Innovation sources and productivity in Catalonian firms: a quantile regression analysis

This paper explores the effects of two main sources of innovation -intramural and external R&D- on the productivity level in a sample of 3,267 Catalonian firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and knowledge-intensive services. JEL codes: O300, C100, O140. Keywords: Innovation sources, R&D, Productivity, Quantile regression

Innovation sources and productivity: a quantile regression analysis

This paper explores the effects of two main sources of innovation —intramural and external R&D— on the productivity level in a sample of 3,267 Catalan firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and services industries.

Innovation sources and productivity in Catalonian firms: a quantile regression analysis

This paper explores the effects of two main sources of innovation - intramural and external R&D— on the productivity level in a sample of 3,267 Catalonian firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and knowledge-intensive services. JEL codes: O300, C100, O140 Keywords: Innovation sources, R&D, Productivity, Quantile Regression

The environmental effects of changing speed limits: a quantile regression approach

Two speed management policies were implemented in the metropolitan area of Barcelona aimed at reducing air pollution concentration levels. In 2008, the maximum speed limit was reduced to 80 km/h and, in 2009, a variable speed system was introduced on some metropolitan motorways. This paper evaluates whether such policies have been successful in promoting cleaner air, not only in terms of mean pollutant levels but also during high and low pollution episodes. We use a quantile regression approach for fixed effect panel data. We find that the variable speed system improves air quality with regard to the two pollutants considered here, being most effective when nitrogen oxide levels are not too low and when particulate matter concentrations are below extremely high levels. However, reducing the maximum speed limit from 120/100 km/h to 80 km/h has no effect – or even a slightly increasing effect –on the two pollutants, depending on the pollution scenario. Length: 32 pages

Optimal, minimax, and Bayesian two-stage designs in two-dose phase II clinical trials

Background: For most cytotoxic and biologic anti-cancer agents, the response rate of the drug is commonly assumed to be non-decreasing with an increasing dose. However, an increasing dose does not always result in an appreciable increase in the response rate. This may especially be true at high doses for a biologic agent. Therefore, in a phase II trial the investigators may be interested in testing the anti-tumor activity of a drug at more than one (often two) doses, instead of only at the maximum tolerated dose (MTD). This way, when the lower dose appears equally effective, this dose can be recommended for further confirmatory testing in a phase III trial under potential long-term toxicity and cost considerations. A common approach to designing such a phase II trial has been to use an independent (e.g., Simon's two-stage) design at each dose ignoring the prior knowledge about the ordering of the response probabilities at the different doses. However, failure to account for this ordering constraint in estimating the response probabilities may result in an inefficient design. In this dissertation, we developed extensions of Simon's optimal and minimax two-stage designs, including both frequentist and Bayesian methods, for two doses that assume ordered response rates between doses. ^ Methods: Optimal and minimax two-stage designs are proposed for phase II clinical trials in settings where the true response rates at two dose levels are ordered. We borrow strength between doses using isotonic regression and control the joint and/or marginal error probabilities. Bayesian two-stage designs are also proposed under a stochastic ordering constraint. ^ Results: Compared to Simon's designs, when controlling the power and type I error at the same levels, the proposed frequentist and Bayesian designs reduce the maximum and expected sample sizes. Most of the proposed designs also increase the probability of early termination when the true response rates are poor. ^ Conclusion: Proposed frequentist and Bayesian designs are superior to Simon's designs in terms of operating characteristics (expected sample size and probability of early termination, when the response rates are poor) Thus, the proposed designs lead to more cost-efficient and ethical trials, and may consequently improve and expedite the drug discovery process. The proposed designs may be extended to designs of multiple group trials and drug combination trials.^

Estimation of Sample Size and Power For Quantile Regression

Quantile regression (QR) was first introduced by Roger Koenker and Gilbert Bassett in 1978. It is robust to outliers which affect least squares estimator on a large scale in linear regression. Instead of modeling mean of the response, QR provides an alternative way to model the relationship between quantiles of the response and covariates. Therefore, QR can be widely used to solve problems in econometrics, environmental sciences and health sciences. Sample size is an important factor in the planning stage of experimental design and observational studies. In ordinary linear regression, sample size may be determined based on either precision analysis or power analysis with closed form formulas. There are also methods that calculate sample size based on precision analysis for QR like C.Jennen-Steinmetz and S.Wellek (2005). A method to estimate sample size for QR based on power analysis was proposed by Shao and Wang (2009). In this paper, a new method is proposed to calculate sample size based on power analysis under hypothesis test of covariate effects. Even though error distribution assumption is not necessary for QR analysis itself, researchers have to make assumptions of error distribution and covariate structure in the planning stage of a study to obtain a reasonable estimate of sample size. In this project, both parametric and nonparametric methods are provided to estimate error distribution. Since the method proposed can be implemented in R, user is able to choose either parametric distribution or nonparametric kernel density estimation for error distribution. User also needs to specify the covariate structure and effect size to carry out sample size and power calculation. The performance of the method proposed is further evaluated using numerical simulation. The results suggest that the sample sizes obtained from our method provide empirical powers that are closed to the nominal power level, for example, 80%.

Vertical alveolar crest bone maintenance around implants in two-stage surgery: an in situ study in dogs

The aim of this study was to evaluate in situ changes in the alveolar crest bone height around immediate implant-supported crowns in comparison to tooth-supported crowns (control) with the cervical margins located at the bone crest level, without occlusal load. In Group I, after extraction of 12 mandibular premolars from 4 adult dogs, implants from Branemark System (MK III TiU RP 4.0 x 11.5 mm) were placed to retain complete acrylic crowns. In Group II, premolars were prepared to receive complete metal crowns. Sixteen weeks after placement of the crowns (38 weeks after tooth extraction), the height of the alveolar bone crest was measured with a digital caliper. Data were analyzed statistically by the Mann-Whitney test at 5% significance level. The in situ analysis showed no statistically significant difference (p=0.880) between the implant-supported and the tooth-supported groups (1.528 + 0.459 mm and 1.570 + 0.263 mm, respectively). Based on the findings of the present study, it may be concluded that initial peri-implant bone loss may result from the remodeling process necessary to establish the biological space, similar to which occurs with tooth-supported crowns.

Demand elasticities for food products in Brazil: a two-stage budgeting system

The object of this article is to estimate demand elasticities for a basket of staple food important for providing the caloric needs of Brazilian households. These elasticities are useful in the measurement of the impact of structural reforms on poverty. A two-stage demand system was constructed, based on data from Household Expenditure Surveys (POF) produced by IBGE (The Brazilian Bureau of Statistics) in 1987/88 and 1995/96. We have used panel data to estimate the model, and have calculated income, own-price, and cross-price elasticities for eight groups of goods and services and, in the second stage, for 11 sub groups of staple food products. We estimated those elasticities for the whole sample of consumers and for two income groups.

Two-stage laparoscopic liver resection for bilateral colorectal liver metastasis

Hepatectomy may prolong the survival of colorectal cancer patients with liver metastases. Two-stage liver surgery is a valid option for the treatment of bilobar colorectal liver metastasis. This video demonstrates technical aspects of a two-stage pure laparoscopic hepatectomy for bilateral liver metastasis. To the authors` knowledge, this is the first description of a two-stage laparoscopic liver resection in the English literature. A 54-year-old man with right colon cancer and synchronous bilobar colorectal liver metastasis underwent laparoscopic right colon resection followed by oxaliplatin-based chemotherapy. The patient then was referred for surgical treatment of liver metastasis. Liver volumetry showed a small left liver remnant. Surgical planning was for a totally laparoscopic two-stage liver resection. The first stage involved laparoscopic resection of segment 3 and ligature of the right portal vein. The postoperative pathology showed high-grade liver steatosis. After 4 weeks, the left liver had regenerated, and volumetry of left liver was 43%. The second stage involved laparoscopic right hepatectomy using the intrahepatic Glissonian approach. Intrahepatic access to the main right Glissonian pedicle was achieved with two small incisions, and an endoscopic vascular stapling device was inserted between these incisions and fired. The line of liver transection was marked following the ischemic area. Liver transection was accomplished with the Harmonic scalpel and an endoscopic stapling device. The specimen was extracted through a suprapubic incision. The falciform ligament was fixed to maintain the left liver in its original anatomic position, avoiding hepatic vein kinking and outflow syndrome. The operative time was 90 min for stage 1 and 240 min for stage 2 of the procedure. The recoveries after the first and second operations were uneventful, and the patient was discharged on postoperative days 2 and 7, respectively. Two-stage liver resections can be performed safely using laparoscopy. The intrahepatic Glissonian approach is a useful tool for pedicle control of the right liver, especially after previous dissection of the hilar plate.

Two-stage transvaginal cervical length screening for preterm birth in twin pregnancies

Aim: To compare cervical length (CL) at 18-21 and 22-25 weeks` gestation in twin pregnancies in prediction of spontaneous preterm delivery and to examine cervical shortening. Methods: Retrospective cohort study of CL measured at 18-21 and 22-25 weeks` gestation in twin pregnancies. Results: Receiver operating characteristics (ROC) curve revealed area of 0.64 (95% CI 0.53-0.75) and 0.80 (95% CI 0.72-0.88) for measurements at 18-21 and 22-25 weeks, respectively (P <= 0.001). Sensitivities of 33.3% and 23% and negative predicting value (NPV) of 97.3% and 86.8% for delivery at <28 and <34 weeks gestation were reached for measurements at 18-21 weeks. Sensitivities of 71.4% and 38.2% and NPV of 99.1% and 91.4% for delivery at <28 and <34 weeks` gestation were reached for measurements at 22-25 weeks. Cervical length shortening analysis showed an area under ROC curve of 0.81 (95% CI 0.73-0.89) and best cut-off was at >= 2 mm/week. Sensitivities of 80% and 60.8% and NPV of 98.9% and 90.6% for delivery at <28 and <34 weeks gestation were reached. Conclusions: In twin gestations, assessment of CL at 22-25 weeks is better than assessment at 18-21 weeks to predict preterm delivery before 34 weeks. Cervical shortening at a rate of >= 2 mm/weeks between 18 and 25 weeks gestation was a good predictor of spontaneous preterm birth in this high-risk population.

Comparison of Preoperative Nd:YAG Laser Anterior Capsulotomy Versus Two-Stage Curvilinear Capsulorhexis in Phacoemulsification of White Intumescent Cataracts

BACKGROUND AND OBJECTIVE: To compare the results of preoperative Nd:YAG laser anterior capsulotomy versus two-stage continuous curvilinear capsulorhexis (CCC) in phacoemulsification of eyes with white intumescent cataracts and liquefied cortex. PATIENTS AND METHODS: Twenty-three eyes with white intumescent cataract were consecutively randomized for phacoemulsification with preoperative Nd:YAG laser anterior capsulotomy (group 1, n = 11) or two-stage CCC (group 2, n = 12) procedures. Intraoperative findings and postoperative outcomes were compared using the nonparametric tests. RESULTS: Postoperative Visual acuity, mean surgical time, mean effective phacoemulsification time, and frequency of complications were not significantly different between the two groups (P > .05). Two cases in each group were converted to the extracapsular technique. Excluding these four patients, surgical time was shorter In group 1 (P = .017). CONCLUSION: Preoperative Nd:YAG laser anterior capsulotomy is a safe technique in decompressing the capsular bag before phacoemulsification of white intumescent cataracts with liquefied cortex.

Microleakage into and from Two-Stage Implants: An In Vitro Comparative Study

Purpose: Gaps between an abutment and a dental implant are unavoidable, and microleakage may occur, leading to problems such as malodor and peri-implantitis. The aim of the present in vitro study was to investigate leakage of Staphylococcus aureus through the implant/abutment interface by the method of bacterial culture, and to compare the leakage rates of two different types of implant-abutment connections. Materials and Methods: Twenty Morse taper implants with abutments were divided into two groups: group A, which were evaluated for microleakage into the inner part of the implants, and group B, which were evaluated for microleakage from the inner part of the implants. Twenty internal-hexagon implants with abutments were also divided into two groups: group C, which were evaluated for microleakage into the inner part of the implants, and group D, which were evaluated for microleakage from the inner part of the implants. For the evaluation of leakage from the implants, the assemblies had the inner parts inoculated with S aureus, and each assembly was incubated in sterile brain heart infusion broth for 1 week. For assessment of leakage into the implants, each assembly was submerged in 4 mL S aureus culture in tubes and incubated for 2 weeks. The microleakage of the two implant connections was compared. Results: Microbial leakage occurred in all groups, and there was no statistically significant difference between groups A and C or between groups B and D. Conclusions: In vitro, S aureus leakage through the implant/abutment interface occurred with both Morse taper and internal-hexagon implants. INT J ORAL MAXILLOFAC IMPLANTS 2011;26:56-62

Estimating Two-Stage Models for Genetic Influences on Alcohol, Tobacco or Drug Use Initiation and Dependence Vulnerability in Twin and Family Data

Genetic research on risk of alcohol, tobacco or drug dependence must make allowance for the partial overlap of risk-factors for initiation of use, and risk-factors for dependence or other outcomes in users. Except in the extreme cases where genetic and environmental risk-factors for initiation and dependence overlap completely or are uncorrelated, there is no consensus about how best to estimate the magnitude of genetic or environmental correlations between Initiation and Dependence in twin and family data. We explore by computer simulation the biases to estimates of genetic and environmental parameters caused by model misspecification when Initiation can only be defined as a binary variable. For plausible simulated parameter values, the two-stage genetic models that we consider yield estimates of genetic and environmental variances for Dependence that, although biased, are not very discrepant from the true values. However, estimates of genetic (or environmental) correlations between Initiation and Dependence may be seriously biased, and may differ markedly under different two-stage models. Such estimates may have little credibility unless external data favor selection of one particular model. These problems can be avoided if Initiation can be assessed as a multiple-category variable (e.g. never versus early-onset versus later onset user), with at least two categories measurable in users at risk for dependence. Under these conditions, under certain distributional assumptions., recovery of simulated genetic and environmental correlations becomes possible, Illustrative application of the model to Australian twin data on smoking confirmed substantial heritability of smoking persistence (42%) with minimal overlap with genetic influences on initiation.

Photonics Active Filters Based on SiC Multi layer Structures: A Two Stage Active Circuit

Characteristics of tunable wavelength filters based on a-SiC:H multi-layered stacked cells are studied both theoretically and experimentally. Results show that the light-activated photonic device combines the demultiplexing operation with the simultaneous photodetection and self amplification of an optical signal. The sensor is a bias wavelength current-controlled device that make use of changes in the wavelength of the background to control the power delivered to the load, acting a photonic active filter. Its gain depends on the background wavelength that controls the electrical field profile across the device.