Liberalisation, care and the struggle for women's social citizenship in Vietnam

social policy;subsidies;Viet Nam;economic liberalization;care work;women workers;women's rights

Gender and enterprise development in Vietnam under Doi-Moi : issues for policy, research and training

Viet Nam;economic development;gender equality;small enterprises;women entrepreneurs

Human trafficking and organised crime

international economy;illegal immigration;international migration;organized crime

Human Security and the Governmentality of Neo-Liberal Mobility: A Feminist Perspective

Transnational migration and its implications for human security as a policy field constitute one of the most complex issues of our time. Current experiences of displacement and security spans between a cyber world characterized by hyper mobility of finance, technology, information and the ‘cosmopolitan’ values of a ‘flexible citizenship’ (Ong, 1999) to the world of human trafficking and smuggling of migrants and refugees as a mode of mobility adopted by people who cross borders on foot, by boat, trucks and planes who are often abandoned to die when arrangements break down (Eschbach/Hagan/Rodriguez, 2001; El-Cherkeh/Hella, 2004). The extant legal vacuum reflects unresolved conflicts of interest at different levels and poses a great challenge to the right to mobility as an expression of the liberal ideal of individual liberty.feminist perspective;human security;neo-liberal mobility

Comparative Analysis Of Zebrafish And Planarian Model Systems For Developmental Neurotoxicity Screens Using An 87-Compound Library

There is a clear need to establish and validate new methodologies to more quickly and efficiently screen chemicals for potential toxic effects, particularly on development. The emergence of alternative animal systems for rapid toxicology screens presents valuable opportunities to evaluate how systems complement each other. In this article, we compare a chemical library of 87-compounds in two such systems, developing zebrafish and freshwater planarians, by screening for developmental neurotoxic effects. We show that the systems’ toxicological profiles are complementary to each other, with zebrafish yielding more detailed morphological endpoints and planarians more behavioral endpoints. Overall, zebrafish was more sensitive to this chemical library, yielding 86/87 hits, compared to 50/87 hits in planarians. The difference in sensitivity could not be attributed to molecular weight, Log Kow or the bioconcentration factor. Of the 87 chemicals, 28 had previously been evaluated in mammalian developmental neuro- (DNT), neuro- or developmental toxicity studies. Of the 28, 20 were hits in the planarian, and 27 were hits in zebrafish. Eighteen of the 28 had previously been identified as DNT hits in mammals and were highly associated with activity in zebrafish and planarian behavioral assays in this study. Only 1 chemical (out of 28) was a false negative in both zebrafish and planarian systems. Differences in endpoint coverage and system sensitivity illustrate the value of a dual systems approach to rapidly query a large chemical-bioactivity space and provide weight-of-evidence for prioritization of chemicals for further testing

On the Redshift Distribution of Gamma Ray Bursts in the Swift Era

A simple physical model for long-duration gamma ray bursts (GRBs) is used to fit the redshift (z) and the jet opening-angle distributions measured with earlier GRB missions and with Swift. The effect of different sensitivities for GRB triggering is sufficient to explain the difference in the z distributions of the pre-Swift and Swift samples, with mean redshifts of ~1.5 and ~2.7, respectively. Assuming that the emission properties of GRBs do not change with time, we find that the data can only be fitted if the comoving rate-density of GRB sources exhibits positive evolution to z >~ 3-5. The mean intrinsic beaming factor of GRBs is found to range from ~34-42, with the Swift average opening half-angle ~10 degree, compared to the pre-Swift average of ~7 degree. Within the uniform jet model, the GRB luminosity function is proportional to L^{-3.25}_*, as inferred from our best fit to the opening angle distribution. Because of the unlikely detection of several GRBs with z <~ 0.25, our analysis indicates that low redshift GRBs represent a different population of GRBs than those detected at higher redshifts. Neglecting possible metallicity effects on GRB host galaxies, we find that ~1 GRB occurs every 600,000 yrs in a local L_* spiral galaxy like the Milky Way. The fraction of high-redshift GRBs is estimated at 8-12% and 2.5-6% at z >= 5 and z >= 7, respectively, assuming continued positive evolution of the GRB rate density to high redshifts.Comment: Accepted for publication in ApJ. The paper contains 29 pages and 24 figure

A Unified Framework for Sparse Non-Negative Least Squares using Multiplicative Updates and the Non-Negative Matrix Factorization Problem

We study the sparse non-negative least squares (S-NNLS) problem. S-NNLS occurs naturally in a wide variety of applications where an unknown, non-negative quantity must be recovered from linear measurements. We present a unified framework for S-NNLS based on a rectified power exponential scale mixture prior on the sparse codes. We show that the proposed framework encompasses a large class of S-NNLS algorithms and provide a computationally efficient inference procedure based on multiplicative update rules. Such update rules are convenient for solving large sets of S-NNLS problems simultaneously, which is required in contexts like sparse non-negative matrix factorization (S-NMF). We provide theoretical justification for the proposed approach by showing that the local minima of the objective function being optimized are sparse and the S-NNLS algorithms presented are guaranteed to converge to a set of stationary points of the objective function. We then extend our framework to S-NMF, showing that our framework leads to many well known S-NMF algorithms under specific choices of prior and providing a guarantee that a popular subclass of the proposed algorithms converges to a set of stationary points of the objective function. Finally, we study the performance of the proposed approaches on synthetic and real-world data.Comment: To appear in Signal Processin