The price elasticity of demand for common stock

We study the price elasticity of demand for the common stock of an individual corporation. Despite the prevelance of assumptions that demand is perfectly elastic, there is little if any direct evidence in the literature to either support or reject that contention. Consistent with the notion of finite price elasticities, we find that the announcement of primary stock oferings by regulated firms depresses their stock prices and little if any evidence that this decline is the result of adverse information about future cash flows. Attempts to relate offer announcement effects directly to possible determinants of price elasticities, however, are inconclusive.

Incidence of hypo- and hyper-capnia in a cross-sectional European cohort of ventilated newborn infants

OBJECTIVE To determine the incidence of hypo- and hyper-capnia in a European cohort of ventilated newborn infants. DESIGN AND SETTING Two-point cross-sectional prospective study in 173 European neonatal intensive care units. PATIENTS AND METHODS Patient characteristics, ventilator settings and measurements, and blood gas analyses were collected for endotracheally ventilated newborn infants on two separate dates. RESULTS A total of 1569 blood gas analyses were performed in 508 included patients with a mean±SD Pco2 of 48±12 mm Hg or 6.4±1.6 kPa (range 17-104 mm Hg or 2.3-13.9 kPa). Hypocapnia (Pco2<30 mm Hg or 4 kPa) and hypercapnia (Pco2>52 mm Hg or 7 kPa) was present in, respectively, 69 (4%) and 492 (31%) of the blood gases. Hypocapnia was most common in the first 3 days of life (7.3%) and hypercapnia after the first week of life (42.6%). Pco2 was significantly higher in preterm infants (49 mm Hg or 6.5 kPa) than term infants (43 mm Hg or 5.7 kPa) and significantly lower during pressure-limited ventilation (47 mm Hg or 6.3±1.6 kPa) compared with volume-targeted ventilation (51 mm Hg or 6.8±1.7 kPa) and high-frequency ventilation (50 mm Hg or 6.7±1.7 kPa). CONCLUSIONS This study shows that hypocapnia is a relatively uncommon finding during neonatal ventilation. The higher incidence of hypercapnia may suggest that permissive hypercapnia has found its way into daily clinical practice.

An Early-Warning System for Hypo-/Hyperglycemic Events Based on Fusion of Adaptive Prediction Models

Introduction: Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia / hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy. Methods: The EWS is based on the combination of data-driven online adaptive prediction models and a warning algorithm. Three modeling approaches have been investigated: (i) autoregressive (ARX) models, (ii) auto-regressive with an output correction module (cARX) models, and (iii) recurrent neural network (RNN) models. The warning algorithm performs postprocessing of the models′ outputs and issues alerts if upcoming hypoglycemic/hyperglycemic events are detected. Fusion of the cARX and RNN models, due to their complementary prediction performances, resulted in the hybrid autoregressive with an output correction module/recurrent neural network (cARN)-based EWS. Results: The EWS was evaluated on 23 T1DM patients under SAP therapy. The ARX-based system achieved hypoglycemic (hyperglycemic) event prediction with median values of accuracy of 100.0% (100.0%), detection time of 10.0 (8.0) min, and daily false alarms of 0.7 (0.5). The respective values for the cARX-based system were 100.0% (100.0%), 17.5 (14.8) min, and 1.5 (1.3) and, for the RNN-based system, were 100.0% (92.0%), 8.4 (7.0) min, and 0.1 (0.2). The hybrid cARN-based EWS presented outperforming results with 100.0% (100.0%) prediction accuracy, detection 16.7 (14.7) min in advance, and 0.8 (0.8) daily false alarms. Conclusion: Combined use of cARX and RNN models for the development of an EWS outperformed the single use of each model, achieving accurate and prompt event prediction with few false alarms, thus providing increased safety and comfort.

Resin composites: Modulus of elasticity and marginal quality

OBJECTIVE To investigate how the modulus of elasticity of resin composites influences marginal quality in restorations submitted to thermocyclic and mechanical loading. METHODS Charisma, Filtek Supreme XTE and Grandio were selected as they were found to possess different moduli of elasticity but quite similar polymerization contraction. MOD cavities (n=30) were prepared in extracted premolars, restored and then subjected to thermocyclic and mechanical loading. Marginal quality of the restorations before and after loading was analyzed on epoxy replicas under a scanning electron microscope. The percentage of gap-free margins and occurrence of paramarginal fractures were registered. Modulus of elasticity and polymerization contraction were analyzed with parametric and margins with nonparametric ANOVA and post hoc Tukey HSD or Wilcoxon rank-sum tests, respectively. The number of paramarginal fractures was analyzed with exact Fisher tests (α=0.05). RESULTS Grandio demonstrated significantly more gap-free enamel margins than Charisma and Filtek Supreme XTE, before and after loading (p<0.01), whereas there was no difference between Charisma and Filtek Supreme XTE (p>0.05). No significant effect of resin composite (p=0.81) on the quality of dentine margins was observed, before or after loading. Deterioration of all margins was evident after loading (p<0.0001). More paramarginal enamel fractures were observed after loading in teeth restored with Grandio when compared to Charisma (p=0.008). CONCLUSIONS The resin composite with the highest modulus of elasticity resulted in the highest number of gap-free enamel margins but with an increased incidence of paramarginal enamel fractures. CLINICAL SIGNIFICANCE The results from this study suggest that the marginal quality of restorations can be improved by the selection of a resin composite with modulus of elasticity close to that of dentine, although an increase in paramarginal enamel fractures can result as a consequence.

Multi-Model Data Fusion to Improve an Early Warning System for Hypo-/Hyperglycemic Events

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

Comparison of Mixed and Kinematic Uniform Boundary Conditions in Homogenized Elasticity of Femoral Trabecular Bone Using Microfinite Element Analyses

Mechanical properties of human trabecular bone play an important role in age-related bone fragility and implant stability. Micro-finite element (microFE) analysis allows computing the apparent elastic properties of trabecular bone biopsies, but the results depend on the type of applied boundary conditions (BCs). In this study, 167 femoral trabecular cubic biopsies with a side length of 5.3 mm were analyzed using microFE analysis to compare their stiffness systematically with kinematic uniform boundary conditions (KUBCs) and periodicity-compatible mixed uniform boundary conditions (PMUBCs). The obtained elastic constants were then used in the volume fraction and fabric-based orthotropic Zysset-Curnier model to identify their respective model parameters. As expected, PMUBCs lead to more compliant apparent elastic properties than KUBCs, especially in shear. The differences in stiffness decreased with bone volume fraction and mean intercept length. Unlike KUBCs, PMUBCs were sensitive to heterogeneity of the biopsies. The Zysset-Curnier model predicted apparent elastic constants successfully in both cases with adjusted coefficients of determination of 0.986 for KUBCs and 0.975 for PMUBCs. The role of these boundary conditions in finite element analyses of whole bones and bone-implant systems will need to be investigated in future work.