Trade and Labour Standards - Theory, New Empirical Evidence, and Policy Implications

Recent trade negotiations, both at the regional and multilateral level, have seen a resurgence of the issue of trade and labour standards. As the world economy becomes increasingly globalised and the volume of world trade flows keeps increasing between the North and the South, it is very likely that the interaction of labour standards and international trade will continue to remain high on the agenda of future trade talks. Labour interests in high-standards countries argue that low labour standards are an unfair source of comparative advantage, and that increasing imports from low-standards countries will have an adverse impact on wages and working conditions in high-standards countries, thus leading to a race to the bottom of standards. For low-standards countries, there is the fear that this is just a form of disguised protectionism and that the imposition of high labour standards upon them is equally unfair since it will erode their competitiveness, the latter being largely based on labour costs. Our objective in the present paper is to cast some light on the above debate from both a theoretical and empirical perspective. In particular, we first discuss some possible theoretical links between labour standards and comparative advantage through their effects on the terms of trade. We then investigate empirically the effects of labour standards on export performance and foreign direct investment flows. Overall, our empirical results suggest that caution should be exercised before drawing broad conclusions on the magnitude and direction of these effects. We conclude by presenting policy implications of our analysis.

Performance analysis of low-flux least-squares single-pixel imaging

A single-pixel camera is able to computationally form spatially resolved images using one photodetector and a spatial light modulator. The images it produces in low-light-level operation are imperfect, even when the number of measurements exceeds the number of pixels, because its photodetection measurements are corrupted by Poisson noise. Conventional performance analysis for single-pixel imaging generates estimates of mean-square error (MSE) from Monte Carlo simulations, which require long computational times. In this letter, we use random matrix theory to develop a closed-form approximation to the MSE of the widely used least-squares inversion method for Poisson noise-limited single-pixel imaging. We present numerical experiments that validate our approximation and a motivating example showing how our framework can be used to answer practical optical design questions for a single-pixel camera.This work was supported in part by the Samsung Scholarship and in part by the US National Science Foundation under Grant 1422034. (Samsung Scholarship; 1422034 - US National Science Foundation)Accepted manuscrip

Study Of Phenothiazine On p53 Core Domain Mutant Y220C: Finding The Anti-tumor Activity Of Phenothiazine

The tumor suppressor protein p53 is a transcription factor that plays a key role in the prevention of cancer development. The p53 cancer mutation Y220C induces formation of a cavity on the protein's surface that can accommodate stabilizing small molecules. We have attempted with the help of virtual screening and molecular docking approach using Lamarckian Genetic Algorithm to elucidate the extent of specificity of p53 cancer mutation Y220C towards different class of Phenothiazines (an anti-cancer agent). 

The 393 residue p53 tumor suppressor protein exists in a dynamic equilibrium to form homotetramers. Each chain comprises several functional domains. The N terminal part of the protein consists of the trans-activation domain (residues 1–63) followed by a proline rich region (64– 92). The central (core) domain (p53 core domain) is responsible for binding. The C terminal part of p53 contains the tetramerization domain (residues 326–355) and the negative regulatory domain at the extreme C terminus (363–393), which contains phosphorylation and acetylation sites and regulates the DNA binding activity of p53.

The docking result of the study of 2,000 Phenothiazines demonstrated that the binding energies were in the range of -10.54 kcal/mol to -1.14 kcal/mol, with 8 molecules showing hydrogen bonds with the active site residues (Lys 164). All the selected 2000 inhibitors were selected on the basis of the structural specificity to the enzyme towards its substrate and inhibitors. Our research provides a blueprint for the design of more potent and specific drugs that rescue p53-Y220C

Smartphone microendoscopy for high resolution fluorescence imaging

High resolution optical endoscopes are increasingly used in diagnosis of various medical conditions of internal organs, such as the gastrointestinal tracts, but they are too expensive for use in resource-poor settings. On the other hand, smartphones with high resolution cameras and Internet access have become more affordable, enabling them to diffuse into most rural areas and developing countries in the past decade. In this letter we describe a smartphone microendoscope that can take fluorescence images with a spatial resolution of 3.1 {\mu}m. Images collected from ex vivo, in vitro and in vivo samples using the device are also presented. The compact and cost-effective smartphone microendoscope may be envisaged as a powerful tool for detecting pre-cancerous lesions of internal organs in low and middle income countries.Comment: 4 pages, 4 figure

Photon-Efficient Computational 3D and Reflectivity Imaging with Single-Photon Detectors

Capturing depth and reflectivity images at low light levels from active illumination of a scene has wide-ranging applications. Conventionally, even with single-photon detectors, hundreds of photon detections are needed at each pixel to mitigate Poisson noise. We develop a robust method for estimating depth and reflectivity using on the order of 1 detected photon per pixel averaged over the scene. Our computational imager combines physically accurate single-photon counting statistics with exploitation of the spatial correlations present in real-world reflectivity and 3D structure. Experiments conducted in the presence of strong background light demonstrate that our computational imager is able to accurately recover scene depth and reflectivity, while traditional maximum-likelihood based imaging methods lead to estimates that are highly noisy. Our framework increases photon efficiency 100-fold over traditional processing and also improves, somewhat, upon first-photon imaging under a total acquisition time constraint in raster-scanned operation. Thus our new imager will be useful for rapid, low-power, and noise-tolerant active optical imaging, and its fixed dwell time will facilitate parallelization through use of a detector array.Comment: 11 pages, 8 figure

Field-effect mobility enhanced by tuning the Fermi level into the band gap of Bi2Se3

By eliminating normal fabrication processes, we preserve the bulk insulating state of calcium-doped Bi2Se3 single crystals in suspended nanodevices, as indicated by the activated temperature dependence of the resistivity at low temperatures. We perform low-energy electron beam irradiation (<16 keV) and electrostatic gating to control the carrier density and therefore the Fermi level position in the nanodevices. In slightly p-doped Bi2-xCaxSe3 devices, continuous tuning of the Fermi level from the bulk valence band to the band-gap reveals dramatic enhancement (> a factor of 10) in the field-effect mobility, which suggests suppressed backscattering expected for the Dirac fermion surface states in the gap of topological insulators

Computational multi-depth single-photon imaging

We present an imaging framework that is able to accurately reconstruct multiple depths at individual pixels from single-photon observations. Our active imaging method models the single-photon detection statistics from multiple reflectors within a pixel, and it also exploits the fact that a multi-depth profile at each pixel can be expressed as a sparse signal. We interpret the multi-depth reconstruction problem as a sparse deconvolution problem using single-photon observations, create a convex problem through discretization and relaxation, and use a modified iterative shrinkage-thresholding algorithm to efficiently solve for the optimal multi-depth solution. We experimentally demonstrate that the proposed framework is able to accurately reconstruct the depth features of an object that is behind a partially-reflecting scatterer and 4 m away from the imager with root mean-square error of 11 cm, using only 19 signal photon detections per pixel in the presence of moderate background light. In terms of root mean-square error, this is a factor of 4.2 improvement over the conventional method of Gaussian-mixture fitting for multi-depth recovery.This material is based upon work supported in part by a Samsung Scholarship, the US National Science Foundation under Grant No. 1422034, and the MIT Lincoln Laboratory Advanced Concepts Committee. We thank Dheera Venkatraman for his assistance with the experiments. (Samsung Scholarship; 1422034 - US National Science Foundation; MIT Lincoln Laboratory Advanced Concepts Committee)Accepted manuscrip