Local Asymptotic Equivalence of the Bai and Ng (2004) and Moon and Perron (2004) Frameworks for Panel Unit Root Testing

This paper considers unit-root tests in large n and large T heterogeneous panels with cross-sectional dependence generated by unobserved factors. We reconsider the two prevalent approaches in the literature, that of Moon and Perron (2004) and the PANIC setup proposed in Bai and Ng (2004). While these have been considered as completely different setups, we show that, in case of Gaussian innovations, the frameworks are asymptotically equivalent in the sense that both experiments are locally asymptotically normal (LAN) with the same central sequence. Using Le Cam's theory of statistical experiments we determine the local asymptotic power envelope and derive an optimal test jointly in both setups. We show that the popular Moon and Perron (2004) and Bai and Ng (2010) tests only attain the power envelope in case there is no heterogeneity in the long-run variance of the idiosyncratic components. The new test is asymptotically uniformly most powerful irrespective of possible heterogeneity. Moreover, it turns out that for any test, satisfying a mild regularity condition, the size and local asymptotic power are the same under both data generating processes. Thus, applied researchers do not need to decide on one of the two frameworks to conduct unit root tests. Monte-Carlo simulations corroborate our asymptotic results and document significant gains in finite-sample power if the variances of the idiosyncratic shocks differ substantially among the cross sectional units

Involvement of mossy cells in sharp wave-ripple activity in vitro

The role of mossy cells (MCs) of the hippocampal dentate area has long remained mysterious. Recent research has begun to unveil their significance in spatial computation of the hippocampus. Here, we used an in vitro model of sharp wave-ripple complexes (SWRs), which contribute to hippocampal memory formation, to investigate MC involvement in this fundamental population activity. We find that a significant fraction of MCs (~47%) is recruited into the active neuronal network during SWRs in the CA3 area. Moreover, MCs receive pronounced, ripple-coherent, excitatory and inhibitory synaptic input. Finally, we find evidence for SWR-related synaptic activity in granule cells that is mediated by MCs. Given the widespread connectivity of MCs within and between hippocampi, our data suggest a role for MCs as a hub functionally coupling the CA3 and the DG during ripple-associated computations

Electrochemical and immunoelectron microscopy evidence of lipid-protein interaction in Langmuir-Blodgett films of the human lung surfactant.

The extracellular lung surfactant surface film (ELSSF) which lines the mammalian lung alveoli at the alveolar air-aqueous cell surface interface is vital in both the breathing and the pulmonary defence processes. The molecular composition of, the structure of and the interaction in the ELSSF was studied, after the ELSSF of human lung lavages could be separated from the subphase and reassembled from its components by using the multicompartment Fromherz-type Langmuir-Blodgett trough. Transmission electron microscopy images of immunogold- labelled and negatively stained isolated film specimens were seen in a continuous layer of mostly phospholipid head groups surfactant-specific protein SpA molecules. Electrical double-layer capacitance and oxygen reduction potential measurements carried out by transferring the surface film from the air-water to a mercury-saline interface of a hanging mercury drop electrode revealed a strong lipid-protein SpA interaction. SpA molecules were partly squeezed out from the film by compression; a proteinless lipid film proved to be a condensed multilayer. Contact with SpA transformed the multilayer into a loose monomolecular film. It is suggested that SpA molecules play a lipid-transporting role, removing lipids in excess from the air-water interface into the aqueous subphase and vice versa. Lipid- protein interaction can be of importance in vivo. An explanation of how the surfactant film works during the two phases of breathing is proposed

Analytical Bethe Ansatz for closed and open gl(n)-spin chains in any representation

We present an "algebraic treatment" of the analytical Bethe Ansatz. For this purpose, we introduce abstract monodromy and transfer matrices which provide an algebraic framework for the analytical Bethe Ansatz. It allows us to deal with a generic gl(n)-spin chain possessing on each site an arbitrary gl(n)-representation. For open spin chains, we use the classification of the reflection matrices to treat all the diagonal boundary cases. As a result, we obtain the Bethe equations in their full generality for closed and open spin chains. The classifications of finite dimensional irreducible representations for the Yangian (closed spin chains) and for the reflection algebras (open spin chains) are directly linked to the calculation of the transfer matrix eigenvalues. As examples, we recover the usual closed and open spin chains, we treat the alternating spin chains and the closed spin chain with impurity

Gene expression model (in)validation by Fourier analysis

The determination of the right model structure describing a gene regulation network and the identification of its parameters are major goals in systems biology. The task is often hampered by the lack of relevant experimental data with sufficiently low noise level, but the subset of genes whose concentration levels exhibit an oscillatory behavior in time can readily be analyzed on the basis of their Fourier spectrum, known to turn complex signals into few relatively noise-free parameters. Such genes therefore offer opportunities of understanding gene regulation quantitatively.Journal ArticleResearch Support, Non-U.S. Gov'tValidation StudiesSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Productive restructuring and the reallocation of work and employment: a survey of the “new” forms of social inequality

O propósito do presente artigo consiste em questionar a inevitabilidade dos processos de segmentação e precarização das relações de trabalho e emprego, responsáveis pela inscrição de “novas” formas de desigualdade social que alicerçam o actual modelo de desenvolvimento das economias e sociedades. Visa-se criticar os limites da lógica econômica e financeira, de contornos globais, que configuram um “novo espírito do capitalismo”, ou seja, uma espécie de divinização da ordem natural das coisas. Impõe-se fazer, por isso, um périplo analítico pelas transformações em curso no mercado de trabalho, acompanhado pela vigilância epistemológica que permita enquadrar e relativizar as (di)visões neoliberais e teses tecnodeterministas dominantes. A perspectivação de cenários sobre o futuro do trabalho encerrará este périplo, permitindo-nos alertar para os condicionalismos histórico-temporais, para a urgência de se desocultar o que de ideológico e político existe nas actuais lógicas de racionalização e para os processos de ressimbolização do trabalho e emprego enquanto “experiência social central” na contemporaneidade.The scope of this paper is to question the inevitability of the processes of segmentation and increased precariousness of the relations of labor and employment, which are responsible for the introduction of “new” forms of social inequality that underpin the current model of development of economies and societies. It seeks to criticize the limits of global financial and economic logic, which constitute a “new spirit of capitalism,” namely a kind of reverence for the natural order of things. It is therefore necessary to conduct an analytical survey of the ongoing changes in the labor market, accompanied by epistemological vigilance which makes it possible to see neoliberal (di)visions and dominant technodeterministic theses in context. The enunciation of scenarios on the future of work will conclude this survey and will make it possible to draw attention to both the historical and temporal constraints and to the urgent need to unveil what is ideological and political in the prevailing logic of rationalization and processes to reinstate work and employment as a “central social experience” in contemporary times

Predicting Cell Cycle Regulated Genes by Causal Interactions

The fundamental difference between classic and modern biology is that technological innovations allow to generate high-throughput data to get insights into molecular interactions on a genomic scale. These high-throughput data can be used to infer gene networks, e.g., the transcriptional regulatory or signaling network, representing a blue print of the current dynamical state of the cellular system. However, gene networks do not provide direct answers to biological questions, instead, they need to be analyzed to reveal functional information of molecular working mechanisms. In this paper we propose a new approach to analyze the transcriptional regulatory network of yeast to predict cell cycle regulated genes. The novelty of our approach is that, in contrast to all other approaches aiming to predict cell cycle regulated genes, we do not use time series data but base our analysis on the prior information of causal interactions among genes. The major purpose of the present paper is to predict cell cycle regulated genes in S. cerevisiae. Our analysis is based on the transcriptional regulatory network, representing causal interactions between genes, and a list of known periodic genes. No further data are used. Our approach utilizes the causal membership of genes and the hierarchical organization of the transcriptional regulatory network leading to two groups of periodic genes with a well defined direction of information flow. We predict genes as periodic if they appear on unique shortest paths connecting two periodic genes from different hierarchy levels. Our results demonstrate that a classical problem as the prediction of cell cycle regulated genes can be seen in a new light if the concept of a causal membership of a gene is applied consequently. This also shows that there is a wealth of information buried in the transcriptional regulatory network whose unraveling may require more elaborate concepts than it might seem at first

Mining and state-space modeling and verification of sub-networks from large-scale biomolecular networks

<p>Abstract</p> <p>Background</p> <p>Biomolecular networks dynamically respond to stimuli and implement cellular function. Understanding these dynamic changes is the key challenge for cell biologists. As biomolecular networks grow in size and complexity, the model of a biomolecular network must become more rigorous to keep track of all the components and their interactions. In general this presents the need for computer simulation to manipulate and understand the biomolecular network model.</p> <p>Results</p> <p>In this paper, we present a novel method to model the regulatory system which executes a cellular function and can be represented as a biomolecular network. Our method consists of two steps. First, a novel scale-free network clustering approach is applied to the large-scale biomolecular network to obtain various sub-networks. Second, a state-space model is generated for the sub-networks and simulated to predict their behavior in the cellular context. The modeling results represent <it>hypotheses </it>that are tested against high-throughput data sets (microarrays and/or genetic screens) for both the natural system and perturbations. Notably, the dynamic modeling component of this method depends on the automated network structure generation of the first component and the sub-network clustering, which are both essential to make the solution tractable.</p> <p>Conclusion</p> <p>Experimental results on time series gene expression data for the human cell cycle indicate our approach is promising for sub-network mining and simulation from large-scale biomolecular network.</p