Hasil untuk "Property"

E. Furubotn, S. Pejovich

G. Libecap

K. Phoon, F. Kulhawy

D. Acemoglu, Thierry Verdier

Erica M. Field

Susan K. Sell

T. Sikor, C. Lund

Arun Agrawal, Elinor Ostrom

(55) 201830603792.0 Status: ACT Identification, using the two-letter code according to WIPO Standard ST.3, of the authority publishing or registering the industrial design CN National Registration Number 305203444 Date of the national registration 2019-06-07 Application number 201830603792.0 Filing date 2018-10-27 Date of publication of the registered industrial design by printing or similar process, or making it available to the public by any other means 2019-06-07 Class and subclass of the Locarno Classification 14-03 Indication of products

Yongmin Chen, Thitima Puttitanun, Thitima Puttitanun

J. Krueger, D. Rector, Sandip Roy et al.

N. Blomley

Beata K. Smarzynska

While existing literature has examined the impact of intellectual property protection on the volume of foreign direct investment (FDI), little is known about its effect on the composition of FDI inflows. The author addresses this question empirically, using a unique firm-level data set from Eastern Europe and the former Soviet Union. She finds that weak protection deters foreign investors in technology-intensive sectors that rely heavily on intellectual property rights. The results also indicate that a weak intellectual property regime encourages investors to undertake projects focusing on distribution rather than local production. The latter effect is present in all sectors, not justthose relying heavily on intellectual property protection.

Sheldon Dantas, Miguel Martín, Yoël Perreau

In this note, we prove that the Daugavet property implies the polynomial Daugavet property, solving a longstanding open problem in the field. Our approach is based on showing that a geometric characterization of the Daugavet property due to Shvidkoy, originally formulated in terms of the weak topology, remains valid when the weak topology is replaced by the weak polynomial topology. Using similar techniques, we further establish that every linear Daugavet center is also a polynomial Daugavet center, and that the weak operator Daugavet property implies its polynomial counterpart. As an application of the latter result, we present new examples of Banach spaces whose $N$-fold symmetric tensor products satisfy the Daugavet property.

Bob Rehder

A desirable property of any theory of causal reasoning is to explain not only why people make causal reasoning errors but also <i>when</i> they make them. The <i>mutation sampler</i> is a rational process model of human causal reasoning that yields normatively correct inferences when sufficient cognitive resources are available but introduces systematic errors when they are not. The mutation sampler has been shown to account for a number of causal reasoning errors, including <i>Markov violations</i>, the phenomenon in which human reasoners treat causally related variables as statistically dependent when they are normatively independent. A Markov violation arises, for example, when an individual reasoning about a causal chain <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>X</mi><mo>→</mo><mi>Y</mi><mo>→</mo><mi>Z</mi></mrow></semantics></math></inline-formula> treats <i>X</i> as informative about the state of <i>Z</i> even when the state of <i>Y</i> is known. Recently, the mutation sampler was used to predict the existence of previously untested experimental conditions in which the <i>sign</i> of Markov violations would switch from positive to negative. Here, it was used to predict the existence of conditions in which Markov violations should <i>disappear</i> entirely. In fact, asking subjects to reason about a novel causal structure with nothing but <i>generative</i> causal relations (a cause makes its effect more likely) resulted in Markov violations in the usual positive direction. But simply describing one of four causal relations as <i>inhibitory</i> (the cause makes its effect less likely) resulted in the elimination of those violations. Theoretical model fitting confirmed how this novel result is predicted by the mutation sampler.

Sagar Chokshi, Piyush Gohil, Vijay Parmar et al.

Machine Learning has become prevalent nowadays for predicting data on the mechanical properties of various materials and is widely used in various polymeric applications. In the present study, Artificial Neural Network (ANN), a computational tool is used to predict the elastic modulus of a composite of longitudinally placed fiber-reinforced polymeric composite. The novelty in carried work is that the property prediction is carried out considering interphase and its properties. For this, tensile properties data of Longitudinally Placed Bamboo Fiber Reinforced Polyester Composite (LUDBPC), Longitudinally Placed Flax Fiber Reinforced Polyester Composite (LUDFPC) and Longitudinally Placed Jute Fiber Reinforced Polyester Composite (LUDJPC) has been procured to generate ANN models. The Levenberg-Marquardt training algorithm is used to generate the ANN models as it gives more accurate results compared to other ANN algorithms based on interphase properties data. The validation of ANN models was also carried out based on fresh experimental results of BPC/FPC by doing the fabrication with hand layup technique and testing of composites with a Universal Testing Machine (UTM). The present work signifies that the developed ANN models give accurate results with experimental results for the prediction of elastic modulus of composite (Ecl) and it can be used for the prediction of longitudinally placed fiber-reinforced composite and Ecl of BPC at volume fraction of fiber (vf):22% is 2248.75 MPa and Ecl of FPC at vf:10% is 3210.50 MPa.

N. Blomley

P. Panda, B. Agarwal

W. Landes, R. Posner

Introduction 1. The Economic Theory of Property 2. How to Think about Copyright 3. A Formal Model of Copyright 4. Basic Copyright Doctrines 5. Copyright in Unpublished Works 6. Fair Use, Parody, and Burlesque 7. The Economics of Trademark Law 8. The Optimal Duration of Copyrights and Trademarks 9. The Legal Protection of Postmodern Art 10. Moral Rights and the Visual Artists Rights Act 11. The Economics of Patent Law 12. The Patent Court: A Statistical Evaluation 13. The Economics of Trade Secrecy Law 14. Antitrust and Intellectual Property 15. The Political Economy of Intellectual Property Law Conclusion Acknowledgments Index

Mehrdad Nasernejad, Jonathan Toledo

In this paper we investigate the monomial ideals which satisfy the copersistence property or nearly copersistence property.