be white. Furthermore, if there is a detrimental system change, the innovation spectrum will display strong peaks in the spectrum at frequency locations associated with changes. Hence the innovation spectrum can be monitored to both set-off an “alarm” when a change occurs and to identify which modal frequency has given rise to the change. The threshold for alarming is based on the simple Chi-Squared PDF for a normalised white noise spectrum [14, 15]. While the method can identify the mode which has deteriorated, it does not necessarily indicate whether there has been a frequency or damping change. The PPM discussed next can monitor frequency changes and so can provide some discrimination in this regard. The Polynomial Phase Method (PPM): In [16] the cubic phase (CP) function was introduced as a tool for revealing frequency related spectral changes. This thesis extends the cubic phase function to a generalised class of polynomial phase functions which can reveal frequency related spectral changes in power systems. A statistical analysis of the technique is performed. When applied to power system analysis, the PPM can provide knowledge of sudden shifts in frequency through both the new frequency estimate and the polynomial phase coefficient information. This knowledge can be then cross-referenced with other detection methods to provide improved detection benchmarks.

Numerical analysis of gain saturation, noise figure, and carrier distribution for quantum-dot semiconductor-optical amplifiers

The gain saturation behaviors and noise figure are numerically analyzed for quantum-dot semiconductor optical amplifiers (QD-SOAs). The carrier and photon distributions in the longitudinal direction as well as the photon energy dependent facet reflectivity are accounted in the rate equations, which are solved with output amplified spontaneous emission spectrum as iterative variables. The longitudinal distributions of the occupation probabilities and spectral-hole burning are presented for electrons in the excited and ground states of quantum dots. The saturation output power 19.7 dBm and device gain 20.6 dB are obtained for a QD-SOA with the cavity length of 6 rum at the bias current of 500 mA. The influences of them electron intradot relaxation time and the QD capture time on the gain spectrum are simulated with the relaxation time of 1, 30, and 60 ps and capture time of 1, 5, and 10 ps. The noise figure as low as 3.5 dB is expected due to the strong polarization sensitive spontaneous emission. The characteristics of gain saturation and noise figure versus input signal power for QD-SOAs are similar to that of semiconductor. linear optical amplifiers with gain clamping by vertical laser fields.

Performance analysis of very-small-aperture lasers

The fabrication of very-small-aperture lasers is demonstrated, and their performance is analyzed. Because of strong optical feedback caused by a gold film on the front facet of the laser, its behavior changes: The threshold current decreases, the density of light inside the laser diode and the redshift effect of the spectra are enhanced, and the laser diode's lifetime is shorter than that of common laser diodes with large driving current. (c) 2005 Optical Society of America

Species diversity structure analysis at two sites in the tropical rain forest of Sumatra

Data from a hilly forest study site at Batang Ule, Sumatra, are organized into 30 100-m × 10-m subplots lying perpendicular to the line of maximal topographic gradient, from the valley to the plateau/ridge. The following methodological question is addressed: what species diversity measures are best used in order to reveal the ecologically distinct regions in the site. The main tool used to answer this question is the α-diversity curve (Hα). Graphical examination of tree and species densities, and α-diversity curves identifies an anomalous species diversity behaviour of the ‘ridge above the slope’ subplots which may have implications on land-facet class definitions. Factor analysis of the α-diversity curves indicates that the diversity space is two-dimensional: i.e. two diversity measures are sufficient to characterize the site; the species density (H0), and the Berger-Parker index (H[infty infinity]). In the two-dimensional diversity-space three distinct species diversity groups are found which relate to the topographic gradient at the Batang Ule site. The results are compared with those for a flat homogeneous site at Pasirmayang, Sumatra. The implications of the results on land-classifications in species-diversity mapping and conservation strategy are discussed.

The nucleus of Comet 67P/Churyumov-Gerasimenko. A new shape model and thermophysical analysis

Context. Comet 67P/Churyumov-Gerasimenko is the target of the European Space Agency Rosetta spacecraft rendez-vous mission. Detailed physical characteristation of the comet before arrival is important for mission planning as well as providing a test bed for ground-based observing and data-analysis methods. Aims: To conduct a long-term observational programme to characterize the physical properties of the nucleus of the comet, via ground-based optical photometry, and to combine our new data with all available nucleus data from the literature. Methods: We applied aperture photometry techniques on our imaging data and combined the extracted rotational lightcurves with data from the literature. Optical lightcurve inversion techniques were applied to constrain the spin state of the nucleus and its broad shape. We performed a detailed surface thermal analysis with the shape model and optical photometry by incorporating both into the new Advanced Thermophysical Model (ATPM), along with all available Spitzer 8-24 μm thermal-IR flux measurements from the literature. Results: A convex triangular-facet shape model was determined with axial ratios b/a = 1.239 and c/a = 0.819. These values can vary by as much as 7% in each axis and still result in a statistically significant fit to the observational data. Our best spin state solution has Psid = 12.76137 ± 0.00006 h, and a rotational pole orientated at Ecliptic coordinates λ = 78°(±10°), β = + 58°(±10°). The nucleus phase darkening behaviour was measured and best characterized using the IAU HG system. Best fit parameters are: G = 0.11 ± 0.12 and HR(1,1,0) = 15.31 ± 0.07. Our shape model combined with the ATPM can satisfactorily reconcile all optical and thermal-IR data, with the fit to the Spitzer 24 μm data taken in February 2004 being exceptionally good. We derive a range of mutually-consistent physical parameters for each thermal-IR data set, including effective radius, geometric albedo, surface thermal inertia and roughness fraction. Conclusions: The overall nucleus dimensions are well constrained and strongly imply a broad nucleus shape more akin to comet 9P/Tempel 1, rather than the highly elongated or "bi-lobed" nuclei seen for comets 103P/Hartley 2 or 8P/Tuttle. The derived low thermal inertia of

Transforaminal versus intra-articular facet steroid injections for the treatment of cervical radiculopathy : a randomized, double-blinded, controlled study.

Cette étude a été subventionnée par le Fonds de recherche du Québec - Santé (FRQ-S, grant # 21230 – 2)

An Analysis of Anchitherine Equids Across the Eocene–Oligocene Boundary in the White River Group of the Western Great Plains

Anchitherine horses are a subfamily of equids that are abundantly represented in the late Eocene and early Oligocene of North America. This group has been heavily studied in the past, but important questions still remain. Some studies have focused on the Eocene-Oligocene boundary and have used these equids along with other taxa to study mammalian diet and climate change through this interval. I reexamine two anchitherine genera, Mesohippus and Miohippus, from stratigraphic sequences of the White River Group in western Nebraska and southwestern South Dakota. These sequences span the Chadronian (late Eocene), Orellan (early Oligocene), and Whitneyan (early Oligocene) North American land-mammal ages. The most recent revision of these genera was done by Prothero and Shubin (1989). I review the characters used for taxonomic identification. This includes characters such as the hypostyle, the articular facet on the third metatarsal, and dental dimensions. To avoid possible biases caused by combining specimens from different stratigraphic levels, specimens were separated by location and stratigraphic level. The length and width of cheek teeth, and tooth rows were measured on 488 specimens. First molar area serves as a proxy for body mass in horses and other mammals, and can be useful for distinguishing among species. Results indicate that the characters used by Prothero and Shubin were highly variable in anchitherine horses and are not useful for distinguishing between these genera. The development of the articular facet on the third metatarsal may be a function of body size and therefore may be of no more utility than first molar area. Variability in first molar area suggests the presence of three species in the medial and late Chadronian, two species in the Orellan, and at least two species in the Whitneyan. Due to a lack of objective criteria separating Mesohippus from Miohippus, I recommend synonymy of these genera, making Mesohippus a junior subjective synonym.

Factors determining the success of radiofrequency denervation in lumbar facet joint pain: a prospective study

Background and aims Radiofrequency denervation (RF) of the lumbar facet joints has been shown to be effective in well-selected patients. However, long-term success varies between studies. We evaluated the influence of selected psychosocial and constitutional factors on the outcome of RF, expressed as the duration of pain relief. Methods This prospective observational study included 44 patients who received RF denervations at the University Hospital of Berne. Success was defined as at least 50% pain reduction 7–21 days, 6 months and 1 year after RF therapy. The Cox-regression analysis was performed to evaluate the influence of the following factors on the duration of success: age, sex, depression, work inability and previous surgery. Results Complete follow-up was available for 41 patients. The success rate 7–21 days after the denervation was 76%. It decreased to 32% at 6 months and to 22% at 1 year. The median success duration was 17 weeks (95% CI 10–26). The Cox-regression analysis showed a significant shorter duration of success for patients with depression (hazard ratio [HR] 2.97, 95% CI 1.32–6.65), previous surgery (HR 2.39, 95% CI 1.10–5.21) and number of treated joints (HR 1.95 for each increase in the number of joints, 95% CI 1.14–3.33). In bivariate analyses, only depression was kept to be significant. Conclusions Depression seems to be related with a short duration of success. Based on these findings, a comprehensive study is warranted to evaluate whether psychosocial factors have to be considered when recruiting patients for radiofrequency denervation.