Looking for an Accounting Identity : The Case of Romania during the 20th Century

This article aims to provide a longitudinal presentation of developments in Romanian accounting during the 20th century and to propose a neo-institutional explanation of this evolution. The historical research methodology employed here is complex. We use a constructive research philosophy, an inductive research approach, a mixture of research types (narrative, oral and interpretative histories), content analysis as our research method and four types of data collection (archives, secondary data, observations and interviews). The interpretative analysis is based on the neo-institutional theoretical framework. The study identifies a “homeAgrown”, normative influence in Romanian accounting practices during the first 50 years of the twentieth century, a coercive one, imposed until 1989, by a centralized communist system, and from 1989 to the present, a mixed isomorphism oriented around French, European and International accounting systems. Lacking a period of introspection, the authors feel that there is little hope that Romanian accounting will reA discover its unique culture, or will manage to build upon or improve its indigenous base in the current international contextAccounting ; Historical approach ; Neo-institutionalism ; XXth century ; Romania

Probabilistic representation for solutions of an irregular porous media type equation: the degenerate case

We consider a possibly degenerate porous media type equation over all of $\R^d$ with $d = 1$, with monotone discontinuous coefficients with linear growth and prove a probabilistic representation of its solution in terms of an associated microscopic diffusion. This equation is motivated by some singular behaviour arising in complex self-organized critical systems. The main idea consists in approximating the equation by equations with monotone non-degenerate coefficients and deriving some new analytical properties of the solution

Looking for an Accounting Identity : The Case of Romania during the 20th Century

Cahier de recherche n° 2010-03 E2This article aims to provide a longitudinal presentation of developments in Romanian accounting during the 20th century and to propose a neo-institutional explanation of this evolution. The historical research methodology employed here is complex. We use a constructive research philosophy, an inductive research approach, a mixture of research types (narrative, oral and interpretative histories), content analysis as our research method and four types of data collection (archives, secondary data, observations and interviews). The interpretative analysis is based on the neo-institutional theoretical framework. The study identifies a “homeAgrown”, normative influence in Romanian accounting practices during the first 50 years of the twentieth century, a coercive one, imposed until 1989, by a centralized communist system, and from 1989 to the present, a mixed isomorphism oriented around French, European and International accounting systems. Lacking a period of introspection, the authors feel that there is little hope that Romanian accounting will reA discover its unique culture, or will manage to build upon or improve its indigenous base in the current international contex

Dynamics of semi-flexible polymer solutions in the highly entangled regime

We present experimental evidence that the effective medium approximation (EMA), developed by D.C. Morse [Phys. Rev. E {\bf 63}, 031502, (2001)], provides the correct scaling law of the macroscopic plateau modulus $G^{0}\propto\rho^{4/3}L^{-1/3}_{p}$ (where $\rho$ is the contour length per unit volume and $L_{p}$ is the persistence length) of semi-flexible polymer solutions, in the highly entangled concentration regime. Competing theories, including a self-consistent binary collision approximation (BCA), have instead predicted $G^{0}\propto\rho^{7/5}L^{-1/5}_{p}$. We have tested both the EMA and BCA scaling predictions using actin filament (F-actin) solutions which permit experimental control of $L_p$ independently of other parameters. A combination of passive video particle tracking microrheology and dynamic light scattering yields independent measurements of the elastic modulus $G$ and $L_{p}$ respectively. Thus we can distinguish between the two proposed laws, in contrast to previous experimental studies, which focus on the (less discriminating) concentration functionality of $G$.Comment: 4 pages, 6 figures, Phys. Rev. Lett. (accepted

Anchoring and agreement in syntactic annotations

We present a study on two key characteristics of human syntactic annotations: anchoring and agreement. Anchoring is a well known cognitive bias in human decision making, where judgments are drawn towards pre-existing values. We study the influence of anchoring on a standard approach to creation of syntactic resources where syntactic annotations are obtained via human editing of tagger and parser output. Our experiments demonstrate a clear anchoring effect and reveal unwanted consequences, including overestimation of parsing performance and lower quality of annotations in comparison with human-based annotations. Using sentences from the Penn Treebank WSJ, we also report systematically obtained inter-annotator agreement estimates for English dependency parsing. Our agreement results control for parser bias, and are consequential in that they are on par with state of the art parsing performance for English newswire. We discuss the impact of our findings on strategies for future annotation efforts and parser evaluations.Comment: EMNLP 201

Revisiting loss-specific training of filter-based MRFs for image restoration

It is now well known that Markov random fields (MRFs) are particularly effective for modeling image priors in low-level vision. Recent years have seen the emergence of two main approaches for learning the parameters in MRFs: (1) probabilistic learning using sampling-based algorithms and (2) loss-specific training based on MAP estimate. After investigating existing training approaches, it turns out that the performance of the loss-specific training has been significantly underestimated in existing work. In this paper, we revisit this approach and use techniques from bi-level optimization to solve it. We show that we can get a substantial gain in the final performance by solving the lower-level problem in the bi-level framework with high accuracy using our newly proposed algorithm. As a result, our trained model is on par with highly specialized image denoising algorithms and clearly outperforms probabilistically trained MRF models. Our findings suggest that for the loss-specific training scheme, solving the lower-level problem with higher accuracy is beneficial. Our trained model comes along with the additional advantage, that inference is extremely efficient. Our GPU-based implementation takes less than 1s to produce state-of-the-art performance.Comment: 10 pages, 2 figures, appear at 35th German Conference, GCPR 2013, Saarbr\"ucken, Germany, September 3-6, 2013. Proceeding