Anders Björklund

Bio: Anders Björklund is an academic researcher from Lund University. The author has contributed to research in topics: Transplantation & Dopamine. The author has an hindex of 165, co-authored 769 publications receiving 84268 citations. Previous affiliations of Anders Björklund include University of Washington & Institute for the Study of Labor.

Globaliseringens motståndare: Mexikos Zapatister som fall av kontrahegemoni i det globala civila samhället

Abstract: Den 1 januari 1994, samma dag som den Mexikanska staten blev medlem i frihandelsavtalet NAFTA, kunde man hora ett ?iYa Basta!? runt om i delstaten Chiapas i sydostra Mexiko. Denna uppsats behandlar den Zapatistiska motstandsrorelsen utifran gramsciansk och neogramsciansk teoribildning for att forklara deras kamp som en reaktion pa den radande neoliberalistiska ekonomiska globaliseringen. Genom att studera deras ideologi och handlingar sa menar vi att de utgor en del av ett kontrahegemoniskt motstand belaget inom den nya globala anti-globaliseringsrorelsen som i sin tur utgor en del av det globala civila samhallet. Zapatisternas struktur och metod har, som ett resultat av den ekonomiska globaliseringen, omvandlats och anpassat sig for att kunna fora sin kamp och visa pa att alternativ till neoliberalismen existerar.

Fluorescence histochemical demonstration of peptides with nh2- or cooh-terminal tryptophan or dopa by condensation

Abstract: Condensation with glyoxylic acid vapor, recently introduced as a highly sensitive method for fluorescence histochemical visualization of biogenic monamines, has been found to allow also the demonstration of certain tryptophan- or dopa-containing peptides. Thus, in model experiments, treatment with glyoxylic acid vapor induced fluorescence from diand tetrapeptides with tryptophan or dopa in NH2-terminal or COOH-terminal position. Peptides without tryptophan or dopa in terminal positions gave no observable fluorescence. Differences were recorded between peptides with NH2-terminal and COOH-terminal tryptophan with respect to their fluorescence yields under different reaction conditions and the spectral characteristics of the fluorophores (excitation/emission maxima: 375-380/500-520 nm and 340-370/435 nm, respectively). In addition, the tryptophan-containing peptides could be distinguished microspectrofluorometrically from the dopacontaining peptides. Thus, the fluorophore of the NH2-terminal dopa peptide had excitation/emission maxima at 330 and 380/495 am, and the corresponding values for the fluorophore of the CO0H-terminal dopa peptide were 330 and 370/460 nm. The glyoxylic acid treatment produced intense fluorescence in certain endocrine cell systems in pituitary, thyroid and gastric mucosa, previously suggested to store peptides with NH2-terminal tryptophan. The present findings support this hypothesis. Sensitive and selective methods for the his

Eltoprazine pour la suppression de dyskinésies induites par le l-dopa

Abstract: La presente invention concerne l’utilisation du medicament eltoprazine pour combattre les dyskinesies dues a une therapie chronique avec le levodopa (L-DOPA) chez des patients souffrant de la maladie de Parkinson.

Econometric Analysis of Cross Section and Panel Data

Abstract: The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Econometric Analysis of Panel Data

Abstract: Preface.1. Introduction.1.1 Panel Data: Some Examples.1.2 Why Should We Use Panel Data? Their Benefits and Limitations.Note.2. The One-way Error Component Regression Model.2.1 Introduction.2.2 The Fixed Effects Model.2.3 The Random Effects Model.2.4 Maximum Likelihood Estimation.2.5 Prediction.2.6 Examples.2.7 Selected Applications.2.8 Computational Note.Notes.Problems.3. The Two-way Error Component Regression Model.3.1 Introduction.3.2 The Fixed Effects Model.3.3 The Random Effects Model.3.4 Maximum Likelihood Estimation.3.5 Prediction.3.6 Examples.3.7 Selected Applications.Notes.Problems.4. Test of Hypotheses with Panel Data.4.1 Tests for Poolability of the Data.4.2 Tests for Individual and Time Effects.4.3 Hausman's Specification Test.4.4 Further Reading.Notes.Problems.5. Heteroskedasticity and Serial Correlation in the Error Component Model.5.1 Heteroskedasticity.5.2 Serial Correlation.Notes.Problems.6. Seemingly Unrelated Regressions with Error Components.6.1 The One-way Model.6.2 The Two-way Model.6.3 Applications and Extensions.Problems.7. Simultaneous Equations with Error Components.7.1 Single Equation Estimation.7.2 Empirical Example: Crime in North Carolina.7.3 System Estimation.7.4 The Hausman and Taylor Estimator.7.5 Empirical Example: Earnings Equation Using PSID Data.7.6 Extensions.Notes.Problems.8. Dynamic Panel Data Models.8.1 Introduction.8.2 The Arellano and Bond Estimator.8.3 The Arellano and Bover Estimator.8.4 The Ahn and Schmidt Moment Conditions.8.5 The Blundell and Bond System GMM Estimator.8.6 The Keane and Runkle Estimator.8.7 Further Developments.8.8 Empirical Example: Dynamic Demand for Cigarettes.8.9 Further Reading.Notes.Problems.9. Unbalanced Panel Data Models.9.1 Introduction.9.2 The Unbalanced One-way Error Component Model.9.3 Empirical Example: Hedonic Housing.9.4 The Unbalanced Two-way Error Component Model.9.5 Testing for Individual and Time Effects Using Unbalanced Panel Data.9.6 The Unbalanced Nested Error Component Model.Notes.Problems.10. Special Topics.10.1 Measurement Error and Panel Data.10.2 Rotating Panels.10.3 Pseudo-panels.10.4 Alternative Methods of Pooling Time Series of Cross-section Data.10.5 Spatial Panels.10.6 Short-run vs Long-run Estimates in Pooled Models.10.7 Heterogeneous Panels.Notes.Problems.11. Limited Dependent Variables and Panel Data.11.1 Fixed and Random Logit and Probit Models.11.2 Simulation Estimation of Limited Dependent Variable Models with Panel Data.11.3 Dynamic Panel Data Limited Dependent Variable Models.11.4 Selection Bias in Panel Data.11.5 Censored and Truncated Panel Data Models.11.6 Empirical Applications.11.7 Empirical Example: Nurses' Labor Supply.11.8 Further Reading.Notes.Problems.12. Nonstationary Panels.12.1 Introduction.12.2 Panel Unit Roots Tests Assuming Cross-sectional Independence.12.3 Panel Unit Roots Tests Allowing for Cross-sectional Dependence.12.4 Spurious Regression in Panel Data.12.5 Panel Cointegration Tests.12.6 Estimation and Inference in Panel Cointegration Models.12.7 Empirical Example: Purchasing Power Parity.12.8 Further Reading.Notes.Problems.References.Index.