Suchergebnisse

Intro -- Contents -- Preface -- Chapter 1 -- Assembly of Nanocatalytic Structures by Molecular Layer Epitaxy Method -- Abstract -- 1. Introduction -- 2. Molecular Layer Epitaxy (MLE) Method -- 3. Heterocatalytic Nanostructures by MLE Method -- 4. Evaluation Criteria for Catalytic Nanostructures -- 5. Materials and Methods -- 6. Results -- 6.1. Structural Analysis -- 6.2. Catalytic Properties -- 7. Discussion -- Conclusion -- Acknowledgments -- References -- Chapter 2 -- Solid Acids as Catalysts for Biodiesel Synthesis -- Abstract -- Introduction -- Heterogeneously Catalyzed Biodiesel Synthesis -- Solid Acid Catalysts: Preparation, Characteristics and Activity in Biodiesel Synthesis -- Modified Silica Based Catalysts -- Metal Oxide Based Acid Catalysts -- Ion-Exchange Resins -- Heteropolyacids -- Zeolite -- Carbon-Based Solid Acids -- Deactivation of Solid Acid Catalysts -- Modified Silica Based Catalysts -- Oxide Based Catalysts -- Ion-Exchange Resin -- Heteropolyacids -- Zeolite -- Carbon Based -- Kinetics of Transesterification Process Catalyzed by Solid Acids -- Conclusion -- Acknowledgments -- References -- Chapter 3 -- Process Optimization of Refined Palm Oil Biodiesel Production Using Calcium Methoxide Obtained from Quick Lime as Heterogeneous Catalyst -- Abstract -- Introduction -- Literature Review -- Biodiesel -- Biodiesel Production via Transesterification Reaction -- Response Surface Methodology -- Materials and Methods -- Quick Lime -- Refined Palm Oil -- Reagents -- Equipments -- Methods -- Preparation of the Catalyst -- Characterization of Catalyst -- Conversion Experiment of Approximate Conditions -- Experimental Design and Statistical Analysis -- Reusability of the Ca(OCH3)2 -- Gas Chromatography (GC) Analysis -- Analysis Method -- Analysis of Fatty Acid Composition in RPO -- Characterization of Biodiesel

International audience ; We use US county-level data to estimate convergence rates for 22 individual states. We find significant heterogeneity. E.g., the California estimate is 19.9% and the New York estimate is 3.3%. Convergence rates are essentially uncorrelated with income levels.

The common effect model in program evaluation assumes that all treated individuals have the same impact from a program. Our paper contributes to the recent literature that tests and goes beyond the common effect model by investigating impact heterogeneity using data from the experimental evaluation of the Mexican conditional cash transfer program PROGRESA. Our analysis builds upon and extends that in Heckman, Smith and Clements (1997) and more recent studies of quantile treatment effects and random coefficient models. We find strong evidence of systematic (i.e. subgroup) variation in impacts in PROGRESA and modest evidence of heterogeneous impacts conditional on the systematic impacts. We find evidence against the perfect positive dependence assumption that underlies the interpretation of quantile treatment effects as impacts at quantiles of the untreated outcome distribution. Our paper concludes with a discussion of the policy relevance of our findings and of heterogeneous impacts more generally.

We investigate impact heterogeneity using data from the experimental evaluation of the Mexican conditional cash transfer program PROGRESA. We build upon, and extend Heckman, Smith and Clements (Heckman, J., Smith, J., Clements, N., 1997. Making the most out of programme evaluations and social experiments: Accounting for heterogeneity in programme impacts. Review of Economic Studies 64, 487–535) and recent studies of quantile treatment effects and random coefficient models. We find strong evidence of systematic (i.e. subgroup) variation in impacts in PROGRESA and modest evidence of heterogeneous impacts conditional on the systematic impacts. Our paper concludes with a discussion of the policy relevance of our findings and of heterogeneous impacts more generally.

The "common effect" model in program evaluation assumes that all treated individuals have the same impact from a program. Our paper contributes to the recent literature that tests and goes beyond the common effect model by investigating impact heterogeneity using data from the experimental evaluation of the Mexican conditional cash transfer program PROGRESA. Our analysis builds upon and extends that in Heckman, Smith and Clements (1997) and more recent studies of quantile treatment effects and random coefficient models. We find strong evidence of systematic (i.e. subgroup) variation in impacts in PROGRESA and modest evidence of heterogeneous impacts conditional on the systematic impacts. We find evidence against the perfect positive dependence assumption that underlies the interpretation of quantile treatment effects as impacts at quantiles of the untreated outcome distribution. Our paper concludes with a discussion of the policy relevance of our findings and of heterogeneous impacts more generally. -- Heterogeneous impacts ; randomized experiment ; quantile treatment effects

The massive collection of personal data by personalization systems has rendered the preservation of privacy of individuals more and more difficult. Most of the proposed approaches to preserve privacy in personalization systems usually address this issue uniformly across users, thus ignoring the fact that users have different privacy attitudes and expectations (even among their own personal data). In this paper, we propose to account for this non-uniformity of privacy expectations by introducing the concept of heterogeneous differential privacy. This notion captures both the variation of privacy expectations among users as well as across different pieces of information related to the same user. We also describe an explicit mechanism achieving heterogeneous differential privacy, which is a modification of the Laplacian mechanism by Dwork, McSherry, Nissim and Smith. In a nutshell, this mechanism achieves heterogeneous differential privacy by manipulating the sensitivity of the function using a linear transformation on the input domain. Finally, we evaluate on real datasets the impact of the proposed mechanism with respect to a semantic clustering task. The results of our experiments demonstrate that heterogeneous differential privacy can account for different privacy attitudes while sustaining a good level of utility as measured by the recall for the semantic clustering task.